diff --git a/datasets/README.md b/datasets/README.md index cf5caac3e1cd..1d8014d57ea3 100644 --- a/datasets/README.md +++ b/datasets/README.md @@ -7,6 +7,21 @@ [![Slack](https://img.shields.io/badge/Chat-Slack-red)](https://flower.ai/join-slack) Flower Datasets (`flwr-datasets`) is a library to quickly and easily create datasets for federated learning, federated evaluation, and federated analytics. It was created by the `Flower Labs` team that also created Flower: A Friendly Federated Learning Framework. + + +> [!TIP] +> For complete documentation that includes API docs, how-to guides and tutorials please visit the [Flower Datasets Documentation](https://flower.ai/docs/datasets/) and for full FL example see the [Flower Examples page](https://github.com/adap/flower/tree/main/examples). + +## Installation + +For a complete installation guide visit the [Flower Datasets Documenation](https://flower.ai/docs/datasets/) + +```bash +pip install flwr-datasets[vision] +``` + +## Overview + Flower Datasets library supports: * **downloading datasets** - choose the dataset from Hugging Face's `datasets`, * **partitioning datasets** - customize the partitioning scheme, @@ -21,43 +36,28 @@ Thanks to using Hugging Face's `datasets` used under the hood, Flower Datasets i * Jax, * Arrow. -Create **custom partitioning schemes** or choose from the **implemented partitioning schemes**: +Create **custom partitioning schemes** or choose from the **implemented [partitioning schemes](https://flower.ai/docs/datasets/ref-api/flwr_datasets.partitioner.html#module-flwr_datasets.partitioner)**: + * Partitioner (the abstract base class) `Partitioner` * IID partitioning `IidPartitioner(num_partitions)` -* Natural ID partitioner `NaturalIdPartitioner` +* Dirichlet partitioning `DirichletPartitioner(num_partitions, partition_by, alpha)` +* InnerDirichlet partitioning `InnerDirichletPartitioner(partition_sizes, partition_by, alpha)` +* Natural ID partitioner `NaturalIdPartitioner(partition_by)` * Size partitioner (the abstract base class for the partitioners dictating the division based the number of samples) `SizePartitioner` -* Linear partitioner `LinearPartitioner` -* Square partitioner `SquarePartitioner` -* Exponential partitioner `ExponentialPartitioner` -* more to come in future releases. - -# Installation - -## With pip +* Linear partitioner `LinearPartitioner(num_partitions)` +* Square partitioner `SquarePartitioner(num_partitions)` +* Exponential partitioner `ExponentialPartitioner(num_partitions)` +* more to come in the future releases (contributions are welcome). +

+ Comparison of partitioning schemes. +
+ Comparison of Partitioning Schemes on CIFAR10 +

-Flower Datasets can be installed from PyPi - -```bash -pip install flwr-datasets -``` - -Install with an extension: - -* for image datasets: - -```bash -pip install flwr-datasets[vision] -``` - -* for audio datasets: - -```bash -pip install flwr-datasets[audio] -``` +PS: This plot was generated using a library function (see [flwr_datasets.visualization](https://flower.ai/docs/datasets/ref-api/flwr_datasets.visualization.html) package for more). -If you plan to change the type of the dataset to run the code with your ML framework, make sure to have it installed too. -# Usage +## Usage Flower Datasets exposes the `FederatedDataset` abstraction to represent the dataset needed for federated learning/evaluation/analytics. It has two powerful methods that let you handle the dataset preprocessing: `load_partition(partition_id, split)` and `load_split(split)`. @@ -67,16 +67,16 @@ Here's a basic quickstart example of how to partition the MNIST dataset: from flwr_datasets import FederatedDataset # The train split of the MNIST dataset will be partitioned into 100 partitions -mnist_fds = FederatedDataset("mnist", partitioners={"train": 100} +fds = FederatedDataset("mnist", partitioners={"train": 100}) -mnist_partition_0 = mnist_fds.load_partition(0, "train") +partition = fds.load_partition(0) -centralized_data = mnist_fds.load_split("test") +centralized_data = fds.load_split("test") ``` For more details, please refer to the specific how-to guides or tutorial. They showcase customization and more advanced features. -# Future release +## Future release Here are a few of the things that we will work on in future releases: @@ -85,6 +85,6 @@ Here are a few of the things that we will work on in future releases: * ✅ More out-of-the-box `Partitioner`s. * ✅ Passing `Partitioner`s via `FederatedDataset`'s `partitioners` argument. * ✅ Customization of the dataset splitting before the partitioning. -* Simplification of the dataset transformation to the popular frameworks/types. +* ✅ Simplification of the dataset transformation to the popular frameworks/types. * Creation of the synthetic data, * Support for Vertical FL. diff --git a/datasets/dev/format.sh b/datasets/dev/format.sh index 8292e0b3ed79..c6977982dd6c 100755 --- a/datasets/dev/format.sh +++ b/datasets/dev/format.sh @@ -3,9 +3,16 @@ set -e cd "$( cd "$( dirname "${BASH_SOURCE[0]}" )" >/dev/null 2>&1 && pwd )"/../ # Python -echo "Formatting started" +echo "Formatting started: Python" python -m isort flwr_datasets/ python -m black -q flwr_datasets/ python -m docformatter -i -r flwr_datasets/ python -m ruff check --fix flwr_datasets/ -echo "Formatting done" +echo "Formatting done: Python" + +# Notebooks +echo "Formatting started: Notebooks" +python -m black --ipynb -q doc/source/*.ipynb +KEYS="metadata.celltoolbar metadata.language_info metadata.toc metadata.notify_time metadata.varInspector metadata.accelerator metadata.vscode cell.metadata.id cell.metadata.heading_collapsed cell.metadata.hidden cell.metadata.code_folding cell.metadata.tags cell.metadata.init_cell cell.metadata.vscode cell.metadata.pycharm" +python -m nbstripout --keep-output doc/source/*.ipynb --extra-keys "$KEYS" +echo "Formatting done: Notebooks" diff --git a/datasets/doc/source/_static/readme/comparison_of_partitioning_schemes.png b/datasets/doc/source/_static/readme/comparison_of_partitioning_schemes.png new file mode 100644 index 000000000000..ed2e323ef649 Binary files /dev/null and b/datasets/doc/source/_static/readme/comparison_of_partitioning_schemes.png differ diff --git a/datasets/doc/source/conf.py b/datasets/doc/source/conf.py index 755147bc9e1d..11285c375f96 100644 --- a/datasets/doc/source/conf.py +++ b/datasets/doc/source/conf.py @@ -38,7 +38,7 @@ author = "The Flower Authors" # The full version, including alpha/beta/rc tags -release = "0.1.0" +release = "0.2.0" # -- General configuration --------------------------------------------------- diff --git a/datasets/doc/source/how-to-install-flwr-datasets.rst b/datasets/doc/source/how-to-install-flwr-datasets.rst index d2fd7923a817..c690ffb1b09c 100644 --- a/datasets/doc/source/how-to-install-flwr-datasets.rst +++ b/datasets/doc/source/how-to-install-flwr-datasets.rst @@ -42,5 +42,5 @@ If everything worked, it should print the version of Flower Datasets to the comm .. code-block:: none - 0.0.1 + 0.2.0 diff --git a/datasets/doc/source/how-to-visualize-label-distribution.ipynb b/datasets/doc/source/how-to-visualize-label-distribution.ipynb new file mode 100644 index 000000000000..26db72047cff --- /dev/null +++ b/datasets/doc/source/how-to-visualize-label-distribution.ipynb @@ -0,0 +1,1122 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "fb7e89caa9e6d772", + "metadata": {}, + "source": [ + "# Visualize Label Distribution" + ] + }, + { + "cell_type": "markdown", + "id": "67c54a8d7c872547", + "metadata": {}, + "source": [ + "If you partition datasets to simulate heterogeneity through label skew and/or size skew, you can now effortlessly visualize the partitioned dataset using `flwr-datasets`.\n", + "\n", + "In this how-to guide, you'll learn how to visualize and compare partitioned datasets when applying different methods or parameters.\n", + "\n", + "All the described visualization functions are compatible with all ``Partitioner`` you can find in\n", + "[flwr_datasets.partitioner](https://flower.ai/docs/datasets/ref-api/flwr_datasets.partitioner.html#module-flwr_datasets.partitioner)\n" + ] + }, + { + "cell_type": "markdown", + "id": "7220467f2c6ba432", + "metadata": {}, + "source": [ + "## Common Setup" + ] + }, + { + "cell_type": "markdown", + "id": "4e2ad2f0a0f7174d", + "metadata": {}, + "source": [ + "Install Flower Datasets library:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "c46514b679f394ce", + "metadata": {}, + "outputs": [], + "source": [ + "! pip install -q \"flwr-datasets[vision]\"" + ] + }, + { + "cell_type": "markdown", + "id": "d7ffd5b6836a5ee0", + "metadata": {}, + "source": [ + "## Plot Label Distribution" + ] + }, + { + "cell_type": "markdown", + "id": "38fbbdfe6b930916", + "metadata": {}, + "source": [ + "### Bar plot" + ] + }, + { + "cell_type": "markdown", + "id": "a5778edf97a7ee04", + "metadata": {}, + "source": [ + "Let's visualize the result of `DirichletPartitioner`.\n", + "We will create a `FederatedDataset` and assign `DirichletPartitioner` to the `train` split:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "42397afaaf50529e", + "metadata": {}, + "outputs": [], + "source": [ + "from flwr_datasets import FederatedDataset\n", + "from flwr_datasets.partitioner import DirichletPartitioner\n", + "from flwr_datasets.visualization import plot_label_distributions\n", + "\n", + "\n", + "fds = FederatedDataset(\n", + " dataset=\"cifar10\",\n", + " partitioners={\n", + " \"train\": DirichletPartitioner(\n", + " num_partitions=10,\n", + " partition_by=\"label\",\n", + " alpha=0.3,\n", + " seed=42,\n", + " min_partition_size=0,\n", + " ),\n", + " },\n", + ")\n", + "\n", + "partitioner = fds.partitioners[\"train\"]" + ] + }, + { + "cell_type": "markdown", + "id": "c4d5855ee8a605d3", + "metadata": {}, + "source": [ + "Once we have the partitioner with the dataset assigned, we are ready to pass it to the plotting function:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "f75b48256ed68897", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig, ax, df = plot_label_distributions(\n", + " partitioner,\n", + " label_name=\"label\",\n", + " plot_type=\"bar\",\n", + " size_unit=\"absolute\",\n", + " partition_id_axis=\"x\",\n", + " legend=True,\n", + " verbose_labels=True,\n", + " title=\"Per Partition Labels Distribution\",\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "be05badab744d9f7", + "metadata": {}, + "source": [ + "You can configure many details directly using the function parameters. The ones that can interest you the most are:\n", + "\n", + "* `size_unit` to have the sizes normalized such that they sum up to 1 and express the fraction of the data in each partition,\n", + "* `legend` and `verbose_labels` in case the dataset has more descriptive names and not numbers,\n", + "* `cmap` to change the values of the bars (for an overview of the available colors, have a look at [link](https://matplotlib.org/stable/users/explain/colors/colormaps.html); check out `cmap=\"tab20b\"`) \n", + "\n", + " And for even greater control, you can specify `plot_kwargs` and `legend_kwargs` as `Dict`, which will be further passed to the `plot` and `legend` functions." + ] + }, + { + "cell_type": "markdown", + "id": "3dbf6dc4ede79f05", + "metadata": {}, + "source": [ + "You can also inspect the exact numbers that were used to create this plot. Three objects are returned (see reference [here](https://flower.ai/docs/datasets/ref-api/flwr_datasets.visualization.plot_label_distributions.html#flwr_datasets.visualization.plot_label_distributions)). Let's inspect the returned DataFrame." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "f6edd14d8b260e9e", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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airplaneautomobilebirdcatdeerdogfroghorseshiptruck
Partition ID
08177941462212343225456384149
11416697530340903868
2041124543511158421
37621591100511201662198213512175
424371421924004251151477
5677917025255247727445900
6422244863809290380506
7122281159721741038172716825154
825629342751848151122401417
91136107350357126711223
\n", + "
" + ], + "text/plain": [ + " airplane automobile bird cat deer dog frog horse ship \\\n", + "Partition ID \n", + "0 817 794 1462 2123 432 25 456 384 14 \n", + "1 1416 6 97 5 3 0 3409 0 3 \n", + "2 0 4 11 2 454 3 511 15 84 \n", + "3 762 159 1100 51 120 166 2 1982 1351 \n", + "4 2 43 714 2 19 2400 425 1 151 \n", + "5 67 79 170 25 2552 477 27 44 590 \n", + "6 422 2 4 486 380 92 90 380 50 \n", + "7 122 2811 597 2174 1038 1727 1 682 515 \n", + "8 256 29 342 75 1 84 8 1511 2240 \n", + "9 1136 1073 503 57 1 26 71 1 2 \n", + "\n", + " truck \n", + "Partition ID \n", + "0 9 \n", + "1 868 \n", + "2 21 \n", + "3 2175 \n", + "4 477 \n", + "5 0 \n", + "6 6 \n", + "7 4 \n", + "8 1417 \n", + "9 23 " + ] + }, + "execution_count": null, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df" + ] + }, + { + "cell_type": "markdown", + "id": "2902213a", + "metadata": {}, + "source": [ + "Each row represents a unique partition ID, and the columns represent unique labels (either in the verbose version if `verbose_labels=True` or typically `int` values otherwise, representing the partition IDs).\n", + "That you can index the DataFrame `df[partition_id, label_id]` to get the number of samples in `partition_id` for the specified `label_id.`" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "8ffe4039", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "714" + ] + }, + "execution_count": null, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df.loc[4, \"bird\"]" + ] + }, + { + "cell_type": "markdown", + "id": "2e6c17af529a668f", + "metadata": {}, + "source": [ + "Let's see a plot with `size_unit=\"percent\"`, which is another excellent way to understand the partitions. In this mode, the number of datapoints for each class in a given partition are normalized, so they sum up to 100." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "a241894a47f3cc9f", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig, ax, df = plot_label_distributions(\n", + " partitioner,\n", + " label_name=\"label\",\n", + " plot_type=\"bar\",\n", + " size_unit=\"percent\",\n", + " partition_id_axis=\"x\",\n", + " legend=True,\n", + " verbose_labels=True,\n", + " cmap=\"tab20b\",\n", + " title=\"Per Partition Labels Distribution\",\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "e7d1fe2e1c0f14c", + "metadata": {}, + "source": [ + "### Heatmap" + ] + }, + { + "cell_type": "markdown", + "id": "ad6a2e53de3cc084", + "metadata": {}, + "source": [ + "You might want to visualize the results of partitioning as a heatmap, which can be especially useful for binary labels. Here's how:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "14a4b4e574866120", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig, ax, df = plot_label_distributions(\n", + " partitioner,\n", + " label_name=\"label\",\n", + " plot_type=\"heatmap\",\n", + " size_unit=\"absolute\",\n", + " partition_id_axis=\"x\",\n", + " legend=True,\n", + " verbose_labels=True,\n", + " title=\"Per Partition Labels Distribution\",\n", + " plot_kwargs={\"annot\": True},\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "5167593e67fa3dbb", + "metadata": {}, + "source": [ + "Note: we used the `plot_kwargs={\"annot\": True}` to add the number directly to the plot." + ] + }, + { + "cell_type": "markdown", + "id": "e2e41273551ac32a", + "metadata": {}, + "source": [ + "If you are a `pandas` fan, then you might be interested that a similar heatmap can be created with the DataFrame object for visualization in jupyter notebook:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "fcc90b52bfd650cf", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
 airplaneautomobilebirdcatdeerdogfroghorseshiptruck
Partition ID          
08177941462212343225456384149
11416697530340903868
2041124543511158421
37621591100511201662198213512175
424371421924004251151477
5677917025255247727445900
6422244863809290380506
7122281159721741038172716825154
825629342751848151122401417
91136107350357126711223
\n" + ], + "text/plain": [ + "" + ] + }, + "execution_count": null, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df.style.background_gradient(axis=None, cmap=\"Greens\", vmin=0)" + ] + }, + { + "cell_type": "markdown", + "id": "37d85e1b40d54918", + "metadata": {}, + "source": [ + "## Plot Comparison of Label Distributions" + ] + }, + { + "cell_type": "markdown", + "id": "4f49259a3de7dd17", + "metadata": {}, + "source": [ + "Now, once you know how to visualize a single partitioned dataset, you'll learn how to compare a few of them on a single plot.\n", + "\n", + "Let's compare:\n", + "\n", + "- IidPartitioner,\n", + "- DirichletPartitioner,\n", + "- ShardPartitioner\n", + "still using the `cifar10` dataset.\n", + "\n", + "We need to create a list of partitioners. Each partitioner needs to have a dataset assigned to it (it does not have to be the same dataset so you can also compare the same partitioning on different datasets)." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "9e84a9192a266f3e", + "metadata": {}, + "outputs": [], + "source": [ + "from flwr_datasets import FederatedDataset\n", + "from flwr_datasets.partitioner import (\n", + " IidPartitioner,\n", + " DirichletPartitioner,\n", + " ShardPartitioner,\n", + ")\n", + "\n", + "partitioner_list = []\n", + "title_list = [\"IidPartitioner\", \"DirichletPartitioner\", \"ShardPartitioner\"]\n", + "\n", + "## IidPartitioner\n", + "fds = FederatedDataset(\n", + " dataset=\"cifar10\",\n", + " partitioners={\n", + " \"train\": IidPartitioner(num_partitions=10),\n", + " },\n", + ")\n", + "partitioner_list.append(fds.partitioners[\"train\"])\n", + "\n", + "## DirichletPartitioner\n", + "fds = FederatedDataset(\n", + " dataset=\"cifar10\",\n", + " partitioners={\n", + " \"train\": DirichletPartitioner(\n", + " num_partitions=10,\n", + " partition_by=\"label\",\n", + " alpha=1.0,\n", + " min_partition_size=0,\n", + " ),\n", + " },\n", + ")\n", + "partitioner_list.append(fds.partitioners[\"train\"])\n", + "\n", + "## ShardPartitioner\n", + "fds = FederatedDataset(\n", + " dataset=\"cifar10\",\n", + " partitioners={\n", + " \"train\": ShardPartitioner(\n", + " num_partitions=10, partition_by=\"label\", num_shards_per_partition=2\n", + " )\n", + " },\n", + ")\n", + "partitioner_list.append(fds.partitioners[\"train\"])" + ] + }, + { + "cell_type": "markdown", + "id": "d18bae80", + "metadata": {}, + "source": [ + "Now let's visualize them side by side" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "f2ee2864", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "from flwr_datasets.visualization import plot_comparison_label_distribution\n", + "\n", + "fig, axes, df_list = plot_comparison_label_distribution(\n", + " partitioner_list=partitioner_list,\n", + " label_name=\"label\",\n", + " subtitle=\"Comparison of Partitioning Schemes on CIFAR10\",\n", + " titles=title_list,\n", + " legend=True,\n", + " verbose_labels=True,\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "862899eb04695380", + "metadata": {}, + "source": [ + "## Bonus: Natural Id Dataset" + ] + }, + { + "cell_type": "markdown", + "id": "4f3f8aaf", + "metadata": {}, + "source": [ + "Nothing stops you from using the `NaturalIdPartitioner` to visualize a dataset with the `id` in it and does not need the artificial partitioning but has the pre-existing partitions. For that dataset, we use `NaturalIdPartitioner`. Let's look at the `speech-commands` dataset that has `speaker_id`, and there are quite a few speakers; therefore, we will show only the first 20 partitions. And since we have quite a few different labels, let's specify `legend_kwargs={\"ncols\": 2}` to display them in two columns (we will also shift the legend slightly to the right)." + ] + }, + { + "cell_type": "markdown", + "id": "f016d21a", + "metadata": {}, + "source": [ + "You'll be using the [Google SpeechCommands](https://huggingface.co/datasets/google/speech_commands) dataset, which is a speech-based dataset. For this, you'll need to install the `\"audio\"` extension for Flower Datasets. It can be easily done like this:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "fd5ca8f4", + "metadata": {}, + "outputs": [], + "source": [ + "! pip install -q \"flwr-datasets[audio]\"" + ] + }, + { + "cell_type": "markdown", + "id": "90ea3642", + "metadata": {}, + "source": [ + "With everything ready, let's visualize the partitions for a naturally partitioned dataset." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "4fe70116", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "from flwr_datasets import FederatedDataset\n", + "from flwr_datasets.partitioner import NaturalIdPartitioner\n", + "from flwr_datasets.visualization import plot_label_distributions\n", + "\n", + "\n", + "fds = FederatedDataset(\n", + " dataset=\"google/speech_commands\",\n", + " subset=\"v0.01\",\n", + " partitioners={\n", + " \"train\": NaturalIdPartitioner(\n", + " partition_by=\"speaker_id\",\n", + " ),\n", + " },\n", + ")\n", + "\n", + "partitioner = fds.partitioners[\"train\"]\n", + "\n", + "fix, ax, df = plot_label_distributions(\n", + " partitioner=partitioner,\n", + " label_name=\"label\",\n", + " max_num_partitions=20,\n", + " plot_type=\"bar\",\n", + " size_unit=\"percent\",\n", + " partition_id_axis=\"x\",\n", + " legend=True,\n", + " title=\"Per Partition Labels Distribution\",\n", + " verbose_labels=True,\n", + " legend_kwargs={\"ncols\": 2, \"bbox_to_anchor\": (1.25, 0.5)},\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "4442c99c", + "metadata": {}, + "source": [ + "## More resources\n", + "\n", + "If you are looking for more resorces, feel free to check:\n", + "\n", + "* `flwr-dataset` documentation\n", + " * [plot_label_distributions](https://flower.ai/docs/datasets/ref-api/flwr_datasets.visualization.plot_label_distributions.html#flwr_datasets.visualization.plot_label_distributions)\n", + " * [plot_comparison_label_distribution](https://flower.ai/docs/datasets/ref-api/flwr_datasets.visualization.plot_comparison_label_distribution.html#flwr_datasets.visualization.plot_comparison_label_distribution)\n", + "* if you want to do any custom modification of the returned plots\n", + " * [matplotlib](https://matplotlib.org/)\n", + " * [seaborn](https://seaborn.pydata.org/)\n", + " * or plot directly using pandas object [pd.DataFrame.plot](https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.plot.html)" + ] + }, + { + "cell_type": "markdown", + "id": "52655972", + "metadata": {}, + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "flwr", + "language": "python", + "name": "python3" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/datasets/doc/source/index.rst b/datasets/doc/source/index.rst index df248969a849..bdcea7650bbc 100644 --- a/datasets/doc/source/index.rst +++ b/datasets/doc/source/index.rst @@ -7,6 +7,15 @@ learning/analytics/evaluation. It is created by the ``Flower Labs`` team that al Flower Datasets Framework ------------------------- +Install +~~~~~~~ + +.. code-block:: bash + + python -m pip install "flwr-datasets[vision]" + +Check out all the details on how to install Flower Datasets in :doc:`how-to-install-flwr-datasets`. + Tutorials ~~~~~~~~~ @@ -32,6 +41,7 @@ Problem-oriented how-to guides show step-by-step how to achieve a specific goal. how-to-use-with-tensorflow how-to-use-with-numpy how-to-use-with-local-data + how-to-visualize-label-distribution how-to-disable-enable-progress-bar References @@ -57,9 +67,16 @@ Main features ------------- Flower Datasets library supports: -- **downloading datasets** - choose the dataset from Hugging Face's ``dataset`` -- **partitioning datasets** - customize the partitioning scheme +- **downloading datasets** - choose the dataset from Hugging Face's ``dataset`` (`link `_) +- **partitioning datasets** - choose one of the implemented partitioning scheme or create your own. - **creating centralized datasets** - leave parts of the dataset unpartitioned (e.g. for centralized evaluation) +- **visualization of the partitioned datasets** - visualize the label distribution of the partitioned dataset (and compare the results on different parameters of the same partitioning schemes, different datasets, different partitioning schemes, or any mix of them) + + +.. image:: ./_static/readme/comparison_of_partitioning_schemes.png + :align: center + :alt: Comparison of Partitioning Schemes on CIFAR10 + Thanks to using Hugging Face's ``datasets`` used under the hood, Flower Datasets integrates with the following popular formats/frameworks: @@ -71,28 +88,19 @@ Thanks to using Hugging Face's ``datasets`` used under the hood, Flower Datasets - Jax - Arrow -Install -------- - -The simplest install is - -.. code-block:: bash - - python -m pip install flwr-datasets - -If you plan to use the image datasets - -.. code-block:: bash - - python -m pip install flwr-datasets[vision] - -If you plan to use the audio datasets - -.. code-block:: bash +Here are a few of the ``Partitioner`` s that are available: (for a full list see `link `_ ) - python -m pip install flwr-datasets[audio] +* Partitioner (the abstract base class) ``Partitioner`` +* IID partitioning ``IidPartitioner(num_partitions)`` +* Dirichlet partitioning ``DirichletPartitioner(num_partitions, partition_by, alpha)`` +* InnerDirichlet partitioning ``InnerDirichletPartitioner(partition_sizes, partition_by, alpha)`` +* Natural ID partitioner ``NaturalIdPartitioner(partition_by)`` +* Size partitioner (the abstract base class for the partitioners dictating the division based the number of samples) ``SizePartitioner`` +* Linear partitioner ``LinearPartitioner(num_partitions)`` +* Square partitioner ``SquarePartitioner(num_partitions)`` +* Exponential partitioner ``ExponentialPartitioner(num_partitions)`` +* more to come in the future releases (contributions are welcome). -Check out the full details on the download in :doc:`how-to-install-flwr-datasets`. How To Use the library ---------------------- diff --git a/datasets/flwr_datasets/federated_dataset.py b/datasets/flwr_datasets/federated_dataset.py index bbc6e99b651e..accfb783f368 100644 --- a/datasets/flwr_datasets/federated_dataset.py +++ b/datasets/flwr_datasets/federated_dataset.py @@ -36,8 +36,9 @@ class FederatedDataset: Download, partition data among clients (edge devices), or load full dataset. - Partitions are created using IidPartitioner. Support for different partitioners - specification and types will come in future releases. + Partitions are created per-split-basis using Partitioners from + `flwr_datasets.partitioner` specified in `partitioners` (see `partitioners` + parameter for more information). Parameters ---------- @@ -57,23 +58,43 @@ class FederatedDataset: into). One or multiple `Partitioner` objects can be specified in that manner, but at most, one per split. shuffle : bool - Whether to randomize the order of samples. Applied prior to resplitting, - speratelly to each of the present splits in the dataset. It uses the `seed` - argument. Defaults to True. + Whether to randomize the order of samples. Applied prior to preprocessing + operations, speratelly to each of the present splits in the dataset. It uses + the `seed` argument. Defaults to True. seed : Optional[int] Seed used for dataset shuffling. It has no effect if `shuffle` is False. The - seed cannot be set in the later stages. If `None`, then fresh, unpredictable entropy - will be pulled from the OS. Defaults to 42. + seed cannot be set in the later stages. If `None`, then fresh, unpredictable + entropy will be pulled from the OS. Defaults to 42. Examples -------- Use MNIST dataset for Federated Learning with 100 clients (edge devices): - >>> mnist_fds = FederatedDataset(dataset="mnist", partitioners={"train": 100}) + >>> from flwr_datasets import FederatedDataset + >>> + >>> fds = FederatedDataset(dataset="mnist", partitioners={"train": 100}) >>> # Load partition for client with ID 10. - >>> partition = mnist_fds.load_partition(10, "train") + >>> partition = fds.load_partition(10) >>> # Use test split for centralized evaluation. - >>> centralized = mnist_fds.load_split("test") + >>> centralized = fds.load_split("test") + + Use CIFAR10 dataset for Federated Laerning with 100 clients: + >>> from flwr_datasets import FederatedDataset + >>> from flwr_datasets.partitioner import DirichletPartitioner + >>> + >>> partitioner = DirichletPartitioner(num_partitions=10, partition_by="label", + >>> alpha=0.5, min_partition_size=10) + >>> fds = FederatedDataset(dataset="cifar10", partitioners={"train": partitioner}) + >>> partition = fds.load_partition(partition_id=0) + + Visualize the partitioned datasets + >>> from flwr_datasets.visualization import plot_label_distributions + >>> + >>> _ = plot_label_distributions( + >>> partitioner=fds.partitioners["train"], + >>> label_name="label", + >>> legend=True, + >>> ) """ # pylint: disable=too-many-instance-attributes diff --git a/datasets/pyproject.toml b/datasets/pyproject.toml index 56cf3038f4ef..017374181f59 100644 --- a/datasets/pyproject.toml +++ b/datasets/pyproject.toml @@ -4,7 +4,7 @@ build-backend = "poetry.core.masonry.api" [tool.poetry] name = "flwr-datasets" -version = "0.1.0" +version = "0.2.0" description = "Flower Datasets" license = "Apache-2.0" authors = ["The Flower Authors "] diff --git a/doc/locales/ko/LC_MESSAGES/framework-docs.po b/doc/locales/ko/LC_MESSAGES/framework-docs.po index 74cb5f00589f..3c41a8647c35 100644 --- a/doc/locales/ko/LC_MESSAGES/framework-docs.po +++ b/doc/locales/ko/LC_MESSAGES/framework-docs.po @@ -8,7 +8,7 @@ msgstr "" "Project-Id-Version: Flower main\n" "Report-Msgid-Bugs-To: \n" "POT-Creation-Date: 2024-06-17 16:09+0200\n" -"PO-Revision-Date: 2024-06-22 10:52+0000\n" +"PO-Revision-Date: 2024-06-23 14:41+0000\n" "Last-Translator: 박태현 \n" "Language-Team: Korean \n" @@ -30,9 +30,11 @@ msgstr "엣지 클라이언트 엔진" #: ../../source/contributor-explanation-architecture.rst:7 msgid "" -"`Flower `_ core framework architecture with Edge " -"Client Engine" -msgstr "`Flower `_의 핵심 프레임워크 아키텍처와 엣지 클라이언트 엔진" +"`Flower `_ core framework architecture with Edge Client " +"Engine" +msgstr "" +"`Flower `_의 핵심 프레임워크 아키텍처와 엣지 클라이언트 엔" +"진" #: ../../source/contributor-explanation-architecture.rst:13 msgid "Virtual Client Engine" @@ -42,7 +44,9 @@ msgstr "가상 클라이언트 엔진" msgid "" "`Flower `_ core framework architecture with Virtual " "Client Engine" -msgstr "`Flower `_의 핵심 프레임워크 아키텍처와 가상 클라이언트 엔진" +msgstr "" +"`Flower `_의 핵심 프레임워크 아키텍처와 가상 클라이언트 엔" +"진" #: ../../source/contributor-explanation-architecture.rst:21 msgid "Virtual Client Engine and Edge Client Engine in the same workload" @@ -50,9 +54,11 @@ msgstr "동일 작업에서 가상 클라이언트 엔진과 엣지 클라이언 #: ../../source/contributor-explanation-architecture.rst:23 msgid "" -"`Flower `_ core framework architecture with both " -"Virtual Client Engine and Edge Client Engine" -msgstr "`Flower `_의 핵심 프레임워크 아키텍처와 가상 및 엣지 클라이언트 엔진" +"`Flower `_ core framework architecture with both Virtual " +"Client Engine and Edge Client Engine" +msgstr "" +"`Flower `_의 핵심 프레임워크 아키텍처와 가상 및 엣지 클라" +"이언트 엔진" #: ../../source/contributor-how-to-build-docker-images.rst:2 msgid "How to build Docker Flower images locally" @@ -60,20 +66,19 @@ msgstr "Docker Flower 이미지를 Locally 구축하는 방법" #: ../../source/contributor-how-to-build-docker-images.rst:4 msgid "" -"Flower provides pre-made docker images on `Docker Hub " -"`_ that include all necessary dependencies" -" for running the SuperLink, SuperNode or ServerApp. You can also build " -"your own custom docker images from scratch with a different version of " -"Python or Linux distribution (Ubuntu/Alpine) if that is what you need. In" -" this guide, we will explain what images exist and how to build them " -"locally." +"Flower provides pre-made docker images on `Docker Hub `_ that include all necessary dependencies for running the " +"SuperLink, SuperNode or ServerApp. You can also build your own custom docker " +"images from scratch with a different version of Python or Linux distribution " +"(Ubuntu/Alpine) if that is what you need. In this guide, we will explain " +"what images exist and how to build them locally." msgstr "" "Flower는 'Docker Hub '_에서 미리 만들어진 " "Docker 이미지들을 제공합니다. 해당 이미지들은 SuperLink, ServerNode 또는 " -"ServerApp을 실행하는 데 필요한 모든 dependencies를 포함합니다. 필요한 경우 " -"다른 버전의 Python이나 Linux 배포판(Ubuntu/Alpine)을 사용해 처음부터 사용자 " -"정의 Docker 이미지를 빌드할 수도 있습니다. 이 가이드에서는 존재하는 " -"이미지들과 이들을 로컬에서 빌드하는 방법에 대해 설명하겠습니다." +"ServerApp을 실행하는 데 필요한 모든 dependencies를 포함합니다. 필요한 경우 다" +"른 버전의 Python이나 Linux 배포판(Ubuntu/Alpine)을 사용해 처음부터 사용자 정" +"의 Docker 이미지를 빌드할 수도 있습니다. 이 가이드에서는 존재하는 이미지들과 " +"이들을 로컬에서 빌드하는 방법에 대해 설명하겠습니다." #: ../../source/contributor-how-to-build-docker-images.rst:10 msgid "" @@ -83,7 +88,7 @@ msgstr "시작하기 전에, 로컬 개발 환경에서 몇 가지 전제 조건 #: ../../source/contributor-how-to-build-docker-images.rst:12 msgid "Clone the flower repository." -msgstr "Flower 리포지토리를 복제합니다." +msgstr "Flower 레포지토리를 복제합니다." #: ../../source/contributor-how-to-build-docker-images.rst:18 #: ../../source/how-to-run-flower-using-docker.rst:165 @@ -93,46 +98,45 @@ msgstr "Docker 데몬이 실행 중인지 확인하십시오." #: ../../source/contributor-how-to-build-docker-images.rst:20 #: ../../source/how-to-run-flower-using-docker.rst:167 msgid "" -"Please follow the first section on :doc:`Run Flower using Docker ` which covers this step in more detail." +"Please follow the first section on :doc:`Run Flower using Docker ` which covers this step in more detail." msgstr "" -":doc:Run Flower using Docker 의 첫 번째 섹션을 " -"따라 주십시오. 해당 부분을 더 자세히 설명해 줍니다." +":doc:Run Flower using Docker 의 첫 번째 섹션" +"을 따라 주십시오. 해당 부분을 더 자세히 설명해 줍니다." #: ../../source/contributor-how-to-build-docker-images.rst:25 msgid "" "The build instructions that assemble the images are located in the " -"respective Dockerfiles. You can find them in the subdirectories of " -"``src/docker``." +"respective Dockerfiles. You can find them in the subdirectories of ``src/" +"docker``." msgstr "" -"이미지들을 조합하는 빌드 instruction들은 해당 Dockerfile에 있습니다. \"src/docker\" 의 하위 " -"디렉토리에서 찾을 수 있습니다." +"이미지들을 조합하는 빌드 명령어들은 해당 Dockerfile에 있습니다. \"src/" +"docker\" 의 하위 디렉토리에서 찾을 수 있습니다." #: ../../source/contributor-how-to-build-docker-images.rst:28 msgid "" "Flower Docker images are configured via build arguments. Through build " -"arguments, we can make the creation of images more flexible. For example," -" in the base image, we can specify the version of Python to install using" -" the ``PYTHON_VERSION`` build argument. Some of the build arguments have " -"default values, others must be specified when building the image. All " -"available build arguments for each image are listed in one of the tables " -"below." +"arguments, we can make the creation of images more flexible. For example, in " +"the base image, we can specify the version of Python to install using the " +"``PYTHON_VERSION`` build argument. Some of the build arguments have default " +"values, others must be specified when building the image. All available " +"build arguments for each image are listed in one of the tables below." msgstr "" -"Flower Docker는 빌드 argument를 통해 구성됩니다. 빌드 argument들을 통해, " +"Flower Docker는 빌드 전달인자를 통해 구성됩니다. 빌드 argument들을 통해, " "이미지를 보다 유연하게 생성할 수 있습니다. 예를 들어, base 이미지에서 " -"\"PYTHON_VERSION\" 빌드 argument를 사용하여 Python 버전을 지정할 수 " -"있습니다. 일부 빌드 argument들은 기본값이며, 이미지를 빌드할 때 지정해야 " -"합니다. 각 이미지에 사용할 수 있는 모든 빌드 argument는 아래 표 중에 " +"\"PYTHON_VERSION\" 빌드 전달인자를 사용하여 Python 버전을 지정할 수 " +"있습니다. 일부 빌드 전달인자들은 기본값이며, 이미지를 빌드할 때 지정해야 " +"합니다. 각 이미지에 사용할 수 있는 모든 빌드 전달인자는 아래 표 중에 " "있습니다." #: ../../source/contributor-how-to-build-docker-images.rst:35 msgid "Building the base image" -msgstr "base 이미지 빌드" +msgstr "기본 이미지 빌드" #: ../../source/contributor-how-to-build-docker-images.rst:41 #: ../../source/contributor-how-to-build-docker-images.rst:98 msgid "Build argument" -msgstr "빌드 argument" +msgstr "빌드 전달인자" #: ../../source/contributor-how-to-build-docker-images.rst:42 #: ../../source/contributor-how-to-build-docker-images.rst:99 @@ -155,7 +159,7 @@ msgstr "``DISTRO``" #: ../../source/contributor-how-to-build-docker-images.rst:46 msgid "The Linux distribution to use as the base image." -msgstr "base 이미지 사용을 위한 Linux 배포판." +msgstr "기본 이미지 사용을 위한 Linux 배포판." #: ../../source/contributor-how-to-build-docker-images.rst:47 #: ../../source/contributor-how-to-build-docker-images.rst:51 @@ -250,20 +254,21 @@ msgstr "``flwr`` 또는 ``flwr-nightly``" #: ../../source/contributor-how-to-build-docker-images.rst:75 msgid "" -"The following example creates a base Ubuntu/Alpine image with Python " -"3.11.0, pip 23.0.1, setuptools 69.0.2 and Flower 1.8.0:" +"The following example creates a base Ubuntu/Alpine image with Python 3.11.0, " +"pip 23.0.1, setuptools 69.0.2 and Flower 1.8.0:" msgstr "" -"다음 예시에서는 Python 3.11.0, pip 23.0.1, setuptools 및 Flower 1.8.0으로 " -"기본 Ubuntu/Alpine 이미지를 만듭니다:" +"다음 예시에서는 Python 3.11.0, pip 23.0.1, setuptools 및 Flower 1.8.0으로 기" +"본 Ubuntu/Alpine 이미지를 만듭니다:" #: ../../source/contributor-how-to-build-docker-images.rst:88 msgid "" -"The name of image is ``flwr_base`` and the tag ``0.1.0``. Remember that " -"the build arguments as well as the name and tag can be adapted to your " -"needs. These values serve as examples only." +"The name of image is ``flwr_base`` and the tag ``0.1.0``. Remember that the " +"build arguments as well as the name and tag can be adapted to your needs. " +"These values serve as examples only." msgstr "" -"이미지의 이름은 ``flwr_base``이고 태그는 ``0.1.0``입니다. 필요에 따라 빌드 argument들 뿐만 아니라 이름과" -" 태그도 정할 수 있습니다. 이 값들은 예시일 뿐입니다." +"이미지의 이름은 ``flwr_base``이고 태그는 ``0.1.0``입니다. 필요에 따라 빌드 " +"전달인자들 뿐만 아니라 이름과 태그도 정할 수 있습니다. 이 값들은 예시일 " +"뿐입니다." #: ../../source/contributor-how-to-build-docker-images.rst:92 msgid "Building the SuperLink/SuperNode or ServerApp image" @@ -275,7 +280,7 @@ msgstr "``BASE_REPOSITORY``" #: ../../source/contributor-how-to-build-docker-images.rst:103 msgid "The repository name of the base image." -msgstr "base 이미지의 리포지토리 이름." +msgstr "기본 이미지의 레포지토리 이름." #: ../../source/contributor-how-to-build-docker-images.rst:105 msgid "``flwr/base``" @@ -295,19 +300,19 @@ msgstr "``1.8.0-py3.10-ubuntu22.04``" #: ../../source/contributor-how-to-build-docker-images.rst:111 msgid "" -"The following example creates a SuperLink/SuperNode or ServerApp image " -"with the official Flower base image:" -msgstr "다음 예시에서는 공식 Flower 기본 이미지로 SuperLink/SuperNode 또는 " -"ServerApp이미지를 만듭니다:" +"The following example creates a SuperLink/SuperNode or ServerApp image with " +"the official Flower base image:" +msgstr "" +"다음 예시에서는 공식 Flower 기본 이미지로 SuperLink/SuperNode 또는 ServerApp" +"이미지를 만듭니다:" #: ../../source/contributor-how-to-build-docker-images.rst:122 msgid "" -"If you want to use your own base image instead of the official Flower " -"base image, all you need to do is set the ``BASE_REPOSITORY`` build " -"argument." +"If you want to use your own base image instead of the official Flower base " +"image, all you need to do is set the ``BASE_REPOSITORY`` build argument." msgstr "" "공식 Flower 기본 이미지 대신 자체 기본 이미지를 사용 하길 원한다면, " -"``BASE_REPOSITORY`` 빌드 argument들을 설정해야 합니다." +"``BASE_REPOSITORY`` 빌드 전달인자들을 설정해야 합니다." #: ../../source/contributor-how-to-build-docker-images.rst:133 msgid "After creating the image, we can test whether the image is working:" @@ -319,29 +324,30 @@ msgstr "번역 기여" #: ../../source/contributor-how-to-contribute-translations.rst:4 msgid "" -"Since `Flower 1.5 `_ we have introduced translations to " -"our doc pages, but, as you might have noticed, the translations are often" -" imperfect. If you speak languages other than English, you might be able " -"to help us in our effort to make Federated Learning accessible to as many" -" people as possible by contributing to those translations! This might " -"also be a great opportunity for those wanting to become open source " -"contributors with little prerequisites." -msgstr "" -"`Flower 1.5 `_ 부터 문서 페이지에 번역을 도입했지만, 아시다시피 번역이 불안전한 " -"경우가 많습니다. 만일 영어 이외의 언어를 사용한다면, 많은 사람들이 Federated Learning에 접근할 수 있도록 번역 " -"작업에 기여함으로써 저희의 노력에 도움을 주실 수 있습니다! 이는 전제 조건이 거의 없는 오픈 소스 기여자가 되고자 하는 사람들에게" -" 좋은 기회가 될 수도 있습니다." +"Since `Flower 1.5 `_ we have introduced translations to our doc pages, " +"but, as you might have noticed, the translations are often imperfect. If you " +"speak languages other than English, you might be able to help us in our " +"effort to make Federated Learning accessible to as many people as possible " +"by contributing to those translations! This might also be a great " +"opportunity for those wanting to become open source contributors with little " +"prerequisites." +msgstr "" +"`Flower 1.5 `_ 부터 문서 페이지에 번역을 도입했지만, 아시다시피 " +"번역이 불안전한 경우가 많습니다. 만일 영어 이외의 언어를 사용한다면, 많은 " +"사람들이 연합 학습에 접근할 수 있도록 번역 작업에 기여함으로써 저희의 노력에 " +"도움을 주실 수 있습니다! 이는 전제 조건이 거의 없는 오픈 소스 기여자가 " +"되고자 하는 사람들에게 좋은 기회가 될 수도 있습니다." #: ../../source/contributor-how-to-contribute-translations.rst:13 msgid "" -"Our translation project is publicly available over on `Weblate " -"`_, this " -"where most of the work will happen." +"Our translation project is publicly available over on `Weblate `_, this where most of " +"the work will happen." msgstr "" -"번역 프로젝트는 `Weblate `_에서 공개적으로 진행되며, 대부분의 작업이 이곳에서 이루어집니다." +"번역 프로젝트는 `Weblate `_에서 공개적으로 진행되며, 대부분의 작업이 이곳에서 이루어집니다." #: ../../source/contributor-how-to-contribute-translations.rst:18 msgid "Contribute to existing languages" @@ -349,43 +355,43 @@ msgstr "기존 언어에 기여하기" #: ../../source/contributor-how-to-contribute-translations.rst:23 msgid "" -"The first thing you will need to do in order to contribute is to create a" -" free Weblate account on this `page " -"`_. More information about" -" profile settings can be found `here " +"The first thing you will need to do in order to contribute is to create a " +"free Weblate account on this `page `_. More information about profile settings can be found `here " "`_." msgstr "" -"기여를 하기 위해 가장 먼저 해야 할 일은 해당 `page " -"`_에서 무료 Weblate 계정을 만드는 " -"것입니다. 프로필 설정에 대한 자세한 정보는 `here " -"`_를 참조하세요." +"기여를 하기 위해 가장 먼저 해야 할 일은 해당 `page `_에서 무료 Weblate 계정을 만드는 것입니다. 프로필 설" +"정에 대한 자세한 정보는 `here `_를 참조하세요." #: ../../source/contributor-how-to-contribute-translations.rst:29 msgid "" -"Once you are signed in to Weblate, you can navigate to the `Flower " -"Framework project `_. Here, you should see the different existing languages" -" that can be found on the website." +"Once you are signed in to Weblate, you can navigate to the `Flower Framework " +"project `_. " +"Here, you should see the different existing languages that can be found on " +"the website." msgstr "" -"Weblate에 로그인한 후, `Flower Framework project " -"`_로 이동할 수 " -"있습니다. 여기에서 웹사이트에 있는 다양한 기존 언어들을 확인할 수 있습니다." +"Weblate에 로그인한 후, `Flower Framework project `_로 이동할 수 있습니다. 여기에서 웹사이트에 " +"있는 다양한 기존 언어들을 확인할 수 있습니다." #: ../../source/contributor-how-to-contribute-translations.rst:34 msgid "" -"Once you have selected the language you want to contribute to, you should" -" see a similar interface to this:" +"Once you have selected the language you want to contribute to, you should " +"see a similar interface to this:" msgstr "기여하고자 하는 언어를 선택하면, 다음과 같은 인터페이스가 나타납니다:" #: ../../source/contributor-how-to-contribute-translations.rst:39 msgid "" "The most straight forward option here is to click on the ``Translate`` " -"button on the top right (in the ``Translation status`` section). This " -"will automatically bring you to the translation interface for " -"untranslated strings." +"button on the top right (in the ``Translation status`` section). This will " +"automatically bring you to the translation interface for untranslated " +"strings." msgstr "" -"여기서 가장 간단한 옵션은 오른쪽 상단(``Translation status`` 부분)에 있는 ``Translate`` 버튼을 " -"클릭하는 것 입니다. 번역되지 않은 문장에 대한 번역 인터페이스로 자동으로 이동합니다." +"여기서 가장 간단한 옵션은 오른쪽 상단(``Translation status`` 부분)에 있는 " +"``Translate`` 버튼을 클릭하는 것 입니다. 번역되지 않은 문장에 대한 번역 인터" +"페이스로 자동으로 이동합니다." #: ../../source/contributor-how-to-contribute-translations.rst:43 msgid "This is what the interface looks like:" @@ -393,44 +399,47 @@ msgstr "인터페이스는 다음과 같습니다:" #: ../../source/contributor-how-to-contribute-translations.rst:47 msgid "" -"You input your translation in the text box at the top and then, once you " -"are happy with it, you either press ``Save and continue`` (to save the " -"translation and go to the next untranslated string), ``Save and stay`` " -"(to save the translation and stay on the same page), ``Suggest`` (to add " -"your translation to suggestions for other users to view), or ``Skip`` (to" -" go to the next untranslated string without saving anything)." +"You input your translation in the text box at the top and then, once you are " +"happy with it, you either press ``Save and continue`` (to save the " +"translation and go to the next untranslated string), ``Save and stay`` (to " +"save the translation and stay on the same page), ``Suggest`` (to add your " +"translation to suggestions for other users to view), or ``Skip`` (to go to " +"the next untranslated string without saving anything)." msgstr "" -"번역문을 상단의 텍스트 상자에 입력한 후, 번역이 만족스러우면 ``Save and continue``(번역을 저장하고 다음 미번역 " -"문장으로 이동), ``Save and stay``(번역을 저장하고 해당 페이지에 머무르기), ``Suggest`` (다른 사용자가 " -"볼 수 있도록 번역을 제안 항목에 추가), ``Skip``(아무것도 저장하지 않고 다음 미번역 문장으로 이동) 중 하나를 선택하면 " -"됩니다." +"번역문을 상단의 텍스트 상자에 입력한 후, 번역이 만족스러우면 ``Save and " +"continue``(번역을 저장하고 다음 미번역 문장으로 이동), ``Save and stay``(번역" +"을 저장하고 해당 페이지에 머무르기), ``Suggest`` (다른 사용자가 볼 수 있도록 " +"번역을 제안 항목에 추가), ``Skip``(아무것도 저장하지 않고 다음 미번역 문장으" +"로 이동) 중 하나를 선택하면 됩니다." #: ../../source/contributor-how-to-contribute-translations.rst:54 msgid "" "In order to help with the translations, you can see on the bottom the " "``Nearby strings``, the ``Comments`` (from other contributors), the " "``Automatic suggestions`` (from machine translation engines), the " -"translations in ``Other languages``, and the ``History`` of translations " -"for this string." +"translations in ``Other languages``, and the ``History`` of translations for " +"this string." msgstr "" -"번역에 도움을 주기위해 하단에서 `주변 문자열``, ``의견``(다른 기여자의), ``자동 제안``(기계 번역의), ``다른 " -"언어``의 번역 및 해당 문장의 번역``히스토리``를 볼 수 있습니다." +"번역에 도움을 주기위해 하단에서 `주변 문자열``, ``의견``(다른 기여자의), ``자" +"동 제안``(기계 번역의), ``다른 언어``의 번역 및 해당 문장의 번역``히스토리``" +"를 볼 수 있습니다." #: ../../source/contributor-how-to-contribute-translations.rst:59 msgid "" -"On the right, under the ``String information`` section, you can also " -"click the link under ``Source string location`` in order to view the " -"source of the doc file containing the string." -msgstr "오른쪽의 ``문자열 정보``에서 ``원본 문자열 위치``를 클릭하여 해당 문장이 포함된 문서의 파일 소스를 볼 수도 있습니다." +"On the right, under the ``String information`` section, you can also click " +"the link under ``Source string location`` in order to view the source of the " +"doc file containing the string." +msgstr "" +"오른쪽의 ``문자열 정보``에서 ``원본 문자열 위치``를 클릭하여 해당 문장이 포함" +"된 문서의 파일 소스를 볼 수도 있습니다." #: ../../source/contributor-how-to-contribute-translations.rst:63 msgid "" -"For more information about translating using Weblate, you can check out " -"this `in-depth guide " -"`_." +"For more information about translating using Weblate, you can check out this " +"`in-depth guide `_." msgstr "" -"Weblate를 통한 번역에 대한 자세한 정보는 `in-depth guide " -"`_를 확인하세요." +"Weblate를 통한 번역에 대한 자세한 정보는 `in-depth guide `_를 확인하세요." #: ../../source/contributor-how-to-contribute-translations.rst:67 msgid "Add new languages" @@ -438,12 +447,13 @@ msgstr "새 언어 추가" #: ../../source/contributor-how-to-contribute-translations.rst:69 msgid "" -"If you want to add a new language, you will first have to contact us, " -"either on `Slack `_, or by opening an issue" -" on our `GitHub repo `_." +"If you want to add a new language, you will first have to contact us, either " +"on `Slack `_, or by opening an issue on our " +"`GitHub repo `_." msgstr "" -"새 언어를 추가하려면, `Slack `에 문의하거나 `GitHub repo " -"`_에서 issue에 들어가 문의 해야 합니다." +"새 언어를 추가하려면, `Slack `에 문의하거나 " +"`GitHub repo `_에서 issue에 들어가 문의 해야 " +"합니다." #: ../../source/contributor-how-to-develop-in-vscode-dev-containers.rst:2 msgid "Develop in VSCode Dev Containers" @@ -451,49 +461,52 @@ msgstr "VSCode Dev Container에서 개발" #: ../../source/contributor-how-to-develop-in-vscode-dev-containers.rst:4 msgid "" -"When working on the Flower framework we want to ensure that all " -"contributors use the same developer environment to format code or run " -"tests. For this purpose we are using the VSCode Remote Containers " -"extension. What is it? Read the following quote:" +"When working on the Flower framework we want to ensure that all contributors " +"use the same developer environment to format code or run tests. For this " +"purpose we are using the VSCode Remote Containers extension. What is it? " +"Read the following quote:" msgstr "" -"Flower 프레임워크 작업시, 모든 기여자들이 코드 포맷팅이나 테스트 실행을 위해 동일한 개발 환경을 사용하길 원합니다. 이를 " -"위해 VSCode Remote Containers 확장을 사용하고 있습니다. 그것이 무엇인지 알아보기 위해 다음 인용문을 " -"읽어보세요:" +"Flower 프레임워크 작업시, 모든 기여자들이 코드 포맷팅이나 테스트 실행을 위해 " +"동일한 개발 환경을 사용하길 원합니다. 이를 위해 VSCode Remote Containers 확장" +"을 사용하고 있습니다. 그것이 무엇인지 알아보기 위해 다음 인용문을 읽어보세요:" #: ../../source/contributor-how-to-develop-in-vscode-dev-containers.rst:7 msgid "" -"The Visual Studio Code Remote - Containers extension lets you use a " -"Docker container as a fully-featured development environment. It allows " -"you to open any folder inside (or mounted into) a container and take " -"advantage of Visual Studio Code's full feature set. A " -":code:`devcontainer.json` file in your project tells VS Code how to " -"access (or create) a development container with a well-defined tool and " -"runtime stack. This container can be used to run an application or to " -"separate tools, libraries, or runtimes needed for working with a " -"codebase." -msgstr "" -"Visual Studio Code Remote - 컨테이너 확장을 사용하면 Docker 컨테이너를 모든 기능을 갖춘 개발 환경으로 " -"사용할 수 있습니다. 이 확장 기능을 사용하면 컨테이너 내부(또는 컨테이너에 마운트된)의 모든 폴더를 열고 Visual Studio" -" Code의 모든 기능을 활용할 수 있습니다. 프로젝트에 있는 :code:`devcontainer.json` 파일은 잘 정의된 " -"도구와 런타임 스택을 사용하여 개발 컨테이너에 액세스(또는 생성)하는 방법을 VS Code에 알려줍니다. 이 컨테이너는 " -"애플리케이션을 실행하거나 코드베이스 작업에 필요한 도구, 라이브러리 또는 런타임을 분리하는 데 사용할 수 있습니다." +"The Visual Studio Code Remote - Containers extension lets you use a Docker " +"container as a fully-featured development environment. It allows you to open " +"any folder inside (or mounted into) a container and take advantage of Visual " +"Studio Code's full feature set. A :code:`devcontainer.json` file in your " +"project tells VS Code how to access (or create) a development container with " +"a well-defined tool and runtime stack. This container can be used to run an " +"application or to separate tools, libraries, or runtimes needed for working " +"with a codebase." +msgstr "" +"Visual Studio Code Remote - 컨테이너 확장을 사용하면 Docker 컨테이너를 모든 " +"기능을 갖춘 개발 환경으로 사용할 수 있습니다. 이 확장 기능을 사용하면 컨테이" +"너 내부(또는 컨테이너에 마운트된)의 모든 폴더를 열고 Visual Studio Code의 모" +"든 기능을 활용할 수 있습니다. 프로젝트에 있는 :code:`devcontainer.json` 파일" +"은 잘 정의된 도구와 런타임 스택을 사용하여 개발 컨테이너에 액세스(또는 생성)" +"하는 방법을 VS Code에 알려줍니다. 이 컨테이너는 애플리케이션을 실행하거나 코" +"드베이스 작업에 필요한 도구, 라이브러리 또는 런타임을 분리하는 데 사용할 수 " +"있습니다." #: ../../source/contributor-how-to-develop-in-vscode-dev-containers.rst:9 msgid "" -"Workspace files are mounted from the local file system or copied or " -"cloned into the container. Extensions are installed and run inside the " -"container, where they have full access to the tools, platform, and file " -"system. This means that you can seamlessly switch your entire development" -" environment just by connecting to a different container." +"Workspace files are mounted from the local file system or copied or cloned " +"into the container. Extensions are installed and run inside the container, " +"where they have full access to the tools, platform, and file system. This " +"means that you can seamlessly switch your entire development environment " +"just by connecting to a different container." msgstr "" -"작업 공간 파일은 로컬 파일 시스템에서 마운트되거나 컨테이너에 복사 또는 클론됩니다. 확장 프로그램은 컨테이너 내부에 설치되고 " -"실행되며, 도구, 플랫폼 및 파일 시스템에 완전한 접근 권한을 갖습니다. 이는 다른 컨테이너에 연결하는 것만으로 전체 개발 환경을 " -"원활하게 전환할 수 있음을 의미합니다." +"작업 공간 파일은 로컬 파일 시스템에서 마운트되거나 컨테이너에 복사 또는 클론" +"됩니다. 확장 프로그램은 컨테이너 내부에 설치되고 실행되며, 도구, 플랫폼 및 파" +"일 시스템에 완전한 접근 권한을 갖습니다. 이는 다른 컨테이너에 연결하는 것만으" +"로 전체 개발 환경을 원활하게 전환할 수 있음을 의미합니다." #: ../../source/contributor-how-to-develop-in-vscode-dev-containers.rst:11 msgid "" -"Source: `Official VSCode documentation " -"`_" +"Source: `Official VSCode documentation `_" msgstr "출처 : 공식 VSCode 문서" #: ../../source/contributor-how-to-develop-in-vscode-dev-containers.rst:15 @@ -502,52 +515,57 @@ msgstr "시작하기" #: ../../source/contributor-how-to-develop-in-vscode-dev-containers.rst:17 msgid "" -"Configuring and setting up the :code:`Dockerfile` as well the " -"configuration for the devcontainer can be a bit more involved. The good " -"thing is you don't have to do it. Usually it should be enough to install " -"`Docker `_ on your system and " -"ensure its available on your command line. Additionally, install the " -"`VSCode Containers Extension `_." -msgstr "" -"`Dockerfile`을 설정하고 구성하는 것과 개발 컨테이너 구성은 약간 복잡할 수 있습니다. 다행히도, 이를 직접 할 필요는 " -"없습니다. 일반적으로 시스템에 `Docker `_를 " -"설치하고 커맨드 라인에서 사용할 수 있는지 확인하는 것으로 충분합니다. 추가로 `VSCode Containers Extension " +"Configuring and setting up the :code:`Dockerfile` as well the configuration " +"for the devcontainer can be a bit more involved. The good thing is you don't " +"have to do it. Usually it should be enough to install `Docker `_ on your system and ensure its available on " +"your command line. Additionally, install the `VSCode Containers Extension " +"`_." +msgstr "" +"`Dockerfile`을 설정하고 구성하는 것과 개발 컨테이너 구성은 약간 복잡할 수 있" +"습니다. 다행히도, 이를 직접 할 필요는 없습니다. 일반적으로 시스템에 `Docker " +"`_를 설치하고 커맨드 라인에서 사용" +"할 수 있는지 확인하는 것으로 충분합니다. 추가로 `VSCode Containers Extension " "`_을 설치하세요." #: ../../source/contributor-how-to-develop-in-vscode-dev-containers.rst:19 msgid "" -"Now you should be good to go. When starting VSCode, it will ask you to " -"run in the container environment and - if you confirm - automatically " -"build the container and use it. To manually instruct VSCode to use the " -"devcontainer, you can, after installing the extension, click the green " -"area in the bottom left corner of your VSCode window and select the " -"option *(Re)Open Folder in Container*." +"Now you should be good to go. When starting VSCode, it will ask you to run " +"in the container environment and - if you confirm - automatically build the " +"container and use it. To manually instruct VSCode to use the devcontainer, " +"you can, after installing the extension, click the green area in the bottom " +"left corner of your VSCode window and select the option *(Re)Open Folder in " +"Container*." msgstr "" -"이제 준비가 완료되었습니다. VSCode를 시작하면 컨테이너 환경에서 실행할지를 묻고, 확인하면 자동으로 컨테이너를 빌드하고 사용할" -" 것입니다. VSCode에 수동으로 개발 컨테이너를 사용하도록 지시하려면, 확장을 설치한 후, VSCode 창의 왼쪽 하단에 있는 " -"초록색 부을 클릭하고 *(Re)Open Folder in Container* 옵션을 선택하세요." +"이제 준비가 완료되었습니다. VSCode를 시작하면 컨테이너 환경에서 실행할지를 묻" +"고, 확인하면 자동으로 컨테이너를 빌드하고 사용할 것입니다. VSCode에 수동으로 " +"개발 컨테이너를 사용하도록 지시하려면, 확장을 설치한 후, VSCode 창의 왼쪽 하" +"단에 있는 초록색 부을 클릭하고 *(Re)Open Folder in Container* 옵션을 선택하세" +"요." #: ../../source/contributor-how-to-develop-in-vscode-dev-containers.rst:21 msgid "" -"In some cases your setup might be more involved. For those cases consult " -"the following sources:" -msgstr "경우에 따라 설정이 더 복잡할 수도 있습니다. 이러한 경우에는 다음 소스를 참조하세요:" +"In some cases your setup might be more involved. For those cases consult the " +"following sources:" +msgstr "" +"경우에 따라 설정이 더 복잡할 수도 있습니다. 이러한 경우에는 다음 소스를 참조" +"하세요:" #: ../../source/contributor-how-to-develop-in-vscode-dev-containers.rst:23 msgid "" -"`Developing inside a Container " -"`_" +"`Developing inside a Container `_" msgstr "" -"`컨테이너 내부 개발`_" +"`컨테이너 내부 개발`_" #: ../../source/contributor-how-to-develop-in-vscode-dev-containers.rst:24 msgid "" -"`Remote development in Containers " -"`_" -msgstr "`컨테이너 원격 개발`_" +"`Remote development in Containers `_" +msgstr "" +"`컨테이너 원격 개발`_" #: ../../source/contributor-how-to-install-development-versions.rst:2 msgid "Install development versions" @@ -563,19 +581,20 @@ msgstr "Poetry 사용하기(권장)" #: ../../source/contributor-how-to-install-development-versions.rst:10 msgid "" -"Install a ``flwr`` pre-release from PyPI: update the ``flwr`` dependency " -"in ``pyproject.toml`` and then reinstall (don't forget to delete " -"``poetry.lock`` (``rm poetry.lock``) before running ``poetry install``)." +"Install a ``flwr`` pre-release from PyPI: update the ``flwr`` dependency in " +"``pyproject.toml`` and then reinstall (don't forget to delete ``poetry." +"lock`` (``rm poetry.lock``) before running ``poetry install``)." msgstr "" -"PyPI에서 ``flwr`` 사전 릴리스 설치하기: ``pyproject.toml``에서 ``flwr``의 dependency를 " -"업데이트한 다음, 재설치하세요(``poetry 설치``이전에 ``poetry.lock`` (``rm poetry.lock``)를 " -"제거하는 것을 잊지 마세요)." +"PyPI에서 ``flwr`` 사전 릴리스 설치하기: ``pyproject.toml``에서 ``flwr``의 " +"의존성을 업데이트한 다음, 재설치하세요(``poetry 설치``이전에 ``poetry.lock`` " +"(``rm poetry.lock``)를 제거하는 것을 잊지 마세요)." #: ../../source/contributor-how-to-install-development-versions.rst:12 msgid "" "``flwr = { version = \"1.0.0a0\", allow-prereleases = true }`` (without " "extras)" -msgstr "``flwr = { version = \"1.0.0a0\", allow-prereleases = true }`` (extras 제외)" +msgstr "" +"``flwr = { version = \"1.0.0a0\", allow-prereleases = true }`` (extras 제외)" #: ../../source/contributor-how-to-install-development-versions.rst:13 msgid "" @@ -587,9 +606,11 @@ msgstr "" #: ../../source/contributor-how-to-install-development-versions.rst:15 msgid "" -"Install ``flwr`` from a local copy of the Flower source code via " -"``pyproject.toml``:" -msgstr "``pyproject.toml``을 통해 Flower 소스 코드의 로컬 복사본에서 ``flwr``을 설치하세요:" +"Install ``flwr`` from a local copy of the Flower source code via ``pyproject." +"toml``:" +msgstr "" +"``pyproject.toml``을 통해 Flower 소스 코드의 로컬 복사본에서 ``flwr``을 설치" +"하세요:" #: ../../source/contributor-how-to-install-development-versions.rst:17 msgid "``flwr = { path = \"../../\", develop = true }`` (without extras)" @@ -597,11 +618,11 @@ msgstr "``flwr = { path = \"../../\", develop = true }`` (extras 제외)" #: ../../source/contributor-how-to-install-development-versions.rst:18 msgid "" -"``flwr = { path = \"../../\", develop = true, extras = [\"simulation\"] " -"}`` (with extras)" +"``flwr = { path = \"../../\", develop = true, extras = [\"simulation\"] }`` " +"(with extras)" msgstr "" -"``flwr = { path = \"../../\", develop = true, extras = [\"simulation\"] " -"}`` (extras 포함)" +"``flwr = { path = \"../../\", develop = true, extras = [\"simulation\"] }`` " +"(extras 포함)" #: ../../source/contributor-how-to-install-development-versions.rst:20 msgid "Install ``flwr`` from a local wheel file via ``pyproject.toml``:" @@ -609,11 +630,11 @@ msgstr "``pyproject.toml``을 통해 로컬 wheel file에서 ``flwr``을 설치 #: ../../source/contributor-how-to-install-development-versions.rst:22 msgid "" -"``flwr = { path = \"../../dist/flwr-1.8.0-py3-none-any.whl\" }`` (without" -" extras)" +"``flwr = { path = \"../../dist/flwr-1.8.0-py3-none-any.whl\" }`` (without " +"extras)" msgstr "" -"``flwr = { path = \"../../dist/flwr-1.8.0-py3-none-any.whl\" }`` (extras " -"제외)" +"``flwr = { path = \"../../dist/flwr-1.8.0-py3-none-any.whl\" }`` (extras 제" +"외)" #: ../../source/contributor-how-to-install-development-versions.rst:23 msgid "" @@ -629,8 +650,8 @@ msgid "" "Dependency Specification `_" msgstr "" -"자세한 내용은 Poetry 문서를 참고하세요: `Poetry Dependency Specification `_" +"자세한 내용은 Poetry 문서를 참고하세요: `Poetry Dependency Specification " +"`_" #: ../../source/contributor-how-to-install-development-versions.rst:28 msgid "Using pip (recommended on Colab)" @@ -638,7 +659,7 @@ msgstr "pip 사용하기(Colab에서 권장)" #: ../../source/contributor-how-to-install-development-versions.rst:30 msgid "Install a ``flwr`` pre-release from PyPI:" -msgstr "PyPI에서 ``flwr`` 사전 릴리스를 설치하기:" +msgstr "PyPI에서 ``flwr`` 사전 릴리즈를 설치하기:" #: ../../source/contributor-how-to-install-development-versions.rst:32 msgid "``pip install -U --pre flwr`` (without extras)" @@ -653,8 +674,8 @@ msgid "" "Python packages can be installed from git repositories. Use one of the " "following commands to install the Flower directly from GitHub." msgstr "" -"Python 패키지는 git 저장소에서 설치할 수 있습니다. 다음 명령어 중 하나를 사용하여 GitHub에서 직접 Flower를 " -"설치하세요." +"Python 패키지는 git 저장소에서 설치할 수 있습니다. 다음 명령어 중 하나를 사용" +"하여 GitHub에서 직접 Flower를 설치하세요." #: ../../source/contributor-how-to-install-development-versions.rst:37 msgid "Install ``flwr`` from the default GitHub branch (``main``):" @@ -662,9 +683,9 @@ msgstr "기본 GitHub branch (``main``)에서 ``flwr`` 를 설치하기:" #: ../../source/contributor-how-to-install-development-versions.rst:39 msgid "" -"``pip install flwr@git+https://github.com/adap/flower.git`` (without " -"extras)" -msgstr "``pip install flwr@git+https://github.com/adap/flower.git`` (extras 제외)" +"``pip install flwr@git+https://github.com/adap/flower.git`` (without extras)" +msgstr "" +"``pip install flwr@git+https://github.com/adap/flower.git`` (extras 제외)" #: ../../source/contributor-how-to-install-development-versions.rst:40 msgid "" @@ -688,11 +709,11 @@ msgstr "" #: ../../source/contributor-how-to-install-development-versions.rst:45 msgid "" -"``pip install flwr[simulation]@git+https://github.com/adap/flower.git" -"@branch-name`` (with extras)" +"``pip install flwr[simulation]@git+https://github.com/adap/flower.git@branch-" +"name`` (with extras)" msgstr "" -"``pip install flwr[simulation]@git+https://github.com/adap/flower.git" -"@branch-name`` (extras 포함)" +"``pip install flwr[simulation]@git+https://github.com/adap/flower.git@branch-" +"name`` (extras 포함)" #: ../../source/contributor-how-to-install-development-versions.rst:49 msgid "Open Jupyter Notebooks on Google Colab" @@ -703,32 +724,32 @@ msgid "" "Open the notebook ``doc/source/tutorial-series-get-started-with-flower-" "pytorch.ipynb``:" msgstr "" -"``doc/source/tutorial-series-get-started-with-flower-" -"pytorch.ipynb``notebook을 엽니다:" +"``doc/source/tutorial-series-get-started-with-flower-pytorch.ipynb``notebook" +"을 엽니다:" #: ../../source/contributor-how-to-install-development-versions.rst:53 msgid "" -"https://colab.research.google.com/github/adap/flower/blob/main/doc/source" -"/tutorial-series-get-started-with-flower-pytorch.ipynb" +"https://colab.research.google.com/github/adap/flower/blob/main/doc/source/" +"tutorial-series-get-started-with-flower-pytorch.ipynb" msgstr "" -"https://colab.research.google.com/github/adap/flower/blob/main/doc/source" -"/tutorial-series-get-started-with-flower-pytorch.ipynb" +"https://colab.research.google.com/github/adap/flower/blob/main/doc/source/" +"tutorial-series-get-started-with-flower-pytorch.ipynb" #: ../../source/contributor-how-to-install-development-versions.rst:55 msgid "" -"Open a development version of the same notebook from branch `branch-name`" -" by changing ``main`` to ``branch-name`` (right after ``blob``):" +"Open a development version of the same notebook from branch `branch-name` by " +"changing ``main`` to ``branch-name`` (right after ``blob``):" msgstr "" -"``main``을 ``branch-name``(``blob`` 바로 뒤)으로 변경하여 동일한 notebook의 개발 버전을 브랜치 " -"`branch-name`에서 엽니다 :" +"``main``을 ``branch-name``(``blob`` 바로 뒤)으로 변경하여 동일한 notebook의 " +"개발 버전을 브랜치 `branch-name`에서 엽니다 :" #: ../../source/contributor-how-to-install-development-versions.rst:57 msgid "" -"https://colab.research.google.com/github/adap/flower/blob/branch-" -"name/doc/source/tutorial-series-get-started-with-flower-pytorch.ipynb" +"https://colab.research.google.com/github/adap/flower/blob/branch-name/doc/" +"source/tutorial-series-get-started-with-flower-pytorch.ipynb" msgstr "" -"https://colab.research.google.com/github/adap/flower/blob/branch-" -"name/doc/source/tutorial-series-get-started-with-flower-pytorch.ipynb" +"https://colab.research.google.com/github/adap/flower/blob/branch-name/doc/" +"source/tutorial-series-get-started-with-flower-pytorch.ipynb" #: ../../source/contributor-how-to-install-development-versions.rst:59 msgid "Install a `whl` on Google Colab:" @@ -736,9 +757,11 @@ msgstr "Google Colab에서 `whl` 설치하기:" #: ../../source/contributor-how-to-install-development-versions.rst:61 msgid "" -"In the vertical icon grid on the left hand side, select ``Files`` > " -"``Upload to session storage``" -msgstr "왼쪽의 수직 아이콘 그리드에서 ``Files`` > ``Upload to session storage``를 선택하세요" +"In the vertical icon grid on the left hand side, select ``Files`` > ``Upload " +"to session storage``" +msgstr "" +"왼쪽의 수직 아이콘 그리드에서 ``Files`` > ``Upload to session storage``를 선" +"택하세요" #: ../../source/contributor-how-to-install-development-versions.rst:62 msgid "Upload the whl (e.g., ``flwr-1.8.0-py3-none-any.whl``)" @@ -746,13 +769,13 @@ msgstr "whl (예:``flwr-1.8.0-py3-none-any.whl``)을 업로드하세요" #: ../../source/contributor-how-to-install-development-versions.rst:63 msgid "" -"Change ``!pip install -q 'flwr[simulation]' torch torchvision " -"matplotlib`` to ``!pip install -q 'flwr-1.8.0-py3-none-" -"any.whl[simulation]' torch torchvision matplotlib``" +"Change ``!pip install -q 'flwr[simulation]' torch torchvision matplotlib`` " +"to ``!pip install -q 'flwr-1.8.0-py3-none-any.whl[simulation]' torch " +"torchvision matplotlib``" msgstr "" -"``!pip install -q 'flwr[simulation]' torch torchvision matplotlib``를 " -"``!pip install -q 'flwr-1.8.0-py3-none-any.whl[simulation]' torch " -"torchvision matplotlib``로 바꾸세요" +"``!pip install -q 'flwr[simulation]' torch torchvision matplotlib``를 ``!pip " +"install -q 'flwr-1.8.0-py3-none-any.whl[simulation]' torch torchvision " +"matplotlib``로 바꾸세요" #: ../../source/contributor-how-to-release-flower.rst:2 msgid "Release Flower" @@ -762,7 +785,8 @@ msgstr "Flower 릴리즈 하기" msgid "" "This document describes the current release process. It may or may not " "change in the future." -msgstr "이 문서는 현재 릴리즈 과정을 설명합니다. 이는 앞으로 변경될 수도 있습니다." +msgstr "" +"이 문서는 현재 릴리즈 과정을 설명합니다. 이는 앞으로 변경될 수도 있습니다." #: ../../source/contributor-how-to-release-flower.rst:7 msgid "During the release" @@ -770,12 +794,11 @@ msgstr "릴리즈 동안에" #: ../../source/contributor-how-to-release-flower.rst:9 msgid "" -"The version number of a release is stated in ``pyproject.toml``. To " -"release a new version of Flower, the following things need to happen (in " -"that order):" +"The version number of a release is stated in ``pyproject.toml``. To release " +"a new version of Flower, the following things need to happen (in that order):" msgstr "" -"릴리즈의 버전 번호는 ``pyproject.toml``에 명시되어 있습니다. Flower의 새 버전을 릴리즈하려면 다음 작업이 " -"순서대로 수행되어야 합니다:" +"릴리즈의 버전 번호는 ``pyproject.toml``에 명시되어 있습니다. Flower의 새 버전" +"을 릴리즈하려면 다음 작업이 순서대로 수행되어야 합니다:" #: ../../source/contributor-how-to-release-flower.rst:11 msgid "" @@ -783,39 +806,42 @@ msgid "" "order to add every new change to the changelog (feel free to make manual " "changes to the changelog afterwards until it looks good)." msgstr "" -"모든 새로운 변경 사항을 변경 로그에 추가하기 위해``python3 " -"src/py/flwr_tool/update_changelog.py ``을 실행합니다 (변경 로그가 " -"만족스러워질 때까지 수동으로 변경해도 됩니다)." +"모든 새로운 변경 사항을 변경 로그에 추가하기 위해``python3 src/py/flwr_tool/" +"update_changelog.py ``을 실행합니다 (변경 로그가 만족스러워질 " +"때까지 수동으로 변경해도 됩니다)." #: ../../source/contributor-how-to-release-flower.rst:12 msgid "" -"Once the changelog has been updated with all the changes, run ``./dev" -"/prepare-release-changelog.sh v``, where ```` " -"is the version stated in ``pyproject.toml`` (notice the ``v`` added " -"before it). This will replace the ``Unreleased`` header of the changelog " -"by the version and current date, and it will add a thanking message for " -"the contributors. Open a pull request with those changes." +"Once the changelog has been updated with all the changes, run ``./dev/" +"prepare-release-changelog.sh v``, where ```` is " +"the version stated in ``pyproject.toml`` (notice the ``v`` added before it). " +"This will replace the ``Unreleased`` header of the changelog by the version " +"and current date, and it will add a thanking message for the contributors. " +"Open a pull request with those changes." msgstr "" -"모든 변경 사항으로 변경 로그가 업데이트되면,``./dev/prepare-release-changelog.sh " -"v``을 실행합니다. 여기서 ````은 ``pyproject.toml``에 명시된 " -"버전 번호입니다 (앞에 ``v``가 추가된 것을 주의하세요). 이 명령어는 변경 로그의 ``Unreleased``헤더를 해당 버전과" -" 현재 날짜로 교체하고, 기여자들에게 감사 메시지가 추가됩니다. 이러한 변경 사항으로 pull request합니다." +"모든 변경 사항으로 변경 로그가 업데이트되면,``./dev/prepare-release-" +"changelog.sh v``을 실행합니다. 여기서 ````은 " +"``pyproject.toml``에 명시된 버전 번호입니다 (앞에 ``v``가 추가된 것을 주의하" +"세요). 이 명령어는 변경 로그의 ``Unreleased``헤더를 해당 버전과 현재 날짜로 " +"교체하고, 기여자들에게 감사 메시지가 추가됩니다. 이러한 변경 사항으로 pull " +"request합니다." #: ../../source/contributor-how-to-release-flower.rst:13 msgid "" "Once the pull request is merged, tag the release commit with the version " -"number as soon as the PR is merged: ``git tag v`` (notice " -"the ``v`` added before the version number), then ``git push --tags``. " -"This will create a draft release on GitHub containing the correct " -"artifacts and the relevant part of the changelog." +"number as soon as the PR is merged: ``git tag v`` (notice the " +"``v`` added before the version number), then ``git push --tags``. This will " +"create a draft release on GitHub containing the correct artifacts and the " +"relevant part of the changelog." msgstr "" "pull request가 병합되면, PR이 병합되는 즉시 버전 번호로 릴리즈 커밋에 태그를 " -"지정합니다:``git tag v`` (버전 번호 앞에 ``v``가 추가된 것을 " -"확인), 그 다음 ``git push --tags``. 이렇게 하면 올바른 아티팩트와 변경 " -"로그의 관련 부분이 포함된 초안 릴리즈가 GitHub에 생성됩니다." +"지정합니다:``git tag v`` (버전 번호 앞에 ``v``가 추가된 것을 확" +"인), 그 다음 ``git push --tags``. 이렇게 하면 올바른 아티팩트와 변경 로그의 " +"관련 부분이 포함된 초안 릴리즈가 GitHub에 생성됩니다." #: ../../source/contributor-how-to-release-flower.rst:14 -msgid "Check the draft release on GitHub, and if everything is good, publish it." +msgid "" +"Check the draft release on GitHub, and if everything is good, publish it." msgstr "GitHub에서 릴리즈 초안을 확인하고, 모든 것이 양호하면 게시하세요." #: ../../source/contributor-how-to-release-flower.rst:15 @@ -824,10 +850,10 @@ msgstr "Docker 이미지 빌드를 위해 CI를 트리거합니다." #: ../../source/contributor-how-to-release-flower.rst:17 msgid "" -"To trigger the workflow, a collaborator must create a " -"``workflow_dispatch`` event in the GitHub CI. This can be done either " -"through the UI or via the GitHub CLI. The event requires only one input, " -"the Flower version, to be released." +"To trigger the workflow, a collaborator must create a ``workflow_dispatch`` " +"event in the GitHub CI. This can be done either through the UI or via the " +"GitHub CLI. The event requires only one input, the Flower version, to be " +"released." msgstr "" "워크플로우를 트리거하려면 공동 작업자가 GitHub CI에서 ``workflow_dispatch``" "를 생성해야 합니다. 이 작업은 UI 또는 GitHub CLI 를 통해 수행할 수 있습니다. " @@ -839,18 +865,19 @@ msgstr "**UI를 통해서**" #: ../../source/contributor-how-to-release-flower.rst:23 msgid "" -"Go to the ``Build docker images`` workflow `page " -"`_." +"Go to the ``Build docker images`` workflow `page `_." msgstr "" "``Build docker images`` 워크플로우 `페이지 `_로 이동합니다." #: ../../source/contributor-how-to-release-flower.rst:24 msgid "" -"Click on the ``Run workflow`` button and type the new version of Flower " -"in the ``Version of Flower`` input field." -msgstr "``Run workflow`` 버튼을 누르고 ``Version of Flower``에 Flower의 새버전을 " -"입력합니다." +"Click on the ``Run workflow`` button and type the new version of Flower in " +"the ``Version of Flower`` input field." +msgstr "" +"``Run workflow`` 버튼을 누르고 ``Version of Flower``에 Flower의 새버전을 입력" +"합니다." #: ../../source/contributor-how-to-release-flower.rst:25 msgid "Click on the **green** ``Run workflow`` button." @@ -864,16 +891,17 @@ msgstr "**GitHub CI를 통해서**" msgid "" "Make sure you are logged in via ``gh auth login`` and that the current " "working directory is the root of the Flower repository." -msgstr "``gh auth login``을 통해 로그인 했는지, 현재 작업 디렉토리가 Flower " -"리포지토리의 root인지 확인하세요." +msgstr "" +"``gh auth login``을 통해 로그인 했는지, 현재 작업 디렉토리가 Flower 리포지토" +"리의 root인지 확인하세요." #: ../../source/contributor-how-to-release-flower.rst:32 msgid "" "Trigger the workflow via ``gh workflow run docker-images.yml -f flwr-" "version=``." msgstr "" -"``gh workflow run docker-images.yml -f flwr-version=``을 통해 " -"워크플로우 를 트리거합니다." +"``gh workflow run docker-images.yml -f flwr-version=``을 통해 워" +"크플로우 를 트리거합니다." #: ../../source/contributor-how-to-release-flower.rst:35 msgid "After the release" @@ -897,10 +925,11 @@ msgstr "``changelog.md``에 ``Unreleased`` 섹션을 새로 추가합니다." #: ../../source/contributor-how-to-release-flower.rst:43 msgid "" -"Merge the pull request on the same day (i.e., before a new nightly " -"release gets published to PyPI)." -msgstr "pull request를 같은 날(즉, 새로운 nightly 릴리즈가 PyPI에 게시되기 전에) " -"병합하세요." +"Merge the pull request on the same day (i.e., before a new nightly release " +"gets published to PyPI)." +msgstr "" +"pull request를 같은 날(즉, 새로운 nightly 릴리즈가 PyPI에 게시되기 전에) 병합" +"하세요." #: ../../source/contributor-how-to-release-flower.rst:46 msgid "Publishing a pre-release" @@ -912,11 +941,11 @@ msgstr "사전 릴리즈 이름" #: ../../source/contributor-how-to-release-flower.rst:51 msgid "" -"PyPI supports pre-releases (alpha, beta, release candidate). Pre-releases" -" MUST use one of the following naming patterns:" +"PyPI supports pre-releases (alpha, beta, release candidate). Pre-releases " +"MUST use one of the following naming patterns:" msgstr "" -"PyPI는 사전 릴리즈(알파, 베타, 릴리스 후보)를 지원합니다. 사전 릴리즈는 " -"반드시 다음 명명 패턴 중 하나를 사용해야 합니다:" +"PyPI는 사전 릴리즈(알파, 베타, 릴리스 후보)를 지원합니다. 사전 릴리즈는 반드" +"시 다음 명명 패턴 중 하나를 사용해야 합니다:" #: ../../source/contributor-how-to-release-flower.rst:53 msgid "Alpha: ``MAJOR.MINOR.PATCHaN``" @@ -954,7 +983,8 @@ msgstr "``1.0.0rc1``" msgid "" "This is in line with PEP-440 and the recommendations from the Python " "Packaging Authority (PyPA):" -msgstr "이는 PEP-440 및 Python Packaging Authority (PyPA)의 권장 사항과 일치합니다:" +msgstr "" +"이는 PEP-440 및 Python Packaging Authority (PyPA)의 권장 사항과 일치합니다:" #: ../../source/contributor-how-to-release-flower.rst:67 msgid "`PEP-440 `_" @@ -962,37 +992,38 @@ msgstr "`PEP-440 `_" #: ../../source/contributor-how-to-release-flower.rst:68 msgid "" -"`PyPA Choosing a versioning scheme " -"`_" +"`PyPA Choosing a versioning scheme `_" msgstr "" "`PyPA 버전 관리 체계 선택하기 `_" #: ../../source/contributor-how-to-release-flower.rst:70 msgid "" -"Note that the approach defined by PyPA is not compatible with SemVer " -"2.0.0 spec, for details consult the `Semantic Versioning Specification " -"`_ (specifically item " -"11 on precedence)." +"Note that the approach defined by PyPA is not compatible with SemVer 2.0.0 " +"spec, for details consult the `Semantic Versioning Specification `_ (specifically item 11 on " +"precedence)." msgstr "" -"PyPA에서 정의한 접근 방식은 SemVer 2.0.0 사양과 호환되지 않으며, 자세한 " -"내용은`Semantic Versioning 관리 사양 `_ (특히 항목 11이 우선순위)을 참조하세요." +"PyPA에서 정의한 접근 방식은 SemVer 2.0.0 사양과 호환되지 않으며, 자세한 내용" +"은`Semantic Versioning 관리 사양 `_ (특히 항목 11이 우선순위)을 참조하세요." #: ../../source/contributor-how-to-release-flower.rst:73 msgid "Pre-release classification" msgstr "사전 릴리즈 분류" #: ../../source/contributor-how-to-release-flower.rst:75 -msgid "Should the next pre-release be called alpha, beta, or release candidate?" -msgstr "다음 사전 릴리를 알파, 베타 또는 릴리스 후보라고 불러야 하나요?" +msgid "" +"Should the next pre-release be called alpha, beta, or release candidate?" +msgstr "다음 사전 릴리즈를 알파, 베타 또는 릴리스 후보라고 불러야 하나요?" #: ../../source/contributor-how-to-release-flower.rst:77 msgid "" -"RC: feature complete, no known issues (apart from issues that are " -"classified as \"won't fix\" for the next stable release) - if no issues " -"surface this will become the next stable release" +"RC: feature complete, no known issues (apart from issues that are classified " +"as \"won't fix\" for the next stable release) - if no issues surface this " +"will become the next stable release" msgstr "" "RC: 기능 완료, 알려진 문제 없음(다음 stable 릴리즈에서 \"수정되지 않음\"으로 " "분류된 문제 제외) - 문제가 나타나지 않으면 다음 stable 릴리즈가 됩니다" @@ -1013,12 +1044,12 @@ msgstr "가상 환경 설정" msgid "" "It is recommended to run your Python setup within a virtual environment. " "This guide shows three different examples how to create a virtual " -"environment with pyenv virtualenv, poetry, or Anaconda. You can follow " -"the instructions or choose your preferred setup." +"environment with pyenv virtualenv, poetry, or Anaconda. You can follow the " +"instructions or choose your preferred setup." msgstr "" "가상 환경 내에서 파이썬 설정을 실행하는 것이 좋습니다. 이 가이드에서는 pyenv " -"virtualenv, poetry 또는 Anaconda를 사용하여 가상 환경을 만드는 세 가지 " -"예제를 보여줍니다. 안내를 따르거나 원하는 설정을 선택할 수 있습니다." +"virtualenv, poetry 또는 Anaconda를 사용하여 가상 환경을 만드는 세 가지 예제" +"를 보여줍니다. 안내를 따르거나 원하는 설정을 선택할 수 있습니다." #: ../../source/contributor-how-to-set-up-a-virtual-env.rst:9 msgid "Python Version" @@ -1027,23 +1058,21 @@ msgstr "Python 버전" #: ../../source/contributor-how-to-set-up-a-virtual-env.rst:11 #: ../../source/how-to-install-flower.rst:8 msgid "" -"Flower requires at least `Python 3.8 `_, " -"but `Python 3.10 `_ or above is " -"recommended." +"Flower requires at least `Python 3.8 `_, but " +"`Python 3.10 `_ or above is recommended." msgstr "" -"Flower는 `Python 3.8 `_이상이 필요하지만, `" -"Python 3.10 `_이상을 권장합니다." +"Flower는 `Python 3.8 `_이상이 필요하지만, " +"`Python 3.10 `_이상을 권장합니다." #: ../../source/contributor-how-to-set-up-a-virtual-env.rst:14 msgid "" -"Due to a known incompatibility with `ray " -"`_, we currently recommend utilizing at " -"most `Python 3.11 `_ for running Flower " -"simulations." +"Due to a known incompatibility with `ray `_, " +"we currently recommend utilizing at most `Python 3.11 `_ for running Flower simulations." msgstr "" -"`Ray `__와 호환되지 않는 것으로 알려져 " -"있으므로, 현재 Flower 시뮬레이션을 실행할 때는 최대 `Python 3.11 " -"`_을 사용하는 것이 좋습니다." +"`Ray `__와 호환되지 않는 것으로 알려져 있으므" +"로, 현재 Flower 시뮬레이션을 실행할 때는 최대 `Python 3.11 `_을 사용하는 것이 좋습니다." #: ../../source/contributor-how-to-set-up-a-virtual-env.rst:19 msgid "Virtualenv with Pyenv/Virtualenv" @@ -1051,23 +1080,23 @@ msgstr "Pyenv/Virtualenv를 사용한 가상 환경" #: ../../source/contributor-how-to-set-up-a-virtual-env.rst:21 msgid "" -"One of the recommended virtual environment is `pyenv " -"`_/`virtualenv `_. Please see `Flower examples " -"`_ for details." +"One of the recommended virtual environment is `pyenv `_/`virtualenv `_. " +"Please see `Flower examples `_ for details." msgstr "" -"권장 가상 환경 중 하나는 `pyenv `_/`" -"virtualenv `_입니다. 자세한 " -"내용은 `Flower examples `" -"_를 참조하세요." +"권장 가상 환경 중 하나는 `pyenv `_/" +"`virtualenv `_입니다. 자세한 내용" +"은 `Flower examples `_를 " +"참조하세요." #: ../../source/contributor-how-to-set-up-a-virtual-env.rst:23 msgid "" "Once Pyenv is set up, you can use it to install `Python Version 3.10 " "`_ or above:" msgstr "" -"Pyenv가 설정되면 이를 사용하여 'Python 버전 3.10 `_ 이상'을 설치할 수 있습니다:" +"Pyenv가 설정되면 이를 사용하여 'Python 버전 3.10 `_ 이상'을 설치할 수 있습니다:" #: ../../source/contributor-how-to-set-up-a-virtual-env.rst:29 msgid "Create the virtualenv with:" @@ -1083,19 +1112,20 @@ msgstr "Poetry를 사용한 가상 환경" #: ../../source/contributor-how-to-set-up-a-virtual-env.rst:46 msgid "" -"The Flower examples are based on `Poetry `_ to manage dependencies. After installing Poetry you " -"simply create a virtual environment with:" +"The Flower examples are based on `Poetry `_ " +"to manage dependencies. After installing Poetry you simply create a virtual " +"environment with:" msgstr "" -"Flower examples은 dependencies을 관리하기 위해 `Poetry `_를 기반으로 합니다. Poetry를 설치한 후 가상 환경을 생성하기만 " -"하면 됩니다:" +"Flower examples은 의존성을 관리하기 위해 `Poetry `_를 기반으로 합니다. Poetry를 설치한 후 가상 환경을 생성하기만 하면 " +"됩니다:" #: ../../source/contributor-how-to-set-up-a-virtual-env.rst:52 msgid "" -"If you open a new terminal you can activate the previously created " -"virtual environment with the following command:" -msgstr "새 터미널을 열면 다음 명령을 사용하여 이전에 생성한 가상 환경을 활성화할 수 " +"If you open a new terminal you can activate the previously created virtual " +"environment with the following command:" +msgstr "" +"새 터미널을 열면 다음 명령을 사용하여 이전에 생성한 가상 환경을 활성화할 수 " "있습니다:" #: ../../source/contributor-how-to-set-up-a-virtual-env.rst:60 @@ -1104,12 +1134,12 @@ msgstr "Anaconda를 사용한 가상 환경" #: ../../source/contributor-how-to-set-up-a-virtual-env.rst:62 msgid "" -"If you prefer to use Anaconda for your virtual environment then install " -"and setup the `conda `_ package. After setting it up you can " -"create a virtual environment with:" +"If you prefer to use Anaconda for your virtual environment then install and " +"setup the `conda `_ package. After setting it up you can create a virtual " +"environment with:" msgstr "" -"가상 환경에서 Anaconda를 사용하려면 `conda `_ 패키지를 설치 및 " "설정하세요. 설정 후 다음을 사용하여 가상 환경을 만들 수 있습니다:" @@ -1123,8 +1153,8 @@ msgstr "그다음은?" #: ../../source/contributor-how-to-set-up-a-virtual-env.rst:78 msgid "" -"As soon as you created your virtual environment you clone one of the " -"`Flower examples `_." +"As soon as you created your virtual environment you clone one of the `Flower " +"examples `_." msgstr "" "가상 환경을 생성하자마자 'Flower examples `_ 중 하나를 클론합니다." @@ -1139,25 +1169,24 @@ msgstr "프로젝트 레이아웃" #: ../../source/contributor-how-to-write-documentation.rst:8 msgid "" -"The Flower documentation lives in the ``doc`` directory. The Sphinx-based" -" documentation system supports both reStructuredText (``.rst`` files) and" -" Markdown (``.md`` files)." +"The Flower documentation lives in the ``doc`` directory. The Sphinx-based " +"documentation system supports both reStructuredText (``.rst`` files) and " +"Markdown (``.md`` files)." msgstr "" "Flower 문서는 ``doc`` 디렉토리에 있습니다. Sphinx 기반 문서 시스템은 " -"reStructuredText 텍스트(``.rst`` 파일)와 Markdown(``.md`` 파일)을 모두 " -"지원합니다." +"reStructuredText 텍스트(``.rst`` 파일)와 Markdown(``.md`` 파일)을 모두 지원합" +"니다." #: ../../source/contributor-how-to-write-documentation.rst:10 #: ../../source/contributor-tutorial-get-started-as-a-contributor.rst:169 msgid "" -"Note that, in order to build the documentation locally (with ``poetry run" -" make html``, like described below), `Pandoc " -"`_ needs to be installed on the " -"system." +"Note that, in order to build the documentation locally (with ``poetry run " +"make html``, like described below), `Pandoc `_ needs to be installed on the system." msgstr "" -"로컬에서 문서를 작성하려면(아래 설명과 같이 ``poetry run make html``로) `" -"Pandoc `_이 시스템에 설치되어 있어야 " -"합니다." +"로컬에서 문서를 작성하려면(아래 설명과 같이 ``poetry run make html``로) " +"`Pandoc `_이 시스템에 설치되어 있어야 합" +"니다." #: ../../source/contributor-how-to-write-documentation.rst:14 msgid "Edit an existing page" @@ -1170,7 +1199,8 @@ msgstr "doc/source/``에서 기존 ``.rst``(또는 ``.md``) 파일을 편집합 #: ../../source/contributor-how-to-write-documentation.rst:17 #: ../../source/contributor-how-to-write-documentation.rst:27 msgid "Compile the docs: ``cd doc``, then ``poetry run make html``" -msgstr "문서를 컴파일합니다: ``cd doc``, ``poetry run make html`` 순으로 컴파일합니다" +msgstr "" +"문서를 컴파일합니다: ``cd doc``, ``poetry run make html`` 순으로 컴파일합니다" #: ../../source/contributor-how-to-write-documentation.rst:18 #: ../../source/contributor-how-to-write-documentation.rst:28 @@ -1195,18 +1225,18 @@ msgstr "``index.rst``에서 새 rst로 연결합니다" #: ../../source/contributor-ref-good-first-contributions.rst:2 msgid "Good first contributions" -msgstr "좋은 첫 번째 기여" +msgstr "훌륭한 첫 번째 기여" #: ../../source/contributor-ref-good-first-contributions.rst:4 msgid "" -"We welcome contributions to Flower! However, it is not always easy to " -"know where to start. We therefore put together a few recommendations on " -"where to start to increase your chances of getting your PR accepted into " -"the Flower codebase." +"We welcome contributions to Flower! However, it is not always easy to know " +"where to start. We therefore put together a few recommendations on where to " +"start to increase your chances of getting your PR accepted into the Flower " +"codebase." msgstr "" "Flower에 대한 기여를 환영합니다! 하지만 어디서부터 시작해야 할지 알기란 쉽지 " -"않습니다. 그래서 저희는 여러분의 PR이 Flower 코드베이스에 채택될 가능성을 " -"높이기 위해 어디서부터 시작해야 하는지 몇 가지 권장 사항을 정리해 보았습니다." +"않습니다. 그래서 저희는 여러분의 PR이 Flower 코드베이스에 채택될 가능성을 높" +"이기 위해 어디서부터 시작해야 하는지 몇 가지 권장 사항을 정리해 보았습니다." #: ../../source/contributor-ref-good-first-contributions.rst:11 msgid "Where to start" @@ -1214,13 +1244,13 @@ msgstr "시작 위치" #: ../../source/contributor-ref-good-first-contributions.rst:13 msgid "" -"Until the Flower core library matures it will be easier to get PR's " -"accepted if they only touch non-core areas of the codebase. Good " -"candidates to get started are:" +"Until the Flower core library matures it will be easier to get PR's accepted " +"if they only touch non-core areas of the codebase. Good candidates to get " +"started are:" msgstr "" "Flower 코어 라이브러리가 완성될 때까지는 코드베이스의 비핵심 영역만 건드리는 " -"것이 PR을 승인받기가 더 쉬울 것입니다. 시작하기에 좋은 후보자는 다음과 " -"같습니다:" +"것이 PR을 승인받기가 더 쉬울 것입니다. 시작하기에 좋은 후보자는 다음과 같습니" +"다:" #: ../../source/contributor-ref-good-first-contributions.rst:17 msgid "Documentation: What's missing? What could be expressed more clearly?" @@ -1240,31 +1270,31 @@ msgstr "Flower Baselines 요청" #: ../../source/contributor-ref-good-first-contributions.rst:25 msgid "" -"If you are not familiar with Flower Baselines, you should probably check-" -"out our `contributing guide for baselines " -"`_." +"If you are not familiar with Flower Baselines, you should probably check-out " +"our `contributing guide for baselines `_." msgstr "" "Flower Baseline에 익숙하지 않다면 ' Baseline 기여 가이드 `_를 확인해보세요." #: ../../source/contributor-ref-good-first-contributions.rst:27 msgid "" -"You should then check out the open `issues " -"`_" -" for baseline requests. If you find a baseline that you'd like to work on" -" and that has no assignees, feel free to assign it to yourself and start " -"working on it!" +"You should then check out the open `issues `_ for baseline " +"requests. If you find a baseline that you'd like to work on and that has no " +"assignees, feel free to assign it to yourself and start working on it!" msgstr "" -"그런 다음 오픈 된 `이슈 `_에서 baseline " "요청을 확인해야 합니다. 작업하고 싶은 기준선을 찾았지만 담당자가 없는 경우, " "자유롭게 자신에게 할당하고 작업을 시작하세요!" #: ../../source/contributor-ref-good-first-contributions.rst:31 msgid "" -"Otherwise, if you don't find a baseline you'd like to work on, be sure to" -" open a new issue with the baseline request template!" -msgstr "그렇지 않으면 작업하고 싶은 baseline을 찾지 못하면 baseline 요청 템플릿으로 " +"Otherwise, if you don't find a baseline you'd like to work on, be sure to " +"open a new issue with the baseline request template!" +msgstr "" +"그렇지 않으면 작업하고 싶은 baseline을 찾지 못하면 baseline 요청 템플릿으로 " "새 이슈를 열어야 합니다!" #: ../../source/contributor-ref-good-first-contributions.rst:34 @@ -1274,8 +1304,8 @@ msgstr "예시 요청" #: ../../source/contributor-ref-good-first-contributions.rst:36 msgid "" "We wish we had more time to write usage examples because we believe they " -"help users to get started with building what they want to build. Here are" -" a few ideas where we'd be happy to accept a PR:" +"help users to get started with building what they want to build. Here are a " +"few ideas where we'd be happy to accept a PR:" msgstr "" "사용 예시는 사용자가 원하는 것을 구축하는 데 도움이 된다고 생각하기 때문에 " "더 많은 시간을 할애하여 작성할 수 있었으면 합니다. 다음은 저희가 기꺼이 PR을 " @@ -1299,15 +1329,15 @@ msgstr "Secure Aggregation 프로토콜" #: ../../source/contributor-ref-secure-aggregation-protocols.rst:4 msgid "" -"Include SecAgg, SecAgg+, and LightSecAgg protocol. The LightSecAgg " -"protocol has not been implemented yet, so its diagram and abstraction may" -" not be accurate in practice. The SecAgg protocol can be considered as a " -"special case of the SecAgg+ protocol." +"Include SecAgg, SecAgg+, and LightSecAgg protocol. The LightSecAgg protocol " +"has not been implemented yet, so its diagram and abstraction may not be " +"accurate in practice. The SecAgg protocol can be considered as a special " +"case of the SecAgg+ protocol." msgstr "" -"SecAgg, SecAgg+, LightSecAgg 프로토콜을 포함합니다. LightSecAgg 프로토콜은 " -"아직 구현되지 않았기 때문에 다이어그램과 추상화가 실제로는 정확하지 않을 수 " -"있습니다. SecAgg 프로토콜은 SecAgg+ 프로토콜의 특수한 경우로 간주할 수 " -"있습니다." +"SecAgg, SecAgg+, LightSecAgg 프로토콜을 포함합니다. LightSecAgg 프로토콜은 아" +"직 구현되지 않았기 때문에 다이어그램과 추상화가 실제로는 정확하지 않을 수 있" +"습니다. SecAgg 프로토콜은 SecAgg+ 프로토콜의 특수한 경우로 간주할 수 있습니" +"다." #: ../../source/contributor-ref-secure-aggregation-protocols.rst:8 msgid "The :code:`SecAgg+` abstraction" @@ -1317,18 +1347,18 @@ msgstr "The :code:`SecAgg+` 추상화" #: ../../source/contributor-ref-secure-aggregation-protocols.rst:161 msgid "" "In this implementation, each client will be assigned with a unique index " -"(int) for secure aggregation, and thus many python dictionaries used have" -" keys of int type rather than ClientProxy type." +"(int) for secure aggregation, and thus many python dictionaries used have " +"keys of int type rather than ClientProxy type." msgstr "" -"구현에서는 각 클라이언트에 secure aggregation를 위한 고유 인덱스(int)가 " -"할당되므로 사용되는 많은 파이썬 dictionaries에는 ClientProxy 타입이 아닌 int " -"타입의 키가 있습니다." +"구현에서는 각 클라이언트에 secure aggregation를 위한 고유 인덱스(int)가 할당" +"되므로 사용되는 많은 파이썬 dictionaries에는 ClientProxy 타입이 아닌 int 타입" +"의 키가 있습니다." #: ../../source/contributor-ref-secure-aggregation-protocols.rst:65 #: ../../source/contributor-ref-secure-aggregation-protocols.rst:198 msgid "" -"The Flower server will execute and process received results in the " -"following order:" +"The Flower server will execute and process received results in the following " +"order:" msgstr "Flower 서버는 수신된 결과를 다음 순서로 실행하고 처리합니다:" #: ../../source/contributor-ref-secure-aggregation-protocols.rst:159 @@ -1345,16 +1375,17 @@ msgstr "GitHub에서 기여하기" #: ../../source/contributor-tutorial-contribute-on-github.rst:4 msgid "" -"This guide is for people who want to get involved with Flower, but who " -"are not used to contributing to GitHub projects." -msgstr "이 가이드는 Flower에 참여하고 싶지만 GitHub 프로젝트에 기여하는 데 익숙하지 " +"This guide is for people who want to get involved with Flower, but who are " +"not used to contributing to GitHub projects." +msgstr "" +"이 가이드는 Flower에 참여하고 싶지만 GitHub 프로젝트에 기여하는 데 익숙하지 " "않은 분들을 위한 것입니다." #: ../../source/contributor-tutorial-contribute-on-github.rst:6 msgid "" -"If you're familiar with how contributing on GitHub works, you can " -"directly checkout our :doc:`getting started guide for contributors " -"`." +"If you're familiar with how contributing on GitHub works, you can directly " +"checkout our :doc:`getting started guide for contributors `." msgstr "" "깃허브에서 기여하는 방식에 익숙하다면 :doc:`기여자를 위한 시작 가이드" "`를 직접 확인하세요." @@ -1372,19 +1403,19 @@ msgid "" "Git is a distributed version control tool. This allows for an entire " "codebase's history to be stored and every developer's machine. It is a " "software that will need to be installed on your local machine, you can " -"follow this `guide `_ to set it up." +"follow this `guide `_ to set it up." msgstr "" "Git은 분산 버전 관리 도구입니다. 이를 통해 전체 코드베이스의 히스토리와 모든 " -"개발자의 컴퓨터를 저장할 수 있습니다. 로컬 컴퓨터에 설치해야 하는 " -"소프트웨어로, 이 `가이드 `_를 따라 설정할 수 있습니다." +"개발자의 컴퓨터를 저장할 수 있습니다. 로컬 컴퓨터에 설치해야 하는 소프트웨어" +"로, 이 `가이드 `_를 따라 설정할 수 있습니다." #: ../../source/contributor-tutorial-contribute-on-github.rst:16 msgid "" "GitHub, itself, is a code hosting platform for version control and " -"collaboration. It allows for everyone to collaborate and work from " -"anywhere on remote repositories." +"collaboration. It allows for everyone to collaborate and work from anywhere " +"on remote repositories." msgstr "" "GitHub는 그 자체로 버전 관리 및 협업을 위한 코드 호스팅 플랫폼입니다. 누구나 " "원격 레포지토리에서 어디서든 협업하고 작업할 수 있습니다." @@ -1393,19 +1424,20 @@ msgstr "" msgid "" "If you haven't already, you will need to create an account on `GitHub " "`_." -msgstr "아직 계정을 만들지 않았다면 `GitHub `_에서 계정을 " +msgstr "" +"아직 계정을 만들지 않았다면 `GitHub `_에서 계정을 " "만들어야 합니다." #: ../../source/contributor-tutorial-contribute-on-github.rst:20 msgid "" -"The idea behind the generic Git and GitHub workflow boils down to this: " -"you download code from a remote repository on GitHub, make changes " -"locally and keep track of them using Git and then you upload your new " -"history back to GitHub." +"The idea behind the generic Git and GitHub workflow boils down to this: you " +"download code from a remote repository on GitHub, make changes locally and " +"keep track of them using Git and then you upload your new history back to " +"GitHub." msgstr "" "일반적인 Git 및 GitHub 워크플로우의 기본 개념은 다음과 같이 요약됩니다. " -"GitHub의 원격 레포지토리에서 코드를 다운로드하고 로컬에서 변경한 후 Git을 " -"사용하여 추적한 다음 새 기록을 다시 GitHub에 업로드하는 것입니다." +"GitHub의 원격 레포지토리에서 코드를 다운로드하고 로컬에서 변경한 후 Git을 사" +"용하여 추적한 다음 새 기록을 다시 GitHub에 업로드하는 것입니다." #: ../../source/contributor-tutorial-contribute-on-github.rst:32 msgid "**Forking the Flower repository**" @@ -1413,25 +1445,25 @@ msgstr "**Flower 레포지토리 포크하기**" #: ../../source/contributor-tutorial-contribute-on-github.rst:24 msgid "" -"A fork is a personal copy of a GitHub repository. To create one for " -"Flower, you must navigate to ``_ (while " -"connected to your GitHub account) and click the ``Fork`` button situated " -"on the top right of the page." +"A fork is a personal copy of a GitHub repository. To create one for Flower, " +"you must navigate to ``_ (while connected to " +"your GitHub account) and click the ``Fork`` button situated on the top right " +"of the page." msgstr "" "포크는 GitHub 리포지토리의 개인 복사본입니다. Flower용 포크를 만들려면 " -"``_로 이동하여(GitHub 계정에 연결된 상태에서)" -" 페이지 오른쪽 상단에 있는 ``포크`` 버튼을 클릭해야 합니다." +"``_로 이동하여(GitHub 계정에 연결된 상태에" +"서) 페이지 오른쪽 상단에 있는 ``포크`` 버튼을 클릭해야 합니다." #: ../../source/contributor-tutorial-contribute-on-github.rst:29 msgid "" "You can change the name if you want, but this is not necessary as this " -"version of Flower will be yours and will sit inside your own account " -"(i.e., in your own list of repositories). Once created, you should see on" -" the top left corner that you are looking at your own version of Flower." +"version of Flower will be yours and will sit inside your own account (i.e., " +"in your own list of repositories). Once created, you should see on the top " +"left corner that you are looking at your own version of Flower." msgstr "" -"원하는 경우 이름을 변경할 수 있지만, 이 버전의 Flower는 자신의 계정(즉, " -"자신의 리포지토리 목록)에 위치하게 되므로 변경할 필요는 없습니다. 만들기가 " -"완료되면 왼쪽 상단에Flower 버전이 표시되는 것을 볼 수 있습니다." +"원하는 경우 이름을 변경할 수 있지만, 이 버전의 Flower는 자신의 계정(즉, 자신" +"의 리포지토리 목록)에 위치하게 되므로 변경할 필요는 없습니다. 만들기가 완료되" +"면 왼쪽 상단에Flower 버전이 표시되는 것을 볼 수 있습니다." #: ../../source/contributor-tutorial-contribute-on-github.rst:47 msgid "**Cloning your forked repository**" @@ -1440,27 +1472,29 @@ msgstr "**포크된 레포지토리 클론하기**" #: ../../source/contributor-tutorial-contribute-on-github.rst:35 msgid "" "The next step is to download the forked repository on your machine to be " -"able to make changes to it. On your forked repository page, you should " -"first click on the ``Code`` button on the right, this will give you the " -"ability to copy the HTTPS link of the repository." +"able to make changes to it. On your forked repository page, you should first " +"click on the ``Code`` button on the right, this will give you the ability to " +"copy the HTTPS link of the repository." msgstr "" -"다음 단계는 컴퓨터에서 포크된 레포지토리를 변경할 수 있도록 다운로드하는 " -"것입니다. 포크된 포지토리 페이지에서 먼저 오른쪽의 ``Code`` 버튼을 클릭하면 " -"레포지토리의 HTTPS 링크를 복사할 수 있습니다." +"다음 단계는 컴퓨터에서 포크된 레포지토리를 변경할 수 있도록 다운로드하는 것입" +"니다. 포크된 포지토리 페이지에서 먼저 오른쪽의 ``Code`` 버튼을 클릭하면 레포" +"지토리의 HTTPS 링크를 복사할 수 있습니다." #: ../../source/contributor-tutorial-contribute-on-github.rst:41 msgid "" "Once you copied the \\, you can open a terminal on your machine, " "navigate to the place you want to download the repository to and type:" -msgstr "\\를 복사한 후에는 컴퓨터에서 터미널을 열고 레포지토리를 다운로드할 " -"위치로 이동하여 입력하면 됩니다:" +msgstr "" +"\\를 복사한 후에는 컴퓨터에서 터미널을 열고 레포지토리를 다운로드할 위" +"치로 이동하여 입력하면 됩니다:" #: ../../source/contributor-tutorial-contribute-on-github.rst:47 msgid "" -"This will create a ``flower/`` (or the name of your fork if you renamed " -"it) folder in the current working directory." -msgstr "현재 작업 디렉터리에``flower/``(또는 포크 이름을 변경한 경우 포크 이름) " -"폴더가 생성됩니다." +"This will create a ``flower/`` (or the name of your fork if you renamed it) " +"folder in the current working directory." +msgstr "" +"현재 작업 디렉터리에``flower/``(또는 포크 이름을 변경한 경우 포크 이름) 폴더" +"가 생성됩니다." #: ../../source/contributor-tutorial-contribute-on-github.rst:66 msgid "**Add origin**" @@ -1472,14 +1506,14 @@ msgstr "그런 다음 레포지토리 폴더로 이동할 수 있습니다:" #: ../../source/contributor-tutorial-contribute-on-github.rst:56 msgid "" -"And here we will need to add an origin to our repository. The origin is " -"the \\ of the remote fork repository. To obtain it, we can do as " -"previously mentioned by going to our fork repository on our GitHub " -"account and copying the link." +"And here we will need to add an origin to our repository. The origin is the " +"\\ of the remote fork repository. To obtain it, we can do as " +"previously mentioned by going to our fork repository on our GitHub account " +"and copying the link." msgstr "" -"여기에 레포지토리에 origin을 추가해야 합니다. origin은 원격 포크 " -"레포지토리의 \\입니다. origin을 얻으려면 앞서 설명한 대로 GitHub " -"계정의 포크 레포지토리로 이동하여 링크를 복사하면 됩니다." +"여기에 레포지토리에 origin을 추가해야 합니다. origin은 원격 포크 레포지토리" +"의 \\입니다. origin을 얻으려면 앞서 설명한 대로 GitHub 계정의 포크 레" +"포지토리로 이동하여 링크를 복사하면 됩니다." #: ../../source/contributor-tutorial-contribute-on-github.rst:61 msgid "" @@ -1495,32 +1529,34 @@ msgstr "**Upstream 추가하기**" msgid "" "Now we will add an upstream address to our repository. Still in the same " "directory, we must run the following command:" -msgstr "이제 레포지토리에 upstream 주소를 추가하겠습니다. 여전히 같은 디렉터리에서 " -"다음 명령을 실행해야 합니다:" +msgstr "" +"이제 레포지토리에 upstream 주소를 추가하겠습니다. 여전히 같은 디렉터리에서 다" +"음 명령을 실행해야 합니다:" #: ../../source/contributor-tutorial-contribute-on-github.rst:76 -msgid "The following diagram visually explains what we did in the previous steps:" +msgid "" +"The following diagram visually explains what we did in the previous steps:" msgstr "다음 다이어그램은 이전 단계에서 수행한 작업을 시각적으로 설명합니다:" #: ../../source/contributor-tutorial-contribute-on-github.rst:80 msgid "" -"The upstream is the GitHub remote address of the parent repository (in " -"this case Flower), i.e. the one we eventually want to contribute to and " -"therefore need an up-to-date history of. The origin is just the GitHub " -"remote address of the forked repository we created, i.e. the copy (fork) " -"in our own account." +"The upstream is the GitHub remote address of the parent repository (in this " +"case Flower), i.e. the one we eventually want to contribute to and therefore " +"need an up-to-date history of. The origin is just the GitHub remote address " +"of the forked repository we created, i.e. the copy (fork) in our own account." msgstr "" -"upstream은 부모 레포지토리(이 경우 Flower)의 GitHub 원격 주소, 즉 우리가 " -"최종적으로 기여하고 싶고 따라서 최신 기록이 필요한 레포지토리입니다. " -"origin은 우리가 만든 포크된 레포지토리의 GitHub 원격 주소, 즉 우리 계정에 " -"있는 사본(포크)입니다." +"upstream은 부모 레포지토리(이 경우 Flower)의 GitHub 원격 주소, 즉 우리가 최종" +"적으로 기여하고 싶고 따라서 최신 기록이 필요한 레포지토리입니다. origin은 우" +"리가 만든 포크된 레포지토리의 GitHub 원격 주소, 즉 우리 계정에 있는 사본(포" +"크)입니다." #: ../../source/contributor-tutorial-contribute-on-github.rst:84 msgid "" "To make sure our local version of the fork is up-to-date with the latest " "changes from the Flower repository, we can execute the following command:" -msgstr "로컬 버전의 포크가 Flower 레포지토리의 최신 변경 사항으로 최신 상태인지 " -"확인하려면 다음 명령을 실행하면 됩니다:" +msgstr "" +"로컬 버전의 포크가 Flower 레포지토리의 최신 변경 사항으로 최신 상태인지 확인" +"하려면 다음 명령을 실행하면 됩니다:" #: ../../source/contributor-tutorial-contribute-on-github.rst:93 msgid "Setting up the coding environment" @@ -1529,12 +1565,12 @@ msgstr "코딩 환경 설정" #: ../../source/contributor-tutorial-contribute-on-github.rst:95 msgid "" "This can be achieved by following this :doc:`getting started guide for " -"contributors ` (note " -"that you won't need to clone the repository). Once you are able to write " -"code and test it, you can finally start making changes!" +"contributors ` (note that " +"you won't need to clone the repository). Once you are able to write code and " +"test it, you can finally start making changes!" msgstr "" ":doc:'기여자를 위한 시작 가이드 '를 참조하세요(리포지토리를 복제할 필요는 없습니다). 코드를 " +"contributor>'를 참조하세요(레포지토리를 복제할 필요는 없습니다). 코드를 " "작성하고 테스트할 수 있게 되면 드디어 변경을 시작할 수 있습니다!" #: ../../source/contributor-tutorial-contribute-on-github.rst:100 @@ -1543,8 +1579,7 @@ msgstr "변경하기" #: ../../source/contributor-tutorial-contribute-on-github.rst:102 msgid "" -"Before making any changes make sure you are up-to-date with your " -"repository:" +"Before making any changes make sure you are up-to-date with your repository:" msgstr "변경하기 전에 레포지토리를 최신 상태로 유지하세요:" #: ../../source/contributor-tutorial-contribute-on-github.rst:108 @@ -1557,16 +1592,15 @@ msgstr "**새 브랜치 만들기**" #: ../../source/contributor-tutorial-contribute-on-github.rst:115 msgid "" -"To make the history cleaner and easier to work with, it is good practice " -"to create a new branch for each feature/project that needs to be " -"implemented." -msgstr "히스토리를 더 깔끔하고 작업하기 쉽게 만들려면 구현해야 하는 각 기능/" -"프로젝트에 대해 새 브랜치를 만드는 것이 좋습니다." +"To make the history cleaner and easier to work with, it is good practice to " +"create a new branch for each feature/project that needs to be implemented." +msgstr "" +"히스토리를 더 깔끔하고 작업하기 쉽게 만들려면 구현해야 하는 각 기능/프로젝트" +"에 대해 새 브랜치를 만드는 것이 좋습니다." #: ../../source/contributor-tutorial-contribute-on-github.rst:118 msgid "" -"To do so, just run the following command inside the repository's " -"directory:" +"To do so, just run the following command inside the repository's directory:" msgstr "이렇게 하려면 레포지토리 디렉토리에서 다음 명령을 실행하면 됩니다:" #: ../../source/contributor-tutorial-contribute-on-github.rst:125 @@ -1574,8 +1608,9 @@ msgid "**Make changes**" msgstr "**변경하기**" #: ../../source/contributor-tutorial-contribute-on-github.rst:125 -msgid "Write great code and create wonderful changes using your favorite editor!" -msgstr "선호하 편집기를 사용하여 멋진 코드를 작성하고 훌륭한 변화를 만들어 보세요!" +msgid "" +"Write great code and create wonderful changes using your favorite editor!" +msgstr "선호하는 편집기를 사용하여 멋진 코드를 작성하고 훌륭한 변화를 만들어 보세요!" #: ../../source/contributor-tutorial-contribute-on-github.rst:138 msgid "**Test and format your code**" @@ -1583,9 +1618,9 @@ msgstr "**코드 테스트 및 서식 지정**" #: ../../source/contributor-tutorial-contribute-on-github.rst:128 msgid "" -"Don't forget to test and format your code! Otherwise your code won't be " -"able to be merged into the Flower repository. This is done so the " -"codebase stays consistent and easy to understand." +"Don't forget to test and format your code! Otherwise your code won't be able " +"to be merged into the Flower repository. This is done so the codebase stays " +"consistent and easy to understand." msgstr "" "코드를 테스트하고 서식을 지정하는 것을 잊지 마세요! 그렇지 않으면 코드를 " "Flower 레포지토리에 병합할 수 없습니다. 이는 코드베이스가 일관성을 유지하고 " @@ -1601,10 +1636,11 @@ msgstr "**Stage 변경**" #: ../../source/contributor-tutorial-contribute-on-github.rst:141 msgid "" -"Before creating a commit that will update your history, you must specify " -"to Git which files it needs to take into account." -msgstr "기록을 업데이트할 커밋을 만들기 전에 어떤 파일을 고려해야 하는지 Git에 " -"지정해야 합니다." +"Before creating a commit that will update your history, you must specify to " +"Git which files it needs to take into account." +msgstr "" +"기록을 업데이트할 커밋을 만들기 전에 어떤 파일을 고려해야 하는지 Git에 지정해" +"야 합니다." #: ../../source/contributor-tutorial-contribute-on-github.rst:143 msgid "This can be done with:" @@ -1612,12 +1648,12 @@ msgstr "이 작업을 수행할 수 있습니다:" #: ../../source/contributor-tutorial-contribute-on-github.rst:149 msgid "" -"To check which files have been modified compared to the last version " -"(last commit) and to see which files are staged for commit, you can use " -"the :code:`git status` command." +"To check which files have been modified compared to the last version (last " +"commit) and to see which files are staged for commit, you can use the :code:" +"`git status` command." msgstr "" -"마지막 버전(마지막 커밋)과 비교하여 수정된 파일을 확인하고 커밋을 위해 " -"스테이징된 파일을 확인하려면 :code:`git status` 명령을 사용하면 됩니다." +"마지막 버전(마지막 커밋)과 비교하여 수정된 파일을 확인하고 커밋을 위해 스테이" +"징된 파일을 확인하려면 :code:`git status` 명령을 사용하면 됩니다." #: ../../source/contributor-tutorial-contribute-on-github.rst:160 msgid "**Commit changes**" @@ -1628,18 +1664,18 @@ msgid "" "Once you have added all the files you wanted to commit using :code:`git " "add`, you can finally create your commit using this command:" msgstr "" -":code:`git add`를 사용하여 커밋하려는 모든 파일을 추가한 후, 마지막으로 이 " -"명령을 사용하여 커밋을 생성할 수 있습니다:" +":code:`git add`를 사용하여 커밋하려는 모든 파일을 추가한 후, 마지막으로 이 명" +"령을 사용하여 커밋을 생성할 수 있습니다:" #: ../../source/contributor-tutorial-contribute-on-github.rst:159 msgid "" -"The \\ is there to explain to others what the commit " -"does. It should be written in an imperative style and be concise. An " -"example would be :code:`git commit -m \"Add images to README\"`." +"The \\ is there to explain to others what the commit does. " +"It should be written in an imperative style and be concise. An example would " +"be :code:`git commit -m \"Add images to README\"`." msgstr "" -"커밋의 내용을 다른 사람에게 설명하기 위해 \\가 있습니다. " -"명령형 스타일로 작성해야 하며 간결해야 합니다. 예를 들면 :code:`git commit -" -"m \"Add images to README\"`." +"커밋의 내용을 다른 사람에게 설명하기 위해 \\가 있습니다. 명" +"령형 스타일로 작성해야 하며 간결해야 합니다. 예를 들면 :code:`git commit -m " +"\"Add images to README\"`." #: ../../source/contributor-tutorial-contribute-on-github.rst:171 msgid "**Push the changes to the fork**" @@ -1647,19 +1683,20 @@ msgstr "**변경 사항을 포크에 푸시**" #: ../../source/contributor-tutorial-contribute-on-github.rst:163 msgid "" -"Once we have committed our changes, we have effectively updated our local" -" history, but GitHub has no way of knowing this unless we push our " -"changes to our origin's remote address:" +"Once we have committed our changes, we have effectively updated our local " +"history, but GitHub has no way of knowing this unless we push our changes to " +"our origin's remote address:" msgstr "" -"변경 사항을 커밋하면 로컬 히스토리를 효과적으로 업데이트한 것이지만, 변경 " -"사항을 원본의 원격 주소로 푸시하지 않는 한 GitHub는 이를 알 방법이 없습니다:" +"변경 사항을 커밋하면 로컬 히스토리를 효과적으로 업데이트한 것이지만, 변경 사" +"항을 원본의 원격 주소로 푸시하지 않는 한 GitHub는 이를 알 방법이 없습니다:" #: ../../source/contributor-tutorial-contribute-on-github.rst:170 msgid "" "Once this is done, you will see on the GitHub that your forked repo was " "updated with the changes you have made." -msgstr "이 작업이 완료되면 변경한 내용으로 포크된 레포지토리가 업데이트된 것을 " -"GitHub에서 확인할 수 있습니다." +msgstr "" +"이 작업이 완료되면 변경한 내용으로 포크된 레포지토리가 업데이트된 것을 GitHub" +"에서 확인할 수 있습니다." #: ../../source/contributor-tutorial-contribute-on-github.rst:174 msgid "Creating and merging a pull request (PR)" @@ -1671,39 +1708,43 @@ msgstr "**PR 만들기**" #: ../../source/contributor-tutorial-contribute-on-github.rst:177 msgid "" -"Once you have pushed changes, on the GitHub webpage of your repository " -"you should see the following message:" -msgstr "변경 사항을 푸시하고 나면 레포지토리의 GitHub 웹페이지에 다음 메시지가 " -"표시됩니다:" +"Once you have pushed changes, on the GitHub webpage of your repository you " +"should see the following message:" +msgstr "" +"변경 사항을 푸시하고 나면 레포지토리의 GitHub 웹페이지에 다음 메시지가 표시됩" +"니다:" #: ../../source/contributor-tutorial-contribute-on-github.rst:181 msgid "Otherwise you can always find this option in the ``Branches`` page." -msgstr "그렇지 않으면 언제든지 ``Branches`` 페이지에서 이 옵션을 찾을 수 있습니다." +msgstr "" +"그렇지 않으면 언제든지 ``Branches`` 페이지에서 이 옵션을 찾을 수 있습니다." #: ../../source/contributor-tutorial-contribute-on-github.rst:183 msgid "" "Once you click the ``Compare & pull request`` button, you should see " "something similar to this:" -msgstr "``Compare & pull request`` 버튼을 클릭하면 이와 비슷한 화면이 표시됩니다:" +msgstr "" +"``Compare & pull request`` 버튼을 클릭하면 이와 비슷한 화면이 표시됩니다:" #: ../../source/contributor-tutorial-contribute-on-github.rst:187 -msgid "At the top you have an explanation of which branch will be merged where:" +msgid "" +"At the top you have an explanation of which branch will be merged where:" msgstr "상단에는 어느 지점이 어디에 병합될 것인지에 대한 설명이 있습니다:" #: ../../source/contributor-tutorial-contribute-on-github.rst:191 msgid "" -"In this example you can see that the request is to merge the branch " -"``doc-fixes`` from my forked repository to branch ``main`` from the " -"Flower repository." +"In this example you can see that the request is to merge the branch ``doc-" +"fixes`` from my forked repository to branch ``main`` from the Flower " +"repository." msgstr "" -"이 예제에서는 내 포크된 레포지토리의 ``doc-fixes`` 브랜치를 Flower " -"레포지토리의 ``main`` 브랜치에 병합하라는 요청을 볼 수 있습니다." +"이 예제에서는 내 포크된 레포지토리의 ``doc-fixes`` 브랜치를 Flower 레포지토리" +"의 ``main`` 브랜치에 병합하라는 요청을 볼 수 있습니다." #: ../../source/contributor-tutorial-contribute-on-github.rst:193 msgid "" "The title should be changed to adhere to the :ref:`pr_title_format` " -"guidelines, otherwise it won't be possible to merge the PR. So in this " -"case, a correct title might be ``docs(framework:skip) Fix typos``." +"guidelines, otherwise it won't be possible to merge the PR. So in this case, " +"a correct title might be ``docs(framework:skip) Fix typos``." msgstr "" "제목은 :ref:`pr_title_format` 가이드라인을 준수하도록 변경해야 하며, 그렇지 " "않으면 PR을 병합할 수 없습니다. 따라서 이 경우 올바른 제목은 " @@ -1711,14 +1752,13 @@ msgstr "" #: ../../source/contributor-tutorial-contribute-on-github.rst:196 msgid "" -"The input box in the middle is there for you to describe what your PR " -"does and to link it to existing issues. We have placed comments (that " -"won't be rendered once the PR is opened) to guide you through the " -"process." +"The input box in the middle is there for you to describe what your PR does " +"and to link it to existing issues. We have placed comments (that won't be " +"rendered once the PR is opened) to guide you through the process." msgstr "" -"가운데에 있는 입력 상자는 PR의 기능을 설명하고 기존 이슈에 연결할 수 있는 " -"곳입니다. 프로세스를 안내하기 위해 코멘트(PR이 열리면 렌더링되지 않음)를 " -"배치했습니다." +"가운데에 있는 입력 상자는 PR의 기능을 설명하고 기존 이슈에 연결할 수 있는 곳" +"입니다. 프로세스를 안내하기 위해 코멘트(PR이 열리면 렌더링되지 않음)를 배치했" +"습니다." #: ../../source/contributor-tutorial-contribute-on-github.rst:199 msgid "It is important to follow the instructions described in comments." @@ -1727,16 +1767,16 @@ msgstr "코멘트에 설명된 지침을 따르는 것이 중요합니다." #: ../../source/contributor-tutorial-contribute-on-github.rst:201 msgid "" "At the bottom you will find the button to open the PR. This will notify " -"reviewers that a new PR has been opened and that they should look over it" -" to merge or to request changes." +"reviewers that a new PR has been opened and that they should look over it to " +"merge or to request changes." msgstr "" "하단에는 PR을 여는 버튼이 있습니다. 이렇게 하면 검토자에게 새 PR이 열렸으며 " "병합하거나 변경을 요청하기 위해 검토해야 함을 알립니다." #: ../../source/contributor-tutorial-contribute-on-github.rst:204 msgid "" -"If your PR is not yet ready for review, and you don't want to notify " -"anyone, you have the option to create a draft pull request:" +"If your PR is not yet ready for review, and you don't want to notify anyone, " +"you have the option to create a draft pull request:" msgstr "" "PR이 아직 검토할 준비가 되지 않았고 다른 사람에게 알리고 싶지 않은 경우 pull " "request 초안을 만드는 옵션이 있습니다:" @@ -1748,10 +1788,11 @@ msgstr "**new changes 만들기**" #: ../../source/contributor-tutorial-contribute-on-github.rst:209 msgid "" "Once the PR has been opened (as draft or not), you can still push new " -"commits to it the same way we did before, by making changes to the branch" -" associated with the PR." -msgstr "PR이 초안으로 열렸든 아니든, PR과 연결된 브랜치를 변경하여 이전과 같은 " -"방식으로 새 커밋을 푸시할 수 있습니다." +"commits to it the same way we did before, by making changes to the branch " +"associated with the PR." +msgstr "" +"PR이 초안으로 열렸든 아니든, PR과 연결된 브랜치를 변경하여 이전과 같은 방식으" +"로 새 커밋을 푸시할 수 있습니다." #: ../../source/contributor-tutorial-contribute-on-github.rst:231 msgid "**Review the PR**" @@ -1759,17 +1800,19 @@ msgstr "**PR 검토하기**" #: ../../source/contributor-tutorial-contribute-on-github.rst:212 msgid "" -"Once the PR has been opened or once the draft PR has been marked as " -"ready, a review from code owners will be automatically requested:" -msgstr "PR이 열리거나 초안 PR이 준비됨으로 표시되면 코드 소유자의 검토가 자동으로 " -"요청됩니다:" +"Once the PR has been opened or once the draft PR has been marked as ready, a " +"review from code owners will be automatically requested:" +msgstr "" +"PR이 열리거나 초안 PR이 준비됨으로 표시되면 코드 소유자의 검토가 자동으로 요" +"청됩니다:" #: ../../source/contributor-tutorial-contribute-on-github.rst:216 msgid "" -"Code owners will then look into the code, ask questions, request changes " -"or validate the PR." -msgstr "그러면 코드 소유자는 코드를 살펴보고, 질문하고, 변경을 요청하거나 PR의 " -"유효성을 검사합니다." +"Code owners will then look into the code, ask questions, request changes or " +"validate the PR." +msgstr "" +"그러면 코드 소유자는 코드를 살펴보고, 질문하고, 변경을 요청하거나 PR의 유효성" +"을 검사합니다." #: ../../source/contributor-tutorial-contribute-on-github.rst:218 msgid "Merging will be blocked if there are ongoing requested changes." @@ -1777,9 +1820,10 @@ msgstr "진행 중인 변경 요청이 있는 경우 병합이 차단됩니다." #: ../../source/contributor-tutorial-contribute-on-github.rst:222 msgid "" -"To resolve them, just push the necessary changes to the branch associated" -" with the PR:" -msgstr "이를 해결하려면 PR과 연결된 브랜치에 필요한 변경 사항을 푸시하면 됩니다:" +"To resolve them, just push the necessary changes to the branch associated " +"with the PR:" +msgstr "" +"이를 해결하려면 PR과 연결된 브랜치에 필요한 변경 사항을 푸시하면 됩니다:" #: ../../source/contributor-tutorial-contribute-on-github.rst:226 msgid "And resolve the conversation:" @@ -1787,8 +1831,7 @@ msgstr "그리고 소통을 통해 해결하세요:" #: ../../source/contributor-tutorial-contribute-on-github.rst:230 msgid "" -"Once all the conversations have been resolved, you can re-request a " -"review." +"Once all the conversations have been resolved, you can re-request a review." msgstr "모든 대화가 해결되면 검토를 다시 요청할 수 있습니다." #: ../../source/contributor-tutorial-contribute-on-github.rst:251 @@ -1797,16 +1840,18 @@ msgstr "**PR이 병합되면**" #: ../../source/contributor-tutorial-contribute-on-github.rst:234 msgid "" -"If all the automatic tests have passed and reviewers have no more changes" -" to request, they can approve the PR and merge it." -msgstr "모든 자동 테스트가 통과되고 검토자가 더 이상 요청할 변경 사항이 없는 경우 " -"PR을 승인하고 병합할 수 있습니다." +"If all the automatic tests have passed and reviewers have no more changes to " +"request, they can approve the PR and merge it." +msgstr "" +"모든 자동 테스트가 통과되고 검토자가 더 이상 요청할 변경 사항이 없는 경우 PR" +"을 승인하고 병합할 수 있습니다." #: ../../source/contributor-tutorial-contribute-on-github.rst:238 msgid "" "Once it is merged, you can delete the branch on GitHub (a button should " "appear to do so) and also delete it locally by doing:" -msgstr "병합이 완료되면 GitHub에서 브랜치를 삭제할 수 있으며(삭제 버튼이 표시되어야 " +msgstr "" +"병합이 완료되면 GitHub에서 브랜치를 삭제할 수 있으며(삭제 버튼이 표시되어야 " "함), 로컬에서도 삭제할 수 있습니다:" #: ../../source/contributor-tutorial-contribute-on-github.rst:245 @@ -1823,40 +1868,43 @@ msgstr "문제" #: ../../source/contributor-tutorial-contribute-on-github.rst:259 msgid "" -"For our documentation, we've started to use the `Diàtaxis framework " -"`_." -msgstr "저희 문서에는 'Diàtaxis 프레임워크 `_'를 사용하기 " -"시작했습니다." +"For our documentation, we've started to use the `Diàtaxis framework `_." +msgstr "" +"저희 문서에는 'Diàtaxis 프레임워크 `_'를 사용하기 시작" +"했습니다." #: ../../source/contributor-tutorial-contribute-on-github.rst:261 msgid "" -"Our \"How to\" guides should have titles that continue the sentence \"How" -" to …\", for example, \"How to upgrade to Flower 1.0\"." +"Our \"How to\" guides should have titles that continue the sentence \"How to " +"…\", for example, \"How to upgrade to Flower 1.0\"." msgstr "" -"'How to' 가이드의 제목은 \"How to …\"라는 문장을 이어가는 제목이어야 " -"합니다(예: \"How to upgrade to Flower 1.0\")." +"'How to' 가이드의 제목은 \"How to …\"라는 문장을 이어가는 제목이어야 합니다" +"(예: \"How to upgrade to Flower 1.0\")." #: ../../source/contributor-tutorial-contribute-on-github.rst:263 msgid "" "Most of our guides do not follow this new format yet, and changing their " "title is (unfortunately) more involved than one might think." -msgstr "대부분의 가이드는 아직 이 새로운 형식을 따르지 않으며, 안타깝게도 제목을 " -"변경하는 작업은 생각보다 복잡합니다." +msgstr "" +"대부분의 가이드는 아직 이 새로운 형식을 따르지 않으며, 안타깝게도 제목을 변경" +"하는 작업은 생각보다 복잡합니다." #: ../../source/contributor-tutorial-contribute-on-github.rst:265 msgid "" -"This issue is about changing the title of a doc from present continuous " -"to present simple." -msgstr "이번 이슈는 문서 제목을 현재 연속형에서 현재 단순형으로 변경하는 것에 관한 " -"것입니다." +"This issue is about changing the title of a doc from present continuous to " +"present simple." +msgstr "" +"이번 이슈는 문서 제목을 현재 연속형에서 현재 단순형으로 변경하는 것에 관한 것" +"입니다." #: ../../source/contributor-tutorial-contribute-on-github.rst:267 msgid "" "Let's take the example of \"Saving Progress\" which we changed to \"Save " "Progress\". Does this pass our check?" msgstr "" -"\"How to saving progress\"을 \"How to save progress\"으로 변경한 예를 들어 " -"보겠습니다. 이것이 우리의 점검을 통과했나요?" +"\"How to saving progress\"을 \"How to save progress\"으로 변경한 예를 들어 보" +"겠습니다. 이것이 우리의 점검을 통과했나요?" #: ../../source/contributor-tutorial-contribute-on-github.rst:269 msgid "Before: \"How to saving progress\" ❌" @@ -1876,7 +1924,7 @@ msgid "" "After cloning and setting up the Flower repo, here's what you should do:" msgstr "" "이것은 사소한 변경이지만 end-to-end 설정을 테스트할 수 있습니다. Flower " -"포지토리를 복제하고 설정한 후에는 다음과 같이 하세요:" +"레포지토리를 복제하고 설정한 후에는 다음과 같이 하세요:" #: ../../source/contributor-tutorial-contribute-on-github.rst:278 msgid "Find the source file in ``doc/source``" @@ -1886,13 +1934,14 @@ msgstr "``doc/source``에서 소스 파일을 찾습니다" msgid "" "Make the change in the ``.rst`` file (beware, the dashes under the title " "should be the same length as the title itself)" -msgstr "``.rst`` 파일에서 변경합니다(제목 아래의 대시는 제목 자체의 길이와 같아야 " -"합니다)" +msgstr "" +"``.rst`` 파일에서 변경합니다(제목 아래의 대시는 제목 자체의 길이와 같아야 합" +"니다)" #: ../../source/contributor-tutorial-contribute-on-github.rst:280 msgid "" -"Build the docs and `check the result `_" +"Build the docs and `check the result `_" msgstr "" "문서를 빌드하고 '결과 확인 `_'합니다" @@ -1903,14 +1952,14 @@ msgstr "파일 이름 바꾸기" #: ../../source/contributor-tutorial-contribute-on-github.rst:285 msgid "" -"You might have noticed that the file name still reflects the old wording." -" If we just change the file, then we break all existing links to it - it " -"is **very important** to avoid that, breaking links can harm our search " -"engine ranking." +"You might have noticed that the file name still reflects the old wording. If " +"we just change the file, then we break all existing links to it - it is " +"**very important** to avoid that, breaking links can harm our search engine " +"ranking." msgstr "" -"파일 이름에 여전히 이전 문구가 반영되어 있는 것을 보셨을 것입니다. 파일만 " -"변경하면 파일에 대한 기존 링크가 모두 끊어지는데, 링크를 끊으면 검색 엔진 " -"순위에 영향을 줄 수 있으므로 이를 방지하는 것이 **매우 중요**합니다." +"파일 이름에 여전히 이전 문구가 반영되어 있는 것을 보셨을 것입니다. 파일만 변" +"경하면 파일에 대한 기존 링크가 모두 끊어지는데, 링크를 끊으면 검색 엔진 순위" +"에 영향을 줄 수 있으므로 이를 방지하는 것이 **매우 중요**합니다." #: ../../source/contributor-tutorial-contribute-on-github.rst:288 msgid "Here's how to change the file name:" @@ -1926,11 +1975,11 @@ msgstr "'doc/source/conf.py'에 리디렉션 규칙을 추가합니다" #: ../../source/contributor-tutorial-contribute-on-github.rst:293 msgid "" -"This will cause a redirect from ``saving-progress.html`` to ``save-" -"progress.html``, old links will continue to work." +"This will cause a redirect from ``saving-progress.html`` to ``save-progress." +"html``, old links will continue to work." msgstr "" -"이렇게 하면 ``saving-progress.html``에서 ``save-progress.html``로 " -"리디렉션되며, 이전 링크는 계속 작동합니다." +"이렇게 하면 ``saving-progress.html``에서 ``save-progress.html``로 리디렉션되" +"며, 이전 링크는 계속 작동합니다." #: ../../source/contributor-tutorial-contribute-on-github.rst:296 msgid "Apply changes in the index file" @@ -1942,8 +1991,8 @@ msgid "" "update the ``index.rst`` file as well. This is where we define the whole " "arborescence of the navbar." msgstr "" -"횡방향 내비게이션 바가 제대로 작동하려면 ``index.rst`` 파일도 업데이트하는 " -"것이 매우 중요합니다. 이 파일은 탐색 모음의 전체 배열을 정의하는 곳입니다." +"횡방향 내비게이션 바가 제대로 작동하려면 ``index.rst`` 파일도 업데이트하는 것" +"이 매우 중요합니다. 이 파일은 탐색 모음의 전체 배열을 정의하는 곳입니다." #: ../../source/contributor-tutorial-contribute-on-github.rst:301 msgid "Find and modify the file name in ``index.rst``" @@ -1955,11 +2004,11 @@ msgstr "PR 열기" #: ../../source/contributor-tutorial-contribute-on-github.rst:306 msgid "" -"Commit the changes (commit messages are always imperative: \"Do " -"something\", in this case \"Change …\")" +"Commit the changes (commit messages are always imperative: \"Do something\", " +"in this case \"Change …\")" msgstr "" -"변경 사항을 커밋합니다(커밋 메시지는 항상 필수 메시지입니다:\"Do something\"(" -"이 경우 는 \"Change …\" )" +"변경 사항을 커밋합니다(커밋 메시지는 항상 필수 메시지입니다:\"Do " +"something\"(이 경우 는 \"Change …\" )" #: ../../source/contributor-tutorial-contribute-on-github.rst:307 msgid "Push the changes to your fork" @@ -1967,9 +2016,10 @@ msgstr "변경 사항을 포크에 푸시합니다" #: ../../source/contributor-tutorial-contribute-on-github.rst:308 msgid "" -"Open a PR (as shown above) with title ``docs(framework) Update how-to " -"guide title``" -msgstr "``docs(framework) Update how-to guide title`` 제목으로 PR(위와 같이)을 엽니다" +"Open a PR (as shown above) with title ``docs(framework) Update how-to guide " +"title``" +msgstr "" +"``docs(framework) Update how-to guide title`` 제목으로 PR(위와 같이)을 엽니다" #: ../../source/contributor-tutorial-contribute-on-github.rst:309 msgid "Wait for it to be approved!" @@ -1990,18 +2040,17 @@ msgstr "다음 단계" #: ../../source/contributor-tutorial-contribute-on-github.rst:316 msgid "" -"Once you have made your first PR, and want to contribute more, be sure to" -" check out the following :" -msgstr "첫 번째 PR을 작성하고 더 많은 기여를 하고 싶다면 다음 을 확인하세요:" +"Once you have made your first PR, and want to contribute more, be sure to " +"check out the following :" +msgstr "첫 번째 PR을 작성하고 더 많은 기여를 하고 싶다면 다음을 확인하세요:" #: ../../source/contributor-tutorial-contribute-on-github.rst:318 msgid "" -":doc:`Good first contributions `, where you should particularly look into the " -":code:`baselines` contributions." +":doc:`Good first contributions `, " +"where you should particularly look into the :code:`baselines` contributions." msgstr "" -":doc:`훌륭한 첫 번째 기여 `, 특히 " -":code:`baselines` 기여를 살펴봐야 합니다." +":doc:`훌륭한 첫 번째 기여 `, 특히 :" +"code:`baselines` 기여를 살펴봐야 합니다." #: ../../source/contributor-tutorial-contribute-on-github.rst:322 #: ../../source/fed/0000-20200102-fed-template.md:60 @@ -2018,23 +2067,23 @@ msgstr "다음과 같은 PR 제목 형식을 적용합니다:" #: ../../source/contributor-tutorial-contribute-on-github.rst:335 msgid "" -"(or ``(:skip) `` to ignore the PR in the " -"changelog)" -msgstr "(또는 ``(:skip) ``를 사용하면 변경 로그에서 PR을 " -"무시합니다.)" +"(or ``(:skip) `` to ignore the PR in the changelog)" +msgstr "" +"(또는 ``(:skip) ``를 사용하면 변경 로그에서 PR을 무시" +"합니다.)" #: ../../source/contributor-tutorial-contribute-on-github.rst:337 msgid "" -"Where ```` needs to be in ``{ci, fix, feat, docs, refactor, " -"break}``, ```` should be in ``{framework, baselines, datasets, " -"examples, or '*' when modifying multiple projects which requires the " -"':skip' flag to be used}``, and ```` starts with a capitalised " -"verb in the imperative mood." +"Where ```` needs to be in ``{ci, fix, feat, docs, refactor, break}``, " +"```` should be in ``{framework, baselines, datasets, examples, or " +"'*' when modifying multiple projects which requires the ':skip' flag to be " +"used}``, and ```` starts with a capitalised verb in the imperative " +"mood." msgstr "" "여기서 ````은 ``{ci, fix, feat, docs, refactor, break}``, ````" -"는 ``{framework, baselines, datasets, examples, or '*' ':skip' 플래그를 " -"사용해야 하는 여러 프로젝트를 수정하는 경우}``로 입력해야 하며, ````" -"는 대문자로 시작해야 합니다." +"는 ``{framework, baselines, datasets, examples, or '*' ':skip' 플래그를 사용" +"해야 하는 여러 프로젝트를 수정하는 경우}``로 입력해야 하며, ````는 " +"대문자로 시작해야 합니다." #: ../../source/contributor-tutorial-contribute-on-github.rst:341 msgid "Valid examples:" @@ -2054,7 +2103,7 @@ msgstr "``ci(*:skip) Enforce PR title format``" #: ../../source/contributor-tutorial-contribute-on-github.rst:347 msgid "Invalid examples:" -msgstr "잘못된 예제입니다:" +msgstr "잘못된 예시입니다:" #: ../../source/contributor-tutorial-contribute-on-github.rst:349 msgid "``feat(framework): Add flwr build CLI command`` (extra ``:``)" @@ -2064,7 +2113,8 @@ msgstr "``feat(framework): Add flwr build CLI command`` ( ``:``제외)" msgid "" "``feat(*) Add flwr build CLI command`` (missing ``skip`` flag along with " "``*``)" -msgstr "``feat(*) Add flwr build CLI command`` (``skip`` flag와 함께 ``*``누락)" +msgstr "" +"``feat(*) Add flwr build CLI command`` (``skip`` flag와 함께 ``*``누락)" #: ../../source/contributor-tutorial-contribute-on-github.rst:351 msgid "``feat(skip) Add flwr build CLI command`` (missing ````)" @@ -2072,7 +2122,8 @@ msgstr "``feat(skip) Add flwr build CLI command`` (````누락)" #: ../../source/contributor-tutorial-contribute-on-github.rst:352 msgid "``feat(framework) add flwr build CLI command`` (non capitalised verb)" -msgstr "``feat(framework) add flwr build CLI command`` (대문자로 표기되지 않은 동사)" +msgstr "" +"``feat(framework) add flwr build CLI command`` (대문자로 표기되지 않은 동사)" #: ../../source/contributor-tutorial-contribute-on-github.rst:353 msgid "``feat(framework) Add flwr build CLI command.`` (dot at the end)" @@ -2104,17 +2155,19 @@ msgid "(Optional) `pyenv `_" msgstr "(선택 사항) `pyenv `_" #: ../../source/contributor-tutorial-get-started-as-a-contributor.rst:10 -msgid "(Optional) `pyenv-virtualenv `_" -msgstr "(선택 사항) `pyenv-virtualenv `_" +msgid "" +"(Optional) `pyenv-virtualenv `_" +msgstr "" +"(선택 사항) `pyenv-virtualenv `_" #: ../../source/contributor-tutorial-get-started-as-a-contributor.rst:12 msgid "" "Flower uses :code:`pyproject.toml` to manage dependencies and configure " -"development tools (the ones which support it). Poetry is a build tool " -"which supports `PEP 517 `_." +"development tools (the ones which support it). Poetry is a build tool which " +"supports `PEP 517 `_." msgstr "" -"Flower는 dependencies을 관리하고 개발 도구(이를 지원하는 도구)를 구성하기 " -"위해 :code:`pyproject.toml`을 사용합니다. Poetry는 `PEP 517 `_을 지원하는 빌드 도구입니다." #: ../../source/contributor-tutorial-get-started-as-a-contributor.rst:18 @@ -2127,7 +2180,7 @@ msgstr "사전 준비" #: ../../source/contributor-tutorial-get-started-as-a-contributor.rst:22 msgid "Some system-wide dependencies are needed." -msgstr "일부 시스템 전체에 대한 dependencies이 필요합니다." +msgstr "일부 시스템 전체에 대한 의존성이 필요합니다." #: ../../source/contributor-tutorial-get-started-as-a-contributor.rst:25 msgid "For macOS" @@ -2135,17 +2188,18 @@ msgstr "macOS의 경우" #: ../../source/contributor-tutorial-get-started-as-a-contributor.rst:27 msgid "" -"Install `homebrew `_. Don't forget the post-" -"installation actions to add `brew` to your PATH." +"Install `homebrew `_. Don't forget the post-installation " +"actions to add `brew` to your PATH." msgstr "" -"`homebrew `_를 설치합니다. 설치 후 `brew`를 PATH에 " -"추가하는 작업을 잊지 마세요." +"`homebrew `_를 설치합니다. 설치 후 `brew`를 PATH에 추가하" +"는 작업을 잊지 마세요." #: ../../source/contributor-tutorial-get-started-as-a-contributor.rst:28 msgid "" -"Install `xz` (to install different Python versions) and `pandoc` to build" -" the docs::" -msgstr "xz`(다른 Python 버전을 설치하려면)와 `pandoc`을 설치하여 문서를 빌드합니다::" +"Install `xz` (to install different Python versions) and `pandoc` to build " +"the docs::" +msgstr "" +"xz`(다른 Python 버전을 설치하려면)와 `pandoc`을 설치하여 문서를 빌드합니다::" #: ../../source/contributor-tutorial-get-started-as-a-contributor.rst:34 msgid "For Ubuntu" @@ -2153,10 +2207,11 @@ msgstr "Ubuntu의 경우" #: ../../source/contributor-tutorial-get-started-as-a-contributor.rst:35 msgid "" -"Ensure you system (Ubuntu 22.04+) is up-to-date, and you have all " -"necessary packages::" -msgstr "시스템(우분투 22.04 이상)이 최신 상태이고 필요한 패키지가 모두 설치되어 " -"있는지 확인하세요:" +"Ensure you system (Ubuntu 22.04+) is up-to-date, and you have all necessary " +"packages::" +msgstr "" +"시스템(우분투 22.04 이상)이 최신 상태이고 필요한 패키지가 모두 설치되어 있는" +"지 확인하세요:" #: ../../source/contributor-tutorial-get-started-as-a-contributor.rst:44 msgid "Create Flower Dev Environment" @@ -2167,27 +2222,27 @@ msgid "" "1. Clone the `Flower repository `_ from " "GitHub::" msgstr "" -"1. GitHub: 에서 ``Flower 레포지토리 `_를 " -"복제합니다::" +"1. GitHub: 에서 ``Flower 레포지토리 `_를 복제" +"합니다::" #: ../../source/contributor-tutorial-get-started-as-a-contributor.rst:52 msgid "" -"Let's create the Python environment for all-things Flower. If you wish to" -" use :code:`pyenv`, we provide two convenience scripts that you can use. " -"If you prefer using something else than :code:`pyenv`, create a new " +"Let's create the Python environment for all-things Flower. If you wish to " +"use :code:`pyenv`, we provide two convenience scripts that you can use. If " +"you prefer using something else than :code:`pyenv`, create a new " "environment, activate and skip to the last point where all packages are " "installed." msgstr "" -"Flower의 모든 것을 위한 파이썬 환경을 만들어 보겠습니다.:code:`pyenv`를 " -"사용하고자 하는 경우 사용할 수 있는 두 가지 편의 스크립트를 " -"제공합니다.:code:`pyenv`가 아닌 다른 것을 사용하려면 새 환경을 생성하고 " -"활성화한 후 모든 패키지가 설치된 마지막 지점으로 건너뛰세요." +"Flower의 모든 것을 위한 파이썬 환경을 만들어 보겠습니다.:code:`pyenv`를 사용" +"하고자 하는 경우 사용할 수 있는 두 가지 편의 스크립트를 제공합니다.:code:" +"`pyenv`가 아닌 다른 것을 사용하려면 새 환경을 생성하고 활성화한 후 모든 패키" +"지가 설치된 마지막 지점으로 건너뛰세요." #: ../../source/contributor-tutorial-get-started-as-a-contributor.rst:54 msgid "" -"If you don't have :code:`pyenv` installed, the following script that will" -" install it, set it up, and create the virtual environment (with " -":code:`Python 3.8.17` by default)::" +"If you don't have :code:`pyenv` installed, the following script that will " +"install it, set it up, and create the virtual environment (with :code:" +"`Python 3.8.17` by default)::" msgstr "" ":code:`pyenv`가 설치되어 있지 않은 경우 다음 스크립트를 사용하여 설치, 설정 " "및 가상 환경을 생성합니다(기본적으로 :code:`Python 3.8.17` 사용):" @@ -2195,8 +2250,8 @@ msgstr "" #: ../../source/contributor-tutorial-get-started-as-a-contributor.rst:58 msgid "" "If you already have :code:`pyenv` installed (along with the :code:`pyenv-" -"virtualenv` plugin), you can use the following convenience script (with " -":code:`Python 3.8.17` by default)::" +"virtualenv` plugin), you can use the following convenience script (with :" +"code:`Python 3.8.17` by default)::" msgstr "" ":code:`pyenv`가 이미 설치되어 있는 경우( :code:`pyenv-virtualenv` 플러그인과 " "함께) 다음과 같은 편의 스크립트를 사용할 수 있습니다(기본적으로 코드:`Python " @@ -2204,11 +2259,11 @@ msgstr "" #: ../../source/contributor-tutorial-get-started-as-a-contributor.rst:62 msgid "" -"3. Install the Flower package in development mode (think :code:`pip " -"install -e`) along with all necessary dependencies::" +"3. Install the Flower package in development mode (think :code:`pip install -" +"e`) along with all necessary dependencies::" msgstr "" -"3. 필요한 모든 dependencies와 함께 개발 모드에서 Flower 패키지를 " -"설치합니다(예:code:`pip install -e`)::" +"3. 필요한 모든 dependencies와 함께 개발 모드에서 Flower 패키지를 설치합니다" +"(예:code:`pip install -e`)::" #: ../../source/contributor-tutorial-get-started-as-a-contributor.rst:69 msgid "Convenience Scripts" @@ -2217,13 +2272,13 @@ msgstr "편의 스크립트" #: ../../source/contributor-tutorial-get-started-as-a-contributor.rst:71 msgid "" "The Flower repository contains a number of convenience scripts to make " -"recurring development tasks easier and less error-prone. See the " -":code:`/dev` subdirectory for a full list. The following scripts are " -"amongst the most important ones:" +"recurring development tasks easier and less error-prone. See the :code:`/" +"dev` subdirectory for a full list. The following scripts are amongst the " +"most important ones:" msgstr "" -"Flower 레포지토리에는 반복적인 개발 작업을 더 쉽고 오류를 줄이기 위한 여러 " -"가지 편의 스크립트가 포함되어 있습니다. 전체 목록은 :code:`/dev` 하위 " -"디렉터리를 참조하세요. 다음 스크립트는 가장 중요한 스크립트 중 하나입니다:" +"Flower 레포지토리에는 반복적인 개발 작업을 더 쉽고 오류를 줄이기 위한 여러 가" +"지 편의 스크립트가 포함되어 있습니다. 전체 목록은 :code:`/dev` 하위 디렉터리" +"를 참조하세요. 다음 스크립트는 가장 중요한 스크립트 중 하나입니다:" #: ../../source/contributor-tutorial-get-started-as-a-contributor.rst:77 msgid "Create/Delete Virtual Environment" @@ -2247,50 +2302,53 @@ msgstr "사전 커밋 훅 추가" #: ../../source/contributor-tutorial-get-started-as-a-contributor.rst:108 msgid "" -"Developers may integrate a pre-commit hook into their workflow utilizing " -"the `pre-commit `_ library. The pre-" -"commit hook is configured to execute two primary operations: " -"``./dev/format.sh`` and ``./dev/test.sh`` scripts." +"Developers may integrate a pre-commit hook into their workflow utilizing the " +"`pre-commit `_ library. The pre-commit hook " +"is configured to execute two primary operations: ``./dev/format.sh`` and ``./" +"dev/test.sh`` scripts." msgstr "" -"개발자는 `pre-commit `_ 라이브러리를 " -"사용하여 사전 커밋 훅을 워크플로에 통합할 수 있습니다. 사전 커밋 훅은 두 " -"가지 기본 작업을 실행하도록 구성됩니다:``./dev/format.sh`` 및 ``./dev/test." -"sh`` 스크립트." +"개발자는 `pre-commit `_ 라이브러리를 사용하" +"여 사전 커밋 훅을 워크플로에 통합할 수 있습니다. 사전 커밋 훅은 두 가지 기본 " +"작업을 실행하도록 구성됩니다:``./dev/format.sh`` 및 ``./dev/test.sh`` 스크립" +"트." #: ../../source/contributor-tutorial-get-started-as-a-contributor.rst:110 msgid "There are multiple ways developers can use this:" msgstr "개발자가 이것을 사용할 수 있는 여러가지 방법이 있습니다:" #: ../../source/contributor-tutorial-get-started-as-a-contributor.rst:112 -msgid "Install the pre-commit hook to your local git directory by simply running:" +msgid "" +"Install the pre-commit hook to your local git directory by simply running:" msgstr "간단하게 실행하여 로컬 git 디렉터리에 사전 커밋 훅을 설치하세요:" #: ../../source/contributor-tutorial-get-started-as-a-contributor.rst:118 msgid "" -"Each ``git commit`` will trigger the execution of formatting and " -"linting/test scripts." +"Each ``git commit`` will trigger the execution of formatting and linting/" +"test scripts." msgstr "각 ``git 커밋``은 포맷 및 린팅/테스트 스크립트의 실행을 트리거합니다." #: ../../source/contributor-tutorial-get-started-as-a-contributor.rst:119 msgid "" -"If in a hurry, bypass the hook using ``--no-verify`` with the ``git " -"commit`` command. ::" -msgstr "급한 경우 ``git commit`` 명령과 함께 `--no-verify``를 사용하여 훅을 넘기세요:" +"If in a hurry, bypass the hook using ``--no-verify`` with the ``git commit`` " +"command. ::" +msgstr "" +"급한 경우 ``git commit`` 명령과 함께 `--no-verify``를 사용하여 훅을 넘기세요:" #: ../../source/contributor-tutorial-get-started-as-a-contributor.rst:124 msgid "" "For developers who prefer not to install the hook permanently, it is " -"possible to execute a one-time check prior to committing changes by using" -" the following command:" +"possible to execute a one-time check prior to committing changes by using " +"the following command:" msgstr "" -"훅을 영구적으로 설치하지 않으려는 개발자의 경우 다음 명령을 사용하여 변경 " -"사항을 커밋하기 전에 일회성 검사를 실행할 수 있습니다:" +"훅을 영구적으로 설치하지 않으려는 개발자의 경우 다음 명령을 사용하여 변경 사" +"항을 커밋하기 전에 일회성 검사를 실행할 수 있습니다:" #: ../../source/contributor-tutorial-get-started-as-a-contributor.rst:130 msgid "" "This executes the formatting and linting checks/tests on all the files " "without modifying the default behavior of ``git commit``." -msgstr "이렇게 하면 ``git commit``의 기본 동작을 수정하지 않고 모든 파일에 대해 포맷 " +msgstr "" +"이렇게 하면 ``git commit``의 기본 동작을 수정하지 않고 모든 파일에 대해 포맷 " "및 린팅 검사/테스트를 실행합니다." #: ../../source/contributor-tutorial-get-started-as-a-contributor.rst:133 @@ -2299,21 +2357,22 @@ msgstr "로컬에서 Github Action(CI) 실행하기" #: ../../source/contributor-tutorial-get-started-as-a-contributor.rst:135 msgid "" -"Developers could run the full set of Github Actions workflows under their" -" local environment by using `Act `_. " -"Please refer to the installation instructions under the linked repository" -" and run the next command under Flower main cloned repository folder::" +"Developers could run the full set of Github Actions workflows under their " +"local environment by using `Act `_. Please " +"refer to the installation instructions under the linked repository and run " +"the next command under Flower main cloned repository folder::" msgstr "" -"개발자는 `Act `_를 사용하여 로컬 환경에서 " -"전체 Github Actions 워크플로우 세트를 실행할 수 있습니다. 링크된 레포지토리 " -"아래의 설치 지침을 참조하여 Flower 메인 클론 레포지토리 폴더 아래에서 다음 " -"명령을 실행하세요::" +"개발자는 `Act `_를 사용하여 로컬 환경에서 전" +"체 Github Actions 워크플로우 세트를 실행할 수 있습니다. 링크된 레포지토리 아" +"래의 설치 지침을 참조하여 Flower 메인 클론 레포지토리 폴더 아래에서 다음 명령" +"을 실행하세요::" #: ../../source/contributor-tutorial-get-started-as-a-contributor.rst:142 msgid "" "The Flower default workflow would run by setting up the required Docker " "machines underneath." -msgstr "Flower 기본 워크플로우는 아래에 필요한 Docker 머신을 설정하여 실행합니다." +msgstr "" +"Flower 기본 워크플로우는 아래에 필요한 Docker 머신을 설정하여 실행합니다." #: ../../source/contributor-tutorial-get-started-as-a-contributor.rst:147 msgid "Build Release" @@ -2321,17 +2380,19 @@ msgstr "릴리즈 빌드" #: ../../source/contributor-tutorial-get-started-as-a-contributor.rst:149 msgid "" -"Flower uses Poetry to build releases. The necessary command is wrapped in" -" a simple script::" -msgstr "Flower는 Poetry를 사용하여 릴리즈를 빌드합니다. 필요한 명령은 간단한 " -"스크립트로 래핑됩니다::" +"Flower uses Poetry to build releases. The necessary command is wrapped in a " +"simple script::" +msgstr "" +"Flower는 Poetry를 사용하여 릴리즈를 빌드합니다. 필요한 명령은 간단한 스크립트" +"로 래핑됩니다::" #: ../../source/contributor-tutorial-get-started-as-a-contributor.rst:154 msgid "" -"The resulting :code:`.whl` and :code:`.tar.gz` releases will be stored in" -" the :code:`/dist` subdirectory." -msgstr "결과물인 :code:`.whl` 및 :code:`.tar.gz` 릴리즈는 :code:`/dist` 하위 " -"디렉터리에 저장됩니다." +"The resulting :code:`.whl` and :code:`.tar.gz` releases will be stored in " +"the :code:`/dist` subdirectory." +msgstr "" +"결과물인 :code:`.whl` 및 :code:`.tar.gz` 릴리즈는 :code:`/dist` 하위 디렉터리" +"에 저장됩니다." #: ../../source/contributor-tutorial-get-started-as-a-contributor.rst:159 msgid "Build Documentation" @@ -2339,13 +2400,13 @@ msgstr "문서 빌드" #: ../../source/contributor-tutorial-get-started-as-a-contributor.rst:161 msgid "" -"Flower's documentation uses `Sphinx `_. " -"There's no convenience script to re-build the documentation yet, but it's" -" pretty easy::" +"Flower's documentation uses `Sphinx `_. There's " +"no convenience script to re-build the documentation yet, but it's pretty " +"easy::" msgstr "" -"Flower의 문서는 `Sphinx `_를 사용합니다. 아직 " -"문서를 다시 작성할 수 있는 편리한 스크립트는 없지만 다음과 같이 쉽게 작성할 " -"수 있습니다:" +"Flower의 문서는 `Sphinx `_를 사용합니다. 아직 문" +"서를 다시 작성할 수 있는 편리한 스크립트는 없지만 다음과 같이 쉽게 작성할 수 " +"있습니다:" #: ../../source/contributor-tutorial-get-started-as-a-contributor.rst:167 msgid "This will generate HTML documentation in ``doc/build/html``." @@ -2353,40 +2414,39 @@ msgstr "그러면 ``doc/build/html``에 HTML 문서가 생성됩니다." #: ../../source/example-fedbn-pytorch-from-centralized-to-federated.rst:2 msgid "Example: FedBN in PyTorch - From Centralized To Federated" -msgstr "예시: PyTorch에서 FedBN - Centralize에서 Federated으로" +msgstr "예시: PyTorch에서 FedBN - 중앙 집중식에서 연합식으로" #: ../../source/example-fedbn-pytorch-from-centralized-to-federated.rst:4 msgid "" -"This tutorial will show you how to use Flower to build a federated " -"version of an existing machine learning workload with `FedBN " -"`_, a federated training strategy " -"designed for non-iid data. We are using PyTorch to train a Convolutional " -"Neural Network(with Batch Normalization layers) on the CIFAR-10 dataset. " -"When applying FedBN, only few changes needed compared to :doc:`Example: " -"PyTorch - From Centralized To Federated `." +"This tutorial will show you how to use Flower to build a federated version " +"of an existing machine learning workload with `FedBN `_, a federated training strategy designed for non-iid data. We " +"are using PyTorch to train a Convolutional Neural Network(with Batch " +"Normalization layers) on the CIFAR-10 dataset. When applying FedBN, only few " +"changes needed compared to :doc:`Example: PyTorch - From Centralized To " +"Federated `." msgstr "" "이 튜토리얼에서는 non-iid data를 위해 설계된 federated 훈련 전략인 `FedBN " "`_으로 기존 머신러닝 워크로드의 federated " "버전을 구축하기 위해 Flower를 사용하는 방법을 보여드립니다. 우리는 PyTorch를 " "사용하여 CIFAR-10 데이터 세트에서 컨볼루션 신경망(일괄 정규화 레이어 포함)을 " -"훈련하고 있습니다. FedBN을 적용할 때, :doc:`예제: 파이토치 -Centralized에서 " -"Federated으로 ` 와 비교했을 " -"때 몇 가지 사항만 변경 하면 됩니다." +"훈련하고 있습니다. FedBN을 적용할 때, :doc:`예제: 파이토치 -중앙 집중식에서 " +"연합식으로 ` 와 비교했을 때 " +"몇 가지 사항만 변경 하면 됩니다." #: ../../source/example-fedbn-pytorch-from-centralized-to-federated.rst:9 #: ../../source/example-pytorch-from-centralized-to-federated.rst:10 msgid "Centralized Training" -msgstr "Centralized 훈련" +msgstr "중앙 집중식 훈련" #: ../../source/example-fedbn-pytorch-from-centralized-to-federated.rst:10 msgid "" -"All files are revised based on :doc:`Example: PyTorch - From Centralized " -"To Federated `. The only " -"thing to do is modifying the file called :code:`cifar.py`, revised part " -"is shown below:" +"All files are revised based on :doc:`Example: PyTorch - From Centralized To " +"Federated `. The only thing " +"to do is modifying the file called :code:`cifar.py`, revised part is shown " +"below:" msgstr "" -"모든 파일은 :doc:`예제: 파이토치 - Centralized에서 Federated으로 `를 기반으로 수정합니다. :code:`cifar." "py`라는 파일을 수정하기만 하면 되며, 수정된 부분은 아래와 같습니다:" @@ -2394,8 +2454,9 @@ msgstr "" msgid "" "The model architecture defined in class Net() is added with Batch " "Normalization layers accordingly." -msgstr "Net() 클래스에 정의된 모델 아키텍처는 그에 따라 배치 정규화 레이어가 " -"추가됩니다." +msgstr "" +"Net() 클래스에 정의된 모델 아키텍처는 그에 따라 배치 정규화 레이어가 추가됩니" +"다." #: ../../source/example-fedbn-pytorch-from-centralized-to-federated.rst:41 #: ../../source/example-pytorch-from-centralized-to-federated.rst:157 @@ -2404,56 +2465,55 @@ msgstr "이제 머신 러닝 워크로드를 실행할 수 있습니다:" #: ../../source/example-fedbn-pytorch-from-centralized-to-federated.rst:47 msgid "" -"So far this should all look fairly familiar if you've used PyTorch " -"before. Let's take the next step and use what we've built to create a " -"federated learning system within FedBN, the system consists of one server" -" and two clients." +"So far this should all look fairly familiar if you've used PyTorch before. " +"Let's take the next step and use what we've built to create a federated " +"learning system within FedBN, the system consists of one server and two " +"clients." msgstr "" "지금까지는 파이토치를 사용해 본 적이 있다면 상당히 익숙하게 보일 것입니다. " "다음 단계로 넘어가서 우리가 구축한 것을 사용하여 FedBN 내에서 하나의 서버와 " -"두 개의 클라이언트로 구성된 federated 학습 시스템을 만들어 보겠습니다." +"두 개의 클라이언트로 구성된 연합학습 시스템을 만들어 보겠습니다." #: ../../source/example-fedbn-pytorch-from-centralized-to-federated.rst:51 #: ../../source/example-pytorch-from-centralized-to-federated.rst:167 msgid "Federated Training" -msgstr "Federated 훈련" +msgstr "연합 훈련" #: ../../source/example-fedbn-pytorch-from-centralized-to-federated.rst:53 msgid "" "If you have read :doc:`Example: PyTorch - From Centralized To Federated " -"`, the following parts are" -" easy to follow, only :code:`get_parameters` and :code:`set_parameters` " -"function in :code:`client.py` needed to revise. If not, please read the " -":doc:`Example: PyTorch - From Centralized To Federated `. first." +"`, the following parts are " +"easy to follow, only :code:`get_parameters` and :code:`set_parameters` " +"function in :code:`client.py` needed to revise. If not, please read the :doc:" +"`Example: PyTorch - From Centralized To Federated `. first." msgstr "" -":doc:`예제: 파이토치 - Centralized에서 Federated으로 `를 읽었다면, 다음 부분은 쉽게 따라할 수 있으며 " ":code:`client.py`의 :code:`get_parameters`와 :code:`set_parameters` 함수만 " -"수정해야 합니다. 그렇지 않은 경우 :doc:`예제: 파이토치 - Centralized에서 " -"Federated으로 `를 먼저 " +"수정해야 합니다. 그렇지 않은 경우 :doc:`예제: 파이토치 - 중앙 집중식에서 " +"연합식으로 `를 먼저 " "읽어보세요." #: ../../source/example-fedbn-pytorch-from-centralized-to-federated.rst:56 msgid "" -"Our example consists of one *server* and two *clients*. In FedBN, " -":code:`server.py` keeps unchanged, we can start the server directly." +"Our example consists of one *server* and two *clients*. In FedBN, :code:" +"`server.py` keeps unchanged, we can start the server directly." msgstr "" -"이 예제는 하나의 *서버*와 두 개의 *클라이언트*로 구성됩니다. FedBN에서 " -":code:`server.py`는 변경되지 않고 그대로 유지되므로 서버를 바로 시작할 수 " -"있습니다." +"이 예제는 하나의 *서버*와 두 개의 *클라이언트*로 구성됩니다. FedBN에서 :code:" +"`server.py`는 변경되지 않고 그대로 유지되므로 서버를 바로 시작할 수 있습니다." #: ../../source/example-fedbn-pytorch-from-centralized-to-federated.rst:62 msgid "" -"Finally, we will revise our *client* logic by changing " -":code:`get_parameters` and :code:`set_parameters` in :code:`client.py`, " -"we will exclude batch normalization parameters from model parameter list " -"when sending to or receiving from the server." +"Finally, we will revise our *client* logic by changing :code:" +"`get_parameters` and :code:`set_parameters` in :code:`client.py`, we will " +"exclude batch normalization parameters from model parameter list when " +"sending to or receiving from the server." msgstr "" -"마지막으로, :code:`client.py`에서 :code:`get_parameters` 및 " -":code:`set_parameters`를 변경하여 *client* 로직을 수정할 것입니다. 서버로 " -"보내거나 서버에서 받을 때 모델 파라미터 목록에서 배치 정규화 파라미터를 " -"제외할 수 있습니다." +"마지막으로, :code:`client.py`에서 :code:`get_parameters` 및 :code:" +"`set_parameters`를 변경하여 *client* 로직을 수정할 것입니다. 서버로 보내거나 " +"서버에서 받을 때 모델 파라미터 목록에서 배치 정규화 파라미터를 제외할 수 있습" +"니다." #: ../../source/example-fedbn-pytorch-from-centralized-to-federated.rst:85 msgid "Now, you can now open two additional terminal windows and run" @@ -2461,13 +2521,13 @@ msgstr "이제 두 개의 터미널 창을 추가로 열고 다음을 실행할 #: ../../source/example-fedbn-pytorch-from-centralized-to-federated.rst:91 msgid "" -"in each window (make sure that the server is still running before you do " -"so) and see your (previously centralized) PyTorch project run federated " -"learning with FedBN strategy across two clients. Congratulations!" +"in each window (make sure that the server is still running before you do so) " +"and see your (previously centralized) PyTorch project run federated learning " +"with FedBN strategy across two clients. Congratulations!" msgstr "" -"를 입력하고(클릭하기 전에 서버가 계속 실행 중인지 확인하세요), (이전에 " -"centralized된) PyTorch 프로젝트가 두 클라이언트에서 FedBN으로 federated " -"학습을 실행하는 것을 확인합니다. 축하합니다!" +"를 입력하고(클릭하기 전에 서버가 계속 실행 중인지 확인하세요), (이전에 중앙 " +"집중된) PyTorch 프로젝트가 두 클라이언트에서 FedBN으로 연합 학습을 실행하는 " +"것을 확인합니다. 축하합니다!" #: ../../source/example-fedbn-pytorch-from-centralized-to-federated.rst:94 #: ../../source/example-jax-from-centralized-to-federated.rst:277 @@ -2478,20 +2538,19 @@ msgstr "다음 단계" #: ../../source/example-fedbn-pytorch-from-centralized-to-federated.rst:96 msgid "" -"The full source code for this example can be found `here " -"`_. Our example is of course somewhat over-" -"simplified because both clients load the exact same dataset, which isn't " -"realistic. You're now prepared to explore this topic further. How about " -"using different subsets of CIFAR-10 on each client? How about adding more" -" clients?" +"The full source code for this example can be found `here `_. Our " +"example is of course somewhat over-simplified because both clients load the " +"exact same dataset, which isn't realistic. You're now prepared to explore " +"this topic further. How about using different subsets of CIFAR-10 on each " +"client? How about adding more clients?" msgstr "" "이 예제의 전체 소스 코드는 '여기 `_'에서 확인할 수 있습니다. " -"물론 이 예제는 두 클라이언트가 완전히 동일한 데이터 세트를 로드하기 때문에 " -"다소 지나치게 단순화되어 있으며, 이는 현실적이지 않습니다. 이제 이 주제를 더 " -"자세히 살펴볼 준비가 되셨습니다. 각 클라이언트에서 서로 다른 CIFAR-10의 하위 " -"집합을 사용해 보는 것은 어떨까요? 클라이언트를 더 추가하는 것은 어떨까요?" +"examples/pytorch-from-centralized-to-federated>`_'에서 확인할 수 있습니다. 물" +"론 이 예제는 두 클라이언트가 완전히 동일한 데이터 세트를 로드하기 때문에 다" +"소 지나치게 단순화되어 있으며, 이는 현실적이지 않습니다. 이제 이 주제를 더 자" +"세히 살펴볼 준비가 되셨습니다. 각 클라이언트에서 서로 다른 CIFAR-10의 하위 집" +"합을 사용해 보는 것은 어떨까요? 클라이언트를 더 추가하는 것은 어떨까요?" #: ../../source/example-jax-from-centralized-to-federated.rst:2 msgid "Example: JAX - Run JAX Federated" @@ -2500,32 +2559,31 @@ msgstr "예시: JAX - JAX Federated 실행" #: ../../source/example-jax-from-centralized-to-federated.rst:4 #: ../../source/tutorial-quickstart-jax.rst:10 msgid "" -"This tutorial will show you how to use Flower to build a federated " -"version of an existing JAX workload. We are using JAX to train a linear " -"regression model on a scikit-learn dataset. We will structure the example" -" similar to our `PyTorch - From Centralized To Federated " -"`_ walkthrough. First, we build a centralized " -"training approach based on the `Linear Regression with JAX " -"`_" -" tutorial`. Then, we build upon the centralized training code to run the " -"training in a federated fashion." -msgstr "" -"이 튜토리얼에서는 Flower를 사용하여 기존 JAX 워크로드의 federated 버전을 " -"구축하는 방법을 보여드립니다. JAX를 사용해 scikit-learn 데이터 세트에서 선형 " -"회귀 모델을 훈련하고 있습니다. 예제는 '파이토치 - Centralized에서 " -"Federated으로 `_ 워크스루와 유사하게 구성하겠습니다. 먼저, `" -"JAX를 사용한 선형 회귀 `_ 튜토리얼`을 기반으로 centralized 학습 접근 " -"방식을 구축합니다. 그런 다음 centralized 트레이닝 코드를 기반으로 federated " -"방식으로 트레이닝을 실행합니다." +"This tutorial will show you how to use Flower to build a federated version " +"of an existing JAX workload. We are using JAX to train a linear regression " +"model on a scikit-learn dataset. We will structure the example similar to " +"our `PyTorch - From Centralized To Federated `_ walkthrough. " +"First, we build a centralized training approach based on the `Linear " +"Regression with JAX `_ tutorial`. Then, we build upon the centralized " +"training code to run the training in a federated fashion." +msgstr "" +"이 튜토리얼에서는 Flower를 사용하여 기존 JAX 워크로드의 연합 버전을 구축하는 " +"방법을 보여드립니다. JAX를 사용해 scikit-learn 데이터 세트에서 선형 회귀 " +"모델을 훈련하고 있습니다. 예제는 '파이토치 - Centralized에서 Federated으로 " +"`_ 워크스루와 유사하게 구성하겠습니다. 먼저, `JAX를 사용한 선형 " +"회귀 `_ 튜토리얼`을 기반으로 centralized 학습 접근 방식을 구축합니다. 그런 " +"다음 centralized 트레이닝 코드를 기반으로 federated 방식으로 트레이닝을 " +"실행합니다." #: ../../source/example-jax-from-centralized-to-federated.rst:10 #: ../../source/tutorial-quickstart-jax.rst:16 msgid "" -"Before we start building our JAX example, we need install the packages " -":code:`jax`, :code:`jaxlib`, :code:`scikit-learn`, and :code:`flwr`:" +"Before we start building our JAX example, we need install the packages :code:" +"`jax`, :code:`jaxlib`, :code:`scikit-learn`, and :code:`flwr`:" msgstr "" "JAX 예제 빌드를 시작하기 전에 :code:`jax`, :code:`jaxlib`, :code:`scikit-" "learn`, :code:`flwr` 패키지를 설치해야 합니다:" @@ -2538,12 +2596,12 @@ msgstr "JAX를 사용한 선형 회귀" #: ../../source/example-jax-from-centralized-to-federated.rst:20 #: ../../source/tutorial-quickstart-jax.rst:26 msgid "" -"We begin with a brief description of the centralized training code based " -"on a :code:`Linear Regression` model. If you want a more in-depth " -"explanation of what's going on then have a look at the official `JAX " -"documentation `_." +"We begin with a brief description of the centralized training code based on " +"a :code:`Linear Regression` model. If you want a more in-depth explanation " +"of what's going on then have a look at the official `JAX documentation " +"`_." msgstr "" -"먼저 :code:`선형 회귀` 모델을 기반으로 하는 centralized 훈련 코드에 대한 " +"먼저 :code:`선형 회귀` 모델을 기반으로 하는 중앙 집중식 훈련 코드에 대한 " "간략한 설명부터 시작하겠습니다. 더 자세한 설명을 원하시면 공식 `JAX 문서 " "`_를 참조하세요." @@ -2552,14 +2610,13 @@ msgstr "" msgid "" "Let's create a new file called :code:`jax_training.py` with all the " "components required for a traditional (centralized) linear regression " -"training. First, the JAX packages :code:`jax` and :code:`jaxlib` need to " -"be imported. In addition, we need to import :code:`sklearn` since we use " -":code:`make_regression` for the dataset and :code:`train_test_split` to " -"split the dataset into a training and test set. You can see that we do " -"not yet import the :code:`flwr` package for federated learning. This will" -" be done later." -msgstr "" -"전통적인(centralized) 선형 회귀 훈련에 필요한 모든 구성 요소가 포함된 " +"training. First, the JAX packages :code:`jax` and :code:`jaxlib` need to be " +"imported. In addition, we need to import :code:`sklearn` since we use :code:" +"`make_regression` for the dataset and :code:`train_test_split` to split the " +"dataset into a training and test set. You can see that we do not yet import " +"the :code:`flwr` package for federated learning. This will be done later." +msgstr "" +"전통적인(중앙 집중식) 선형 회귀 훈련에 필요한 모든 구성 요소가 포함된 " ":code:`jax_training.py`라는 새 파일을 생성해 보겠습니다. 먼저, JAX 패키지인 " ":code:`jax`와 :code:`jaxlib`를 가져와야 합니다. 또한 데이터 세트에 " ":code:`make_regression`을 사용하고 데이터 세트를 학습 및 테스트 세트로 " @@ -2570,38 +2627,39 @@ msgstr "" #: ../../source/example-jax-from-centralized-to-federated.rst:37 #: ../../source/tutorial-quickstart-jax.rst:43 msgid "" -"The :code:`load_data()` function loads the mentioned training and test " -"sets." -msgstr "code:`load_data()` 함수는 앞서 언급한 트레이닝 및 테스트 세트를 로드합니다." +"The :code:`load_data()` function loads the mentioned training and test sets." +msgstr "" +"code:`load_data()` 함수는 앞서 언급한 트레이닝 및 테스트 세트를 로드합니다." #: ../../source/example-jax-from-centralized-to-federated.rst:47 #: ../../source/tutorial-quickstart-jax.rst:53 msgid "" -"The model architecture (a very simple :code:`Linear Regression` model) is" -" defined in :code:`load_model()`." -msgstr "모델 아키텍처(매우 간단한 :code:`선형 회귀` 모델)는 :code:`load_model()`에 " -"정의되어 있습니다." +"The model architecture (a very simple :code:`Linear Regression` model) is " +"defined in :code:`load_model()`." +msgstr "" +"모델 아키텍처(매우 간단한 :code:`선형 회귀` 모델)는 :code:`load_model()`에 정" +"의되어 있습니다." #: ../../source/example-jax-from-centralized-to-federated.rst:59 #: ../../source/tutorial-quickstart-jax.rst:65 msgid "" -"We now need to define the training (function :code:`train()`), which " -"loops over the training set and measures the loss (function " -":code:`loss_fn()`) for each batch of training examples. The loss function" -" is separate since JAX takes derivatives with a :code:`grad()` function " -"(defined in the :code:`main()` function and called in :code:`train()`)." +"We now need to define the training (function :code:`train()`), which loops " +"over the training set and measures the loss (function :code:`loss_fn()`) for " +"each batch of training examples. The loss function is separate since JAX " +"takes derivatives with a :code:`grad()` function (defined in the :code:" +"`main()` function and called in :code:`train()`)." msgstr "" -"이제 훈련 집합을 반복하고 각 훈련 예제 배치에 대해 손실을 측정하는(함수 " -":code:`loss_fn()`) 훈련(함수 :code:`train()`)을 정의해야 합니다. JAX는 " -":code:`grad()` 함수(:code:`main()` 함수에 정의되고 :code:`train()`에서 " -"호출됨)로 파생물을 취하므로 손실 함수는 분리되어 있습니다." +"이제 훈련 집합을 반복하고 각 훈련 예제 배치에 대해 손실을 측정하는(함수 :" +"code:`loss_fn()`) 훈련(함수 :code:`train()`)을 정의해야 합니다. JAX는 :code:" +"`grad()` 함수(:code:`main()` 함수에 정의되고 :code:`train()`에서 호출됨)로 파" +"생물을 취하므로 손실 함수는 분리되어 있습니다." #: ../../source/example-jax-from-centralized-to-federated.rst:77 #: ../../source/tutorial-quickstart-jax.rst:83 msgid "" -"The evaluation of the model is defined in the function " -":code:`evaluation()`. The function takes all test examples and measures " -"the loss of the linear regression model." +"The evaluation of the model is defined in the function :code:`evaluation()`. " +"The function takes all test examples and measures the loss of the linear " +"regression model." msgstr "" "모델의 평가는 :code:`evaluation()` 함수에 정의되어 있습니다. 이 함수는 모든 " "테스트 예제를 가져와 선형 회귀 모델의 손실을 측정합니다." @@ -2610,29 +2668,29 @@ msgstr "" #: ../../source/tutorial-quickstart-jax.rst:94 msgid "" "Having defined the data loading, model architecture, training, and " -"evaluation we can put everything together and train our model using JAX. " -"As already mentioned, the :code:`jax.grad()` function is defined in " -":code:`main()` and passed to :code:`train()`." +"evaluation we can put everything together and train our model using JAX. As " +"already mentioned, the :code:`jax.grad()` function is defined in :code:" +"`main()` and passed to :code:`train()`." msgstr "" -"데이터 로딩, 모델 아키텍처, 훈련 및 평가를 정의했으므로 이제 모든 것을 " -"종합하여 JAX를 사용 모델을 훈련할 수 있습니다. 이미 언급했듯이 :code:`jax." -"grad()` 함수는 :code:`main()`에 정의되어 :code:`train()`에 전달됩니다." +"데이터 로딩, 모델 아키텍처, 훈련 및 평가를 정의했으므로 이제 모든 것을 종합하" +"여 JAX를 사용 모델을 훈련할 수 있습니다. 이미 언급했듯이 :code:`jax.grad()` " +"함수는 :code:`main()`에 정의되어 :code:`train()`에 전달됩니다." #: ../../source/example-jax-from-centralized-to-federated.rst:105 #: ../../source/tutorial-quickstart-jax.rst:111 msgid "You can now run your (centralized) JAX linear regression workload:" -msgstr "이제 (centralized) JAX 선형 회귀 워크로드를 실행할 수 있습니다:" +msgstr "이제 (중앙 집중식) JAX 선형 회귀 워크로드를 실행할 수 있습니다:" #: ../../source/example-jax-from-centralized-to-federated.rst:111 #: ../../source/tutorial-quickstart-jax.rst:117 msgid "" -"So far this should all look fairly familiar if you've used JAX before. " -"Let's take the next step and use what we've built to create a simple " -"federated learning system consisting of one server and two clients." +"So far this should all look fairly familiar if you've used JAX before. Let's " +"take the next step and use what we've built to create a simple federated " +"learning system consisting of one server and two clients." msgstr "" -"지금까지는 JAX를 사용해 본 적이 있다면 이 모든 것이 상당히 익숙해 보일 " -"것입니다. 다음 단계로 넘어가서 우리가 구축한 것을 사용하여 하나의 서버와 두 " -"개의 클라이언트로 구성된 간단한 연합 학습 시스템을 만들어 보겠습니다." +"지금까지는 JAX를 사용해 본 적이 있다면 이 모든 것이 상당히 익숙해 보일 것입니" +"다. 다음 단계로 넘어가서 우리가 구축한 것을 사용하여 하나의 서버와 두 개의 클" +"라이언트로 구성된 간단한 연합 학습 시스템을 만들어 보겠습니다." #: ../../source/example-jax-from-centralized-to-federated.rst:115 #: ../../source/tutorial-quickstart-jax.rst:121 @@ -2642,36 +2700,36 @@ msgstr "JAX와 Flower의 만남" #: ../../source/example-jax-from-centralized-to-federated.rst:117 #: ../../source/tutorial-quickstart-jax.rst:123 msgid "" -"The concept of federating an existing workload is always the same and " -"easy to understand. We have to start a *server* and then use the code in " -":code:`jax_training.py` for the *clients* that are connected to the " -"*server*. The *server* sends model parameters to the clients. The " -"*clients* run the training and update the parameters. The updated " -"parameters are sent back to the *server*, which averages all received " -"parameter updates. This describes one round of the federated learning " -"process, and we repeat this for multiple rounds." -msgstr "" -"기존 워크로드를 federating하는 개념은 항상 동일하고 이해하기 쉽습니다. 서버*" -"를 시작한 다음 *서버*에 연결된 *클라이언트*에 대해 :code:`jax_training.py`의 " +"The concept of federating an existing workload is always the same and easy " +"to understand. We have to start a *server* and then use the code in :code:" +"`jax_training.py` for the *clients* that are connected to the *server*. The " +"*server* sends model parameters to the clients. The *clients* run the " +"training and update the parameters. The updated parameters are sent back to " +"the *server*, which averages all received parameter updates. This describes " +"one round of the federated learning process, and we repeat this for multiple " +"rounds." +msgstr "" +"기존 워크로드를 연합하는 개념은 항상 동일하고 이해하기 쉽습니다. 서버*를 " +"시작한 다음 *서버*에 연결된 *클라이언트*에 대해 :code:`jax_training.py`의 " "코드를 사용해야 합니다. *서버*는 모델 파라미터를 클라이언트로 전송합니다. " "클라이언트는 학습을 실행하고 파라미터를 업데이트합니다. 업데이트된 " "파라미터는 *서버*로 다시 전송되며, 수신된 모든 파라미터 업데이트의 평균을 " -"구합니다. 이는 federated 학습 프로세스의 한 라운드를 설명하며, 이 과정을 " -"여러 라운드에 걸쳐 반복합니다." +"구합니다. 이는 연합 학습 프로세스의 한 라운드를 설명하며, 이 과정을 여러 " +"라운드에 걸쳐 반복합니다." #: ../../source/example-jax-from-centralized-to-federated.rst:123 #: ../../source/example-pytorch-from-centralized-to-federated.rst:181 #: ../../source/tutorial-quickstart-jax.rst:129 msgid "" -"Our example consists of one *server* and two *clients*. Let's set up " -":code:`server.py` first. The *server* needs to import the Flower package " -":code:`flwr`. Next, we use the :code:`start_server` function to start a " -"server and tell it to perform three rounds of federated learning." +"Our example consists of one *server* and two *clients*. Let's set up :code:" +"`server.py` first. The *server* needs to import the Flower package :code:" +"`flwr`. Next, we use the :code:`start_server` function to start a server and " +"tell it to perform three rounds of federated learning." msgstr "" "이 예제는 하나의 *서버*와 두 개의 *클라이언트*로 구성됩니다. 먼저 " ":code:`server.py`를 설정해 보겠습니다. *server*는 Flower 패키지 :code:`flwr`" "를 가져와야 합니다. 다음으로, :code:`start_server` 함수를 사용하여 서버를 " -"시작하고 세 차례의 federated 학습을 수행하도록 지시합니다." +"시작하고 세 차례의 연합 학습을 수행하도록 지시합니다." #: ../../source/example-jax-from-centralized-to-federated.rst:133 #: ../../source/example-pytorch-from-centralized-to-federated.rst:191 @@ -2682,39 +2740,38 @@ msgstr "이미 *서버*를 시작할 수 있습니다:" #: ../../source/example-jax-from-centralized-to-federated.rst:139 #: ../../source/tutorial-quickstart-jax.rst:145 msgid "" -"Finally, we will define our *client* logic in :code:`client.py` and build" -" upon the previously defined JAX training in :code:`jax_training.py`. Our" -" *client* needs to import :code:`flwr`, but also :code:`jax` and " -":code:`jaxlib` to update the parameters on our JAX model:" +"Finally, we will define our *client* logic in :code:`client.py` and build " +"upon the previously defined JAX training in :code:`jax_training.py`. Our " +"*client* needs to import :code:`flwr`, but also :code:`jax` and :code:" +"`jaxlib` to update the parameters on our JAX model:" msgstr "" -"마지막으로, :code:`client.py`에서 *client* 로직을 정의하고 " -":code:`jax_training.py`에서 이전에 정의한 JAX 교육을 기반으로 빌드합니다. " -"*클라이언트*는 :code:`flwr`을 가져와야 하며, JAX 모델의 파라미터를 " -"업데이트하기 위해 :code:`jax` 및 :code:`jaxlib`도 가져와야 합니다:" +"마지막으로, :code:`client.py`에서 *client* 로직을 정의하고 :code:" +"`jax_training.py`에서 이전에 정의한 JAX 교육을 기반으로 빌드합니다. *클라이언" +"트*는 :code:`flwr`을 가져와야 하며, JAX 모델의 파라미터를 업데이트하기 위해 :" +"code:`jax` 및 :code:`jaxlib`도 가져와야 합니다:" #: ../../source/example-jax-from-centralized-to-federated.rst:154 #: ../../source/tutorial-quickstart-jax.rst:160 msgid "" -"Implementing a Flower *client* basically means implementing a subclass of" -" either :code:`flwr.client.Client` or :code:`flwr.client.NumPyClient`. " -"Our implementation will be based on :code:`flwr.client.NumPyClient` and " -"we'll call it :code:`FlowerClient`. :code:`NumPyClient` is slightly " -"easier to implement than :code:`Client` if you use a framework with good " -"NumPy interoperability (like JAX) because it avoids some of the " -"boilerplate that would otherwise be necessary. :code:`FlowerClient` needs" -" to implement four methods, two methods for getting/setting model " -"parameters, one method for training the model, and one method for testing" -" the model:" +"Implementing a Flower *client* basically means implementing a subclass of " +"either :code:`flwr.client.Client` or :code:`flwr.client.NumPyClient`. Our " +"implementation will be based on :code:`flwr.client.NumPyClient` and we'll " +"call it :code:`FlowerClient`. :code:`NumPyClient` is slightly easier to " +"implement than :code:`Client` if you use a framework with good NumPy " +"interoperability (like JAX) because it avoids some of the boilerplate that " +"would otherwise be necessary. :code:`FlowerClient` needs to implement four " +"methods, two methods for getting/setting model parameters, one method for " +"training the model, and one method for testing the model:" msgstr "" "Flower *클라이언트*를 구현한다는 것은 기본적으로 :code:`flwr.client.Client` " -"또는 :code:`flwr.client.NumPyClient`의 서브클래스를 구현하는 것을 " -"의미합니다. 구현은 :code:`flwr.client.NumPyClient`를 기반으로 하며, 이를 " -":code:`FlowerClient`라고 부를 것입니다. :code:`NumPyClient`는 필요한 일부 " -"보일러플레이를 피할 수 있기 때문에 NumPy 상호 운용성이 좋은 프레임워크(예: " -"JAX)를 사용하는 경우 :code:`Client`보다 구현하기가 약간 더 쉽습니다. " -"code:`FlowerClient`는 모델 매개변수를 가져오거나 설정하는 메서드 2개, 모델 " -"학습을 위한 메서드 1개, 모델 테스트를 위한 메서드 1개 등 총 4개의 메서드를 " -"구현해야 합니다:" +"또는 :code:`flwr.client.NumPyClient`의 서브클래스를 구현하는 것을 의미합니" +"다. 구현은 :code:`flwr.client.NumPyClient`를 기반으로 하며, 이를 :code:" +"`FlowerClient`라고 부를 것입니다. :code:`NumPyClient`는 필요한 일부 보일러플" +"레이를 피할 수 있기 때문에 NumPy 상호 운용성이 좋은 프레임워크(예: JAX)를 사" +"용하는 경우 :code:`Client`보다 구현하기가 약간 더 쉽습니다. code:" +"`FlowerClient`는 모델 매개변수를 가져오거나 설정하는 메서드 2개, 모델 학습을 " +"위한 메서드 1개, 모델 테스트를 위한 메서드 1개 등 총 4개의 메서드를 구현해야 " +"합니다:" #: ../../source/example-jax-from-centralized-to-federated.rst:161 #: ../../source/tutorial-quickstart-jax.rst:167 @@ -2725,8 +2782,7 @@ msgstr ":code:`set_parameters (선택사항)`" #: ../../source/example-pytorch-from-centralized-to-federated.rst:219 #: ../../source/tutorial-quickstart-jax.rst:166 msgid "" -"set the model parameters on the local model that are received from the " -"server" +"set the model parameters on the local model that are received from the server" msgstr "서버에서 수신한 로컬 모델의 모델 파라미터를 설정합니다" #: ../../source/example-jax-from-centralized-to-federated.rst:161 @@ -2738,10 +2794,11 @@ msgstr "매개 변수를 NumPy :code:`ndarray`로 변환" #: ../../source/example-pytorch-from-centralized-to-federated.rst:220 #: ../../source/tutorial-quickstart-jax.rst:168 msgid "" -"loop over the list of model parameters received as NumPy " -":code:`ndarray`'s (think list of neural network layers)" -msgstr "(신경망 레이어 목록으로 생각하면 됩니다) NumPy :code:`ndarray`로 받은 모델 " -"파라미터 목록에 대해 반복합니다" +"loop over the list of model parameters received as NumPy :code:`ndarray`'s " +"(think list of neural network layers)" +msgstr "" +"(신경망 레이어 목록으로 생각하면 됩니다) NumPy :code:`ndarray`로 받은 모델 파" +"라미터 목록에 대해 반복합니다" #: ../../source/example-jax-from-centralized-to-federated.rst:163 #: ../../source/example-pytorch-from-centralized-to-federated.rst:221 @@ -2755,11 +2812,11 @@ msgstr ":code:`get_parameters`" #: ../../source/example-pytorch-from-centralized-to-federated.rst:222 #: ../../source/tutorial-quickstart-jax.rst:170 msgid "" -"get the model parameters and return them as a list of NumPy " -":code:`ndarray`'s (which is what :code:`flwr.client.NumPyClient` expects)" +"get the model parameters and return them as a list of NumPy :code:" +"`ndarray`'s (which is what :code:`flwr.client.NumPyClient` expects)" msgstr "" -"모델 매개변수를 가져와서 NumPy :code:`ndarray`의 목록으로 반환합니다(이는 " -":code:`flwr.client.NumPyClient`가 기대하는 바와 같습니다)" +"모델 매개변수를 가져와서 NumPy :code:`ndarray`의 목록으로 반환합니다(이는 :" +"code:`flwr.client.NumPyClient`가 기대하는 바와 같습니다)" #: ../../source/example-jax-from-centralized-to-federated.rst:167 #: ../../source/example-pytorch-from-centralized-to-federated.rst:225 @@ -2776,8 +2833,8 @@ msgstr ":code:`fit`" #: ../../source/tutorial-quickstart-jax.rst:172 #: ../../source/tutorial-quickstart-jax.rst:176 msgid "" -"update the parameters of the local model with the parameters received " -"from the server" +"update the parameters of the local model with the parameters received from " +"the server" msgstr "서버에서 받은 파라미터로 로컬 모델의 파라미터를 업데이트합니다" #: ../../source/example-jax-from-centralized-to-federated.rst:167 @@ -2813,9 +2870,9 @@ msgstr "로컬 손실을 서버로 반환합니다" #: ../../source/example-jax-from-centralized-to-federated.rst:174 #: ../../source/tutorial-quickstart-jax.rst:180 msgid "" -"The challenging part is to transform the JAX model parameters from " -":code:`DeviceArray` to :code:`NumPy ndarray` to make them compatible with" -" `NumPyClient`." +"The challenging part is to transform the JAX model parameters from :code:" +"`DeviceArray` to :code:`NumPy ndarray` to make them compatible with " +"`NumPyClient`." msgstr "" "어려운 부분은 JAX 모델 매개변수를 :code:`DeviceArray`에서 :code:`NumPy " "ndarray`로 변환하여 `NumPyClient`와 호환되도록 하는 것입니다." @@ -2823,97 +2880,96 @@ msgstr "" #: ../../source/example-jax-from-centralized-to-federated.rst:176 #: ../../source/tutorial-quickstart-jax.rst:182 msgid "" -"The two :code:`NumPyClient` methods :code:`fit` and :code:`evaluate` make" -" use of the functions :code:`train()` and :code:`evaluate()` previously " +"The two :code:`NumPyClient` methods :code:`fit` and :code:`evaluate` make " +"use of the functions :code:`train()` and :code:`evaluate()` previously " "defined in :code:`jax_training.py`. So what we really do here is we tell " -"Flower through our :code:`NumPyClient` subclass which of our already " -"defined functions to call for training and evaluation. We included type " -"annotations to give you a better understanding of the data types that get" -" passed around." -msgstr "" -"두 개의 :code:`NumPyClient` 메서드인 :code:`fit`과 :code:`evaluate`는 이전에 " -":code:`jax_training.py`에 정의된 함수 :code:`train()`과 :code:`evaluate()`를 " -"사용합니다. 따라서 여기서 우리가 실제로 하는 일은 이미 정의된 함수 중 훈련과 " -"평가를 위해 호출할 함수를 :code:`NumPyClient` 서브클래스를 통해 Flower에게 " -"알려주는 것입니다. 전달되는 데이터 유형을 더 잘 이해할 수 있도록 유형 type " -"annotation을 포함했습니다." +"Flower through our :code:`NumPyClient` subclass which of our already defined " +"functions to call for training and evaluation. We included type annotations " +"to give you a better understanding of the data types that get passed around." +msgstr "" +"두 개의 :code:`NumPyClient` 메서드인 :code:`fit`과 :code:`evaluate`는 이전" +"에 :code:`jax_training.py`에 정의된 함수 :code:`train()`과 :code:`evaluate()`" +"를 사용합니다. 따라서 여기서 우리가 실제로 하는 일은 이미 정의된 함수 중 훈련" +"과 평가를 위해 호출할 함수를 :code:`NumPyClient` 서브클래스를 통해 Flower에" +"게 알려주는 것입니다. 전달되는 데이터 유형을 더 잘 이해할 수 있도록 유형 " +"type annotation을 포함했습니다." #: ../../source/example-jax-from-centralized-to-federated.rst:245 #: ../../source/tutorial-quickstart-jax.rst:251 msgid "Having defined the federation process, we can run it." -msgstr "federation 프로세스를 정의했으면 이제 실행할 수 있습니다." +msgstr "연합 프로세스를 정의했으면 이제 실행할 수 있습니다." #: ../../source/example-jax-from-centralized-to-federated.rst:268 #: ../../source/example-pytorch-from-centralized-to-federated.rst:301 #: ../../source/tutorial-quickstart-jax.rst:274 msgid "And that's it. You can now open two additional terminal windows and run" -msgstr "" +msgstr "여기까지입니다. 이제 두 개의 터미널 창을 추가로 열고 다음을 실행할 수 " +"있습니다" #: ../../source/example-jax-from-centralized-to-federated.rst:274 #: ../../source/tutorial-quickstart-jax.rst:280 msgid "" -"in each window (make sure that the server is still running before you do " -"so) and see your JAX project run federated learning across two clients. " +"in each window (make sure that the server is still running before you do so) " +"and see your JAX project run federated learning across two clients. " "Congratulations!" msgstr "" "를 입력하고(그 전에 서버가 계속 실행 중인지 확인하세요) 두 클라이언트에서 " -"federated 학습을 실행하는 JAX 프로젝트를 확인합니다. 축하합니다!" +"연합 학습을 실행하는 JAX 프로젝트를 확인합니다. 축하합니다!" #: ../../source/example-jax-from-centralized-to-federated.rst:279 #: ../../source/tutorial-quickstart-jax.rst:285 msgid "" "The source code of this example was improved over time and can be found " -"here: `Quickstart JAX `_. Our example is somewhat over-simplified because both " +"here: `Quickstart JAX `_. Our example is somewhat over-simplified because both " "clients load the same dataset." msgstr "" -"이 예제의 소스 코드는 시간이 지남에 따라 개선되었으며 여기에서 확인할 수 " -"있습니다: 'Quickstart JAX `_. 두 클라이언트가 동일한 데이터 세트를 로드하기 때문에 이 " -"예제는 다소 단순화되어 있습니다." +"이 예제의 소스 코드는 시간이 지남에 따라 개선되었으며 여기에서 확인할 수 있습" +"니다: 'Quickstart JAX `_. 두 클라이언트가 동일한 데이터 세트를 로드하기 때문에 이 예" +"제는 다소 단순화되어 있습니다." #: ../../source/example-jax-from-centralized-to-federated.rst:282 #: ../../source/tutorial-quickstart-jax.rst:288 msgid "" -"You're now prepared to explore this topic further. How about using a more" -" sophisticated model or using a different dataset? How about adding more " +"You're now prepared to explore this topic further. How about using a more " +"sophisticated model or using a different dataset? How about adding more " "clients?" msgstr "" -"이제 이 주제를 더 자세히 살펴볼 준비가 되었습니다. 더 정교한 모델을 " -"사용하거나 다른 데이터 집합을 사용해 보는 것은 어떨까요? 클라이언트를 더 " -"추가하는 것은 어떨까요?" +"이제 이 주제를 더 자세히 살펴볼 준비가 되었습니다. 더 정교한 모델을 사용하거" +"나 다른 데이터 집합을 사용해 보는 것은 어떨까요? 클라이언트를 더 추가하는 것" +"은 어떨까요?" #: ../../source/example-pytorch-from-centralized-to-federated.rst:2 msgid "Example: PyTorch - From Centralized To Federated" -msgstr "예제: 파이토치 - 중앙 Centralized에서 Federated으로" +msgstr "예제: 파이토치 - 중앙 집중식에서 연합식으로" #: ../../source/example-pytorch-from-centralized-to-federated.rst:4 msgid "" -"This tutorial will show you how to use Flower to build a federated " -"version of an existing machine learning workload. We are using PyTorch to" -" train a Convolutional Neural Network on the CIFAR-10 dataset. First, we " -"introduce this machine learning task with a centralized training approach" -" based on the `Deep Learning with PyTorch " -"`_ " -"tutorial. Then, we build upon the centralized training code to run the " -"training in a federated fashion." +"This tutorial will show you how to use Flower to build a federated version " +"of an existing machine learning workload. We are using PyTorch to train a " +"Convolutional Neural Network on the CIFAR-10 dataset. First, we introduce " +"this machine learning task with a centralized training approach based on the " +"`Deep Learning with PyTorch `_ tutorial. Then, we build upon the centralized " +"training code to run the training in a federated fashion." msgstr "" -"이 튜토리얼에서는 Flower를 사용해 기존 머신 러닝 워크로드의 federated 버전을 " +"이 튜토리얼에서는 Flower를 사용해 기존 머신 러닝 워크로드의 연합 버전을 " "구축하는 방법을 보여드립니다. 여기서는 PyTorch를 사용해 CIFAR-10 데이터 " "세트에서 컨볼루션 신경망을 훈련합니다. 먼저, 'PyTorch로 딥 러닝 " "`_ " "튜토리얼을 기반으로 centralized 학습 접근 방식을 사용하여 이 머신 러닝 " -"작업을 소개합니다. 그런 다음 centralized 훈련 코드를 기반으로 federated 방식 " +"작업을 소개합니다. 그런 다음 centralized 훈련 코드를 기반으로 연합 방식 " "훈련을 실행합니다." #: ../../source/example-pytorch-from-centralized-to-federated.rst:12 msgid "" -"We begin with a brief description of the centralized CNN training code. " -"If you want a more in-depth explanation of what's going on then have a " -"look at the official `PyTorch tutorial " -"`_." +"We begin with a brief description of the centralized CNN training code. If " +"you want a more in-depth explanation of what's going on then have a look at " +"the official `PyTorch tutorial `_." msgstr "" -"centralized CNN 트레이닝 코드에 대한 간략한 설명부터 시작하겠습니다. 무슨 " +"중앙 집중식 CNN 트레이닝 코드에 대한 간략한 설명부터 시작하겠습니다. 무슨 " "일이 일어나고 있는지 더 자세히 설명하려면 공식 `PyTorch 튜토리얼 " "`_을 " "참조하세요." @@ -2921,18 +2977,17 @@ msgstr "" #: ../../source/example-pytorch-from-centralized-to-federated.rst:15 msgid "" "Let's create a new file called :code:`cifar.py` with all the components " -"required for a traditional (centralized) training on CIFAR-10. First, all" -" required packages (such as :code:`torch` and :code:`torchvision`) need " -"to be imported. You can see that we do not import any package for " -"federated learning. You can keep all these imports as they are even when " -"we add the federated learning components at a later point." +"required for a traditional (centralized) training on CIFAR-10. First, all " +"required packages (such as :code:`torch` and :code:`torchvision`) need to be " +"imported. You can see that we do not import any package for federated " +"learning. You can keep all these imports as they are even when we add the " +"federated learning components at a later point." msgstr "" -"CIFAR-10에 대한 기존 (centralized) 교육에 필요한 모든 구성 요소가 포함된 " +"CIFAR-10에 대한 기존 (중앙 집중식) 교육에 필요한 모든 구성 요소가 포함된 " ":code:`cifar.py`라는 새 파일을 생성해 보겠습니다. 먼저, 필요한 모든 " -"패키지(예: :code:`torch` 및 :code:`torchvision`)를 가져와야 합니다. " -"federated 학습을 위한 패키지를 가져오지 않는 것을 확인 할 수 있습니. 나중에 " -"federated 학습 구성 요소를 추가할 때에도 이러한 모든 가져오기를 그대로 " -"유지할 수 있습니다." +"패키지(예: :code:`torch` 및 :code:`torchvision`)를 가져와야 합니다. 연합 " +"학습을 위한 패키지를 가져오지 않는 것을 확인 할 수 있습니. 나중에 연합 학습 " +"구성 요소를 추가할 때에도 이러한 모든 가져오기를 그대로 유지할 수 있습니다." #: ../../source/example-pytorch-from-centralized-to-federated.rst:32 msgid "" @@ -2946,124 +3001,125 @@ msgstr "" #: ../../source/example-pytorch-from-centralized-to-federated.rst:56 msgid "" -"The :code:`load_data()` function loads the CIFAR-10 training and test " -"sets. The :code:`transform` normalized the data after loading." +"The :code:`load_data()` function loads the CIFAR-10 training and test sets. " +"The :code:`transform` normalized the data after loading." msgstr "" -":code:`load_data()` 함수는 CIFAR-10 훈련 및 테스트 세트를 로드합니다. " -":code:`transform`은 로드 후 데이터를 정규화합니다." +":code:`load_data()` 함수는 CIFAR-10 훈련 및 테스트 세트를 로드합니다. :code:" +"`transform`은 로드 후 데이터를 정규화합니다." #: ../../source/example-pytorch-from-centralized-to-federated.rst:74 msgid "" -"We now need to define the training (function :code:`train()`) which loops" -" over the training set, measures the loss, backpropagates it, and then " -"takes one optimizer step for each batch of training examples." +"We now need to define the training (function :code:`train()`) which loops " +"over the training set, measures the loss, backpropagates it, and then takes " +"one optimizer step for each batch of training examples." msgstr "" "이제 학습 집합을 반복하고, 손실을 측정하고, 이를 역전파한 다음 각 학습 예제 " -"배치에 대해 하나의 최적화 단계를 수행하는 학습(함수 :code:`train()`)을 " -"정의해야 합니다." +"배치에 대해 하나의 최적화 단계를 수행하는 학습(함수 :code:`train()`)을 정의해" +"야 합니다." #: ../../source/example-pytorch-from-centralized-to-federated.rst:76 msgid "" -"The evaluation of the model is defined in the function :code:`test()`. " -"The function loops over all test samples and measures the loss of the " -"model based on the test dataset." +"The evaluation of the model is defined in the function :code:`test()`. The " +"function loops over all test samples and measures the loss of the model " +"based on the test dataset." msgstr "" -"모델 평가는 :code:`test()` 함수에 정의되어 있습니다. 이 함수는 모든 테스트 " -"샘플을 반복하고 테스트 데이터 세트에 따라 모델의 손실을 측정합니다." +"모델 평가는 :code:`test()` 함수에 정의되어 있습니다. 이 함수는 모든 테스트 샘" +"플을 반복하고 테스트 데이터 세트에 따라 모델의 손실을 측정합니다." #: ../../source/example-pytorch-from-centralized-to-federated.rst:136 msgid "" "Having defined the data loading, model architecture, training, and " "evaluation we can put everything together and train our CNN on CIFAR-10." -msgstr "데이터 로딩, 모델 아키텍처, 훈련 및 평가를 정의했으면 모든 것을 종합하여 " +msgstr "" +"데이터 로딩, 모델 아키텍처, 훈련 및 평가를 정의했으면 모든 것을 종합하여 " "CIFAR-10에서 CNN을 훈련할 수 있습니다." #: ../../source/example-pytorch-from-centralized-to-federated.rst:163 msgid "" -"So far, this should all look fairly familiar if you've used PyTorch " -"before. Let's take the next step and use what we've built to create a " -"simple federated learning system consisting of one server and two " -"clients." +"So far, this should all look fairly familiar if you've used PyTorch before. " +"Let's take the next step and use what we've built to create a simple " +"federated learning system consisting of one server and two clients." msgstr "" -"지금까지는 파이토치를 사용해 본 적이 있다면 상당히 익숙하게 보일 것입니다. " -"다음 단계로 넘어가서 구축한 것을 사용하여 하나의 서버와 두 개의 클라이언트로 " -"구성된 간단한 연합 학습 시스템을 만들어 보겠습니다." +"지금까지는 파이토치를 사용해 본 적이 있다면 상당히 익숙하게 보일 것입니다. 다" +"음 단계로 넘어가서 구축한 것을 사용하여 하나의 서버와 두 개의 클라이언트로 구" +"성된 간단한 연합 학습 시스템을 만들어 보겠습니다." #: ../../source/example-pytorch-from-centralized-to-federated.rst:169 msgid "" -"The simple machine learning project discussed in the previous section " -"trains the model on a single dataset (CIFAR-10), we call this centralized" -" learning. This concept of centralized learning, as shown in the previous" -" section, is probably known to most of you, and many of you have used it " -"previously. Normally, if you'd want to run machine learning workloads in " -"a federated fashion, then you'd have to change most of your code and set " -"everything up from scratch. This can be a considerable effort." +"The simple machine learning project discussed in the previous section trains " +"the model on a single dataset (CIFAR-10), we call this centralized learning. " +"This concept of centralized learning, as shown in the previous section, is " +"probably known to most of you, and many of you have used it previously. " +"Normally, if you'd want to run machine learning workloads in a federated " +"fashion, then you'd have to change most of your code and set everything up " +"from scratch. This can be a considerable effort." msgstr "" "이전 섹션에서 설명한 간단한 머신 러닝 프로젝트는 단일 데이터 세트(CIFAR-10)" -"로 모델을 학습시키는데, 이를 centralized 학습이라고 부릅니다. 이전 섹션에서 " -"설명한 centralized 학습의 개념은 대부분 알고 계실 것이며, 많은 분들이 이전에 " -"사용해 보셨을 것입니다. 일반적으로 머신 러닝 워크로드를 federated 방식으로 " +"로 모델을 학습시키는데, 이를 중앙 집중식 학습이라고 부릅니다. 이전 섹션에서 " +"설명한 중앙 집중식 학습의 개념은 대부분 알고 계실 것이며, 많은 분들이 이전에 " +"사용해 보셨을 것입니다. 일반적으로 머신 러닝 워크로드를 연합 방식으로 " "실행하려면 대부분의 코드를 변경하고 모든 것을 처음부터 다시 설정해야 합니다. " "이는 상당한 노력이 필요할 수 있습니다." #: ../../source/example-pytorch-from-centralized-to-federated.rst:173 msgid "" -"However, with Flower you can evolve your pre-existing code into a " -"federated learning setup without the need for a major rewrite." -msgstr "하지만 Flower를 사용하면 대대적인 재작성 없이도 기존 코드를 연합 학습 " -"설정으로 발전시킬 수 있습니다." +"However, with Flower you can evolve your pre-existing code into a federated " +"learning setup without the need for a major rewrite." +msgstr "" +"하지만 Flower를 사용하면 대대적인 재작성 없이도 기존 코드를 연합 학습 설정으" +"로 발전시킬 수 있습니다." #: ../../source/example-pytorch-from-centralized-to-federated.rst:175 msgid "" -"The concept is easy to understand. We have to start a *server* and then " -"use the code in :code:`cifar.py` for the *clients* that are connected to " -"the *server*. The *server* sends model parameters to the clients. The " -"*clients* run the training and update the parameters. The updated " -"parameters are sent back to the *server* which averages all received " -"parameter updates. This describes one round of the federated learning " -"process and we repeat this for multiple rounds." +"The concept is easy to understand. We have to start a *server* and then use " +"the code in :code:`cifar.py` for the *clients* that are connected to the " +"*server*. The *server* sends model parameters to the clients. The *clients* " +"run the training and update the parameters. The updated parameters are sent " +"back to the *server* which averages all received parameter updates. This " +"describes one round of the federated learning process and we repeat this for " +"multiple rounds." msgstr "" "개념은 이해하기 쉽습니다. *서버*를 시작한 다음 *서버*에 연결된 *클라이언트*" "에 대해 :code:`cifar.py`의 코드를 사용해야 합니다. *서버*는 모델 파라미터를 " "클라이언트로 전송합니다. *클라이언트*는 학습을 실행하고 파라미터를 " "업데이트합니다. 업데이트된 파라미터는 *서버*로 다시 전송되며, *서버*는 " -"수신된 모든 파라미터 업데이트의 평균을 구합니다. 이것은 federated 학습 " -"프로세스의 한 라운드를 설명하며 여러 라운드에 걸쳐 이 과정을 반복합니다." +"수신된 모든 파라미터 업데이트의 평균을 구합니다. 이것은 연합 학습 프로세스의 " +"한 라운드를 설명하며 여러 라운드에 걸쳐 이 과정을 반복합니다." #: ../../source/example-pytorch-from-centralized-to-federated.rst:197 msgid "" -"Finally, we will define our *client* logic in :code:`client.py` and build" -" upon the previously defined centralized training in :code:`cifar.py`. " -"Our *client* needs to import :code:`flwr`, but also :code:`torch` to " -"update the parameters on our PyTorch model:" +"Finally, we will define our *client* logic in :code:`client.py` and build " +"upon the previously defined centralized training in :code:`cifar.py`. Our " +"*client* needs to import :code:`flwr`, but also :code:`torch` to update the " +"parameters on our PyTorch model:" msgstr "" "마지막으로, :code:`client.py`에서 *client* 로직을 정의하고 :code:`cifar.py`" -"에서 이전에 정의한 centralized 학습을 기반으로 구축합니다. *클라이언트*는 " +"에서 이전에 정의한 중앙 집중식 학습을 기반으로 구축합니다. *클라이언트*는 " ":code:`flwr`을 가져와야 하며, PyTorch 모델의 파라미터를 업데이트하기 위해 " ":code:`torch`도 가져와야 합니다:" #: ../../source/example-pytorch-from-centralized-to-federated.rst:213 msgid "" -"Implementing a Flower *client* basically means implementing a subclass of" -" either :code:`flwr.client.Client` or :code:`flwr.client.NumPyClient`. " -"Our implementation will be based on :code:`flwr.client.NumPyClient` and " -"we'll call it :code:`CifarClient`. :code:`NumPyClient` is slightly easier" -" to implement than :code:`Client` if you use a framework with good NumPy " -"interoperability (like PyTorch or TensorFlow/Keras) because it avoids " -"some of the boilerplate that would otherwise be necessary. " -":code:`CifarClient` needs to implement four methods, two methods for " -"getting/setting model parameters, one method for training the model, and " -"one method for testing the model:" +"Implementing a Flower *client* basically means implementing a subclass of " +"either :code:`flwr.client.Client` or :code:`flwr.client.NumPyClient`. Our " +"implementation will be based on :code:`flwr.client.NumPyClient` and we'll " +"call it :code:`CifarClient`. :code:`NumPyClient` is slightly easier to " +"implement than :code:`Client` if you use a framework with good NumPy " +"interoperability (like PyTorch or TensorFlow/Keras) because it avoids some " +"of the boilerplate that would otherwise be necessary. :code:`CifarClient` " +"needs to implement four methods, two methods for getting/setting model " +"parameters, one method for training the model, and one method for testing " +"the model:" msgstr "" "Flower *클라이언트*를 구현한다는 것은 기본적으로 :code:`flwr.client.Client` " -"또는 :code:`flwr.client.NumPyClient`의 서브클래스를 구현하는 것을 " -"의미합니다. 우리의 구현은 :code:`flwr.client.NumPyClient`를 기반으로 하며, " -"이를 :code:`CifarClient`라고 부를 것입니다. :code:`NumPyClient`는 파이토치나 " -"텐서플로우/Keras처럼 NumPy 상호운용성이 좋은 프레임워크를 사용하는 경우 " -"필요한 일부 보일러플레이트를 피하기 때문에 :code:`Client`보다 구현하기가 " -"조금 더 쉽습니다. code:`CifarClient`는 모델 파라미터를 가져오거나 설정하는 " -"메서드 2개, 모델 학습을 위한 메서드 1개, 모델 테스트를 위한 메서드 1개 등 네 " -"가지 메서드를 구현해야 합니다:" +"또는 :code:`flwr.client.NumPyClient`의 서브클래스를 구현하는 것을 의미합니" +"다. 우리의 구현은 :code:`flwr.client.NumPyClient`를 기반으로 하며, 이를 :" +"code:`CifarClient`라고 부를 것입니다. :code:`NumPyClient`는 파이토치나 텐서플" +"로우/Keras처럼 NumPy 상호운용성이 좋은 프레임워크를 사용하는 경우 필요한 일" +"부 보일러플레이트를 피하기 때문에 :code:`Client`보다 구현하기가 조금 더 쉽습" +"니다. code:`CifarClient`는 모델 파라미터를 가져오거나 설정하는 메서드 2개, 모" +"델 학습을 위한 메서드 1개, 모델 테스트를 위한 메서드 1개 등 네 가지 메서드를 " +"구현해야 합니다:" #: ../../source/example-pytorch-from-centralized-to-federated.rst:219 msgid ":code:`set_parameters`" @@ -3079,62 +3135,61 @@ msgstr "로컬 손실 및 정확도를 서버에 반환합니다" #: ../../source/example-pytorch-from-centralized-to-federated.rst:232 msgid "" -"The two :code:`NumPyClient` methods :code:`fit` and :code:`evaluate` make" -" use of the functions :code:`train()` and :code:`test()` previously " -"defined in :code:`cifar.py`. So what we really do here is we tell Flower " -"through our :code:`NumPyClient` subclass which of our already defined " -"functions to call for training and evaluation. We included type " -"annotations to give you a better understanding of the data types that get" -" passed around." -msgstr "" -"두 개의 :code:`NumPyClient` 메서드인 :code:`fit`과 :code:`evaluate`는 이전에 " -":code:`cifar.py`에 정의된 함수인 :code:`train()`과 :code:`test()`를 " -"활용합니다. 따라서 여기서 실제로 하는 일은 :code:`NumPyClient` 서브클래스를 " -"통해 이미 정의된 함수 중 훈련과 평가를 위해 호출할 함수를 Flower에 알려주는 " -"것입니다. 전달되는 데이터 유형을 더 잘 이해할 수 있도록 type annotations을 " -"포함했습니다." +"The two :code:`NumPyClient` methods :code:`fit` and :code:`evaluate` make " +"use of the functions :code:`train()` and :code:`test()` previously defined " +"in :code:`cifar.py`. So what we really do here is we tell Flower through " +"our :code:`NumPyClient` subclass which of our already defined functions to " +"call for training and evaluation. We included type annotations to give you a " +"better understanding of the data types that get passed around." +msgstr "" +"두 개의 :code:`NumPyClient` 메서드인 :code:`fit`과 :code:`evaluate`는 이전" +"에 :code:`cifar.py`에 정의된 함수인 :code:`train()`과 :code:`test()`를 활용합" +"니다. 따라서 여기서 실제로 하는 일은 :code:`NumPyClient` 서브클래스를 통해 이" +"미 정의된 함수 중 훈련과 평가를 위해 호출할 함수를 Flower에 알려주는 것입니" +"다. 전달되는 데이터 유형을 더 잘 이해할 수 있도록 type annotations을 포함했습" +"니다." #: ../../source/example-pytorch-from-centralized-to-federated.rst:280 msgid "" "All that's left to do it to define a function that loads both model and " -"data, creates a :code:`CifarClient`, and starts this client. You load " -"your data and model by using :code:`cifar.py`. Start :code:`CifarClient` " -"with the function :code:`fl.client.start_client()` by pointing it at the " -"same IP address we used in :code:`server.py`:" +"data, creates a :code:`CifarClient`, and starts this client. You load your " +"data and model by using :code:`cifar.py`. Start :code:`CifarClient` with the " +"function :code:`fl.client.start_client()` by pointing it at the same IP " +"address we used in :code:`server.py`:" msgstr "" -"이제 모델과 데이터를 모두 로드하는 함수를 정의하고, :code:`CifarClient`를 " -"생성하고, 이 클라이언트를 시작하는 작업만 남았습니다. 코드:`cifar.py`를 " -"사용하여 데이터와 모델을 로드합니다. :code:`server.py`에서 사용한 것과 " -"동일한 IP 주소를 지정하여 :code:`fl.client.start_client()` 함수로 " -":code:`CifarClient`를 시작합니다:" +"이제 모델과 데이터를 모두 로드하는 함수를 정의하고, :code:`CifarClient`를 생" +"성하고, 이 클라이언트를 시작하는 작업만 남았습니다. 코드:`cifar.py`를 사용하" +"여 데이터와 모델을 로드합니다. :code:`server.py`에서 사용한 것과 동일한 IP 주" +"소를 지정하여 :code:`fl.client.start_client()` 함수로 :code:`CifarClient`를 " +"시작합니다:" #: ../../source/example-pytorch-from-centralized-to-federated.rst:307 msgid "" -"in each window (make sure that the server is running before you do so) " -"and see your (previously centralized) PyTorch project run federated " -"learning across two clients. Congratulations!" +"in each window (make sure that the server is running before you do so) and " +"see your (previously centralized) PyTorch project run federated learning " +"across two clients. Congratulations!" msgstr "" -"를 입력하고(그 전에 서버가 실행 중인지 확인하세요) (이전에는centralized) " -"PyTorch 프로젝트가 두 클라이언트에서 federated 학습을 실행하는 것을 " -"확인합니다. 축하합니다!" +"를 입력하고(그 전에 서버가 실행 중인지 확인하세요) (이전에는 중앙 집중식) " +"PyTorch 프로젝트가 두 클라이언트에서 연합 학습을 실행하는 것을 확인합니다. " +"축하합니다!" #: ../../source/example-pytorch-from-centralized-to-federated.rst:312 msgid "" "The full source code for this example: `PyTorch: From Centralized To " -"Federated (Code) `_. Our example is, of course, " -"somewhat over-simplified because both clients load the exact same " -"dataset, which isn't realistic. You're now prepared to explore this topic" -" further. How about using different subsets of CIFAR-10 on each client? " -"How about adding more clients?" -msgstr "" -"이 예제의 전체 소스 코드: `파이토치: 중앙 Centralized에서 Federated으로 " -"(코드) `_. 물론 이 예제는 두 클라이언트가 완전히 동일한 " -"데이터 세트를 로드하기 때문에 다소 지나치게 단순화되어 있으며, 이는 " -"현실적이지 않습니다. 이제 이 주제를 더 자세히 살펴볼 준비가 되셨습니다. 각 " -"클라이언트에서 서로 다른 CIFAR-10의 하위 집합을 사용해 보는 것은 어떨까요? " -"클라이언트를 더 추가하는 것은 어떨까요?" +"Federated (Code) `_. Our example is, of course, somewhat over-" +"simplified because both clients load the exact same dataset, which isn't " +"realistic. You're now prepared to explore this topic further. How about " +"using different subsets of CIFAR-10 on each client? How about adding more " +"clients?" +msgstr "" +"이 예제의 전체 소스 코드: `파이토치: 중앙 Centralized에서 Federated으로 (코" +"드) `_. 물론 이 예제는 두 클라이언트가 완전히 동일한 데" +"이터 세트를 로드하기 때문에 다소 지나치게 단순화되어 있으며, 이는 현실적이지 " +"않습니다. 이제 이 주제를 더 자세히 살펴볼 준비가 되셨습니다. 각 클라이언트에" +"서 서로 다른 CIFAR-10의 하위 집합을 사용해 보는 것은 어떨까요? 클라이언트를 " +"더 추가하는 것은 어떨까요?" #: ../../source/explanation-differential-privacy.rst:2 #: ../../source/explanation-differential-privacy.rst:11 @@ -3144,27 +3199,26 @@ msgstr "차분 프라이버시" #: ../../source/explanation-differential-privacy.rst:3 msgid "" -"The information in datasets like healthcare, financial transactions, user" -" preferences, etc., is valuable and has the potential for scientific " -"breakthroughs and provides important business insights. However, such " -"data is also sensitive and there is a risk of compromising individual " -"privacy." +"The information in datasets like healthcare, financial transactions, user " +"preferences, etc., is valuable and has the potential for scientific " +"breakthroughs and provides important business insights. However, such data " +"is also sensitive and there is a risk of compromising individual privacy." msgstr "" -"의료, 금융 거래, 사용자 선호도 등과 같은 데이터 세트의 정보는 가치 있고 " -"과학적 혁신의 잠재력을 지니고 있으며 중요한 비즈니스 인사이트를 제공합니다. " -"그러나 이러한 데이터는 또한 민감한 정보이며 개인의 프라이버시를 침해할 " -"위험이 있습니다." +"의료, 금융 거래, 사용자 선호도 등과 같은 데이터 세트의 정보는 가치 있고 과학" +"적 혁신의 잠재력을 지니고 있으며 중요한 비즈니스 인사이트를 제공합니다. 그러" +"나 이러한 데이터는 또한 민감한 정보이며 개인의 프라이버시를 침해할 위험이 있" +"습니다." #: ../../source/explanation-differential-privacy.rst:6 msgid "" "Traditional methods like anonymization alone would not work because of " -"attacks like Re-identification and Data Linkage. That's where " -"differential privacy comes in. It provides the possibility of analyzing " -"data while ensuring the privacy of individuals." +"attacks like Re-identification and Data Linkage. That's where differential " +"privacy comes in. It provides the possibility of analyzing data while " +"ensuring the privacy of individuals." msgstr "" -"익명화와 같은 기존 방법만으로는 재식별 및 데이터 연결과 같은 공격으로 인해 " -"효과가 없습니다. 그래서 차분 프라이버시가 등장했습니다. 차등 개인정보 보호는 " -"개인의 프라이버시를 보장하면서 데이터를 분석할 수 있는 가능성을 제공합니다." +"익명화와 같은 기존 방법만으로는 재식별 및 데이터 연결과 같은 공격으로 인해 효" +"과가 없습니다. 그래서 차분 프라이버시가 등장했습니다. 차등 개인정보 보호는 개" +"인의 프라이버시를 보장하면서 데이터를 분석할 수 있는 가능성을 제공합니다." #: ../../source/explanation-differential-privacy.rst:12 msgid "" @@ -3172,8 +3226,8 @@ msgid "" "instance, Alice's data). Differential Privacy (DP) guarantees that any " "analysis (M), like calculating the average income, will produce nearly " "identical results for both datasets (O and O' would be similar). This " -"preserves group patterns while obscuring individual details, ensuring the" -" individual's information remains hidden in the crowd." +"preserves group patterns while obscuring individual details, ensuring the " +"individual's information remains hidden in the crowd." msgstr "" "하나의 레코드(예: 앨리스의 데이터)를 제외하고는 동일한 두 개의 데이터 세트가 " "있다고 상상해 보세요. 차분 프라이버(DP)는 평균 소득 계산과 같은 모든 분석(M)" @@ -3189,12 +3243,11 @@ msgstr "DP 소개" msgid "" "One of the most commonly used mechanisms to achieve DP is adding enough " "noise to the output of the analysis to mask the contribution of each " -"individual in the data while preserving the overall accuracy of the " -"analysis." +"individual in the data while preserving the overall accuracy of the analysis." msgstr "" -"DP를 달성하기 위해 가장 일반적으로 사용되는 메커니즘 중 하나는 분석의 " -"전반적인 정확도를 유지하면서 데이터에서 각 개인의 기여도를 가릴 수 있도록 " -"분석 결과에 충분한 노이즈를 추가하는 것입니다." +"DP를 달성하기 위해 가장 일반적으로 사용되는 메커니즘 중 하나는 분석의 전반적" +"인 정확도를 유지하면서 데이터에서 각 개인의 기여도를 가릴 수 있도록 분석 결과" +"에 충분한 노이즈를 추가하는 것입니다." #: ../../source/explanation-differential-privacy.rst:25 msgid "Formal Definition" @@ -3204,19 +3257,19 @@ msgstr "공식 정의" msgid "" "Differential Privacy (DP) provides statistical guarantees against the " "information an adversary can infer through the output of a randomized " -"algorithm. It provides an unconditional upper bound on the influence of a" -" single individual on the output of the algorithm by adding noise [1]. A " -"randomized mechanism M provides (:math:`\\epsilon`, " -":math:`\\delta`)-differential privacy if for any two neighboring " -"databases, D :sub:`1` and D :sub:`2`, that differ in only a single " -"record, and for all possible outputs S ⊆ Range(A):" +"algorithm. It provides an unconditional upper bound on the influence of a " +"single individual on the output of the algorithm by adding noise [1]. A " +"randomized mechanism M provides (:math:`\\epsilon`, :math:`\\delta`)-" +"differential privacy if for any two neighboring databases, D :sub:`1` and D :" +"sub:`2`, that differ in only a single record, and for all possible outputs S " +"⊆ Range(A):" msgstr "" "차분 프라이버시(DP)는 공격자가 무작위 알고리즘의 출력을 통해 유추할 수 있는 " -"정보에 대해 통계적 보장을 제공합니다. 이는 노이즈를 추가하여 알고리즘의 " -"출력에 대한 한 개인의 영향력에 대한 무조건적인 상한선을 제공합니다[1]. " -"무작위 메커니즘 M은 하나의 레코드만 다른 두 개의 인접 데이터베이스인 " -"D:sub:`1`과 D:sub:`2`의 경우, 가능한 모든 출력 S ⊆ Range(A)에 대해 (:math:`" -"\\epsilon`, :math:`\\delta`)-차분 프라이버시를 제공합니다:" +"정보에 대해 통계적 보장을 제공합니다. 이는 노이즈를 추가하여 알고리즘의 출력" +"에 대한 한 개인의 영향력에 대한 무조건적인 상한선을 제공합니다[1]. 무작위 메" +"커니즘 M은 하나의 레코드만 다른 두 개의 인접 데이터베이스인 D:sub:`1`과 D:" +"sub:`2`의 경우, 가능한 모든 출력 S ⊆ Range(A)에 대해 (:math:`\\epsilon`, :" +"math:`\\delta`)-차분 프라이버시를 제공합니다:" #: ../../source/explanation-differential-privacy.rst:32 msgid "" @@ -3231,19 +3284,19 @@ msgid "" "The :math:`\\epsilon` parameter, also known as the privacy budget, is a " "metric of privacy loss. It also controls the privacy-utility trade-off; " "lower :math:`\\epsilon` values indicate higher levels of privacy but are " -"likely to reduce utility as well. The :math:`\\delta` parameter accounts " -"for a small probability on which the upper bound :math:`\\epsilon` does " -"not hold. The amount of noise needed to achieve differential privacy is " -"proportional to the sensitivity of the output, which measures the maximum" -" change in the output due to the inclusion or removal of a single record." +"likely to reduce utility as well. The :math:`\\delta` parameter accounts for " +"a small probability on which the upper bound :math:`\\epsilon` does not " +"hold. The amount of noise needed to achieve differential privacy is " +"proportional to the sensitivity of the output, which measures the maximum " +"change in the output due to the inclusion or removal of a single record." msgstr "" "프라이버시 예산이라고도 하는 :math:`\\epsilon` 매개변수는 프라이버시 손실을 " -"측정하는 지표입니다. 이 매개변수는 프라이버시와 효용의 균형을 제어하며, " -":math:`\\epsilon` 값이 낮을수록 프라이버시 수준이 높지만 효용도 감소할 " -"가능성이 높습니다. math:`\\delta` 매개변수는 상한값인 :math:`\\epsilon`이 " -"적용되지 않는 작은 확률을 설명합니다. 차분 프라이버시를 달성하는 데 필요한 " -"노이즈의 양은 출력의 감도에 비례하며, 이는 단일 레코드의 포함 또는 제거로 " -"인한 출력의 최대 변화를 측정합니다." +"측정하는 지표입니다. 이 매개변수는 프라이버시와 효용의 균형을 제어하며, :" +"math:`\\epsilon` 값이 낮을수록 프라이버시 수준이 높지만 효용도 감소할 가능성" +"이 높습니다. math:`\\delta` 매개변수는 상한값인 :math:`\\epsilon`이 적용되지 " +"않는 작은 확률을 설명합니다. 차분 프라이버시를 달성하는 데 필요한 노이즈의 양" +"은 출력의 감도에 비례하며, 이는 단일 레코드의 포함 또는 제거로 인한 출력의 최" +"대 변화를 측정합니다." #: ../../source/explanation-differential-privacy.rst:45 msgid "Differential Privacy in Machine Learning" @@ -3253,40 +3306,39 @@ msgstr "머신 러닝의 차분 프라이버시" msgid "" "DP can be utilized in machine learning to preserve the privacy of the " "training data. Differentially private machine learning algorithms are " -"designed in a way to prevent the algorithm to learn any specific " -"information about any individual data points and subsequently prevent the" -" model from revealing sensitive information. Depending on the stage at " -"which noise is introduced, various methods exist for applying DP to " -"machine learning algorithms. One approach involves adding noise to the " -"training data (either to the features or labels), while another method " -"entails injecting noise into the gradients of the loss function during " -"model training. Additionally, such noise can be incorporated into the " -"model's output." -msgstr "" -"머신 러닝에서 DP를 활용하여 학습 데이터의 개인정보를 보호할 수 있습니다. " -"차분 비공개 머신 러닝 알고리즘은 알고리즘이 개별 데이터 포인트에 대한 특정 " -"정보를 학습하지 못하도록 하여 모델이 민감한 정보를 노출하지 않도록 하는 " -"방식으로 설계되었습니다. 노이즈가 도입되는 단계에 따라 머신 러닝 알고리즘에 " -"DP를 적용하는 다양한 방법이 존재합니다. 한 가지 방법은 학습 데이터(특징 또는 " -"레이블)에 노이즈를 추가하는 것이고, 다른 방법은 모델 학습 중에 손실 함수의 " -"기울기에 노이즈를 주입하는 것입니다. 또한 이러한 노이즈를 모델의 출력에 " -"통합할 수도 있습니다." +"designed in a way to prevent the algorithm to learn any specific information " +"about any individual data points and subsequently prevent the model from " +"revealing sensitive information. Depending on the stage at which noise is " +"introduced, various methods exist for applying DP to machine learning " +"algorithms. One approach involves adding noise to the training data (either " +"to the features or labels), while another method entails injecting noise " +"into the gradients of the loss function during model training. Additionally, " +"such noise can be incorporated into the model's output." +msgstr "" +"머신 러닝에서 DP를 활용하여 학습 데이터의 개인정보를 보호할 수 있습니다. 차" +"분 비공개 머신 러닝 알고리즘은 알고리즘이 개별 데이터 포인트에 대한 특정 정보" +"를 학습하지 못하도록 하여 모델이 민감한 정보를 노출하지 않도록 하는 방식으로 " +"설계되었습니다. 노이즈가 도입되는 단계에 따라 머신 러닝 알고리즘에 DP를 적용" +"하는 다양한 방법이 존재합니다. 한 가지 방법은 학습 데이터(특징 또는 레이블)" +"에 노이즈를 추가하는 것이고, 다른 방법은 모델 학습 중에 손실 함수의 기울기에 " +"노이즈를 주입하는 것입니다. 또한 이러한 노이즈를 모델의 출력에 통합할 수도 있" +"습니다." #: ../../source/explanation-differential-privacy.rst:53 msgid "Differential Privacy in Federated Learning" -msgstr "Federated 학습의 차분 프라이버시" +msgstr "연합 학습의 차분 프라이버시" #: ../../source/explanation-differential-privacy.rst:54 msgid "" "Federated learning is a data minimization approach that allows multiple " "parties to collaboratively train a model without sharing their raw data. " "However, federated learning also introduces new privacy challenges. The " -"model updates between parties and the central server can leak information" -" about the local data. These leaks can be exploited by attacks such as " +"model updates between parties and the central server can leak information " +"about the local data. These leaks can be exploited by attacks such as " "membership inference and property inference attacks, or model inversion " "attacks." msgstr "" -"Federated 학습은 여러 당사자가 원시 데이터를 공유하지 않고도 공동으로 모델을 " +"연합 학습은 여러 당사자가 원시 데이터를 공유하지 않고도 공동으로 모델을 " "학습할 수 있는 데이터 최소화 접근 방식입니다. 그러나 연합 학습은 새로운 " "개인정보 보호 문제를 야기하기도 합니다. 당사자와 중앙 서버 간의 모델 " "업데이트는 로컬 데이터에 대한 정보를 유출할 수 있습니다. 이러한 유출은 " @@ -3295,43 +3347,43 @@ msgstr "" #: ../../source/explanation-differential-privacy.rst:58 msgid "" -"DP can play a crucial role in federated learning to provide privacy for " -"the clients' data." -msgstr "DP는 federated학습에서 클라이언트의 데이터에 대한 개인 정보 보호를 제공하는 " -"데 중요한 역할을 할 수 있습니다." +"DP can play a crucial role in federated learning to provide privacy for the " +"clients' data." +msgstr "DP는 연합 학습에서 클라이언트의 데이터에 대한 개인 정보 보호를 제공하는 데 " +"중요한 역할을 할 수 있습니다." #: ../../source/explanation-differential-privacy.rst:60 msgid "" -"Depending on the granularity of privacy provision or the location of " -"noise addition, different forms of DP exist in federated learning. In " -"this explainer, we focus on two approaches of DP utilization in federated" -" learning based on where the noise is added: at the server (also known as" -" the center) or at the client (also known as the local)." +"Depending on the granularity of privacy provision or the location of noise " +"addition, different forms of DP exist in federated learning. In this " +"explainer, we focus on two approaches of DP utilization in federated " +"learning based on where the noise is added: at the server (also known as the " +"center) or at the client (also known as the local)." msgstr "" -"개인 정보 제공의 세분성 또는 노이즈 추가 위치에 따라 federated 학습에는 " -"다양한 형태의 DP가 존재합니다. 이 설명에서는 노이즈가 추가되는 위치에 따라 " -"서버(중앙이라고도 함) 또는 클라이언트(로컬이라고도 함)에서의 federated " -"학습에서 DP를 활용하는 두 가지 접근 방식에 중점을 둡니다." +"개인 정보 제공의 세분성 또는 노이즈 추가 위치에 따라 연합 학습에는 다양한 " +"형태의 DP가 존재합니다. 이 설명에서는 노이즈가 추가되는 위치에 따라 서버(" +"중앙이라고도 함) 또는 클라이언트(로컬이라고도 함)에서의 연합 학습에서 DP를 " +"활용하는 두 가지 접근 방식에 중점을 둡니다." #: ../../source/explanation-differential-privacy.rst:63 msgid "" -"**Central Differential Privacy**: DP is applied by the server and the " -"goal is to prevent the aggregated model from leaking information about " -"each client's data." +"**Central Differential Privacy**: DP is applied by the server and the goal " +"is to prevent the aggregated model from leaking information about each " +"client's data." msgstr "" -"**중앙 차분 프라이버시**: DP는 서버에서 적용되며 집계된 모델이 각 " -"클라이언트의 데이터에 대한 정보를 유출하는 것을 방지하는 것이 목표입니다." +"**중앙 차분 프라이버시**: DP는 서버에서 적용되며 집계된 모델이 각 클라이언트" +"의 데이터에 대한 정보를 유출하는 것을 방지하는 것이 목표입니다." #: ../../source/explanation-differential-privacy.rst:65 msgid "" "**Local Differential Privacy**: DP is applied on the client side before " -"sending any information to the server and the goal is to prevent the " -"updates that are sent to the server from leaking any information about " -"the client's data." +"sending any information to the server and the goal is to prevent the updates " +"that are sent to the server from leaking any information about the client's " +"data." msgstr "" -"**로컬 차분 개인정보 보호**: DP는 정보를 서버로 보내기 전에 클라이언트 " -"측에서 적용되며, 서버로 전송되는 업데이트가 클라이언트 데이터에 대한 정보를 " -"유출하는 것을 방지하는 것이 목표입니다." +"**로컬 차분 개인정보 보호**: DP는 정보를 서버로 보내기 전에 클라이언트 측에" +"서 적용되며, 서버로 전송되는 업데이트가 클라이언트 데이터에 대한 정보를 유출" +"하는 것을 방지하는 것이 목표입니다." #: ../../source/explanation-differential-privacy.rst:-1 #: ../../source/explanation-differential-privacy.rst:68 @@ -3341,30 +3393,30 @@ msgstr "중앙 차분 프라이버시" #: ../../source/explanation-differential-privacy.rst:69 msgid "" -"In this approach, which is also known as user-level DP, the central " -"server is responsible for adding noise to the globally aggregated " -"parameters. It should be noted that trust in the server is required." +"In this approach, which is also known as user-level DP, the central server " +"is responsible for adding noise to the globally aggregated parameters. It " +"should be noted that trust in the server is required." msgstr "" -"사용자 수준 DP라고도 하는 이 접근 방식에서는 중앙 서버가 전역적으로 집계된 " -"매개변수에 노이즈를 추가하는 역할을 담당합니다. 서버에 대한 신뢰가 " -"필요하다는 점에 유의해야 합니다." +"사용자 수준 DP라고도 하는 이 접근 방식에서는 중앙 서버가 전역적으로 집계된 매" +"개변수에 노이즈를 추가하는 역할을 담당합니다. 서버에 대한 신뢰가 필요하다는 " +"점에 유의해야 합니다." #: ../../source/explanation-differential-privacy.rst:76 msgid "" -"While there are various ways to implement central DP in federated " -"learning, we concentrate on the algorithms proposed by [2] and [3]. The " -"overall approach is to clip the model updates sent by the clients and add" -" some amount of noise to the aggregated model. In each iteration, a " -"random set of clients is chosen with a specific probability for training." -" Each client performs local training on its own data. The update of each " -"client is then clipped by some value `S` (sensitivity `S`). This would " -"limit the impact of any individual client which is crucial for privacy " -"and often beneficial for robustness. A common approach to achieve this is" -" by restricting the `L2` norm of the clients' model updates, ensuring " -"that larger updates are scaled down to fit within the norm `S`." -msgstr "" -"federated 학습에서 중앙 DP를 구현하는 방법은 여러 가지가 있지만, 여기서는 [2]" -"와 [3]에서 제안한 알고리즘에 집중합니다. 전반적인 접근 방식은 클라이언트가 " +"While there are various ways to implement central DP in federated learning, " +"we concentrate on the algorithms proposed by [2] and [3]. The overall " +"approach is to clip the model updates sent by the clients and add some " +"amount of noise to the aggregated model. In each iteration, a random set of " +"clients is chosen with a specific probability for training. Each client " +"performs local training on its own data. The update of each client is then " +"clipped by some value `S` (sensitivity `S`). This would limit the impact of " +"any individual client which is crucial for privacy and often beneficial for " +"robustness. A common approach to achieve this is by restricting the `L2` " +"norm of the clients' model updates, ensuring that larger updates are scaled " +"down to fit within the norm `S`." +msgstr "" +"연합 학습에서 중앙 DP를 구현하는 방법은 여러 가지가 있지만, 여기서는 [2]와 " +"[3]에서 제안한 알고리즘에 집중합니다. 전반적인 접근 방식은 클라이언트가 " "전송한 모델 업데이트를 잘라내고 집계된 모델에 약간의 노이즈를 추가하는 " "것입니다. 각 반복에서 특정 확률로 훈련할 무작위 클라이언트 세트가 " "선택됩니다. 각 클라이언트는 자체 데이터에 대해 로컬 학습을 수행합니다. 그런 " @@ -3380,17 +3432,17 @@ msgstr "클리핑" #: ../../source/explanation-differential-privacy.rst:89 msgid "" -"Afterwards, the Gaussian mechanism is used to add noise in order to " -"distort the sum of all clients' updates. The amount of noise is scaled to" -" the sensitivity value to obtain a privacy guarantee. The Gaussian " -"mechanism is used with a noise sampled from `N (0, σ²)` where `σ = ( " -"noise_scale * S ) / (number of sampled clients)`." +"Afterwards, the Gaussian mechanism is used to add noise in order to distort " +"the sum of all clients' updates. The amount of noise is scaled to the " +"sensitivity value to obtain a privacy guarantee. The Gaussian mechanism is " +"used with a noise sampled from `N (0, σ²)` where `σ = ( noise_scale * S ) / " +"(number of sampled clients)`." msgstr "" -"그 후 가우시안 메커니즘을 사용하여 모든 클라이언트의 업데이트 합계를 " -"왜곡하기 위해 노이즈를 추가합니다. 노이즈의 양은 감도 값에 따라 조정되어 " -"프라이버시 보장을 얻습니다. 가우시안 메커니즘은 `N (0, σ²)`에서 샘플링된 " -"노이즈와 함께 사용됩니다. 여기서 `σ = (noise_scale * S) / (샘플링된 " -"클라이언트 수)`입니다." +"그 후 가우시안 메커니즘을 사용하여 모든 클라이언트의 업데이트 합계를 왜곡하" +"기 위해 노이즈를 추가합니다. 노이즈의 양은 감도 값에 따라 조정되어 프라이버" +"시 보장을 얻습니다. 가우시안 메커니즘은 `N (0, σ²)`에서 샘플링된 노이즈와 함" +"께 사용됩니다. 여기서 `σ = (noise_scale * S) / (샘플링된 클라이언트 수)`입니" +"다." #: ../../source/explanation-differential-privacy.rst:94 msgid "Clipping" @@ -3398,39 +3450,40 @@ msgstr "클리핑" #: ../../source/explanation-differential-privacy.rst:96 msgid "" -"There are two forms of clipping commonly used in Central DP: Fixed " -"Clipping and Adaptive Clipping." -msgstr "Central DP에서 일반적으로 사용되는 클리핑에는 고정 클리핑과 조정 클리핑의 두 " +"There are two forms of clipping commonly used in Central DP: Fixed Clipping " +"and Adaptive Clipping." +msgstr "중앙 DP에서 일반적으로 사용되는 클리핑에는 고정 클리핑과 조정 클리핑의 두 " "가지 형태가 있습니다." #: ../../source/explanation-differential-privacy.rst:98 msgid "" -"**Fixed Clipping** : A predefined fix threshold is set for the magnitude " -"of clients' updates. Any update exceeding this threshold is clipped back " -"to the threshold value." +"**Fixed Clipping** : A predefined fix threshold is set for the magnitude of " +"clients' updates. Any update exceeding this threshold is clipped back to the " +"threshold value." msgstr "" -"**고정 클리핑** : 클라이언트의 업데이트 크기에 대해 미리 정의된 고정 " -"임계값이 설정됩니다. 이 임계값을 초과하는 모든 업데이트는 임계값으로 다시 " -"클리핑됩니다." +"**고정 클리핑** : 클라이언트의 업데이트 크기에 대해 미리 정의된 고정 임계값" +"이 설정됩니다. 이 임계값을 초과하는 모든 업데이트는 임계값으로 다시 클리핑됩" +"니다." #: ../../source/explanation-differential-privacy.rst:100 msgid "" -"**Adaptive Clipping** : The clipping threshold dynamically adjusts based " -"on the observed update distribution [4]. It means that the clipping value" -" is tuned during the rounds with respect to the quantile of the update " -"norm distribution." +"**Adaptive Clipping** : The clipping threshold dynamically adjusts based on " +"the observed update distribution [4]. It means that the clipping value is " +"tuned during the rounds with respect to the quantile of the update norm " +"distribution." msgstr "" -"**조 클리핑** : 클리핑 임계값은 관찰된 업데이트 분포에 따라 동적으로 " +"**조정 클리핑** : 클리핑 임계값은 관찰된 업데이트 분포에 따라 동적으로 " "조정됩니다[4]. 즉, 클리핑 값은 업데이트 표준 분포의 사분위수에 따라 라운드가 " "진행되는 동안 조정됩니다." #: ../../source/explanation-differential-privacy.rst:102 msgid "" -"The choice between fixed and adaptive clipping depends on various factors" -" such as privacy requirements, data distribution, model complexity, and " +"The choice between fixed and adaptive clipping depends on various factors " +"such as privacy requirements, data distribution, model complexity, and " "others." -msgstr "고정 클리핑과 조정 클리핑 중 선택은 개인정보 보호 요구 사항, 데이터 배포, " -"모델 복잡성 등 다양한 요인에 따라 달라집니다." +msgstr "" +"고정 클리핑과 조정 클리핑 중 선택은 개인정보 보호 요구 사항, 데이터 배포, 모" +"델 복잡성 등 다양한 요인에 따라 달라집니다." #: ../../source/explanation-differential-privacy.rst:-1 #: ../../source/explanation-differential-privacy.rst:105 @@ -3441,13 +3494,13 @@ msgstr "로컬 차분 프라이버시" #: ../../source/explanation-differential-privacy.rst:107 msgid "" "In this approach, each client is responsible for performing DP. Local DP " -"avoids the need for a fully trusted aggregator, but it should be noted " -"that local DP leads to a decrease in accuracy but better privacy in " -"comparison to central DP." +"avoids the need for a fully trusted aggregator, but it should be noted that " +"local DP leads to a decrease in accuracy but better privacy in comparison to " +"central DP." msgstr "" -"이 접근 방식에서는 각 클라이언트가 DP를 수행할 책임이 있습니다. 로컬 DP는 " -"완전히 신뢰할 수 있는 애그리게이터가 필요하지 않지만, 로컬 DP는 중앙 DP에 " -"비해 정확도는 떨어져도 개인 정보 보호는 더 우수하다는 점에 유의해야 합니다." +"이 접근 방식에서는 각 클라이언트가 DP를 수행할 책임이 있습니다. 로컬 DP는 완" +"전히 신뢰할 수 있는 애그리게이터가 필요하지 않지만, 로컬 DP는 중앙 DP에 비해 " +"정확도는 떨어져도 개인 정보 보호는 더 우수하다는 점에 유의해야 합니다." #: ../../source/explanation-differential-privacy.rst:116 msgid "In this explainer, we focus on two forms of achieving Local DP:" @@ -3456,25 +3509,25 @@ msgstr "이 설명에서는 로컬 DP를 달성하는 두 가지 형태에 중 #: ../../source/explanation-differential-privacy.rst:118 msgid "" "Each client adds noise to the local updates before sending them to the " -"server. To achieve (:math:`\\epsilon`, :math:`\\delta`)-DP, considering " -"the sensitivity of the local model to be ∆, Gaussian noise is applied " -"with a noise scale of σ where:" +"server. To achieve (:math:`\\epsilon`, :math:`\\delta`)-DP, considering the " +"sensitivity of the local model to be ∆, Gaussian noise is applied with a " +"noise scale of σ where:" msgstr "" "각 클라이언트는 로컬 업데이트를 서버로 보내기 전에 로컬 업데이트에 노이즈를 " -"추가합니다. 로컬 모델의 감도를 ∆로 간주하여 가우시안 노이즈가 σ의 노이즈 " -"스케일로 적용되어 (:math:`\\epsilon`, :math:`\\delta`)-DP를 달성하기 위해, " -"여기서 σ는 노이즈 스케일입니다:" +"추가합니다. 로컬 모델의 감도를 ∆로 간주하여 가우시안 노이즈가 σ의 노이즈 스케" +"일로 적용되어 (:math:`\\epsilon`, :math:`\\delta`)-DP를 달성하기 위해, 여기" +"서 σ는 노이즈 스케일입니다:" #: ../../source/explanation-differential-privacy.rst:120 msgid "" "\\small\n" -"\\frac{∆ \\times \\sqrt{2 \\times " -"\\log\\left(\\frac{1.25}{\\delta}\\right)}}{\\epsilon}\n" +"\\frac{∆ \\times \\sqrt{2 \\times \\log\\left(\\frac{1.25}{\\delta}\\right)}}" +"{\\epsilon}\n" "\n" msgstr "" "\\small\n" -"\\frac{∆ \\times \\sqrt{2 \\times \\log\\left(\\frac{1.25}{\\delta}\\right" -")}}{\\epsilon}\n" +"\\frac{∆ \\times \\sqrt{2 \\times \\log\\left(\\frac{1.25}{\\delta}\\right)}}" +"{\\epsilon}\n" "\n" #: ../../source/explanation-differential-privacy.rst:125 @@ -3483,15 +3536,16 @@ msgid "" "training (DP-SGD). More specifically, in this approach, gradients are " "clipped and an amount of calibrated noise is injected into the gradients." msgstr "" -"각 클라이언트는 로컬 트레이닝(DP-SGD) 중에 모델의 gradient에 노이즈를 " -"추가합니다. 보다 구체적으로, 이 접근 방식에서는 gradient이 클리핑되고 보정된 " -"노이즈가 gradient에 주입됩니다." +"각 클라이언트는 로컬 트레이닝(DP-SGD) 중에 모델의 gradient에 노이즈를 추가합" +"니다. 보다 구체적으로, 이 접근 방식에서는 gradient이 클리핑되고 보정된 노이즈" +"가 gradient에 주입됩니다." #: ../../source/explanation-differential-privacy.rst:128 msgid "" "Please note that these two approaches are providing privacy at different " "levels." -msgstr "이 두 가지 접근 방식은 서로 다른 수준의 개인정보 보호 기능을 제공한다는 점에 " +msgstr "" +"이 두 가지 접근 방식은 서로 다른 수준의 개인정보 보호 기능을 제공한다는 점에 " "유의하세요." #: ../../source/explanation-differential-privacy.rst:131 @@ -3504,38 +3558,37 @@ msgstr "[1] Dwork 외. 차분 프라이버시의 알고리즘적 기초." #: ../../source/explanation-differential-privacy.rst:135 msgid "" -"[2] McMahan et al. Learning Differentially Private Recurrent Language " -"Models." +"[2] McMahan et al. Learning Differentially Private Recurrent Language Models." msgstr "[2] McMahan 외. 차분적 개인 반복 언어 모델 학습." #: ../../source/explanation-differential-privacy.rst:137 msgid "" -"[3] Geyer et al. Differentially Private Federated Learning: A Client " -"Level Perspective." -msgstr "[3] Geyer 외. 차분적 개인 Federated 학습: 고객 수준의 관점." +"[3] Geyer et al. Differentially Private Federated Learning: A Client Level " +"Perspective." +msgstr "[3] Geyer 외. 차분적 개인 연합 학습: 고객 수준의 관점." #: ../../source/explanation-differential-privacy.rst:139 -msgid "[4] Galen et al. Differentially Private Learning with Adaptive Clipping." +msgid "" +"[4] Galen et al. Differentially Private Learning with Adaptive Clipping." msgstr "[4] Galen 외. 조정형 클리핑을 통한 차분적 개인 학습." #: ../../source/explanation-federated-evaluation.rst:2 #: ../../source/tutorial-series-what-is-federated-learning.ipynb:292 msgid "Federated evaluation" -msgstr "Federated 평가" +msgstr "연합 평가" #: ../../source/explanation-federated-evaluation.rst:4 msgid "" "There are two main approaches to evaluating models in federated learning " -"systems: centralized (or server-side) evaluation and federated (or " -"client-side) evaluation." +"systems: centralized (or server-side) evaluation and federated (or client-" +"side) evaluation." msgstr "" -"federated 학습 시스템에서 모델을 평가하는 데는 centralized(또는 서버 측) " -"평가와 federated(또는 클라이언트 측) 평가라는 두 가지 주요 접근 방식이 " -"있습니다." +"연합 학습 시스템에서 모델을 평가하는 데는 중앙 집중식(또는 서버 측) 평가와 " +"연합(또는 클라이언트 측) 평가라는 두 가지 주요 접근 방식이 있습니다." #: ../../source/explanation-federated-evaluation.rst:8 msgid "Centralized Evaluation" -msgstr "Centralized 평가" +msgstr "중앙 집중식 평가" #: ../../source/explanation-federated-evaluation.rst:11 msgid "Built-In Strategies" @@ -3548,7 +3601,7 @@ msgid "" "function that can take the current global model parameters as input and " "return evaluation results:" msgstr "" -"모든 기본 제공 전략은 초기화 중에 평가 함수를 제공하여 centralized 평가를 " +"모든 기본 제공 전략은 초기화 중에 평가 함수를 제공하여 중앙 집중식 평가를 " "지원합니다. 평가 함수는 현재 글로벌 모델 파라미터를 입력으로 받아 평가 " "결과를 반환할 수 있는 모든 함수입니다:" @@ -3558,97 +3611,95 @@ msgstr "사용자 정의 전략" #: ../../source/explanation-federated-evaluation.rst:60 msgid "" -"The :code:`Strategy` abstraction provides a method called " -":code:`evaluate` that can directly be used to evaluate the current global" -" model parameters. The current server implementation calls " -":code:`evaluate` after parameter aggregation and before federated " -"evaluation (see next paragraph)." +"The :code:`Strategy` abstraction provides a method called :code:`evaluate` " +"that can directly be used to evaluate the current global model parameters. " +"The current server implementation calls :code:`evaluate` after parameter " +"aggregation and before federated evaluation (see next paragraph)." msgstr "" -"코드:`전략` 추상화는 현재 전역 모델 파라미터를 평가하는 데 직접 사용할 수 " -"있는 :코드:`평가`라는 메서드를 제공합니다. 현재 서버 구현에서는 매개변수 " -"집계 후와 연합 평가 전에 :code:`evaluate`를 호출합니다(다음 단락 참조)." +"코드:`전략` 추상화는 현재 전역 모델 파라미터를 평가하는 데 직접 사용할 수 있" +"는 :코드:`평가`라는 메서드를 제공합니다. 현재 서버 구현에서는 매개변수 집계 " +"후와 연합 평가 전에 :code:`evaluate`를 호출합니다(다음 단락 참조)." #: ../../source/explanation-federated-evaluation.rst:65 msgid "Federated Evaluation" -msgstr "Federated 평가" +msgstr "연합 평가" #: ../../source/explanation-federated-evaluation.rst:68 msgid "Implementing Federated Evaluation" -msgstr "Federated 평가 구현" +msgstr "연합 평가 구현" #: ../../source/explanation-federated-evaluation.rst:70 msgid "" -"Client-side evaluation happens in the :code:`Client.evaluate` method and " -"can be configured from the server side." -msgstr "클라이언트 측 평가는 :code:`Client.evaluate` 메서드에서 이루어지며 서버 " -"측에서 구성할 수 있습니다." +"Client-side evaluation happens in the :code:`Client.evaluate` method and can " +"be configured from the server side." +msgstr "" +"클라이언트 측 평가는 :code:`Client.evaluate` 메서드에서 이루어지며 서버 측에" +"서 구성할 수 있습니다." #: ../../source/explanation-federated-evaluation.rst:101 msgid "Configuring Federated Evaluation" -msgstr "Federated 평가 구성" +msgstr "연합 평가 구성" #: ../../source/explanation-federated-evaluation.rst:103 msgid "" "Federated evaluation can be configured from the server side. Built-in " "strategies support the following arguments:" -msgstr "Federated 평가는 서버 측에서 구성할 수 있습니다. 기본 제공 전략은 다음 " -"인수를 지원합니다:" +msgstr "연합 평가는 서버 측에서 구성할 수 있습니다. 기본 제공 전략은 다음 인수를 " +"지원합니다:" #: ../../source/explanation-federated-evaluation.rst:105 msgid "" -":code:`fraction_evaluate`: a :code:`float` defining the fraction of " -"clients that will be selected for evaluation. If " -":code:`fraction_evaluate` is set to :code:`0.1` and :code:`100` clients " -"are connected to the server, then :code:`10` will be randomly selected " -"for evaluation. If :code:`fraction_evaluate` is set to :code:`0.0`, " -"federated evaluation will be disabled." +":code:`fraction_evaluate`: a :code:`float` defining the fraction of clients " +"that will be selected for evaluation. If :code:`fraction_evaluate` is set " +"to :code:`0.1` and :code:`100` clients are connected to the server, then :" +"code:`10` will be randomly selected for evaluation. If :code:" +"`fraction_evaluate` is set to :code:`0.0`, federated evaluation will be " +"disabled." msgstr "" ":code:`fraction_evaluate`: 평가를 위해 선택될 클라이언트의 비율을 정의하는 " ":code:`float`입니다. 코드:`fraction_evaluate`가 :code:`0.1`로 설정되어 있고 " ":code:`100` 클라이언트가 서버에 연결되어 있는 경우 :code:`10`이 평가를 위해 " "무작위로 선택됩니다. code:`fraction_evaluate`가 :code:`0.0`으로 설정된 경우 " -"federated 평가가 비활성화됩니다." +"연합 평가가 비활성화됩니다." #: ../../source/explanation-federated-evaluation.rst:106 msgid "" -":code:`min_evaluate_clients`: an :code:`int`: the minimum number of " -"clients to be selected for evaluation. If :code:`fraction_evaluate` is " -"set to :code:`0.1`, :code:`min_evaluate_clients` is set to 20, and " -":code:`100` clients are connected to the server, then :code:`20` clients " -"will be selected for evaluation." +":code:`min_evaluate_clients`: an :code:`int`: the minimum number of clients " +"to be selected for evaluation. If :code:`fraction_evaluate` is set to :code:" +"`0.1`, :code:`min_evaluate_clients` is set to 20, and :code:`100` clients " +"are connected to the server, then :code:`20` clients will be selected for " +"evaluation." msgstr "" -":code:`min_evaluate_clients`: 평가를 위해 선택할 최소 클라이언트 수. " -":code:`int`. 코드:`fraction_evaluate`가 :code:`0.1`로 설정되어 있고 " -":code:`fraction_evaluate`가 20으로 설정되어 있으며 :code:`100` 클라이언트가 " -"서버에 연결되어 있는 경우 :code:`20` 클라이언트가 평가를 위해 선택됩니다." +":code:`min_evaluate_clients`: 평가를 위해 선택할 최소 클라이언트 수. :code:" +"`int`. 코드:`fraction_evaluate`가 :code:`0.1`로 설정되어 있고 :code:" +"`fraction_evaluate`가 20으로 설정되어 있으며 :code:`100` 클라이언트가 서버에 " +"연결되어 있는 경우 :code:`20` 클라이언트가 평가를 위해 선택됩니다." #: ../../source/explanation-federated-evaluation.rst:107 msgid "" ":code:`min_available_clients`: an :code:`int` that defines the minimum " -"number of clients which need to be connected to the server before a round" -" of federated evaluation can start. If fewer than " -":code:`min_available_clients` are connected to the server, the server " -"will wait until more clients are connected before it continues to sample " -"clients for evaluation." -msgstr "" -":code:`min_available_clients`: federated 평가 단계를 시작하기 전에 서버에 " -"연결해야 하는 최소 클라이언트 수를 정의하는 :code:`int`입니다. 서버에 연결된 " -"클라이언트가 :code:`min_available_clients`보다 적으면 서버는 더 많은 " -"클라이언트가 연결될 때까지 기다렸다가 평가를 위한 클라이언트 샘플링을 " -"계속합니다." +"number of clients which need to be connected to the server before a round of " +"federated evaluation can start. If fewer than :code:`min_available_clients` " +"are connected to the server, the server will wait until more clients are " +"connected before it continues to sample clients for evaluation." +msgstr "" +":code:`min_available_clients`: federated 평가 단계를 시작하기 전에 서버에 연" +"결해야 하는 최소 클라이언트 수를 정의하는 :code:`int`입니다. 서버에 연결된 클" +"라이언트가 :code:`min_available_clients`보다 적으면 서버는 더 많은 클라이언트" +"가 연결될 때까지 기다렸다가 평가를 위한 클라이언트 샘플링을 계속합니다." #: ../../source/explanation-federated-evaluation.rst:108 msgid "" ":code:`on_evaluate_config_fn`: a function that returns a configuration " -"dictionary which will be sent to the selected clients. The function will " -"be called during each round and provides a convenient way to customize " -"client-side evaluation from the server side, for example, to configure " -"the number of validation steps performed." +"dictionary which will be sent to the selected clients. The function will be " +"called during each round and provides a convenient way to customize client-" +"side evaluation from the server side, for example, to configure the number " +"of validation steps performed." msgstr "" -"code:`on_evaluate_config_fn`: 선택한 클라이언트로 전송할 구성 사전을 " -"반환하는 함수입니다. 이 함수는 각 단계 중에 호출되며, 서버 측에서 클라이언트 " -"측 평가를 사용자 지정하는 편리한 방법을 제공합니다(예: 수행되는 유효성 검사 " -"단계 수 구성)." +"code:`on_evaluate_config_fn`: 선택한 클라이언트로 전송할 구성 사전을 반환하" +"는 함수입니다. 이 함수는 각 단계 중에 호출되며, 서버 측에서 클라이언트 측 평" +"가를 사용자 지정하는 편리한 방법을 제공합니다(예: 수행되는 유효성 검사 단계 " +"수 구성)." #: ../../source/explanation-federated-evaluation.rst:135 msgid "Evaluating Local Model Updates During Training" @@ -3656,9 +3707,8 @@ msgstr "훈련 중 로컬 모델 업데이트 평가" #: ../../source/explanation-federated-evaluation.rst:137 msgid "" -"Model parameters can also be evaluated during training. " -":code:`Client.fit` can return arbitrary evaluation results as a " -"dictionary:" +"Model parameters can also be evaluated during training. :code:`Client.fit` " +"can return arbitrary evaluation results as a dictionary:" msgstr "" "모델 파라미터는 훈련 중에도 평가할 수 있습니다. :code:`Client.fit`은 임의의 " "평가 결과를 dictionary로 반환할 수 있습니다:" @@ -3669,12 +3719,12 @@ msgstr "전체 코드 예제" #: ../../source/explanation-federated-evaluation.rst:179 msgid "" -"For a full code example that uses both centralized and federated " -"evaluation, see the *Advanced TensorFlow Example* (the same approach can " -"be applied to workloads implemented in any other framework): " -"https://github.com/adap/flower/tree/main/examples/advanced-tensorflow" +"For a full code example that uses both centralized and federated evaluation, " +"see the *Advanced TensorFlow Example* (the same approach can be applied to " +"workloads implemented in any other framework): https://github.com/adap/" +"flower/tree/main/examples/advanced-tensorflow" msgstr "" -"federated 평가와 centralized 평가를 모두 사용하는 전체 코드 예제는 *고급 " +"연합 평가와 중앙 집중식 평가를 모두 사용하는 전체 코드 예제는 *고급 " "텐서플로우 예제*(다른 프레임워크에서 구현된 워크로드에도 동일한 접근 방식을 " "적용할 수 있음)를 참조하세요: https://github.com/adap/flower/tree/main/" "examples/advanced-tensorflow" @@ -3850,13 +3900,13 @@ msgstr "운행 중 작업 추적을 위한 깃허브 이슈를 예약합니다" #: ../../source/fed/0001-20220311-flower-enhancement-doc.md:37 msgid "" -"ensure community participants can successfully drive changes to " -"completion across one or more releases while stakeholders are adequately " -"represented throughout the process" +"ensure community participants can successfully drive changes to completion " +"across one or more releases while stakeholders are adequately represented " +"throughout the process" msgstr "" -"커뮤니티 참여자가 하나 이상의 릴리즈에서 변경 사항을 성공적으로 완료할 수 " -"있도록 하는 동시에 이해 관계자가 프로세스 전반에 걸쳐 적절히 대표되도록 " -"보장합니다" +"커뮤니티 참여자가 하나 이상의 릴리즈에서 변경 사항을 성공적으로 완료할 수 있" +"도록 하는 동시에 이해 관계자가 프로세스 전반에 걸쳐 적절히 대표되도록 보장합" +"니다" #: ../../source/fed/0001-20220311-flower-enhancement-doc.md:39 msgid "Hence, an Enhancement Doc combines aspects of" @@ -3883,72 +3933,72 @@ msgstr "를 하나의 파일로 통합하여 커뮤니티와 협력해 점진적 #: ../../source/fed/0001-20220311-flower-enhancement-doc.md:49 msgid "" "For far-fetching changes or features proposed to Flower, an abstraction " -"beyond a single GitHub issue or pull request is required to understand " -"and communicate upcoming changes to the project." +"beyond a single GitHub issue or pull request is required to understand and " +"communicate upcoming changes to the project." msgstr "" -"Flower에 제안된 변경 사항이나 기능을 멀리 가져오는 경우, 프로젝트의 향후 " -"변경 사항을 이해하고 전달하기 위해 단일 GitHub 이슈 또는 pull request를 " -"넘어서는 abstraction이 필요합니다." +"Flower에 제안된 변경 사항이나 기능을 멀리 가져오는 경우, 프로젝트의 향후 변" +"경 사항을 이해하고 전달하기 위해 단일 GitHub 이슈 또는 pull request를 넘어서" +"는 abstraction이 필요합니다." #: ../../source/fed/0001-20220311-flower-enhancement-doc.md:51 msgid "" -"The purpose of this process is to reduce the amount of \"tribal " -"knowledge\" in our community. By moving decisions from Slack threads, " -"video calls, and hallway conversations into a well-tracked artifact, this" -" process aims to enhance communication and discoverability." +"The purpose of this process is to reduce the amount of \"tribal knowledge\" " +"in our community. By moving decisions from Slack threads, video calls, and " +"hallway conversations into a well-tracked artifact, this process aims to " +"enhance communication and discoverability." msgstr "" -"이 프로세스의 목적은 커뮤니티 내 '부족한 지식'의 양을 줄이는 것입니다. 이 " -"프로세스는 Slack 스레드, 영상 통화, 복도 대화에서 나온 의사 결정을 잘 추적된 " -"아티팩트로 옮김으로써 커뮤니케이션과 검색 가능성을 향상시키는 것을 목표로 " -"합니다." +"이 프로세스의 목적은 커뮤니티 내 '부족한 지식'의 양을 줄이는 것입니다. 이 프" +"로세스는 Slack 스레드, 영상 통화, 복도 대화에서 나온 의사 결정을 잘 추적된 아" +"티팩트로 옮김으로써 커뮤니케이션과 검색 가능성을 향상시키는 것을 목표로 합니" +"다." #: ../../source/fed/0001-20220311-flower-enhancement-doc.md:55 msgid "" -"Roughly any larger, user-facing enhancement should follow the Enhancement" -" process. If an enhancement would be described in either written or " -"verbal communication to anyone besides the author or developer, then " -"consider creating an Enhancement Doc." +"Roughly any larger, user-facing enhancement should follow the Enhancement " +"process. If an enhancement would be described in either written or verbal " +"communication to anyone besides the author or developer, then consider " +"creating an Enhancement Doc." msgstr "" "대략적으로 사용자를 대상으로 하는 대규모 개선 사항은 개선 프로세스를 따라야 " -"합니다. 개선 사항을 작성자나 개발자 이외의 다른 사람에게 서면 또는 구두로 " -"설명해야 하는 경우에는 개선 문서 작성을 고려하세요." +"합니다. 개선 사항을 작성자나 개발자 이외의 다른 사람에게 서면 또는 구두로 설" +"명해야 하는 경우에는 개선 문서 작성을 고려하세요." #: ../../source/fed/0001-20220311-flower-enhancement-doc.md:57 msgid "" -"Similarly, any technical effort (refactoring, major architectural change)" -" that will impact a large section of the development community should " -"also be communicated widely. The Enhancement process is suited for this " -"even if it will have zero impact on the typical user or operator." +"Similarly, any technical effort (refactoring, major architectural change) " +"that will impact a large section of the development community should also be " +"communicated widely. The Enhancement process is suited for this even if it " +"will have zero impact on the typical user or operator." msgstr "" -"마찬가지로 개발 커뮤니티의 많은 부분에 영향을 미치는 기술적 노력(리팩토링, " -"주요 아키텍처 변경)도 널리 알려야 합니다. 개선 프로세스는 일반 사용자나 " -"운영자에게 전혀 영향을 미치지 않더라도 이를 위해 적합합니다." +"마찬가지로 개발 커뮤니티의 많은 부분에 영향을 미치는 기술적 노력(리팩토링, 주" +"요 아키텍처 변경)도 널리 알려야 합니다. 개선 프로세스는 일반 사용자나 운영자" +"에게 전혀 영향을 미치지 않더라도 이를 위해 적합합니다." #: ../../source/fed/0001-20220311-flower-enhancement-doc.md:61 msgid "" -"For small changes and additions, going through the Enhancement process " -"would be time-consuming and unnecessary. This includes, for example, " -"adding new Federated Learning algorithms, as these only add features " -"without changing how Flower works or is used." +"For small changes and additions, going through the Enhancement process would " +"be time-consuming and unnecessary. This includes, for example, adding new " +"Federated Learning algorithms, as these only add features without changing " +"how Flower works or is used." msgstr "" "작은 변경 및 추가의 경우, 개선 프로세스를 거치는 것은 시간이 많이 걸리고 " -"불필요합니다. 예를 들어, 새로운 Federated 학습 알고리즘을 추가하는 것은 " -"Flower의 작동 방식이나 사용 방식을 변경하지 않고 기능만 추가하는 것이기 " -"때문입니다." +"불필요합니다. 예를 들어, 새로운 연합 학습 알고리즘을 추가하는 것은 Flower의 " +"작동 방식이나 사용 방식을 변경하지 않고 기능만 추가하는 것이기 때문입니다." #: ../../source/fed/0001-20220311-flower-enhancement-doc.md:63 msgid "" "Enhancements are different from feature requests, as they are already " -"providing a laid-out path for implementation and are championed by " -"members of the community." -msgstr "기능 개선은 이미 구현할 수 있는 경로가 마련되어 있고 커뮤니티 구성원들이 " -"지지하는 것이므로 기능 요청과는 다릅니다." +"providing a laid-out path for implementation and are championed by members " +"of the community." +msgstr "" +"기능 개선은 이미 구현할 수 있는 경로가 마련되어 있고 커뮤니티 구성원들이 지지" +"하는 것이므로 기능 요청과는 다릅니다." #: ../../source/fed/0001-20220311-flower-enhancement-doc.md:67 msgid "" "An Enhancement is captured in a Markdown file that follows a defined " -"template and a workflow to review and store enhancement docs for " -"reference — the Enhancement Doc." +"template and a workflow to review and store enhancement docs for reference " +"— the Enhancement Doc." msgstr "" "개선 사항은 정의된 템플릿과 참조용으로 Enhancement Doc.를 검토하고 저장하는 " "워크플로우를 따르는 Markdown 파일에 캡처됩니다." @@ -4002,11 +4052,11 @@ msgstr "Metadata" #: ../../source/fed/0001-20220311-flower-enhancement-doc.md:92 msgid "" -"**fed-number** (Required) The `fed-number` of the last Flower Enhancement" -" Doc + 1. With this number, it becomes easy to reference other proposals." +"**fed-number** (Required) The `fed-number` of the last Flower Enhancement " +"Doc + 1. With this number, it becomes easy to reference other proposals." msgstr "" -"**피드 번호** (필수) 마지막 Flower Enhancement 문서의 `피드 번호` + 1. 이 " -"번호를 사용하면 다른 제안을 쉽게 참조할 수 있습니다." +"**피드 번호** (필수) 마지막 Flower Enhancement 문서의 `피드 번호` + 1. 이 번" +"호를 사용하면 다른 제안을 쉽게 참조할 수 있습니다." #: ../../source/fed/0001-20220311-flower-enhancement-doc.md:94 msgid "**title** (Required) The title of the proposal in plain language." @@ -4014,33 +4064,35 @@ msgstr "**제목** (필수) 제안서의 제목을 평이한 언어로 입력합 #: ../../source/fed/0001-20220311-flower-enhancement-doc.md:96 msgid "" -"**status** (Required) The current status of the proposal. See " -"[workflow](#workflow) for the possible states." -msgstr "**상태** (필수) 제안의 현재 상태입니다. 가능한 상태는 [워크플로](#워크플로)" +"**status** (Required) The current status of the proposal. See [workflow]" +"(#workflow) for the possible states." +msgstr "" +"**상태** (필수) 제안의 현재 상태입니다. 가능한 상태는 [워크플로](#워크플로)" "를 참조하세요." #: ../../source/fed/0001-20220311-flower-enhancement-doc.md:98 msgid "" -"**authors** (Required) A list of authors of the proposal. This is simply " -"the GitHub ID." +"**authors** (Required) A list of authors of the proposal. This is simply the " +"GitHub ID." msgstr "**저자** (필수) 제안서의 작성자 목록입니다. 간단히 GitHub ID입니다." #: ../../source/fed/0001-20220311-flower-enhancement-doc.md:100 msgid "" -"**creation-date** (Required) The date that the proposal was first " -"submitted in a PR." +"**creation-date** (Required) The date that the proposal was first submitted " +"in a PR." msgstr "**생성 날짜** (필수) PR에서 제안서를 처음 제출한 날짜입니다." #: ../../source/fed/0001-20220311-flower-enhancement-doc.md:102 msgid "" "**last-updated** (Optional) The date that the proposal was last changed " "significantly." -msgstr "**마지막 업데이트** (선택 사항) 제안서가 마지막으로 크게 변경된 날짜입니다." +msgstr "" +"**마지막 업데이트** (선택 사항) 제안서가 마지막으로 크게 변경된 날짜입니다." #: ../../source/fed/0001-20220311-flower-enhancement-doc.md:104 msgid "" -"**see-also** (Optional) A list of other proposals that are relevant to " -"this one." +"**see-also** (Optional) A list of other proposals that are relevant to this " +"one." msgstr "**함께 보기** (선택 사항) 이 제안과 관련된 다른 제안 목록입니다." #: ../../source/fed/0001-20220311-flower-enhancement-doc.md:106 @@ -4048,7 +4100,8 @@ msgid "**replaces** (Optional) A list of proposals that this one replaces." msgstr "**대체** (선택 사항) 이 제안이 대체하는 제안 목록입니다." #: ../../source/fed/0001-20220311-flower-enhancement-doc.md:108 -msgid "**superseded-by** (Optional) A list of proposals that this one supersedes." +msgid "" +"**superseded-by** (Optional) A list of proposals that this one supersedes." msgstr "**대체됨** (선택 사항) 이 제안이 대체하는 제안의 목록입니다." #: ../../source/fed/0001-20220311-flower-enhancement-doc.md:111 @@ -4058,54 +4111,55 @@ msgstr "워크플로우" #: ../../source/fed/0001-20220311-flower-enhancement-doc.md:113 msgid "" "The idea forming the enhancement should already have been discussed or " -"pitched in the community. As such, it needs a champion, usually the " -"author, who shepherds the enhancement. This person also has to find " -"committers to Flower willing to review the proposal." +"pitched in the community. As such, it needs a champion, usually the author, " +"who shepherds the enhancement. This person also has to find committers to " +"Flower willing to review the proposal." msgstr "" -"개선 사항을 구성하는 아이디어는 이미 커뮤니티에서 논의되었거나 제안된 적이 " -"있어야 합니다. 따라서 개선 사항을 주도하는 사(보통 작성자)이 필요합니다. 이 " -"사람은 또한 제안을 검토할 의향이 있는 Flower 커미터를 찾아야 합니다." +"개선 사항을 구성하는 아이디어는 이미 커뮤니티에서 논의되었거나 제안된 적이 있" +"어야 합니다. 따라서 개선 사항을 주도하는 사(보통 작성자)이 필요합니다. 이 사" +"람은 또한 제안을 검토할 의향이 있는 Flower 커미터를 찾아야 합니다." #: ../../source/fed/0001-20220311-flower-enhancement-doc.md:115 msgid "" "New enhancements are checked in with a file name in the form of `NNNN-" -"YYYYMMDD-enhancement-title.md`, with `NNNN` being the Flower Enhancement " -"Doc number, to `enhancements`. All enhancements start in `provisional` " -"state as part of a pull request. Discussions are done as part of the pull" -" request review." +"YYYYMMDD-enhancement-title.md`, with `NNNN` being the Flower Enhancement Doc " +"number, to `enhancements`. All enhancements start in `provisional` state as " +"part of a pull request. Discussions are done as part of the pull request " +"review." msgstr "" -"새 개선 사항은 `NNNN-YYYYMMDD-enhancement-title.md` 형식의 파일 이름으로 " -"체크인되며, `NNNN`은 Flower 개선 문서 번호이고 `enhancements`에 해당합니다. " -"모든 개선 사항은 pull request의 일부로 `잠정` 상태에서 시작됩니다. 토론은 " -"pull request 검토의 일부로 이루어집니다." +"새 개선 사항은 `NNNN-YYYYMMDD-enhancement-title.md` 형식의 파일 이름으로 체크" +"인되며, `NNNN`은 Flower 개선 문서 번호이고 `enhancements`에 해당합니다. 모든 " +"개선 사항은 pull request의 일부로 `잠정` 상태에서 시작됩니다. 토론은 pull " +"request 검토의 일부로 이루어집니다." #: ../../source/fed/0001-20220311-flower-enhancement-doc.md:117 msgid "" -"Once an enhancement has been reviewed and approved, its status is changed" -" to `implementable`. The actual implementation is then done in separate " -"pull requests. These pull requests should mention the respective " -"enhancement as part of their description. After the implementation is " -"done, the proposal status is changed to `implemented`." +"Once an enhancement has been reviewed and approved, its status is changed to " +"`implementable`. The actual implementation is then done in separate pull " +"requests. These pull requests should mention the respective enhancement as " +"part of their description. After the implementation is done, the proposal " +"status is changed to `implemented`." msgstr "" -"개선 사항이 검토 및 승인되면 상태가 '구현 가능'으로 변경됩니다. 그런 다음 " -"실제 구현은 별도의 pull requests를 통해 이루어집니다. 이러한 pull requests는 " -"설명의 일부로 해당 개선 사항을 언급해야 합니다. 구현이 완료되면 제안 상태는 " -"'구현됨'으로 변경됩니다." +"개선 사항이 검토 및 승인되면 상태가 '구현 가능'으로 변경됩니다. 그런 다음 실" +"제 구현은 별도의 pull requests를 통해 이루어집니다. 이러한 pull requests는 설" +"명의 일부로 해당 개선 사항을 언급해야 합니다. 구현이 완료되면 제안 상태는 '구" +"현됨'으로 변경됩니다." #: ../../source/fed/0001-20220311-flower-enhancement-doc.md:119 msgid "" -"Under certain conditions, other states are possible. An Enhancement has " -"the following states:" -msgstr "특정 조건에서는 다른 상태도 가능합니다. 개선에는 다음과 같은 상태가 있습니다:" +"Under certain conditions, other states are possible. An Enhancement has the " +"following states:" +msgstr "" +"특정 조건에서는 다른 상태도 가능합니다. 개선에는 다음과 같은 상태가 있습니다:" #: ../../source/fed/0001-20220311-flower-enhancement-doc.md:121 msgid "" "`provisional`: The enhancement has been proposed and is actively being " -"defined. This is the starting state while the proposal is being fleshed " -"out and actively defined and discussed." +"defined. This is the starting state while the proposal is being fleshed out " +"and actively defined and discussed." msgstr "" -"'잠정적': 개선 사항이 제안되어 활발히 정의되고 있습니다. 제안이 구체화되고 " -"활발하게 정의 및 논의되는 동안의 시작 단계입니다." +"'잠정적': 개선 사항이 제안되어 활발히 정의되고 있습니다. 제안이 구체화되고 활" +"발하게 정의 및 논의되는 동안의 시작 단계입니다." #: ../../source/fed/0001-20220311-flower-enhancement-doc.md:122 msgid "`implementable`: The enhancement has been reviewed and approved." @@ -4118,15 +4172,17 @@ msgid "" msgstr "`구현됨`: 개선 사항이 구현되었으며 더 이상 활발히 변경되지 않습니다." #: ../../source/fed/0001-20220311-flower-enhancement-doc.md:124 -msgid "`deferred`: The enhancement is proposed but not actively being worked on." +msgid "" +"`deferred`: The enhancement is proposed but not actively being worked on." msgstr "'지연됨': 개선 사항이 제안되었지만 아직 활발히 작업 중이 아닙니다." #: ../../source/fed/0001-20220311-flower-enhancement-doc.md:125 msgid "" -"`rejected`: The authors and reviewers have decided that this enhancement " -"is not moving forward." -msgstr "`거부됨`: 작성자와 검토자는 이 개선 사항을 더 이상 진행하지 않기로 " -"결정했습니다." +"`rejected`: The authors and reviewers have decided that this enhancement is " +"not moving forward." +msgstr "" +"`거부됨`: 작성자와 검토자는 이 개선 사항을 더 이상 진행하지 않기로 결정했습니" +"다." #: ../../source/fed/0001-20220311-flower-enhancement-doc.md:126 msgid "`withdrawn`: The authors have withdrawn the enhancement." @@ -4138,21 +4194,21 @@ msgstr "'대체됨': 개선 사항이 새로운 개선 사항으로 대체되었 #: ../../source/fed/0001-20220311-flower-enhancement-doc.md:131 msgid "" -"Adding an additional process to the ones already provided by GitHub " -"(Issues and Pull Requests) adds more complexity and can be a barrier for " -"potential first-time contributors." +"Adding an additional process to the ones already provided by GitHub (Issues " +"and Pull Requests) adds more complexity and can be a barrier for potential " +"first-time contributors." msgstr "" -"GitHub에서 이미 제공하는 프로세스(이슈 및 Pull Requests)에 추가 프로세스를 " -"추가하면 더 복잡해지고 잠재적인 처음인 기여자에게는 장벽이 될 수 있습니다." +"GitHub에서 이미 제공하는 프로세스(이슈 및 Pull Requests)에 추가 프로세스를 추" +"가하면 더 복잡해지고 잠재적인 처음인 기여자에게는 장벽이 될 수 있습니다." #: ../../source/fed/0001-20220311-flower-enhancement-doc.md:133 msgid "" "Expanding the proposal template beyond the single-sentence description " -"currently required in the features issue template may be a heavy burden " -"for non-native English speakers." +"currently required in the features issue template may be a heavy burden for " +"non-native English speakers." msgstr "" -"현재 기능 이슈 템플릿에서 요구되는 한 문장 설명 이상으로 제안서 템플릿을 " -"확장하는 것은 영어가 모국어가 아닌 사용자에게는 큰 부담이 될 수 있습니다." +"현재 기능 이슈 템플릿에서 요구되는 한 문장 설명 이상으로 제안서 템플릿을 확장" +"하는 것은 영어가 모국어가 아닌 사용자에게는 큰 부담이 될 수 있습니다." #: ../../source/fed/0001-20220311-flower-enhancement-doc.md:137 msgid "GitHub Issues" @@ -4161,19 +4217,19 @@ msgstr "GitHub 이슈" #: ../../source/fed/0001-20220311-flower-enhancement-doc.md:139 msgid "" "Using GitHub Issues for these kinds of enhancements is doable. One could " -"use, for example, tags, to differentiate and filter them from other " -"issues. The main issue is in discussing and reviewing an enhancement: " -"GitHub issues only have a single thread for comments. Enhancements " -"usually have multiple threads of discussion at the same time for various " -"parts of the doc. Managing these multiple discussions can be confusing " -"when using GitHub Issues." -msgstr "" -"이러한 종류의 개선을 위해 GitHub 이슈를 사용하면 가능합니다. 예를 들어 " -"태그를 사용하여 다른 이슈와 구별하고 필터링할 수 있습니다. 주요 이슈는 개선 " -"사항에 대해 토론하고 검토하는 것입니다: GitHub 이슈에는 댓글 스레드가 하나만 " -"있습니다. 개선 사항에는 일반적으로 문서의 여러 부분에 대해 동시에 여러 개의 " -"토론 스레드가 있습니다. GitHub 이슈를 사용할 때 이러한 여러 토론을 관리하면 " -"혼란스러울 수 있습니다." +"use, for example, tags, to differentiate and filter them from other issues. " +"The main issue is in discussing and reviewing an enhancement: GitHub issues " +"only have a single thread for comments. Enhancements usually have multiple " +"threads of discussion at the same time for various parts of the doc. " +"Managing these multiple discussions can be confusing when using GitHub " +"Issues." +msgstr "" +"이러한 종류의 개선을 위해 GitHub 이슈를 사용하면 가능합니다. 예를 들어 태그" +"를 사용하여 다른 이슈와 구별하고 필터링할 수 있습니다. 주요 이슈는 개선 사항" +"에 대해 토론하고 검토하는 것입니다: GitHub 이슈에는 댓글 스레드가 하나만 있습" +"니다. 개선 사항에는 일반적으로 문서의 여러 부분에 대해 동시에 여러 개의 토론 " +"스레드가 있습니다. GitHub 이슈를 사용할 때 이러한 여러 토론을 관리하면 혼란스" +"러울 수 있습니다." #: ../../source/fed/0001-20220311-flower-enhancement-doc.md:141 msgid "Google Docs" @@ -4181,17 +4237,16 @@ msgstr "Google 문서 도구" #: ../../source/fed/0001-20220311-flower-enhancement-doc.md:143 msgid "" -"Google Docs allow for multiple threads of discussions. But as Google Docs" -" are hosted outside the project, their discoverability by the community " -"needs to be taken care of. A list of links to all proposals has to be " -"managed and made available for the community. Compared to shipping " -"proposals as part of Flower's repository, the potential for missing links" -" is much higher." +"Google Docs allow for multiple threads of discussions. But as Google Docs " +"are hosted outside the project, their discoverability by the community needs " +"to be taken care of. A list of links to all proposals has to be managed and " +"made available for the community. Compared to shipping proposals as part of " +"Flower's repository, the potential for missing links is much higher." msgstr "" "Google 문서는 여러 스레드의 토론을 허용합니다. 하지만 Google 문서는 프로젝트 " -"외부에서 호스팅되므로 커뮤니티에서 검색할 수 있도록 관리해야 합니다. 모든 " -"제안에 대한 링크 목록을 관리하고 커뮤니티에 제공해야 합니다. Flower 저장소의 " -"일부로 제안서를 보낼 때와 비교하면 링크가 누락될 가능성이 훨씬 더 높습니다." +"외부에서 호스팅되므로 커뮤니티에서 검색할 수 있도록 관리해야 합니다. 모든 제" +"안에 대한 링크 목록을 관리하고 커뮤니티에 제공해야 합니다. Flower 저장소의 일" +"부로 제안서를 보낼 때와 비교하면 링크가 누락될 가능성이 훨씬 더 높습니다." #: ../../source/fed/index.md:1 msgid "FED - Flower Enhancement Doc" @@ -4203,9 +4258,10 @@ msgstr "종합 평가 결과" #: ../../source/how-to-aggregate-evaluation-results.rst:4 msgid "" -"The Flower server does not prescribe a way to aggregate evaluation " -"results, but it enables the user to fully customize result aggregation." -msgstr "Flower 서버는 평가 결과를 집계하는 방법을 규정하고 있지 않지만 사용자가 결과 " +"The Flower server does not prescribe a way to aggregate evaluation results, " +"but it enables the user to fully customize result aggregation." +msgstr "" +"Flower 서버는 평가 결과를 집계하는 방법을 규정하고 있지 않지만 사용자가 결과 " "집계를 완전히 사용자 지정할 수 있습니다." #: ../../source/how-to-aggregate-evaluation-results.rst:8 @@ -4214,20 +4270,21 @@ msgstr "사용자 지정 평가 결과 집계" #: ../../source/how-to-aggregate-evaluation-results.rst:10 msgid "" -"The same :code:`Strategy`-customization approach can be used to aggregate" -" custom evaluation results coming from individual clients. Clients can " -"return custom metrics to the server by returning a dictionary:" +"The same :code:`Strategy`-customization approach can be used to aggregate " +"custom evaluation results coming from individual clients. Clients can return " +"custom metrics to the server by returning a dictionary:" msgstr "" -"동일한 :code:`Strategy`-사용자 지정 방식을 사용하여 개별 클라이언트로부터 " -"오는 사용자 지정 평가 결과를 집계할 수 있습니다. 클라이언트는 dictionary를 " -"반환하여 사용자 지정 지표를 서버에 반환할 수 있습니다:" +"동일한 :code:`Strategy`-사용자 지정 방식을 사용하여 개별 클라이언트로부터 오" +"는 사용자 지정 평가 결과를 집계할 수 있습니다. 클라이언트는 dictionary를 반환" +"하여 사용자 지정 지표를 서버에 반환할 수 있습니다:" #: ../../source/how-to-aggregate-evaluation-results.rst:36 msgid "" "The server can then use a customized strategy to aggregate the metrics " "provided in these dictionaries:" -msgstr "그런 다음 서버는 사용자 지정 전략을 사용하여 이러한 dictionaries에서 " -"제공하는 메트릭을 집계할 수 있습니다:" +msgstr "" +"그런 다음 서버는 사용자 지정 전략을 사용하여 이러한 dictionaries에서 제공하" +"는 메트릭을 집계할 수 있습니다:" #: ../../source/how-to-authenticate-supernodes.rst:2 msgid "Authenticate SuperNodes" @@ -4235,13 +4292,12 @@ msgstr "SuperNodes 인증하기" #: ../../source/how-to-authenticate-supernodes.rst:4 msgid "" -"Flower has built-in support for authenticated SuperNodes that you can use" -" to verify the identities of each SuperNode connecting to a SuperLink. " -"Flower node authentication works similar to how GitHub SSH authentication" -" works:" +"Flower has built-in support for authenticated SuperNodes that you can use to " +"verify the identities of each SuperNode connecting to a SuperLink. Flower " +"node authentication works similar to how GitHub SSH authentication works:" msgstr "" -"Flower는 SuperLink에 연결하는 각 SuperNodes의 신원을 확인하는 데 사용할 수 " -"있는 인증된 SuperNodes에 대한 기본 지원을 제공합니다. Flower 노드 인증은 " +"Flower는 SuperLink에 연결하는 각 SuperNodes의 신원을 확인하는 데 사용할 수 있" +"는 인증된 SuperNodes에 대한 기본 지원을 제공합니다. Flower 노드 인증은 " "GitHub SSH 인증 방식과 유사하게 작동합니다:" #: ../../source/how-to-authenticate-supernodes.rst:7 @@ -4250,16 +4306,17 @@ msgstr "SuperLink(서버)는 알려진 (클라이언트) 노드 공개키 목록 #: ../../source/how-to-authenticate-supernodes.rst:8 msgid "" -"Using ECDH, both SuperNode and SuperLink independently derive a shared " -"secret" -msgstr "SuperNode와 SuperLink는 ECDH를 사용하여 독립적으로 공유된 비밀을 도출합니다" +"Using ECDH, both SuperNode and SuperLink independently derive a shared secret" +msgstr "" +"SuperNode와 SuperLink는 ECDH를 사용하여 독립적으로 공유된 비밀을 도출합니다" #: ../../source/how-to-authenticate-supernodes.rst:9 msgid "" "Shared secret is used to compute the HMAC value of the message sent from " "SuperNode to SuperLink as a token" -msgstr "비밀 공유는 SuperNode에서 SuperLink로 토큰으로 전송된 메시지의 HMAC 값을 " -"계산하는 데 사용됩니다" +msgstr "" +"비밀 공유는 SuperNode에서 SuperLink로 토큰으로 전송된 메시지의 HMAC 값을 계산" +"하는 데 사용됩니다" #: ../../source/how-to-authenticate-supernodes.rst:10 msgid "SuperLink verifies the token" @@ -4267,27 +4324,28 @@ msgstr "SuperLink가 토큰을 확인합니다" #: ../../source/how-to-authenticate-supernodes.rst:12 msgid "" -"We recommend you to check out the complete `code example " -"`_ demonstrating federated learning with Flower in an " -"authenticated setting." +"We recommend you to check out the complete `code example `_ demonstrating " +"federated learning with Flower in an authenticated setting." msgstr "" -"인증된 환경에서 Flower로 federated 학습을 시연하는 전체 '코드 예제 " -"`" -"_를 확인하는 것이 좋습니다." +"인증된 환경에서 Flower로 연합 학습을 시연하는 전체 '코드 예제 `_를 확인하는 것이 " +"좋습니다." #: ../../source/how-to-authenticate-supernodes.rst:15 msgid "" -"This guide covers a preview feature that might change in future versions " -"of Flower." -msgstr "이 가이드에서는 향후 버전의 Flower에서 변경될 수 있는 미리보기 기능에 대해 " -"설명합니다." +"This guide covers a preview feature that might change in future versions of " +"Flower." +msgstr "" +"이 가이드에서는 향후 버전의 Flower에서 변경될 수 있는 미리보기 기능에 대해 설" +"명합니다." #: ../../source/how-to-authenticate-supernodes.rst:18 msgid "" -"For increased security, node authentication can only be used when " -"encrypted connections (SSL/TLS) are enabled." -msgstr "보안을 강화하기 위해 노드 인증은 암호화된 연결(SSL/TLS)을 사용하도록 설정한 " +"For increased security, node authentication can only be used when encrypted " +"connections (SSL/TLS) are enabled." +msgstr "" +"보안을 강화하기 위해 노드 인증은 암호화된 연결(SSL/TLS)을 사용하도록 설정한 " "경우에만 사용할 수 있습니다." #: ../../source/how-to-authenticate-supernodes.rst:21 @@ -4297,20 +4355,19 @@ msgstr ":code:`SuperLink`에서 노드 인증 활성화" #: ../../source/how-to-authenticate-supernodes.rst:23 msgid "" "To enable node authentication, first you need to configure SSL/TLS " -"connections to secure the SuperLink<>SuperNode communication. You can " -"find the complete guide `here `_. After configuring secure connections, you" -" can enable client authentication in a long-running Flower " -":code:`SuperLink`. Use the following terminal command to start a Flower " -":code:`SuperNode` that has both secure connections and node " -"authentication enabled:" +"connections to secure the SuperLink<>SuperNode communication. You can find " +"the complete guide `here `_. After configuring secure connections, you can enable " +"client authentication in a long-running Flower :code:`SuperLink`. Use the " +"following terminal command to start a Flower :code:`SuperNode` that has both " +"secure connections and node authentication enabled:" msgstr "" "노드 인증을 활성화하려면 먼저 SuperLink<>SuperNode 통신을 보호하기 위해 SSL/" "TLS 연결을 구성해야 합니다. 전체 가이드는 `여기 `_에서 확인할 수 있습니다. 보안 " -"연결을 구성한 후, 장기 실행하는 Flower :code:`SuperLink`에서 클라이언트 " -"인증을 활성화할 수 있습니다. 다음 터미널 명령을 사용하여 보안 연결과 노드 " -"인증이 모두 활성화된 Flower :code:`SuperNode`를 시작하세요:" +"연결을 구성한 후, 장기 실행하는 Flower :code:`SuperLink`에서 클라이언트 인증" +"을 활성화할 수 있습니다. 다음 터미널 명령을 사용하여 보안 연결과 노드 인증이 " +"모두 활성화된 Flower :code:`SuperNode`를 시작하세요:" #: ../../source/how-to-authenticate-supernodes.rst:38 msgid "Let's break down the authentication flags:" @@ -4318,51 +4375,51 @@ msgstr "인증 플래그를 세분화해 보겠습니다:" #: ../../source/how-to-authenticate-supernodes.rst:40 msgid "" -"The first flag :code:`--auth-list-public-keys` expects a path to a CSV " -"file storing all known node public keys. You need to store all known node" -" public keys that are allowed to participate in a federation in one CSV " -"file (:code:`.csv`)." +"The first flag :code:`--auth-list-public-keys` expects a path to a CSV file " +"storing all known node public keys. You need to store all known node public " +"keys that are allowed to participate in a federation in one CSV file (:code:" +"`.csv`)." msgstr "" -"첫 번째 플래그 :code:`--auth-list-public-keys`는 알려진 모든 노드 공개키를 " -"저장하는 CSV 파일의 경로를 기대합니다. federation에 참여하도록 허용된 모든 " -"알려진 노드 공개 키를 하나의 CSV 파일(:code:`.csv`)에 저장해야 합니다." +"첫 번째 플래그 :code:`--auth-list-public-keys`는 알려진 모든 노드 공개키를 저" +"장하는 CSV 파일의 경로를 기대합니다. federation에 참여하도록 허용된 모든 알려" +"진 노드 공개 키를 하나의 CSV 파일(:code:`.csv`)에 저장해야 합니다." #: ../../source/how-to-authenticate-supernodes.rst:42 msgid "" "A valid CSV file storing known node public keys should list the keys in " "OpenSSH format, separated by commas and without any comments. For an " -"example, refer to our code sample, which contains a CSV file with two " -"known node public keys." +"example, refer to our code sample, which contains a CSV file with two known " +"node public keys." msgstr "" "알려진 노드 공개키를 저장하는 유효한 CSV 파일은 쉼표로 구분하고 주석 없이 " -"OpenSSH 형식으로 키를 나열해야 합니다. 예를 들어, 두 개의 알려진 노드 " -"공개키가 포함된 CSV 파일이 포함된 코드 샘플을 참조하세요." +"OpenSSH 형식으로 키를 나열해야 합니다. 예를 들어, 두 개의 알려진 노드 공개키" +"가 포함된 CSV 파일이 포함된 코드 샘플을 참조하세요." #: ../../source/how-to-authenticate-supernodes.rst:44 msgid "" -"The second and third flags :code:`--auth-superlink-private-key` and :code" -":`--auth-superlink-public-key` expect paths to the server's private and " -"public keys. For development purposes, you can generate a private and " -"public key pair using :code:`ssh-keygen -t ecdsa -b 384`." +"The second and third flags :code:`--auth-superlink-private-key` and :code:`--" +"auth-superlink-public-key` expect paths to the server's private and public " +"keys. For development purposes, you can generate a private and public key " +"pair using :code:`ssh-keygen -t ecdsa -b 384`." msgstr "" -"두 번째 및 세 번째 플래그 :code:`--auth-superlink-private-key` 및 :code" -":`--auth-superlink-public-key`는 서버의 개인 및 공개 키의 경로를 예상합니다. " -"개발 목적으로 :code:`ssh-keygen -t ecdsa -b 384`를 사용하여 개인 및 공개 키 " -"쌍을 생성할 수 있습니다." +"두 번째 및 세 번째 플래그 :code:`--auth-superlink-private-key` 및 :code:`--" +"auth-superlink-public-key`는 서버의 개인 및 공개 키의 경로를 예상합니다. 개" +"발 목적으로 :code:`ssh-keygen -t ecdsa -b 384`를 사용하여 개인 및 공개 키 쌍" +"을 생성할 수 있습니다." #: ../../source/how-to-authenticate-supernodes.rst:47 msgid "" "In Flower 1.9, there is no support for dynamically removing, editing, or " -"adding known node public keys to the SuperLink. To change the set of " -"known nodes, you need to shut the server down, edit the CSV file, and " -"start the server again. Support for dynamically changing the set of known" -" nodes is on the roadmap to be released in Flower 1.10 (ETA: June)." +"adding known node public keys to the SuperLink. To change the set of known " +"nodes, you need to shut the server down, edit the CSV file, and start the " +"server again. Support for dynamically changing the set of known nodes is on " +"the roadmap to be released in Flower 1.10 (ETA: June)." msgstr "" -"Flower 1.9에서는 알려진 노드 공개키를 SuperLink에 동적으로 제거, 편집 또는 " -"추가하는 기능이 지원되지 않습니다. 알려진 노드 집합을 변경하려면 서버를 " -"종료하고 CSV 파일을 편집한 다음 서버를 다시 시작해야 합니다. 알려진 노드 " -"집합을 동적으로 변경하는 기능은 Flower 1.10(출시 예정일: 6월)에서 로드맵에 " -"포함되어 있습니다." +"Flower 1.9에서는 알려진 노드 공개키를 SuperLink에 동적으로 제거, 편집 또는 추" +"가하는 기능이 지원되지 않습니다. 알려진 노드 집합을 변경하려면 서버를 종료하" +"고 CSV 파일을 편집한 다음 서버를 다시 시작해야 합니다. 알려진 노드 집합을 동" +"적으로 변경하는 기능은 Flower 1.10(출시 예정일: 6월)에서 로드맵에 포함되어 있" +"습니다." #: ../../source/how-to-authenticate-supernodes.rst:53 msgid "Enable node authentication in :code:`SuperNode`" @@ -4371,26 +4428,26 @@ msgstr ":code:`SuperNode`에서 노드 인증을 활성화합니다" #: ../../source/how-to-authenticate-supernodes.rst:55 msgid "" "Similar to the long-running Flower server (:code:`SuperLink`), you can " -"easily enable node authentication in the long-running Flower client " -"(:code:`SuperNode`). Use the following terminal command to start an " -"authenticated :code:`SuperNode`:" +"easily enable node authentication in the long-running Flower client (:code:" +"`SuperNode`). Use the following terminal command to start an authenticated :" +"code:`SuperNode`:" msgstr "" "장기 실행 중인 Flower 서버(:code:`SuperLink`)와 마찬가지로, 장기 실행 중인 " -"Flower 클라이언트(:code:`SuperNode`)에서도 노드 인증을 쉽게 활성화할 수 " -"있습니다. 다음 터미널 명령을 사용하여 인증된 :code:`SuperNode`를 시작하세요:" +"Flower 클라이언트(:code:`SuperNode`)에서도 노드 인증을 쉽게 활성화할 수 있습" +"니다. 다음 터미널 명령을 사용하여 인증된 :code:`SuperNode`를 시작하세요:" #: ../../source/how-to-authenticate-supernodes.rst:66 msgid "" -"The :code:`--auth-supernode-private-key` flag expects a path to the " -"node's private key file and the :code:`--auth-supernode-public-key` flag " -"expects a path to the node's public key file. For development purposes, " -"you can generate a private and public key pair using :code:`ssh-keygen -t" -" ecdsa -b 384`." +"The :code:`--auth-supernode-private-key` flag expects a path to the node's " +"private key file and the :code:`--auth-supernode-public-key` flag expects a " +"path to the node's public key file. For development purposes, you can " +"generate a private and public key pair using :code:`ssh-keygen -t ecdsa -b " +"384`." msgstr "" -":code:`--auth-supernode-private-key` 플래그는 노드의 개인 키 파일 경로를, " -":code:`--auth-supernode-public-key` 플래그는 노드의 공개 키 파일 경로를 " -"예상합니다. 개발 목적으로 :code:`ssh-keygen -t ecdsa -b 384`를 사용하여 개인 " -"및 공개 키 쌍을 생성할 수 있습니다." +":code:`--auth-supernode-private-key` 플래그는 노드의 개인 키 파일 경로를, :" +"code:`--auth-supernode-public-key` 플래그는 노드의 공개 키 파일 경로를 예상합" +"니다. 개발 목적으로 :code:`ssh-keygen -t ecdsa -b 384`를 사용하여 개인 및 공" +"개 키 쌍을 생성할 수 있습니다." #: ../../source/how-to-authenticate-supernodes.rst:70 msgid "Security notice" @@ -4398,19 +4455,18 @@ msgstr "보안 공지" #: ../../source/how-to-authenticate-supernodes.rst:72 msgid "" -"The system's security relies on the credentials of the SuperLink and each" -" SuperNode. Therefore, it is imperative to safeguard and safely store the" -" credentials to avoid security risks such as Public Key Infrastructure " -"(PKI) impersonation attacks. The node authentication mechanism also " -"involves human interaction, so please ensure that all of the " -"communication is done in a secure manner, using trusted communication " -"methods." +"The system's security relies on the credentials of the SuperLink and each " +"SuperNode. Therefore, it is imperative to safeguard and safely store the " +"credentials to avoid security risks such as Public Key Infrastructure (PKI) " +"impersonation attacks. The node authentication mechanism also involves human " +"interaction, so please ensure that all of the communication is done in a " +"secure manner, using trusted communication methods." msgstr "" -"시스템의 보안은 SuperLink와 각SuperNode의 자격 증명에 의존합니다. 따라서 " -"공개키 기반구조(PKI) 사칭 공격과 같은 보안 위험을 피하기 위해 자격 증명을 " -"보호하고 안전하게 보관하는 것이 필수적입니다. 노드 인증 메커니즘에는 사람의 " -"상호 작용도 포함되므로 모든 통신이 신뢰할 수 있는 통신 방법을 사용하여 " -"안전한 방식으로 이루어지도록 하세요." +"시스템의 보안은 SuperLink와 각SuperNode의 자격 증명에 의존합니다. 따라서 공개" +"키 기반구조(PKI) 사칭 공격과 같은 보안 위험을 피하기 위해 자격 증명을 보호하" +"고 안전하게 보관하는 것이 필수적입니다. 노드 인증 메커니즘에는 사람의 상호 작" +"용도 포함되므로 모든 통신이 신뢰할 수 있는 통신 방법을 사용하여 안전한 방식으" +"로 이루어지도록 하세요." #: ../../source/how-to-authenticate-supernodes.rst:77 #: ../../source/how-to-enable-ssl-connections.rst:68 @@ -4421,15 +4477,15 @@ msgstr "결론" #: ../../source/how-to-authenticate-supernodes.rst:79 msgid "" -"You should now have learned how to start a long-running Flower server " -"(:code:`SuperLink`) and client (:code:`SuperNode`) with node " -"authentication enabled. You should also know the significance of the " -"private key and store it safely to minimize security risks." +"You should now have learned how to start a long-running Flower server (:code:" +"`SuperLink`) and client (:code:`SuperNode`) with node authentication " +"enabled. You should also know the significance of the private key and store " +"it safely to minimize security risks." msgstr "" -"이제 노드 인증이 활성화된 상태에서 장기간 실행되는 Flower " -"서버(:code:`SuperLink`)와 클라이언트(:code:`SuperNode`)를 시작하는 방법을 " -"배웠을 것입니다. 또한 보안 위험을 최소화하기 위해 개인키의 중요성을 알고 " -"안전하게 보관해야 합니다." +"이제 노드 인증이 활성화된 상태에서 장기간 실행되는 Flower 서버(:code:" +"`SuperLink`)와 클라이언트(:code:`SuperNode`)를 시작하는 방법을 배웠을 것입니" +"다. 또한 보안 위험을 최소화하기 위해 개인키의 중요성을 알고 안전하게 보관해" +"야 합니다." #: ../../source/how-to-configure-clients.rst:2 msgid "Configure clients" @@ -4438,13 +4494,13 @@ msgstr "클라이언트 구성" #: ../../source/how-to-configure-clients.rst:4 msgid "" "Along with model parameters, Flower can send configuration values to " -"clients. Configuration values can be used for various purposes. They are," -" for example, a popular way to control client-side hyperparameters from " -"the server." +"clients. Configuration values can be used for various purposes. They are, " +"for example, a popular way to control client-side hyperparameters from the " +"server." msgstr "" -"모델 파라미터와 함께 Flower는 설정 값을 클라이언트에 전송할 수 있습니다. " -"구성 값은 다양한 용도로 사용할 수 있습니다. 예를 들어 서버에서 클라이언트 측 " -"하이퍼파라미터를 제어하는 데 널리 사용되는 방법입니다." +"모델 파라미터와 함께 Flower는 설정 값을 클라이언트에 전송할 수 있습니다. 구" +"성 값은 다양한 용도로 사용할 수 있습니다. 예를 들어 서버에서 클라이언트 측 하" +"이퍼파라미터를 제어하는 데 널리 사용되는 방법입니다." #: ../../source/how-to-configure-clients.rst:7 msgid "Configuration values" @@ -4452,48 +4508,48 @@ msgstr "구성 값" #: ../../source/how-to-configure-clients.rst:9 msgid "" -"Configuration values are represented as a dictionary with ``str`` keys " -"and values of type ``bool``, ``bytes``, ``double`` (64-bit precision " -"float), ``int``, or ``str`` (or equivalent types in different languages)." -" Here is an example of a configuration dictionary in Python:" +"Configuration values are represented as a dictionary with ``str`` keys and " +"values of type ``bool``, ``bytes``, ``double`` (64-bit precision float), " +"``int``, or ``str`` (or equivalent types in different languages). Here is an " +"example of a configuration dictionary in Python:" msgstr "" "구성 값은 ``str`` 키와 ``bool``, ``bytes``, ``double``(64비트 정밀도 정수), " -"``int`` 또는 ``str``(또는 다른 언어의 동등한 유형) 유형의 값으로 구성된 " -"사전으로 표현됩니다. 다음은 Python의 구성 사전 예제입니다:" +"``int`` 또는 ``str``(또는 다른 언어의 동등한 유형) 유형의 값으로 구성된 사전" +"으로 표현됩니다. 다음은 Python의 구성 사전 예제입니다:" #: ../../source/how-to-configure-clients.rst:20 msgid "" "Flower serializes these configuration dictionaries (or *config dict* for " -"short) to their ProtoBuf representation, transports them to the client " -"using gRPC, and then deserializes them back to Python dictionaries." +"short) to their ProtoBuf representation, transports them to the client using " +"gRPC, and then deserializes them back to Python dictionaries." msgstr "" -"Flower는 이러한 구성 dictionaries(또는 줄여서 *config dict*)를 ProtoBuf " -"표현으로 직렬화하고, gRPC를 사용하여 클라이언트로 전송한 다음 다시 Python " +"Flower는 이러한 구성 dictionaries(또는 줄여서 *config dict*)를 ProtoBuf 표현" +"으로 직렬화하고, gRPC를 사용하여 클라이언트로 전송한 다음 다시 Python " "dictionaries로 역직렬화합니다." #: ../../source/how-to-configure-clients.rst:24 msgid "" -"Currently, there is no support for directly sending collection types " -"(e.g., ``Set``, ``List``, ``Map``) as values in configuration " -"dictionaries. There are several workarounds to send collections as values" -" by converting them to one of the supported value types (and converting " -"them back on the client-side)." +"Currently, there is no support for directly sending collection types (e.g., " +"``Set``, ``List``, ``Map``) as values in configuration dictionaries. There " +"are several workarounds to send collections as values by converting them to " +"one of the supported value types (and converting them back on the client-" +"side)." msgstr "" "현재 구성 사전에서 컬렉션 유형(예: ``Set``, ``List``, ``Map``)을 값으로 직접 " -"전송하는 기능은 지원되지 않습니다. 컬렉션을 지원되는 값 유형 중 하나로 " -"변환한 다음 클라이언트 측에서 다시 변환하여 값으로 보내는 몇 가지 해결 " -"방법이 있습니다." +"전송하는 기능은 지원되지 않습니다. 컬렉션을 지원되는 값 유형 중 하나로 변환" +"한 다음 클라이언트 측에서 다시 변환하여 값으로 보내는 몇 가지 해결 방법이 있" +"습니다." #: ../../source/how-to-configure-clients.rst:26 msgid "" "One can, for example, convert a list of floating-point numbers to a JSON " -"string, then send the JSON string using the configuration dictionary, and" -" then convert the JSON string back to a list of floating-point numbers on" -" the client." +"string, then send the JSON string using the configuration dictionary, and " +"then convert the JSON string back to a list of floating-point numbers on the " +"client." msgstr "" -"예를 들어 부동 소수점 숫자 목록을 JSON 문자열로 변환한 다음 구성 " -"dictionary을 사용하여 JSON 문자열을 전송한 다음 클라이언트에서 다시 부동 " -"소수점 숫자 목록으로 변환할 수 있습니다." +"예를 들어 부동 소수점 숫자 목록을 JSON 문자열로 변환한 다음 구성 dictionary" +"을 사용하여 JSON 문자열을 전송한 다음 클라이언트에서 다시 부동 소수점 숫자 목" +"록으로 변환할 수 있습니다." #: ../../source/how-to-configure-clients.rst:30 msgid "Configuration through built-in strategies" @@ -4501,68 +4557,68 @@ msgstr "기본 제공 전략을 통한 구성" #: ../../source/how-to-configure-clients.rst:32 msgid "" -"The easiest way to send configuration values to clients is to use a " -"built-in strategy like :code:`FedAvg`. Built-in strategies support so-" -"called configuration functions. A configuration function is a function " -"that the built-in strategy calls to get the configuration dictionary for " -"the current round. It then forwards the configuration dictionary to all " -"the clients selected during that round." +"The easiest way to send configuration values to clients is to use a built-in " +"strategy like :code:`FedAvg`. Built-in strategies support so-called " +"configuration functions. A configuration function is a function that the " +"built-in strategy calls to get the configuration dictionary for the current " +"round. It then forwards the configuration dictionary to all the clients " +"selected during that round." msgstr "" -"클라이언트에 구성 값을 보내는 가장 쉬운 방법은 :code:`FedAvg`와 같은 기본 " -"제공 전략을 사용하는 것입니다. 기본 제공 전략은 소위 구성 함수를 지원합니다. " -"구성 함수는 내장 전략이 현재 단계의 구성 사전을 가져오기 위해 호출하는 " -"함수입니다. 그런 다음 해당 단계 동안 선택된 모든 클라이언트에 구성 사전을 " -"전달합니다." +"클라이언트에 구성 값을 보내는 가장 쉬운 방법은 :code:`FedAvg`와 같은 기본 제" +"공 전략을 사용하는 것입니다. 기본 제공 전략은 소위 구성 함수를 지원합니다. 구" +"성 함수는 내장 전략이 현재 단계의 구성 사전을 가져오기 위해 호출하는 함수입니" +"다. 그런 다음 해당 단계 동안 선택된 모든 클라이언트에 구성 사전을 전달합니다." #: ../../source/how-to-configure-clients.rst:34 msgid "" "Let's start with a simple example. Imagine we want to send (a) the batch " -"size that the client should use, (b) the current global round of " -"federated learning, and (c) the number of epochs to train on the client-" -"side. Our configuration function could look like this:" +"size that the client should use, (b) the current global round of federated " +"learning, and (c) the number of epochs to train on the client-side. Our " +"configuration function could look like this:" msgstr "" "간단한 예부터 시작하겠습니다. (a) 클라이언트가 사용해야 하는 배치 크기, (b) " -"현재 글로벌 연합 federated 라운드, (c) 클라이언트 측에서 학습할 에포크 수를 " -"전송하고 싶다고 가정해 보겠습니다. 구성 함수는 다음과 같습니다:" +"현재 글로벌 연합 라운드, (c) 클라이언트 측에서 학습할 에포크 수를 전송하고 " +"싶다고 가정해 보겠습니다. 구성 함수는 다음과 같습니다:" #: ../../source/how-to-configure-clients.rst:47 msgid "" "To make the built-in strategies use this function, we can pass it to " -"``FedAvg`` during initialization using the parameter " -":code:`on_fit_config_fn`:" +"``FedAvg`` during initialization using the parameter :code:" +"`on_fit_config_fn`:" msgstr "" -"기본 제공 전략이 이 함수를 사용하도록 하려면 초기화 중에 매개 변수 " -":code:`on_fit_config_fn`을 사용하여 ``FedAvg``에 이 함수를 전달하면 됩니다:" +"기본 제공 전략이 이 함수를 사용하도록 하려면 초기화 중에 매개 변수 :code:" +"`on_fit_config_fn`을 사용하여 ``FedAvg``에 이 함수를 전달하면 됩니다:" #: ../../source/how-to-configure-clients.rst:56 -msgid "One the client side, we receive the configuration dictionary in ``fit``:" +msgid "" +"One the client side, we receive the configuration dictionary in ``fit``:" msgstr "클라이언트 측에서는 ``fit``으로 구성 dictionary을 받습니다:" #: ../../source/how-to-configure-clients.rst:67 msgid "" "There is also an `on_evaluate_config_fn` to configure evaluation, which " -"works the same way. They are separate functions because one might want to" -" send different configuration values to `evaluate` (for example, to use a" -" different batch size)." +"works the same way. They are separate functions because one might want to " +"send different configuration values to `evaluate` (for example, to use a " +"different batch size)." msgstr "" "평가를 구성하는 `on_evaluate_config_fn`도 있으며, 같은 방식으로 작동합니다. " -"다른 배치 크기를 사용하기 위해 다른 구성 값을 `evaluate`로 보내려고 할 수 " -"있기 때문에 이 함수는 별도의 함수입니다." +"다른 배치 크기를 사용하기 위해 다른 구성 값을 `evaluate`로 보내려고 할 수 있" +"기 때문에 이 함수는 별도의 함수입니다." #: ../../source/how-to-configure-clients.rst:69 msgid "" -"The built-in strategies call this function every round (that is, every " -"time `Strategy.configure_fit` or `Strategy.configure_evaluate` runs). " -"Calling `on_evaluate_config_fn` every round allows us to vary/change the " -"config dict over consecutive rounds. If we wanted to implement a " -"hyperparameter schedule, for example, to increase the number of local " -"epochs during later rounds, we could do the following:" +"The built-in strategies call this function every round (that is, every time " +"`Strategy.configure_fit` or `Strategy.configure_evaluate` runs). Calling " +"`on_evaluate_config_fn` every round allows us to vary/change the config dict " +"over consecutive rounds. If we wanted to implement a hyperparameter " +"schedule, for example, to increase the number of local epochs during later " +"rounds, we could do the following:" msgstr "" "기본 제공 전략은 매 라운드마다 이 함수를 호출합니다(즉, `Strategy." -"configure_fit` 또는 `Strategy.configure_evaluate`가 실행될 때마다). 매 " -"라운드마다 `on_evaluate_config_fn`을 호출하면 연속된 라운드에서 config " -"dict를 변경/변경할 수 있습니다. 예를 들어 이후 라운드에서 로컬 에포크 수를 " -"늘리기 위해 하이퍼파라미터 일정을 구현하려면 다음과 같이 할 수 있습니다:" +"configure_fit` 또는 `Strategy.configure_evaluate`가 실행될 때마다). 매 라운드" +"마다 `on_evaluate_config_fn`을 호출하면 연속된 라운드에서 config dict를 변경/" +"변경할 수 있습니다. 예를 들어 이후 라운드에서 로컬 에포크 수를 늘리기 위해 하" +"이퍼파라미터 일정을 구현하려면 다음과 같이 할 수 있습니다:" #: ../../source/how-to-configure-clients.rst:82 msgid "The :code:`FedAvg` strategy will call this function *every round*." @@ -4576,24 +4632,24 @@ msgstr "개별 클라이언트 구성" msgid "" "In some cases, it is necessary to send different configuration values to " "different clients." -msgstr "경우에 따라 다른 구성 값을 다른 클라이언트에 보내야 하는 경우도 있습니다." +msgstr "" +"경우에 따라 다른 구성 값을 다른 클라이언트에 보내야 하는 경우도 있습니다." #: ../../source/how-to-configure-clients.rst:89 msgid "" -"This can be achieved by customizing an existing strategy or by " -":doc:`implementing a custom strategy from scratch `. Here's a nonsensical example that customizes :code:`FedAvg`" -" by adding a custom ``\"hello\": \"world\"`` configuration key/value pair" -" to the config dict of a *single client* (only the first client in the " -"list, the other clients in this round to not receive this \"special\" " -"config value):" +"This can be achieved by customizing an existing strategy or by :doc:" +"`implementing a custom strategy from scratch `. " +"Here's a nonsensical example that customizes :code:`FedAvg` by adding a " +"custom ``\"hello\": \"world\"`` configuration key/value pair to the config " +"dict of a *single client* (only the first client in the list, the other " +"clients in this round to not receive this \"special\" config value):" msgstr "" "이는 기존 전략을 사용자 지정하거나 :doc:`implementing a custom strategy from " -"scratch `를 통해 수행할 수 있습니다. 다음은 " -"사용자 지정 ``\"hello\"'를 추가하여 :code:`FedAvg`를 사용자 지정하는 " -"무의미한 예입니다: \"world\"`` 구성 키/값 쌍을 *단일 클라이언트*의 config " -"dict에 추가합니다(목록의 첫 번째 클라이언트만, 이 라운드의 다른 클라이언트는 " -"이 \"특별한\" 구성 값을 수신하지 않음):" +"scratch `를 통해 수행할 수 있습니다. 다음은 사용" +"자 지정 ``\"hello\"'를 추가하여 :code:`FedAvg`를 사용자 지정하는 무의미한 예" +"입니다: \"world\"`` 구성 키/값 쌍을 *단일 클라이언트*의 config dict에 추가합" +"니다(목록의 첫 번째 클라이언트만, 이 라운드의 다른 클라이언트는 이 \"특별한" +"\" 구성 값을 수신하지 않음):" #: ../../source/how-to-configure-logging.rst:2 msgid "Configure logging" @@ -4602,22 +4658,22 @@ msgstr "로깅 구성" #: ../../source/how-to-configure-logging.rst:4 msgid "" "The Flower logger keeps track of all core events that take place in " -"federated learning workloads. It presents information by default " -"following a standard message format:" +"federated learning workloads. It presents information by default following a " +"standard message format:" msgstr "" -"Flower 로거는 federated 학습 워크로드에서 발생하는 모든 핵심 이벤트를 " -"추적합니다. 기본적으로 표준 메시지 형식에 따라 정보를 표시합니다:" +"Flower 로거는 federated 학습 워크로드에서 발생하는 모든 핵심 이벤트를 추적합" +"니다. 기본적으로 표준 메시지 형식에 따라 정보를 표시합니다:" #: ../../source/how-to-configure-logging.rst:13 msgid "" -"containing relevant information including: log message level (e.g. " -":code:`INFO`, :code:`DEBUG`), a timestamp, the line where the logging " -"took place from, as well as the log message itself. In this way, the " -"logger would typically display information on your terminal as follows:" +"containing relevant information including: log message level (e.g. :code:" +"`INFO`, :code:`DEBUG`), a timestamp, the line where the logging took place " +"from, as well as the log message itself. In this way, the logger would " +"typically display information on your terminal as follows:" msgstr "" "로그 메시지 수준(예: :code:`INFO`, :code:`DEBUG`), 타임스탬프, 로깅이 발생한 " -"줄, 로그 메시지 자체 등 관련 정보를 포함합니다. 이러한 방식으로 로거는 " -"일반적으로 다음과 같은 정보를 터미널에 표시합니다:" +"줄, 로그 메시지 자체 등 관련 정보를 포함합니다. 이러한 방식으로 로거는 일반적" +"으로 다음과 같은 정보를 터미널에 표시합니다:" #: ../../source/how-to-configure-logging.rst:34 msgid "Saving log to file" @@ -4627,34 +4683,32 @@ msgstr "파일에 로그 저장" msgid "" "By default, the Flower log is outputted to the terminal where you launch " "your Federated Learning workload from. This applies for both gRPC-based " -"federation (i.e. when you do :code:`fl.server.start_server`) and when " -"using the :code:`VirtualClientEngine` (i.e. when you do " -":code:`fl.simulation.start_simulation`). In some situations you might " -"want to save this log to disk. You can do so by calling the " -"`fl.common.logger.configure() " -"`_" -" function. For example:" -msgstr "" -"기본적으로 Flower 로그는 Federated 학습 워크로드를 실행하는 터미널에 " -"출력됩니다. 이는 gRPC 기반 페더레이션(즉,:code:`fl.simulation." -"start_simulation`를 실행하는 경우)과 :code:`VirtualClientEngine`을 사용하는 " -"경우(즉, :코드:`fl.simulation.start_simulation`을 실행하는 경우) 모두에 " -"적용됩니다. 경우에 따라 이 로그를 디스크에 저장하고 싶을 수도 있습니다. 이 " -"경우 `fl.common.logger.configure() `_ 함수를 호출하여 저장할 수 있습니다. 예를 " -"들어:" +"federation (i.e. when you do :code:`fl.server.start_server`) and when using " +"the :code:`VirtualClientEngine` (i.e. when you do :code:`fl.simulation." +"start_simulation`). In some situations you might want to save this log to " +"disk. You can do so by calling the `fl.common.logger.configure() `_ function. " +"For example:" +msgstr "" +"기본적으로 Flower 로그는 Federated 학습 워크로드를 실행하는 터미널에 출력됩니" +"다. 이는 gRPC 기반 페더레이션(즉,:code:`fl.simulation.start_simulation`를 실" +"행하는 경우)과 :code:`VirtualClientEngine`을 사용하는 경우(즉, :코드:`fl." +"simulation.start_simulation`을 실행하는 경우) 모두에 적용됩니다. 경우에 따라 " +"이 로그를 디스크에 저장하고 싶을 수도 있습니다. 이 경우 `fl.common.logger." +"configure() `_ 함수를 호출하여 저장할 수 있습니다. 예를 들어:" #: ../../source/how-to-configure-logging.rst:53 msgid "" -"With the above, Flower will record the log you see on your terminal to " -":code:`log.txt`. This file will be created in the same directory as were " -"you are running the code from. If we inspect we see the log above is also" -" recorded but prefixing with :code:`identifier` each line:" +"With the above, Flower will record the log you see on your terminal to :code:" +"`log.txt`. This file will be created in the same directory as were you are " +"running the code from. If we inspect we see the log above is also recorded " +"but prefixing with :code:`identifier` each line:" msgstr "" -"위와 같이 하면 Flower는 터미널에 표시되는 로그를 :code:`log.txt`에 " -"기록합니다. 이 파일은 코드를 실행한 디렉터리와 동일한 디렉터리에 생성됩니다. " -"검사해보면 위의 로그도 기록되지만 각 줄 앞에 :code:`identifier` 접두사가 " -"붙는 것을 확인할 수 있습니다:" +"위와 같이 하면 Flower는 터미널에 표시되는 로그를 :code:`log.txt`에 기록합니" +"다. 이 파일은 코드를 실행한 디렉터리와 동일한 디렉터리에 생성됩니다. 검사해보" +"면 위의 로그도 기록되지만 각 줄 앞에 :code:`identifier` 접두사가 붙는 것을 확" +"인할 수 있습니다:" #: ../../source/how-to-configure-logging.rst:74 msgid "Log your own messages" @@ -4662,19 +4716,20 @@ msgstr "나만의 메시지 기록" #: ../../source/how-to-configure-logging.rst:76 msgid "" -"You might expand the information shown by default with the Flower logger " -"by adding more messages relevant to your application. You can achieve " -"this easily as follows." +"You might expand the information shown by default with the Flower logger by " +"adding more messages relevant to your application. You can achieve this " +"easily as follows." msgstr "" "애플리케이션과 관련된 메시지를 더 추가하여 Flower 로거에 기본적으로 표시되는 " "정보를 확장할 수 있습니다. 다음과 같이 쉽게 추가할 수 있습니다." #: ../../source/how-to-configure-logging.rst:102 msgid "" -"In this way your logger will show, in addition to the default messages, " -"the ones introduced by the clients as specified above." -msgstr "이렇게 하면 로거에 기본 메시지 외에 위에서 지정한 대로 클라이언트가 소개한 " -"메시지가 표시됩니다." +"In this way your logger will show, in addition to the default messages, the " +"ones introduced by the clients as specified above." +msgstr "" +"이렇게 하면 로거에 기본 메시지 외에 위에서 지정한 대로 클라이언트가 소개한 메" +"시지가 표시됩니다." #: ../../source/how-to-configure-logging.rst:128 msgid "Log to a remote service" @@ -4682,23 +4737,22 @@ msgstr "원격 서비스에 로그인" #: ../../source/how-to-configure-logging.rst:130 msgid "" -"The :code:`fl.common.logger.configure` function, also allows specifying a" -" host to which logs can be pushed (via :code:`POST`) through a native " -"Python :code:`logging.handler.HTTPHandler`. This is a particularly useful" -" feature in :code:`gRPC`-based Federated Learning workloads where " -"otherwise gathering logs from all entities (i.e. the server and the " -"clients) might be cumbersome. Note that in Flower simulation, the server " -"automatically displays all logs. You can still specify a " -":code:`HTTPHandler` should you wish to backup or analyze the logs " -"somewhere else." -msgstr "" -"또한 :code:`fl.common.logger.configure` 함수를 사용하면 네이티브 Python " -":code:`logging.handler.HTTPHandler`를 통해 로그를 푸시할 수 있는 호스트를 " -"지정할 수 있습니다(:code:`POST`를 통해). 이는 모든 엔티티(예: 서버 및 " -"클라이언트)에서 로그를 수집하는 것이 번거로울 수 있는 :code:`gRPC` 기반 " -"Federated 학습 워크로드에서 특히 유용한 기능입니다. Flower 시뮬레이션에서는 " -"서버가 모든 로그를 자동으로 표시합니다. 로그를 다른 곳에 백업하거나 " -"분석하려는 경우 :code:`HTTPHandler`를 지정할 수 있습니다." +"The :code:`fl.common.logger.configure` function, also allows specifying a " +"host to which logs can be pushed (via :code:`POST`) through a native Python :" +"code:`logging.handler.HTTPHandler`. This is a particularly useful feature " +"in :code:`gRPC`-based Federated Learning workloads where otherwise gathering " +"logs from all entities (i.e. the server and the clients) might be " +"cumbersome. Note that in Flower simulation, the server automatically " +"displays all logs. You can still specify a :code:`HTTPHandler` should you " +"wish to backup or analyze the logs somewhere else." +msgstr "" +"또한 :code:`fl.common.logger.configure` 함수를 사용하면 네이티브 Python :" +"code:`logging.handler.HTTPHandler`를 통해 로그를 푸시할 수 있는 호스트를 지정" +"할 수 있습니다(:code:`POST`를 통해). 이는 모든 엔티티(예: 서버 및 클라이언트)" +"에서 로그를 수집하는 것이 번거로울 수 있는 :code:`gRPC` 기반 Federated 학습 " +"워크로드에서 특히 유용한 기능입니다. Flower 시뮬레이션에서는 서버가 모든 로그" +"를 자동으로 표시합니다. 로그를 다른 곳에 백업하거나 분석하려는 경우 :code:" +"`HTTPHandler`를 지정할 수 있습니다." #: ../../source/how-to-enable-ssl-connections.rst:2 msgid "Enable SSL connections" @@ -4706,33 +4760,32 @@ msgstr "SSL 연결 사용" #: ../../source/how-to-enable-ssl-connections.rst:4 msgid "" -"This guide describes how to a SSL-enabled secure Flower server " -"(:code:`SuperLink`) can be started and how a Flower client " -"(:code:`SuperNode`) can establish a secure connections to it." +"This guide describes how to a SSL-enabled secure Flower server (:code:" +"`SuperLink`) can be started and how a Flower client (:code:`SuperNode`) can " +"establish a secure connections to it." msgstr "" -"이 가이드에서는 SSL을 지원하는 보안 Flower 서버(:코드:`SuperLink`)를 " -"시작하는 방법과 Flower 클라이언트(:코드:`SuperNode`)가 이 서버에 보안 연결을 " -"설정하는 방법을 설명합니다." +"이 가이드에서는 SSL을 지원하는 보안 Flower 서버(:코드:`SuperLink`)를 시작하" +"는 방법과 Flower 클라이언트(:코드:`SuperNode`)가 이 서버에 보안 연결을 설정하" +"는 방법을 설명합니다." #: ../../source/how-to-enable-ssl-connections.rst:7 msgid "" -"A complete code example demonstrating a secure connection can be found " -"`here `_." +"A complete code example demonstrating a secure connection can be found `here " +"`_." msgstr "" "보안 연결을 보여주는 전체 코드 예제는 '여기 `_'에서 확인할 수 있습니다." #: ../../source/how-to-enable-ssl-connections.rst:10 msgid "" -"The code example comes with a :code:`README.md` file which explains how " -"to start it. Although it is already SSL-enabled, it might be less " -"descriptive on how it does so. Stick to this guide for a deeper " -"introduction to the topic." +"The code example comes with a :code:`README.md` file which explains how to " +"start it. Although it is already SSL-enabled, it might be less descriptive " +"on how it does so. Stick to this guide for a deeper introduction to the " +"topic." msgstr "" "코드 예제에는 시작 방법을 설명하는 :code:`README.md` 파일이 함께 제공됩니다. " -"이미 SSL을 사용하도록 설정되어 있지만 그 방법에 대한 설명이 부족할 수 " -"있습니다. 이 가이드를 참고하여 이 주제에 대해 자세히 알아보세요." +"이미 SSL을 사용하도록 설정되어 있지만 그 방법에 대한 설명이 부족할 수 있습니" +"다. 이 가이드를 참고하여 이 주제에 대해 자세히 알아보세요." #: ../../source/how-to-enable-ssl-connections.rst:16 msgid "Certificates" @@ -4741,10 +4794,10 @@ msgstr "인증서" #: ../../source/how-to-enable-ssl-connections.rst:18 msgid "" "Using SSL-enabled connections requires certificates to be passed to the " -"server and client. For the purpose of this guide we are going to generate" -" self-signed certificates. As this can become quite complex we are going " -"to ask you to run the script in :code:`examples/advanced-" -"tensorflow/certificates/generate.sh` with the following command sequence:" +"server and client. For the purpose of this guide we are going to generate " +"self-signed certificates. As this can become quite complex we are going to " +"ask you to run the script in :code:`examples/advanced-tensorflow/" +"certificates/generate.sh` with the following command sequence:" msgstr "" "SSL 사용 연결을 사용하려면 서버와 클라이언트에 인증서를 전달해야 합니다. 이 " "가이드에서는 자체 서명된 인증서를 생성하겠습니다. 이 과정은 상당히 복잡할 수 " @@ -4753,27 +4806,27 @@ msgstr "" #: ../../source/how-to-enable-ssl-connections.rst:29 msgid "" -"This will generate the certificates in :code:`examples/advanced-" -"tensorflow/.cache/certificates`." +"This will generate the certificates in :code:`examples/advanced-tensorflow/." +"cache/certificates`." msgstr "" -"이렇게 하면 :code:`examples/advanced-tensorflow/.cache/certificates`에 " -"인증서가 생성됩니다." +"이렇게 하면 :code:`examples/advanced-tensorflow/.cache/certificates`에 인증서" +"가 생성됩니다." #: ../../source/how-to-enable-ssl-connections.rst:31 msgid "" -"The approach for generating SSL certificates in the context of this " -"example can serve as an inspiration and starting point, but it should not" -" be used as a reference for production environments. Please refer to " -"other sources regarding the issue of correctly generating certificates " -"for production environments. For non-critical prototyping or research " -"projects, it might be sufficient to use the self-signed certificates " -"generated using the scripts mentioned in this guide." +"The approach for generating SSL certificates in the context of this example " +"can serve as an inspiration and starting point, but it should not be used as " +"a reference for production environments. Please refer to other sources " +"regarding the issue of correctly generating certificates for production " +"environments. For non-critical prototyping or research projects, it might be " +"sufficient to use the self-signed certificates generated using the scripts " +"mentioned in this guide." msgstr "" -"이 예의 맥락에서 SSL 인증서를 생성하는 접근 방식은 영감과 출발점이 될 수 " -"있지만 프로덕션 환경에 대한 참조로 사용해서는 안 됩니다. 프로덕션 환경용 " -"인증서를 올바르게 생성하는 문제에 대해서는 다른 출처를 참조하세요. 중요하지 " -"않은 프로토타이핑 또는 연구 프로젝트의 경우, 이 가이드에 언급된 스크립트를 " -"사용하여 생성한 자체 서명 인증서를 사용하는 것으로 충분할 수 있습니다." +"이 예의 맥락에서 SSL 인증서를 생성하는 접근 방식은 영감과 출발점이 될 수 있지" +"만 프로덕션 환경에 대한 참조로 사용해서는 안 됩니다. 프로덕션 환경용 인증서" +"를 올바르게 생성하는 문제에 대해서는 다른 출처를 참조하세요. 중요하지 않은 프" +"로토타이핑 또는 연구 프로젝트의 경우, 이 가이드에 언급된 스크립트를 사용하여 " +"생성한 자체 서명 인증서를 사용하는 것으로 충분할 수 있습니다." #: ../../source/how-to-enable-ssl-connections.rst:39 msgid "Server (SuperLink)" @@ -4781,18 +4834,20 @@ msgstr "서버(SuperLink)" #: ../../source/how-to-enable-ssl-connections.rst:41 msgid "" -"Use the following terminal command to start a sever (SuperLink) that uses" -" the previously generated certificates:" -msgstr "다음 터미널 명령을 사용하여 이전에 생성한 인증서를 사용하는 서버(SuperLink)" +"Use the following terminal command to start a sever (SuperLink) that uses " +"the previously generated certificates:" +msgstr "" +"다음 터미널 명령을 사용하여 이전에 생성한 인증서를 사용하는 서버(SuperLink)" "를 시작합니다:" #: ../../source/how-to-enable-ssl-connections.rst:50 msgid "" "When providing certificates, the server expects a tuple of three " -"certificates paths: CA certificate, server certificate and server private" -" key." -msgstr "인증서를 제공할 때 서버는 세 가지 인증서 경로의 튜플을 기대합니다: CA " -"인증서, 서버 인증서 및 서버 개인 키입니다." +"certificates paths: CA certificate, server certificate and server private " +"key." +msgstr "" +"인증서를 제공할 때 서버는 세 가지 인증서 경로의 튜플을 기대합니다: CA 인증" +"서, 서버 인증서 및 서버 개인 키입니다." #: ../../source/how-to-enable-ssl-connections.rst:54 msgid "Client (SuperNode)" @@ -4800,23 +4855,25 @@ msgstr "클라이언트(SuperNode)" #: ../../source/how-to-enable-ssl-connections.rst:56 msgid "" -"Use the following terminal command to start a client (SuperNode) that " -"uses the previously generated certificates:" -msgstr "다음 터미널 명령을 사용하여 이전에 생성한 인증서를 사용하는 " -"클라이언트(SuperNode)를 시작합니다:" +"Use the following terminal command to start a client (SuperNode) that uses " +"the previously generated certificates:" +msgstr "" +"다음 터미널 명령을 사용하여 이전에 생성한 인증서를 사용하는 클라이언트" +"(SuperNode)를 시작합니다:" #: ../../source/how-to-enable-ssl-connections.rst:64 msgid "" -"When setting :code:`root_certificates`, the client expects a file path to" -" PEM-encoded root certificates." -msgstr "코드:`root_certificates`를 설정하면 클라이언트는 PEM 인코딩된 루트 인증서의 " +"When setting :code:`root_certificates`, the client expects a file path to " +"PEM-encoded root certificates." +msgstr "" +"코드:`root_certificates`를 설정하면 클라이언트는 PEM 인코딩된 루트 인증서의 " "파일 경로를 예상합니다." #: ../../source/how-to-enable-ssl-connections.rst:70 msgid "" -"You should now have learned how to generate self-signed certificates " -"using the given script, start an SSL-enabled server and have a client " -"establish a secure connection to it." +"You should now have learned how to generate self-signed certificates using " +"the given script, start an SSL-enabled server and have a client establish a " +"secure connection to it." msgstr "" "이제 주어진 스크립트를 사용하여 자체 서명 인증서를 생성하고, SSL 사용 서버를 " "시작하고, 클라이언트가 보안 연결을 설정하는 방법을 배웠을 것입니다." @@ -4827,8 +4884,8 @@ msgstr "추가 리소스" #: ../../source/how-to-enable-ssl-connections.rst:77 msgid "" -"These additional sources might be relevant if you would like to dive " -"deeper into the topic of certificates:" +"These additional sources might be relevant if you would like to dive deeper " +"into the topic of certificates:" msgstr "인증서에 대해 더 자세히 알아보고 싶다면 이러한 추가 자료를 참고하세요:" #: ../../source/how-to-enable-ssl-connections.rst:79 @@ -4837,7 +4894,7 @@ msgstr "'암호화하세요 `_'" #: ../../source/how-to-enable-ssl-connections.rst:80 msgid "`certbot `_" -msgstr "인증봇 `_" +msgstr "`인증봇 `_" #: ../../source/how-to-implement-strategies.rst:2 msgid "Implement strategies" @@ -4845,18 +4902,18 @@ msgstr "전략 구현" #: ../../source/how-to-implement-strategies.rst:4 msgid "" -"The strategy abstraction enables implementation of fully custom " -"strategies. A strategy is basically the federated learning algorithm that" -" runs on the server. Strategies decide how to sample clients, how to " -"configure clients for training, how to aggregate updates, and how to " -"evaluate models. Flower provides a few built-in strategies which are " -"based on the same API described below." +"The strategy abstraction enables implementation of fully custom strategies. " +"A strategy is basically the federated learning algorithm that runs on the " +"server. Strategies decide how to sample clients, how to configure clients " +"for training, how to aggregate updates, and how to evaluate models. Flower " +"provides a few built-in strategies which are based on the same API described " +"below." msgstr "" "전략 추상화를 통해 완전한 맞춤형 전략을 구현할 수 있습니다. 전략은 " -"기본적으로 서버에서 실행되는 federated 학습 알고리즘입니다. 전략은 " -"클라이언트를 샘플링하는 방법, 학습을 위해 클라이언트를 구성하는 방법, " -"업데이트를 집계하는 방법, 모델을 평가하는 방법을 결정합니다. Flower는 아래에 " -"설명된 것과 동일한 API를 기반으로 하는 몇 가지 기본 제공 전략을 제공합니다." +"기본적으로 서버에서 실행되는 연합 학습 알고리즘입니다. 전략은 클라이언트를 " +"샘플링하는 방법, 학습을 위해 클라이언트를 구성하는 방법, 업데이트를 집계하는 " +"방법, 모델을 평가하는 방법을 결정합니다. Flower는 아래에 설명된 것과 동일한 " +"API를 기반으로 하는 몇 가지 기본 제공 전략을 제공합니다." #: ../../source/how-to-implement-strategies.rst:11 msgid "The :code:`Strategy` abstraction" @@ -4864,15 +4921,14 @@ msgstr ":code:`Strategy` 추상화" #: ../../source/how-to-implement-strategies.rst:13 msgid "" -"All strategy implementation are derived from the abstract base class " -":code:`flwr.server.strategy.Strategy`, both built-in implementations and " -"third party implementations. This means that custom strategy " -"implementations have the exact same capabilities at their disposal as " -"built-in ones." +"All strategy implementation are derived from the abstract base class :code:" +"`flwr.server.strategy.Strategy`, both built-in implementations and third " +"party implementations. This means that custom strategy implementations have " +"the exact same capabilities at their disposal as built-in ones." msgstr "" -"모든 전략 구현은 기본 제공 구현과 타사 구현 모두 추상 기본 클래스인 " -":code:`flwr.server.strategy.Strategy`에서 파생됩니다. 즉, 사용자 정의 전략 " -"구현은 기본 제공 구현과 완전히 동일한 기능을 사용할 수 있습니다." +"모든 전략 구현은 기본 제공 구현과 타사 구현 모두 추상 기본 클래스인 :code:" +"`flwr.server.strategy.Strategy`에서 파생됩니다. 즉, 사용자 정의 전략 구현은 " +"기본 제공 구현과 완전히 동일한 기능을 사용할 수 있습니다." #: ../../source/how-to-implement-strategies.rst:18 msgid "" @@ -4882,13 +4938,13 @@ msgstr "전략 추상화에서는 구현해야 하는 몇 가지 추상적인 #: ../../source/how-to-implement-strategies.rst:75 msgid "" -"Creating a new strategy means implementing a new :code:`class` (derived " -"from the abstract base class :code:`Strategy`) that implements for the " -"previously shown abstract methods:" +"Creating a new strategy means implementing a new :code:`class` (derived from " +"the abstract base class :code:`Strategy`) that implements for the previously " +"shown abstract methods:" msgstr "" -"새 전략을 생성한다는 것은 이전에 표시된 추상 메서드에 대해 구현하는 새로운 " -":code:`class`(추상 기본 클래스 :code:`Strategy`에서 파생됨)를 구현하는 것을 " -"의미합니다:" +"새 전략을 생성한다는 것은 이전에 표시된 추상 메서드에 대해 구현하는 새로운 :" +"code:`class`(추상 기본 클래스 :code:`Strategy`에서 파생됨)를 구현하는 것을 의" +"미합니다:" #: ../../source/how-to-implement-strategies.rst:100 msgid "The Flower server calls these methods in the following order:" @@ -4904,19 +4960,18 @@ msgstr ":code:`initialize_parameters` 메서드" #: ../../source/how-to-implement-strategies.rst:182 msgid "" -":code:`initialize_parameters` is called only once, at the very beginning " -"of an execution. It is responsible for providing the initial global model" -" parameters in a serialized form (i.e., as a :code:`Parameters` object)." +":code:`initialize_parameters` is called only once, at the very beginning of " +"an execution. It is responsible for providing the initial global model " +"parameters in a serialized form (i.e., as a :code:`Parameters` object)." msgstr "" "code:`initialize_parameters`는 실행을 처음 시작할 때 한 번만 호출됩니다. 이 " -"함수는 초기 전역 모델 파라미터를 직렬화된 형식(즉, :code:`Parameters` 객체)" -"으로 제공하는 역할을 합니다." +"함수는 초기 전역 모델 파라미터를 직렬화된 형식(즉, :code:`Parameters` 객체)으" +"로 제공하는 역할을 합니다." #: ../../source/how-to-implement-strategies.rst:184 msgid "" -"Built-in strategies return user-provided initial parameters. The " -"following example shows how initial parameters can be passed to " -":code:`FedAvg`:" +"Built-in strategies return user-provided initial parameters. The following " +"example shows how initial parameters can be passed to :code:`FedAvg`:" msgstr "" "기본 제공 전략은 사용자가 제공한 초기 매개 변수를 반환합니다. 다음 예는 초기 " "매개 변수를 :code:`FedAvg`에 전달하는 방법을 보여줍니다:" @@ -4924,32 +4979,31 @@ msgstr "" #: ../../source/how-to-implement-strategies.rst:209 msgid "" "The Flower server will call :code:`initialize_parameters`, which either " -"returns the parameters that were passed to :code:`initial_parameters`, or" -" :code:`None`. If no parameters are returned from " -":code:`initialize_parameters` (i.e., :code:`None`), the server will " -"randomly select one client and ask it to provide its parameters. This is " -"a convenience feature and not recommended in practice, but it can be " -"useful for prototyping. In practice, it is recommended to always use " -"server-side parameter initialization." -msgstr "" -"Flower 서버는 :code:`initialize_parameters`를 호출하여 " -":code:`initial_parameters`에 전달된 파라미터를 반환하거나 :code:`None`을 " -"반환합니다. :code:`initial_parameters`에서 반환되는 매개변수가 없는 경우(즉, " -":code:`None`) 서버는 무작위로 클라이언트 하나를 선택하여 해당 클라이언트에 " -"매개변수를 제공하도록 요청합니다. 이는 편의 기능이며 실제로는 권장하지 " -"않지만 프로토타이핑에는 유용할 수 있습니다. 실제로는 항상 서버 측 매개변수 " -"초기화를 사용하는 것이 좋습니다." +"returns the parameters that were passed to :code:`initial_parameters`, or :" +"code:`None`. If no parameters are returned from :code:" +"`initialize_parameters` (i.e., :code:`None`), the server will randomly " +"select one client and ask it to provide its parameters. This is a " +"convenience feature and not recommended in practice, but it can be useful " +"for prototyping. In practice, it is recommended to always use server-side " +"parameter initialization." +msgstr "" +"Flower 서버는 :code:`initialize_parameters`를 호출하여 :code:" +"`initial_parameters`에 전달된 파라미터를 반환하거나 :code:`None`을 반환합니" +"다. :code:`initial_parameters`에서 반환되는 매개변수가 없는 경우(즉, :code:" +"`None`) 서버는 무작위로 클라이언트 하나를 선택하여 해당 클라이언트에 매개변수" +"를 제공하도록 요청합니다. 이는 편의 기능이며 실제로는 권장하지 않지만 프로토" +"타이핑에는 유용할 수 있습니다. 실제로는 항상 서버 측 매개변수 초기화를 사용하" +"는 것이 좋습니다." #: ../../source/how-to-implement-strategies.rst:213 msgid "" "Server-side parameter initialization is a powerful mechanism. It can be " -"used, for example, to resume training from a previously saved checkpoint." -" It is also the fundamental capability needed to implement hybrid " -"approaches, for example, to fine-tune a pre-trained model using federated" -" learning." +"used, for example, to resume training from a previously saved checkpoint. It " +"is also the fundamental capability needed to implement hybrid approaches, " +"for example, to fine-tune a pre-trained model using federated learning." msgstr "" "서버 측 파라미터 초기화는 강력한 메커니즘입니다. 예를 들어 이전에 저장한 " -"체크포인트에서 학습을 재개하는 데 사용할 수 있습니다. 또한 federated 학습을 " +"체크포인트에서 학습을 재개하는 데 사용할 수 있습니다. 또한 연합 학습을 " "사용하여 사전 학습된 모델을 미세 조정하는 등 하이브리드 접근 방식을 구현하는 " "데 필요한 기본 기능입니다." @@ -4959,23 +5013,23 @@ msgstr ":code:`configure_fit` 메서드" #: ../../source/how-to-implement-strategies.rst:218 msgid "" -":code:`configure_fit` is responsible for configuring the upcoming round " -"of training. What does *configure* mean in this context? Configuring a " -"round means selecting clients and deciding what instructions to send to " -"these clients. The signature of :code:`configure_fit` makes this clear:" +":code:`configure_fit` is responsible for configuring the upcoming round of " +"training. What does *configure* mean in this context? Configuring a round " +"means selecting clients and deciding what instructions to send to these " +"clients. The signature of :code:`configure_fit` makes this clear:" msgstr "" -":code:`configure_fit`은 다가오는 학 라운드를 구성하는 역할을 합니다. 이 " -"문맥에서 *구성*은 무엇을 의미하나요? 라운드를 구성한다는 것은 클라이언트를 " -"선택하고 이 클라이언트에게 어떤 지침을 보낼지 결정하는 것을 의미합니다. " -"code:`configure_fit`의 시그니처를 보면 이를 명확히 알 수 있습니다:" +":code:`configure_fit`은 다가오는 학 라운드를 구성하는 역할을 합니다. 이 문맥" +"에서 *구성*은 무엇을 의미하나요? 라운드를 구성한다는 것은 클라이언트를 선택하" +"고 이 클라이언트에게 어떤 지침을 보낼지 결정하는 것을 의미합니다. code:" +"`configure_fit`의 시그니처를 보면 이를 명확히 알 수 있습니다:" #: ../../source/how-to-implement-strategies.rst:231 msgid "" "The return value is a list of tuples, each representing the instructions " -"that will be sent to a particular client. Strategy implementations " -"usually perform the following steps in :code:`configure_fit`:" +"that will be sent to a particular client. Strategy implementations usually " +"perform the following steps in :code:`configure_fit`:" msgstr "" -"반환 값은 튜플 목록으로, 각 튜플은 특정 클라이언트로 전송될 instruction을 " +"반환 값은 튜플 목록으로, 각 튜플은 특정 클라이언트로 전송될 명령어를 " "나타냅니다. 전략 구현은 일반적으로 :code:`configure_fit`에서 다음 단계를 " "수행합니다:" @@ -4985,39 +5039,38 @@ msgid "" "Use the :code:`client_manager` to randomly sample all (or a subset of) " "available clients (each represented as a :code:`ClientProxy` object)" msgstr "" -":code:`client_manager`를 사용하여 사용 가능한 모든 클라이언트(또는 그 하위 " -"집합)를 무작위로 샘플링합니다(각각 :code:`ClientProxy` 개체로 표시됨)" +":code:`client_manager`를 사용하여 사용 가능한 모든 클라이언트(또는 그 하위 집" +"합)를 무작위로 샘플링합니다(각각 :code:`ClientProxy` 개체로 표시됨)" #: ../../source/how-to-implement-strategies.rst:234 msgid "" "Pair each :code:`ClientProxy` with the same :code:`FitIns` holding the " "current global model :code:`parameters` and :code:`config` dict" msgstr "" -"각 :code:`ClientProxy`를 현재 글로벌 모델 :code:`parameters` 및 " -":code:`config` dict를 보유한 동일한 :code:`FitIns`와 쌍을 이룹니다" +"각 :code:`ClientProxy`를 현재 글로벌 모델 :code:`parameters` 및 :code:" +"`config` dict를 보유한 동일한 :code:`FitIns`와 쌍을 이룹니다" #: ../../source/how-to-implement-strategies.rst:236 msgid "" "More sophisticated implementations can use :code:`configure_fit` to " -"implement custom client selection logic. A client will only participate " -"in a round if the corresponding :code:`ClientProxy` is included in the " -"list returned from :code:`configure_fit`." +"implement custom client selection logic. A client will only participate in a " +"round if the corresponding :code:`ClientProxy` is included in the list " +"returned from :code:`configure_fit`." msgstr "" -"보다 정교한 구현은 :code:`configure_fit`을 사용하여 사용자 지정 클라이언트 " -"선택 로직을 구현할 수 있습니다. 클라이언트는 :code:`configure_fit`에서 " -"반환된 목록에 해당 :code:`ClientProxy`가 포함된 경우에만 라운드에 참여합니다." +"보다 정교한 구현은 :code:`configure_fit`을 사용하여 사용자 지정 클라이언트 선" +"택 로직을 구현할 수 있습니다. 클라이언트는 :code:`configure_fit`에서 반환된 " +"목록에 해당 :code:`ClientProxy`가 포함된 경우에만 라운드에 참여합니다." #: ../../source/how-to-implement-strategies.rst:240 msgid "" "The structure of this return value provides a lot of flexibility to the " "user. Since instructions are defined on a per-client basis, different " -"instructions can be sent to each client. This enables custom strategies " -"to train, for example, different models on different clients, or use " -"different hyperparameters on different clients (via the :code:`config` " -"dict)." +"instructions can be sent to each client. This enables custom strategies to " +"train, for example, different models on different clients, or use different " +"hyperparameters on different clients (via the :code:`config` dict)." msgstr "" "이 반환 값의 구조는 사용자에게 많은 유연성을 제공합니다. instructions은 " -"클라이언트별로 정의되므로 각 클라이언트에 서로 다른 instructions을 전송할 수 " +"클라이언트별로 정의되므로 각 클라이언트에 서로 다른 명령어를 전송할 수 " "있습니다. 이를 통해 예를 들어 클라이언트마다 다른 모델을 학습시키거나 " "클라이언트마다 다른 하이퍼파라미터를 사용하는 사용자 지정 전략을 사용할 수 " "있습니다(:code:`config` dict를 통해)." @@ -5028,9 +5081,8 @@ msgstr ":code:`aggregate_fit` 메서드" #: ../../source/how-to-implement-strategies.rst:245 msgid "" -":code:`aggregate_fit` is responsible for aggregating the results returned" -" by the clients that were selected and asked to train in " -":code:`configure_fit`." +":code:`aggregate_fit` is responsible for aggregating the results returned by " +"the clients that were selected and asked to train in :code:`configure_fit`." msgstr "" "code:`aggregate_fit`은 :code:`configure_fit`에서 훈련하도록 선택되고 요청된 " "클라이언트가 반환한 결과를 집계하는 역할을 담당합니다." @@ -5038,26 +5090,26 @@ msgstr "" #: ../../source/how-to-implement-strategies.rst:258 msgid "" "Of course, failures can happen, so there is no guarantee that the server " -"will get results from all the clients it sent instructions to (via " -":code:`configure_fit`). :code:`aggregate_fit` therefore receives a list " -"of :code:`results`, but also a list of :code:`failures`." +"will get results from all the clients it sent instructions to (via :code:" +"`configure_fit`). :code:`aggregate_fit` therefore receives a list of :code:" +"`results`, but also a list of :code:`failures`." msgstr "" -"물론 실패가 발생할 수 있으므로 서버가 명령을 보낸 모든 클라이언트로부터 " -"결과를 얻을 수 있다는 보장은 없습니다(:code:`configure_fit`을 통해). 따라서 " -":code:`aggregate_fit`은 :code:`results` 목록뿐만 아니라 :code:`failures` " -"목록도 받습니다." +"물론 실패가 발생할 수 있으므로 서버가 명령을 보낸 모든 클라이언트로부터 결과" +"를 얻을 수 있다는 보장은 없습니다(:code:`configure_fit`을 통해). 따라서 :" +"code:`aggregate_fit`은 :code:`results` 목록뿐만 아니라 :code:`failures` 목록" +"도 받습니다." #: ../../source/how-to-implement-strategies.rst:260 msgid "" -":code:`aggregate_fit` returns an optional :code:`Parameters` object and a" -" dictionary of aggregated metrics. The :code:`Parameters` return value is" -" optional because :code:`aggregate_fit` might decide that the results " +":code:`aggregate_fit` returns an optional :code:`Parameters` object and a " +"dictionary of aggregated metrics. The :code:`Parameters` return value is " +"optional because :code:`aggregate_fit` might decide that the results " "provided are not sufficient for aggregation (e.g., too many failures)." msgstr "" "code:`aggregate_fit`은 선택적 :code:`Parameters` 개체와 집계된 메트릭의 " "dictionary를 반환합니다. :code:`Parameters` 반환 값은 :code:`aggregate_fit`" -"이 제공된 결과가 집계에 충분하지 않다고 판단할 수 있으므로(예: 실패 수가 " -"너무 많음) 선택 사항입니다." +"이 제공된 결과가 집계에 충분하지 않다고 판단할 수 있으므로(예: 실패 수가 너" +"무 많음) 선택 사항입니다." #: ../../source/how-to-implement-strategies.rst:263 msgid "The :code:`configure_evaluate` method" @@ -5065,59 +5117,56 @@ msgstr ":code:`configure_evaluate` 메서드" #: ../../source/how-to-implement-strategies.rst:265 msgid "" -":code:`configure_evaluate` is responsible for configuring the upcoming " -"round of evaluation. What does *configure* mean in this context? " -"Configuring a round means selecting clients and deciding what " -"instructions to send to these clients. The signature of " -":code:`configure_evaluate` makes this clear:" +":code:`configure_evaluate` is responsible for configuring the upcoming round " +"of evaluation. What does *configure* mean in this context? Configuring a " +"round means selecting clients and deciding what instructions to send to " +"these clients. The signature of :code:`configure_evaluate` makes this clear:" msgstr "" ":code:`configure_evaluate`는 다가오는 평가 라운드를 구성하는 역할을 합니다. " -"이 문맥에서 *구성*은 무엇을 의미하나요? 라운드를 구성한다는 것은 " -"클라이언트를 선택하고 이러한 클라이언트에 전송할 지침을 결정하는 것을 " -"의미합니다. :code:`configure_evaluate`의 시그니처를 보면 이를 명확히 알 수 " -"있습니다:" +"이 문맥에서 *구성*은 무엇을 의미하나요? 라운드를 구성한다는 것은 클라이언트" +"를 선택하고 이러한 클라이언트에 전송할 지침을 결정하는 것을 의미합니다. :" +"code:`configure_evaluate`의 시그니처를 보면 이를 명확히 알 수 있습니다:" #: ../../source/how-to-implement-strategies.rst:278 msgid "" "The return value is a list of tuples, each representing the instructions " -"that will be sent to a particular client. Strategy implementations " -"usually perform the following steps in :code:`configure_evaluate`:" +"that will be sent to a particular client. Strategy implementations usually " +"perform the following steps in :code:`configure_evaluate`:" msgstr "" -"반환 값은 튜플 목록으로, 각 튜플은 특정 클라이언트로 전송될 instructions을 " +"반환 값은 튜플 목록으로, 각 튜플은 특정 클라이언트로 전송될 명령어를 " "나타냅니다. 전략 구현은 일반적으로 :code:`configure_evaluate`에서 다음 " "단계를 수행합니다:" #: ../../source/how-to-implement-strategies.rst:281 msgid "" -"Pair each :code:`ClientProxy` with the same :code:`EvaluateIns` holding " -"the current global model :code:`parameters` and :code:`config` dict" +"Pair each :code:`ClientProxy` with the same :code:`EvaluateIns` holding the " +"current global model :code:`parameters` and :code:`config` dict" msgstr "" -"각 :code:`ClientProxy`를 현재 글로벌 모델 :code:`parameters` 및 " -":code:`config` dict를 보유한 동일한 :code:`EvaluateIns`와 쌍을 이룹니다" +"각 :code:`ClientProxy`를 현재 글로벌 모델 :code:`parameters` 및 :code:" +"`config` dict를 보유한 동일한 :code:`EvaluateIns`와 쌍을 이룹니다" #: ../../source/how-to-implement-strategies.rst:283 msgid "" "More sophisticated implementations can use :code:`configure_evaluate` to " -"implement custom client selection logic. A client will only participate " -"in a round if the corresponding :code:`ClientProxy` is included in the " -"list returned from :code:`configure_evaluate`." +"implement custom client selection logic. A client will only participate in a " +"round if the corresponding :code:`ClientProxy` is included in the list " +"returned from :code:`configure_evaluate`." msgstr "" -"보다 정교한 구현은 :code:`configure_evaluate`를 사용하여 사용자 지정 " -"클라이언트 선택 로직을 구현할 수 있습니다. 클라이언트는 " -":code:`configure_evaluate`에서 반환된 목록에 해당 :code:`ClientProxy`가 " -"포함된 경우에만 라운드에 참여합니다." +"보다 정교한 구현은 :code:`configure_evaluate`를 사용하여 사용자 지정 클라이언" +"트 선택 로직을 구현할 수 있습니다. 클라이언트는 :code:`configure_evaluate`에" +"서 반환된 목록에 해당 :code:`ClientProxy`가 포함된 경우에만 라운드에 참여합니" +"다." #: ../../source/how-to-implement-strategies.rst:287 msgid "" "The structure of this return value provides a lot of flexibility to the " "user. Since instructions are defined on a per-client basis, different " -"instructions can be sent to each client. This enables custom strategies " -"to evaluate, for example, different models on different clients, or use " -"different hyperparameters on different clients (via the :code:`config` " -"dict)." +"instructions can be sent to each client. This enables custom strategies to " +"evaluate, for example, different models on different clients, or use " +"different hyperparameters on different clients (via the :code:`config` dict)." msgstr "" -"이 반환 값의 구조는 사용자에게 많은 유연성을 제공합니다. instructions은 " -"클라이언트별로 정의되므로 각 클라이언트에 서로 다른 instructions을 전송할 수 " +"이 반환 값의 구조는 사용자에게 많은 유연성을 제공합니다. 명령어는 " +"클라이언트별로 정의되므로 각 클라이언트에 서로 다른 명령어를 전송할 수 " "있습니다. 이를 통해 사용자 지정 전략을 통해 예를 들어 클라이언트마다 다른 " "모델을 평가하거나 클라이언트마다 다른 하이퍼파라미터를 사용할 수 " "있습니다(:code:`config` dict를 통해)." @@ -5129,35 +5178,35 @@ msgstr ":code:`aggregate_evaluate` 메서드" #: ../../source/how-to-implement-strategies.rst:293 msgid "" ":code:`aggregate_evaluate` is responsible for aggregating the results " -"returned by the clients that were selected and asked to evaluate in " -":code:`configure_evaluate`." +"returned by the clients that were selected and asked to evaluate in :code:" +"`configure_evaluate`." msgstr "" -"code:`aggregate_evaluate`는 :code:`configure_evaluate`에서 선택되어 평가를 " -"요청한 클라이언트가 반환한 결과를 집계하는 역할을 담당합니다." +"code:`aggregate_evaluate`는 :code:`configure_evaluate`에서 선택되어 평가를 요" +"청한 클라이언트가 반환한 결과를 집계하는 역할을 담당합니다." #: ../../source/how-to-implement-strategies.rst:306 msgid "" "Of course, failures can happen, so there is no guarantee that the server " -"will get results from all the clients it sent instructions to (via " -":code:`configure_evaluate`). :code:`aggregate_evaluate` therefore " -"receives a list of :code:`results`, but also a list of :code:`failures`." +"will get results from all the clients it sent instructions to (via :code:" +"`configure_evaluate`). :code:`aggregate_evaluate` therefore receives a list " +"of :code:`results`, but also a list of :code:`failures`." msgstr "" -"물론 실패가 발생할 수 있으므로 서버가 명령을 보낸 모든 클라이언트로부터 " -"결과를 얻을 수 있다는 보장은 없습니다(:code:`configure_evaluate`를 통해). " -"따라서 :code:`aggregate_evaluate`는 :code:`results` 목록뿐만 아니라 " -":code:`failures` 목록도 받습니다." +"물론 실패가 발생할 수 있으므로 서버가 명령을 보낸 모든 클라이언트로부터 결과" +"를 얻을 수 있다는 보장은 없습니다(:code:`configure_evaluate`를 통해). 따라" +"서 :code:`aggregate_evaluate`는 :code:`results` 목록뿐만 아니라 :code:" +"`failures` 목록도 받습니다." #: ../../source/how-to-implement-strategies.rst:308 msgid "" -":code:`aggregate_evaluate` returns an optional :code:`float` (loss) and a" -" dictionary of aggregated metrics. The :code:`float` return value is " -"optional because :code:`aggregate_evaluate` might decide that the results" -" provided are not sufficient for aggregation (e.g., too many failures)." +":code:`aggregate_evaluate` returns an optional :code:`float` (loss) and a " +"dictionary of aggregated metrics. The :code:`float` return value is optional " +"because :code:`aggregate_evaluate` might decide that the results provided " +"are not sufficient for aggregation (e.g., too many failures)." msgstr "" "code:`aggregate_evaluate`는 선택적 :code:`float`(손실)와 집계된 메트릭의 " "dictionary를 반환합니다. code:`float` 반환 값은 :code:`aggregate_evaluate`가 " -"제공된 결과가 집계에 충분하지 않다고 판단할 수 있으므로(예: 실패 수가 너무 " -"많음) 선택 사항입니다." +"제공된 결과가 집계에 충분하지 않다고 판단할 수 있으므로(예: 실패 수가 너무 많" +"음) 선택 사항입니다." #: ../../source/how-to-implement-strategies.rst:311 msgid "The :code:`evaluate` method" @@ -5166,26 +5215,25 @@ msgstr ":code:`evaluate` 메서드" #: ../../source/how-to-implement-strategies.rst:313 msgid "" ":code:`evaluate` is responsible for evaluating model parameters on the " -"server-side. Having :code:`evaluate` in addition to " -":code:`configure_evaluate`/:code:`aggregate_evaluate` enables strategies " -"to perform both servers-side and client-side (federated) evaluation." +"server-side. Having :code:`evaluate` in addition to :code:" +"`configure_evaluate`/:code:`aggregate_evaluate` enables strategies to " +"perform both servers-side and client-side (federated) evaluation." msgstr "" ":code:`evaluate`는 서버 측에서 모델 매개변수를 평가하는 역할을 담당합니다. " "code:`configure_evaluate`/:code:`aggregate_evaluate`와 함께 :code:`evaluate`" -"를 사용하면 서버 측과 클라이언트 측(federated) 평가를 모두 수행할 수 있는 " -"전략을 사용할 수 있습니다." +"를 사용하면 서버 측과 클라이언트 측(federated) 평가를 모두 수행할 수 있는 전" +"략을 사용할 수 있습니다." #: ../../source/how-to-implement-strategies.rst:323 msgid "" -"The return value is again optional because the strategy might not need to" -" implement server-side evaluation or because the user-defined " -":code:`evaluate` method might not complete successfully (e.g., it might " -"fail to load the server-side evaluation data)." +"The return value is again optional because the strategy might not need to " +"implement server-side evaluation or because the user-defined :code:" +"`evaluate` method might not complete successfully (e.g., it might fail to " +"load the server-side evaluation data)." msgstr "" -"반환 값은 전략에서 서버 측 평가를 구현할 필요가 없거나 사용자 정의 " -":code:`evaluate` 메서드가 성공적으로 완료되지 않을 수 있기 때문에(예: 서버 " -"측 평가 데이터를 로드하지 못할 수 있음) 다시 선택 사항으로 설정할 수 " -"있습니다." +"반환 값은 전략에서 서버 측 평가를 구현할 필요가 없거나 사용자 정의 :code:" +"`evaluate` 메서드가 성공적으로 완료되지 않을 수 있기 때문에(예: 서버 측 평가 " +"데이터를 로드하지 못할 수 있음) 다시 선택 사항으로 설정할 수 있습니다." #: ../../source/how-to-install-flower.rst:2 msgid "Install Flower" @@ -5206,17 +5254,18 @@ msgstr "pip 사용" #: ../../source/how-to-install-flower.rst:17 msgid "" -"Stable releases are available on `PyPI " -"`_::" -msgstr "안정적인 릴리즈는 `PyPI `_:: 에서 확인할 수 " +"Stable releases are available on `PyPI `_::" +msgstr "" +"안정적인 릴리즈는 `PyPI `_:: 에서 확인할 수 " "있습니다::" #: ../../source/how-to-install-flower.rst:21 msgid "" "For simulations that use the Virtual Client Engine, ``flwr`` should be " "installed with the ``simulation`` extra::" -msgstr "가상 클라이언트 엔진을 사용하는 시뮬레이션의 경우 ``flwr``을 ``simulation``" -"extra와 함께 설치해야 합니다:" +msgstr "" +"가상 클라이언트 엔진을 사용하는 시뮬레이션의 경우 ``flwr``을 " +"``simulation``extra와 함께 설치해야 합니다:" #: ../../source/how-to-install-flower.rst:27 msgid "Using conda (or mamba)" @@ -5228,15 +5277,16 @@ msgstr "Flower은 'conda-forge' 채널에서도 설치할 수 있습니다." #: ../../source/how-to-install-flower.rst:31 msgid "" -"If you have not added ``conda-forge`` to your channels, you will first " -"need to run the following::" +"If you have not added ``conda-forge`` to your channels, you will first need " +"to run the following::" msgstr "채널에 'conda-forge'를 추가하지 않은 경우 먼저 다음을 실행해야 합니다:" #: ../../source/how-to-install-flower.rst:36 msgid "" -"Once the ``conda-forge`` channel has been enabled, ``flwr`` can be " -"installed with ``conda``::" -msgstr "conda-forge`` 채널이 활성화되면 ``flwr``을 ``conda``로 설치할 수 있습니다::" +"Once the ``conda-forge`` channel has been enabled, ``flwr`` can be installed " +"with ``conda``::" +msgstr "" +"conda-forge`` 채널이 활성화되면 ``flwr``을 ``conda``로 설치할 수 있습니다::" #: ../../source/how-to-install-flower.rst:40 msgid "or with ``mamba``::" @@ -5249,11 +5299,11 @@ msgstr "설치 확인" #: ../../source/how-to-install-flower.rst:48 msgid "" "The following command can be used to verify if Flower was successfully " -"installed. If everything worked, it should print the version of Flower to" -" the command line::" +"installed. If everything worked, it should print the version of Flower to " +"the command line::" msgstr "" -"다음 명령을 사용하여 Flower가 성공적으로 설치되었는지 확인할 수 있습니다. " -"모든 것이 정상적으로 작동하면 명령줄에 Flower의 버전이 출력됩니다:" +"다음 명령을 사용하여 Flower가 성공적으로 설치되었는지 확인할 수 있습니다. 모" +"든 것이 정상적으로 작동하면 명령줄에 Flower의 버전이 출력됩니다:" #: ../../source/how-to-install-flower.rst:55 msgid "Advanced installation options" @@ -5265,7 +5315,8 @@ msgstr "Docker를 통해 설치" #: ../../source/how-to-install-flower.rst:60 msgid ":doc:`How to run Flower using Docker `" -msgstr ":doc:`Docker를 사용하여 Flower를 실행하는 방법 `" #: ../../source/how-to-install-flower.rst:63 @@ -5274,17 +5325,17 @@ msgstr "사전 릴리즈 설치" #: ../../source/how-to-install-flower.rst:65 msgid "" -"New (possibly unstable) versions of Flower are sometimes available as " -"pre-release versions (alpha, beta, release candidate) before the stable " -"release happens::" +"New (possibly unstable) versions of Flower are sometimes available as pre-" +"release versions (alpha, beta, release candidate) before the stable release " +"happens::" msgstr "" -"새(불안정할 수 있는) 버전의 Flower는 안정 버전이 출시되기 전에 사전 릴리즈 " -"버전(알파, 베타, 릴리즈 후보)으로 제공되는 경우가 있습니다:" +"새(불안정할 수 있는) 버전의 Flower는 안정 버전이 출시되기 전에 사전 릴리즈 버" +"전(알파, 베타, 릴리즈 후보)으로 제공되는 경우가 있습니다:" #: ../../source/how-to-install-flower.rst:69 msgid "" -"For simulations that use the Virtual Client Engine, ``flwr`` pre-releases" -" should be installed with the ``simulation`` extra::" +"For simulations that use the Virtual Client Engine, ``flwr`` pre-releases " +"should be installed with the ``simulation`` extra::" msgstr "" "가상 클라이언트 엔진을 사용하는 시뮬레이션의 경우 ``flwr`` 사전 릴리즈를 " "``simulation`` extra와 함께 설치해야 합니다:" @@ -5295,15 +5346,16 @@ msgstr "야간 릴리즈 설치" #: ../../source/how-to-install-flower.rst:76 msgid "" -"The latest (potentially unstable) changes in Flower are available as " -"nightly releases::" -msgstr "Flower의 최신 (불안정할 수 있는) 변경 사항은 다음과 같이 야간 릴리즈로 " -"제공됩니다:" +"The latest (potentially unstable) changes in Flower are available as nightly " +"releases::" +msgstr "" +"Flower의 최신 (불안정할 수 있는) 변경 사항은 다음과 같이 야간 릴리즈로 제공됩" +"니다:" #: ../../source/how-to-install-flower.rst:80 msgid "" -"For simulations that use the Virtual Client Engine, ``flwr-nightly`` " -"should be installed with the ``simulation`` extra::" +"For simulations that use the Virtual Client Engine, ``flwr-nightly`` should " +"be installed with the ``simulation`` extra::" msgstr "" "가상 클라이언트 엔진을 사용하는 시뮬레이션의 경우, ``flwr-nightly``를 " "``simulation`` extr와 함께 설치해야 합니다::" @@ -5314,24 +5366,24 @@ msgstr "모니터 시뮬레이션" #: ../../source/how-to-monitor-simulation.rst:4 msgid "" -"Flower allows you to monitor system resources while running your " -"simulation. Moreover, the Flower simulation engine is powerful and " -"enables you to decide how to allocate resources per client manner and " -"constrain the total usage. Insights from resource consumption can help " -"you make smarter decisions and speed up the execution time." +"Flower allows you to monitor system resources while running your simulation. " +"Moreover, the Flower simulation engine is powerful and enables you to decide " +"how to allocate resources per client manner and constrain the total usage. " +"Insights from resource consumption can help you make smarter decisions and " +"speed up the execution time." msgstr "" -"Flower를 사용하면 시뮬레이션을 실행하는 동안 시스템 리소스를 모니터링할 수 " -"있습니다. 또한 Flower 시뮬레이션 엔진은 강력하며 클라이언트별 리소스 할당 " -"방법을 결정하고 총 사용량을 제한할 수 있습니다. 리소스 소비에 대한 " -"인사이트를 통해 더 현명한 결정을 내리고 실행 시간을 단축할 수 있습니다." +"Flower를 사용하면 시뮬레이션을 실행하는 동안 시스템 리소스를 모니터링할 수 있" +"습니다. 또한 Flower 시뮬레이션 엔진은 강력하며 클라이언트별 리소스 할당 방법" +"을 결정하고 총 사용량을 제한할 수 있습니다. 리소스 소비에 대한 인사이트를 통" +"해 더 현명한 결정을 내리고 실행 시간을 단축할 수 있습니다." #: ../../source/how-to-monitor-simulation.rst:6 msgid "" -"The specific instructions assume you are using macOS and have the " -"`Homebrew `_ package manager installed." +"The specific instructions assume you are using macOS and have the `Homebrew " +"`_ package manager installed." msgstr "" -"구체적인 지침은 macOS를 사용 중이고 'Homebrew `_ 패키지 " -"관리자가 설치되어 있다고 가정합니다." +"구체적인 지침은 macOS를 사용 중이고 'Homebrew `_ 패키지 관" +"리자가 설치되어 있다고 가정합니다." #: ../../source/how-to-monitor-simulation.rst:10 msgid "Downloads" @@ -5339,15 +5391,15 @@ msgstr "다운로드" #: ../../source/how-to-monitor-simulation.rst:16 msgid "" -"`Prometheus `_ is used for data collection, while" -" `Grafana `_ will enable you to visualize the " -"collected data. They are both well integrated with `Ray " -"`_ which Flower uses under the hood." +"`Prometheus `_ is used for data collection, while " +"`Grafana `_ will enable you to visualize the collected " +"data. They are both well integrated with `Ray `_ which " +"Flower uses under the hood." msgstr "" "`Prometheus `_는 데이터 수집에 사용되며, `Grafana " "`_는 수집된 데이터를 시각화할 수 있게 해줍니다. 이 두 " -"도구는 모두 Flower가 내부적으로 사용하는 `Ray `_와 잘 " -"통합되어 있습니다." +"도구는 모두 Flower가 내부적으로 사용하는 `Ray `_와 잘 통" +"합되어 있습니다." #: ../../source/how-to-monitor-simulation.rst:18 msgid "" @@ -5365,25 +5417,25 @@ msgstr "이전 세대 Intel Mac 장치에서는:" #: ../../source/how-to-monitor-simulation.rst:34 msgid "" -"Open the respective configuration files and change them. Depending on " -"your device, use one of the two following commands:" -msgstr "각 구성 파일을 열고 변경합니다. 장치에 따라 다음 두 명령 중 하나를 " -"사용합니다:" +"Open the respective configuration files and change them. Depending on your " +"device, use one of the two following commands:" +msgstr "" +"각 구성 파일을 열고 변경합니다. 장치에 따라 다음 두 명령 중 하나를 사용합니" +"다:" #: ../../source/how-to-monitor-simulation.rst:44 msgid "" -"and then delete all the text in the file and paste a new Prometheus " -"config you see below. You may adjust the time intervals to your " -"requirements:" +"and then delete all the text in the file and paste a new Prometheus config " +"you see below. You may adjust the time intervals to your requirements:" msgstr "" -"를 입력한 다음 파일의 모든 텍스트를 삭제하고 아래에 표시된 새 Prometheus " -"설정을 붙여넣습니다. 요구 사항에 따라 시간 간격을 조정할 수 있습니다:" +"를 입력한 다음 파일의 모든 텍스트를 삭제하고 아래에 표시된 새 Prometheus 설정" +"을 붙여넣습니다. 요구 사항에 따라 시간 간격을 조정할 수 있습니다:" #: ../../source/how-to-monitor-simulation.rst:59 msgid "" -"Now after you have edited the Prometheus configuration, do the same with " -"the Grafana configuration files. Open those using one of the following " -"commands as before:" +"Now after you have edited the Prometheus configuration, do the same with the " +"Grafana configuration files. Open those using one of the following commands " +"as before:" msgstr "" "이제 Prometheus 구성을 편집한 후 Grafana 구성 파일에 대해서도 동일한 작업을 " "수행합니다. 이전과 마찬가지로 다음 명령 중 하나를 사용하여 파일을 엽니다:" @@ -5392,14 +5444,16 @@ msgstr "" msgid "" "Your terminal editor should open and allow you to apply the following " "configuration as before." -msgstr "터미널 편집기가 열리면 이전과 마찬가지로 다음 구성을 적용할 수 있습니다." +msgstr "" +"터미널 편집기가 열리면 이전과 마찬가지로 다음 구성을 적용할 수 있습니다." #: ../../source/how-to-monitor-simulation.rst:84 msgid "" -"Congratulations, you just downloaded all the necessary software needed " -"for metrics tracking. Now, let’s start it." -msgstr "축하합니다. 매트릭 트레킹에 필요한 모든 소프트웨어를 다운로드하셨습니다. " -"이제 시작해 보겠습니다." +"Congratulations, you just downloaded all the necessary software needed for " +"metrics tracking. Now, let’s start it." +msgstr "" +"축하합니다. 매트릭 트레킹에 필요한 모든 소프트웨어를 다운로드하셨습니다. 이" +"제 시작해 보겠습니다." #: ../../source/how-to-monitor-simulation.rst:88 msgid "Tracking metrics" @@ -5409,14 +5463,15 @@ msgstr "매트릭 트래킹" msgid "" "Before running your Flower simulation, you have to start the monitoring " "tools you have just installed and configured." -msgstr "Flower 시뮬레이션을 실행하기 전에 방금 설치 및 구성한 모니터링 도구를 " -"시작해야 합니다." +msgstr "" +"Flower 시뮬레이션을 실행하기 전에 방금 설치 및 구성한 모니터링 도구를 시작해" +"야 합니다." #: ../../source/how-to-monitor-simulation.rst:97 msgid "" -"Please include the following argument in your Python code when starting a" -" simulation." -msgstr "시뮬레이션을 시작할 때 Python 코드에 다음 argument를 포함하세요." +"Please include the following argument in your Python code when starting a " +"simulation." +msgstr "시뮬레이션을 시작할 때 Python 코드에 다음 전달인자를 포함하세요." #: ../../source/how-to-monitor-simulation.rst:108 msgid "Now, you are ready to start your workload." @@ -5424,9 +5479,10 @@ msgstr "이제 워크로드를 시작할 준비가 되었습니다." #: ../../source/how-to-monitor-simulation.rst:110 msgid "" -"Shortly after the simulation starts, you should see the following logs in" -" your terminal:" -msgstr "시뮬레이션이 시작되고 얼마 지나지 않아 터미널에 다음 로그가 표시됩니다:" +"Shortly after the simulation starts, you should see the following logs in " +"your terminal:" +msgstr "" +"시뮬레이션이 시작되고 얼마 지나지 않아 터미널에 다음 로그가 표시됩니다:" #: ../../source/how-to-monitor-simulation.rst:117 msgid "You can look at everything at ``_ ." @@ -5434,24 +5490,24 @@ msgstr "``_ 에서 모든 것을 볼 수 있습니다." #: ../../source/how-to-monitor-simulation.rst:119 msgid "" -"It's a Ray Dashboard. You can navigate to Metrics (on the left panel, the" -" lowest option)." -msgstr "Ray 대시보드입니다. 메트릭(왼쪽 패널의 가장 아래 옵션)으로 이동할 수 " -"있습니다." +"It's a Ray Dashboard. You can navigate to Metrics (on the left panel, the " +"lowest option)." +msgstr "" +"Ray 대시보드입니다. 메트릭(왼쪽 패널의 가장 아래 옵션)으로 이동할 수 있습니" +"다." #: ../../source/how-to-monitor-simulation.rst:121 msgid "" -"Or alternatively, you can just see them in Grafana by clicking on the " -"right-up corner, “View in Grafana”. Please note that the Ray dashboard is" -" only accessible during the simulation. After the simulation ends, you " -"can only use Grafana to explore the metrics. You can start Grafana by " -"going to ``http://localhost:3000/``." +"Or alternatively, you can just see them in Grafana by clicking on the right-" +"up corner, “View in Grafana”. Please note that the Ray dashboard is only " +"accessible during the simulation. After the simulation ends, you can only " +"use Grafana to explore the metrics. You can start Grafana by going to " +"``http://localhost:3000/``." msgstr "" -"또는 오른쪽 위 모서리인 \"Grafana에서 보기\"를 클릭하여 Grafana에서 바로 " -"확인할 수도 있습니다. Ray 대시보드는 시뮬레이션 중에만 액세스할 수 있다는 " -"점에 유의하세요. 시뮬레이션이 종료된 후에는 Grafana를 사용하여 메트릭을 " -"탐색할 수만 있습니다. ``http://localhost:3000/``로 이동하여 Grafana를 시작할 " -"수 있습니다." +"또는 오른쪽 위 모서리인 \"Grafana에서 보기\"를 클릭하여 Grafana에서 바로 확인" +"할 수도 있습니다. Ray 대시보드는 시뮬레이션 중에만 액세스할 수 있다는 점에 유" +"의하세요. 시뮬레이션이 종료된 후에는 Grafana를 사용하여 메트릭을 탐색할 수만 " +"있습니다. ``http://localhost:3000/``로 이동하여 Grafana를 시작할 수 있습니다." #: ../../source/how-to-monitor-simulation.rst:123 msgid "" @@ -5468,26 +5524,26 @@ msgstr "리소스 할당" #: ../../source/how-to-monitor-simulation.rst:134 msgid "" -"You must understand how the Ray library works to efficiently allocate " -"system resources to simulation clients on your own." -msgstr "Ray 라이브러리가 어떻게 작동하는지 이해해야 시뮬레이션 클라이언트에 시스템 " -"리소스를 효율적으로 할당할 수 있습니다." +"You must understand how the Ray library works to efficiently allocate system " +"resources to simulation clients on your own." +msgstr "" +"Ray 라이브러리가 어떻게 작동하는지 이해해야 시뮬레이션 클라이언트에 시스템 리" +"소스를 효율적으로 할당할 수 있습니다." #: ../../source/how-to-monitor-simulation.rst:136 msgid "" "Initially, the simulation (which Ray handles under the hood) starts by " "default with all the available resources on the system, which it shares " -"among the clients. It doesn't mean it divides it equally among all of " -"them, nor that the model training happens at all of them simultaneously. " -"You will learn more about that in the later part of this blog. You can " -"check the system resources by running the following:" -msgstr "" -"처음에 시뮬레이션(Ray가 내부에서 처리하는)은 기본적으로 시스템에서 사용 " -"가능한 모든 리소스를 사용하여 시작되며, 이 리소스는 클라이언트 간에 " -"공유됩니다. 그렇다고 해서 모든 클라이언트에게 균등하게 분배하거나 모든 " -"클라이언트에서 동시에 모델 학습이 이루어지는 것은 아닙니다. 이에 대한 자세한 " -"내용은 이 블로그의 뒷부분에서 설명합니다. 다음을 실행하여 시스템 리소스를 " -"확인할 수 있습니다:" +"among the clients. It doesn't mean it divides it equally among all of them, " +"nor that the model training happens at all of them simultaneously. You will " +"learn more about that in the later part of this blog. You can check the " +"system resources by running the following:" +msgstr "" +"처음에 시뮬레이션(Ray가 내부에서 처리하는)은 기본적으로 시스템에서 사용 가능" +"한 모든 리소스를 사용하여 시작되며, 이 리소스는 클라이언트 간에 공유됩니다. " +"그렇다고 해서 모든 클라이언트에게 균등하게 분배하거나 모든 클라이언트에서 동" +"시에 모델 학습이 이루어지는 것은 아닙니다. 이에 대한 자세한 내용은 이 블로그" +"의 뒷부분에서 설명합니다. 다음을 실행하여 시스템 리소스를 확인할 수 있습니다:" #: ../../source/how-to-monitor-simulation.rst:143 msgid "In Google Colab, the result you see might be similar to this:" @@ -5495,10 +5551,11 @@ msgstr "Google Colab에서는 이와 유사한 결과가 표시될 수 있습니 #: ../../source/how-to-monitor-simulation.rst:155 msgid "" -"However, you can overwrite the defaults. When starting a simulation, do " -"the following (you don't need to overwrite all of them):" -msgstr "그러나 기본값을 덮어쓸 수 있습니다. 시뮬레이션을 시작할 때 다음을 수행합니다(" -"모두 덮어쓸 필요는 없음):" +"However, you can overwrite the defaults. When starting a simulation, do the " +"following (you don't need to overwrite all of them):" +msgstr "" +"그러나 기본값을 덮어쓸 수 있습니다. 시뮬레이션을 시작할 때 다음을 수행합니다" +"(모두 덮어쓸 필요는 없음):" #: ../../source/how-to-monitor-simulation.rst:175 msgid "Let’s also specify the resource for a single client." @@ -5506,28 +5563,28 @@ msgstr "단일 클라이언트에 대한 리소스도 지정해 보겠습니다. #: ../../source/how-to-monitor-simulation.rst:205 msgid "" -"Now comes the crucial part. Ray will start a new client only when it has " -"all the required resources (such that they run in parallel) when the " -"resources allow." +"Now comes the crucial part. Ray will start a new client only when it has all " +"the required resources (such that they run in parallel) when the resources " +"allow." msgstr "" -"이제 중요한 부분이 나옵니다. Ray는 리소스가 허용하는 경우에만 필요한 모든 " -"리소스가 있을 때(병렬로 실행되는 등) 새 클라이언트를 시작합니다." +"이제 중요한 부분이 나옵니다. Ray는 리소스가 허용하는 경우에만 필요한 모든 리" +"소스가 있을 때(병렬로 실행되는 등) 새 클라이언트를 시작합니다." #: ../../source/how-to-monitor-simulation.rst:207 msgid "" -"In the example above, only one client will be run, so your clients won't " -"run concurrently. Setting :code:`client_num_gpus = 0.5` would allow " -"running two clients and therefore enable them to run concurrently. Be " -"careful not to require more resources than available. If you specified " -":code:`client_num_gpus = 2`, the simulation wouldn't start (even if you " -"had 2 GPUs but decided to set 1 in :code:`ray_init_args`)." +"In the example above, only one client will be run, so your clients won't run " +"concurrently. Setting :code:`client_num_gpus = 0.5` would allow running two " +"clients and therefore enable them to run concurrently. Be careful not to " +"require more resources than available. If you specified :code:" +"`client_num_gpus = 2`, the simulation wouldn't start (even if you had 2 GPUs " +"but decided to set 1 in :code:`ray_init_args`)." msgstr "" -"위의 예에서는 하나의 클라이언트만 실행되므로 클라이언트가 동시에 실행되지 " -"않습니다. :code:`client_num_gpus = 0.5` 를 설정하면 두 개의 클라이언트를 " -"실행할 수 있으므로 동시에 실행할 수 있습니다. 사용 가능한 리소스보다 더 많은 " -"리소스를 요구하지 않도록 주의하세요. :code:`client_num_gpus = 2`를 지정하면 " -"시뮬레이션이 시작되지 않습니다(GPU가 2개이지만 :code:`ray_init_args`에서 " -"1개를 설정한 경우에도 마찬가지입니다)." +"위의 예에서는 하나의 클라이언트만 실행되므로 클라이언트가 동시에 실행되지 않" +"습니다. :code:`client_num_gpus = 0.5` 를 설정하면 두 개의 클라이언트를 실행" +"할 수 있으므로 동시에 실행할 수 있습니다. 사용 가능한 리소스보다 더 많은 리소" +"스를 요구하지 않도록 주의하세요. :code:`client_num_gpus = 2`를 지정하면 시뮬" +"레이션이 시작되지 않습니다(GPU가 2개이지만 :code:`ray_init_args`에서 1개를 설" +"정한 경우에도 마찬가지입니다)." #: ../../source/how-to-monitor-simulation.rst:212 ../../source/ref-faq.rst:2 msgid "FAQ" @@ -5539,29 +5596,29 @@ msgstr "질문: 기록된 메트릭이 보이지 않습니다." #: ../../source/how-to-monitor-simulation.rst:216 msgid "" -"A: The timeframe might not be properly set. The setting is in the top " -"right corner (\"Last 30 minutes\" by default). Please change the " -"timeframe to reflect the period when the simulation was running." +"A: The timeframe might not be properly set. The setting is in the top right " +"corner (\"Last 30 minutes\" by default). Please change the timeframe to " +"reflect the period when the simulation was running." msgstr "" -"A: 기간이 제대로 설정되지 않았을 수 있습니다. 설정은 오른쪽 상단에 있습니다(" -"기본값은 '지난 30분'). 시뮬레이션이 실행된 기간을 반영하도록 기간을 변경해 " +"A: 기간이 제대로 설정되지 않았을 수 있습니다. 설정은 오른쪽 상단에 있습니다" +"(기본값은 '지난 30분'). 시뮬레이션이 실행된 기간을 반영하도록 기간을 변경해 " "주세요." #: ../../source/how-to-monitor-simulation.rst:218 msgid "" -"Q: I see “Grafana server not detected. Please make sure the Grafana " -"server is running and refresh this page” after going to the Metrics tab " -"in Ray Dashboard." +"Q: I see “Grafana server not detected. Please make sure the Grafana server " +"is running and refresh this page” after going to the Metrics tab in Ray " +"Dashboard." msgstr "" -"질문: \"Grafana 서버가 감지되지 않았습니다. Ray 대시보드의 메트릭 탭으로 " -"이동한 후 Grafana 서버가 실행 중인지 확인하고 이 페이지를 새로고침하세요." -"\"라는 메시지가 표시됩니다." +"질문: \"Grafana 서버가 감지되지 않았습니다. Ray 대시보드의 메트릭 탭으로 이동" +"한 후 Grafana 서버가 실행 중인지 확인하고 이 페이지를 새로고침하세요.\"라는 " +"메시지가 표시됩니다." #: ../../source/how-to-monitor-simulation.rst:220 msgid "" -"A: You probably don't have Grafana running. Please check the running " -"services" -msgstr "A: Grafana가 실행되고 있지 않을 수 있습니다. 실행 중인 서비스를 확인하세요" +"A: You probably don't have Grafana running. Please check the running services" +msgstr "" +"A: Grafana가 실행되고 있지 않을 수 있습니다. 실행 중인 서비스를 확인하세요" #: ../../source/how-to-monitor-simulation.rst:226 msgid "" @@ -5573,8 +5630,8 @@ msgstr "" #: ../../source/how-to-monitor-simulation.rst:228 msgid "" -"A: Either the simulation has already finished, or you still need to start" -" Prometheus." +"A: Either the simulation has already finished, or you still need to start " +"Prometheus." msgstr "A: 시뮬레이션이 이미 완료되었거나 아직 Prometheus를 시작해야 합니다." #: ../../source/how-to-monitor-simulation.rst:232 @@ -5599,14 +5656,13 @@ msgstr "Docker를 사용하여 Flower 실행" #: ../../source/how-to-run-flower-using-docker.rst:4 msgid "" -"The simplest way to get started with Flower is by using the pre-made " -"Docker images, which you can find on `Docker Hub " -"`__. Supported architectures include " -"``amd64`` and ``arm64v8``." +"The simplest way to get started with Flower is by using the pre-made Docker " +"images, which you can find on `Docker Hub `__. Supported architectures include ``amd64`` and ``arm64v8``." msgstr "" "Flower를 시작하는 가장 간단한 방법은 `Docker Hub `__에서 찾을 수 있는 미리 만들어진 Docker 이미지를 사용하는 것입니다. " -"지원되는 아키텍처는 ``amd64`` 및 ``arm64v8``입니다." +"flwr>`__에서 찾을 수 있는 미리 만들어진 Docker 이미지를 사용하는 것입니다. 지" +"원되는 아키텍처는 ``amd64`` 및 ``arm64v8``입니다." #: ../../source/how-to-run-flower-using-docker.rst:8 msgid "Before you start, make sure that the Docker daemon is running:" @@ -5614,10 +5670,9 @@ msgstr "시작하기 전에 Docker daemon이 실행 중인지 확인하세요:" #: ../../source/how-to-run-flower-using-docker.rst:15 msgid "" -"If you do not see the version of Docker but instead get an error saying " -"that the command was not found, you will need to install Docker first. " -"You can find installation instruction `here `_." +"If you do not see the version of Docker but instead get an error saying that " +"the command was not found, you will need to install Docker first. You can " +"find installation instruction `here `_." msgstr "" "전이 표시되지 않고 대신 명령을 찾을 수 없다는 오류가 표시되는 경우 먼저 " "Docker를 설치해야 합니다. `여기 `_에서 " @@ -5625,26 +5680,26 @@ msgstr "" #: ../../source/how-to-run-flower-using-docker.rst:21 msgid "" -"On Linux, Docker commands require ``sudo`` privilege. If you want to " -"avoid using ``sudo``, you can follow the `Post-installation steps " -"`_ on the " -"official Docker website." +"On Linux, Docker commands require ``sudo`` privilege. If you want to avoid " +"using ``sudo``, you can follow the `Post-installation steps `_ on the official Docker " +"website." msgstr "" -"Linux에서 Docker 명령을 실행하려면 ``sudo`` 권한이 필요합니다. sudo``를 " +"Linux에서 Docker 명령을 실행하려면 ``sudo`` 권한이 필요합니다. ``sudo`` 를 " "사용하지 않으려면 공식 Docker 웹사이트의 `Post-installation steps " "`_를 따르세요." #: ../../source/how-to-run-flower-using-docker.rst:27 msgid "" -"To ensure optimal performance and compatibility, the SuperLink, SuperNode" -" and ServerApp image must have the same version when running together. " -"This guarantees seamless integration and avoids potential conflicts or " -"issues that may arise from using different versions." +"To ensure optimal performance and compatibility, the SuperLink, SuperNode " +"and ServerApp image must have the same version when running together. This " +"guarantees seamless integration and avoids potential conflicts or issues " +"that may arise from using different versions." msgstr "" "최적의 성능과 호환성을 보장하려면 SuperLink, SuperNode 및 ServerApp 이미지를 " -"함께 실행할 때 버전이 동일해야 합니다. 이렇게 하면 원활한 통합을 보장하고 " -"서로 다른 버전을 사용할 때 발생할 수 있는 잠재적인 충돌이나 문제를 방지할 수 " -"있습니다." +"함께 실행할 때 버전이 동일해야 합니다. 이렇게 하면 원활한 통합을 보장하고 서" +"로 다른 버전을 사용할 때 발생할 수 있는 잠재적인 충돌이나 문제를 방지할 수 있" +"습니다." #: ../../source/how-to-run-flower-using-docker.rst:32 msgid "Flower SuperLink" @@ -5660,60 +5715,60 @@ msgstr "Flower를 사용해보고 싶다면 다음 명령을 사용하면 됩니 #: ../../source/how-to-run-flower-using-docker.rst:43 msgid "" -"The command pulls the Docker image with the tag ``1.8.0`` from Docker " -"Hub. The tag specifies the Flower version. In this case, Flower 1.8.0. " -"The ``--rm`` flag tells Docker to remove the container after it exits." +"The command pulls the Docker image with the tag ``1.8.0`` from Docker Hub. " +"The tag specifies the Flower version. In this case, Flower 1.8.0. The ``--" +"rm`` flag tells Docker to remove the container after it exits." msgstr "" "이 명령은 Docker Hub에서 ``1.8.0`` 태그가 있는 Docker 이미지를 가져옵니다. " -"이 태그는 Flower 버전을 지정합니다. 이 경우, Flower 1.8.0입니다. '`--rm`` " -"플래그는 컨테이너가 종료된 후 컨테이너를 제거하도록 Docker에 지시합니다." +"이 태그는 Flower 버전을 지정합니다. 이 경우, Flower 1.8.0입니다. '`--rm`` 플" +"래그는 컨테이너가 종료된 후 컨테이너를 제거하도록 Docker에 지시합니다." #: ../../source/how-to-run-flower-using-docker.rst:49 msgid "" "By default, the Flower SuperLink keeps state in-memory. When using the " -"Docker flag ``--rm``, the state is not persisted between container " -"starts. We will show below how to save the state in a file on your host " -"system." +"Docker flag ``--rm``, the state is not persisted between container starts. " +"We will show below how to save the state in a file on your host system." msgstr "" "기본적으로 Flower SuperLink는 상태를 in-memory에 유지합니다. Docker 플래그 " -"`--rm``을 사용하는 경우 컨테이너 시작 사이에 상태가 유지되지 않습니다. " -"아래에서 호스트 시스템의 파일에 상태를 저장하는 방법을 보여드리겠습니다." +"`--rm``을 사용하는 경우 컨테이너 시작 사이에 상태가 유지되지 않습니다. 아래에" +"서 호스트 시스템의 파일에 상태를 저장하는 방법을 보여드리겠습니다." #: ../../source/how-to-run-flower-using-docker.rst:53 msgid "" -"The ``-p :`` flag tells Docker to map the ports " -"``9091``/``9092`` of the host to ``9091``/``9092`` of the container, " -"allowing you to access the Driver API on ``http://localhost:9091`` and " -"the Fleet API on ``http://localhost:9092``. Lastly, any flag that comes " -"after the tag is passed to the Flower SuperLink. Here, we are passing the" -" flag ``--insecure``." +"The ``-p :`` flag tells Docker to map the ports ``9091``/" +"``9092`` of the host to ``9091``/``9092`` of the container, allowing you to " +"access the Driver API on ``http://localhost:9091`` and the Fleet API on " +"``http://localhost:9092``. Lastly, any flag that comes after the tag is " +"passed to the Flower SuperLink. Here, we are passing the flag ``--insecure``." msgstr "" -"``-p :`` 플래그는 호스트의 포트 ``9091``/``9092``를 " -"컨테이너의 ``9091``/``9092``에 매핑하여 ``http://localhost:9091``의 드라이버 " -"API와 ``http://localhost:9092``의 Fleet API에 액세스할 수 있도록 Docker에 " -"지시합니다. 마지막으로, 태그 뒤에 오는 모든 플래그는 Flower SuperLink에 " -"전달됩니다. 여기서는 ``--insecure``플래그를 전달합니다." +"``-p :`` 플래그는 호스트의 포트 ``9091``/``9092``를 컨테이너" +"의 ``9091``/``9092``에 매핑하여 ``http://localhost:9091``의 드라이버 API와 " +"``http://localhost:9092``의 Fleet API에 액세스할 수 있도록 Docker에 지시합니" +"다. 마지막으로, 태그 뒤에 오는 모든 플래그는 Flower SuperLink에 전달됩니다. " +"여기서는 ``--insecure``플래그를 전달합니다." #: ../../source/how-to-run-flower-using-docker.rst:60 #: ../../source/how-to-run-flower-using-docker.rst:259 #: ../../source/how-to-run-flower-using-docker.rst:376 msgid "" "The ``--insecure`` flag enables insecure communication (using HTTP, not " -"HTTPS) and should only be used for testing purposes. We strongly " -"recommend enabling `SSL `__ when " -"deploying to a production environment." +"HTTPS) and should only be used for testing purposes. We strongly recommend " +"enabling `SSL `__ when deploying to a " +"production environment." msgstr "" -"``--insecure`` 플래그는 안전하지 않은 통신(HTTPS가 아닌 HTTP 사용)을 " -"활성화하며 테스트 목적으로만 사용해야 합니다. 프로덕션 환경에 배포할 때는 `" -"SSL `__을 활성화할 것을 강력히 권장합니다." +"``--insecure`` 플래그는 안전하지 않은 통신(HTTPS가 아닌 HTTP 사용)을 활성화하" +"며 테스트 목적으로만 사용해야 합니다. 프로덕션 환경에 배포할 때는 `SSL " +"`__을 활성화할 것을 강력히 권장합니" +"다." #: ../../source/how-to-run-flower-using-docker.rst:65 msgid "" "You can use ``--help`` to view all available flags that the SuperLink " "supports:" -msgstr "'`--help``을 사용하면 SuperLink가 지원하는 모든 플래그를 볼 수 있습니다:" +msgstr "" +"'`--help``을 사용하면 SuperLink가 지원하는 모든 플래그를 볼 수 있습니다:" #: ../../source/how-to-run-flower-using-docker.rst:72 msgid "Mounting a volume to store the state on the host system" @@ -5721,49 +5776,47 @@ msgstr "호스트 시스템에 상태를 저장할 볼륨 마운트하기" #: ../../source/how-to-run-flower-using-docker.rst:74 msgid "" -"If you want to persist the state of the SuperLink on your host system, " -"all you need to do is specify a directory where you want to save the file" -" on your host system and a name for the database file. By default, the " -"SuperLink container runs with a non-root user called ``app`` with the " -"user ID ``49999``. It is recommended to create new directory and change " -"the user ID of the directory to ``49999`` to ensure the mounted directory" -" has the proper permissions. If you later want to delete the directory, " -"you can change the user ID back to the current user ID by running ``sudo " -"chown -R $USER:$(id -gn) state``." -msgstr "" -"호스트 시스템에서 SuperLink의 상태를 유지하려면 호스트 시스템에서 파일을 " -"저장할 디렉터리와 데이터베이스 파일의 이름을 지정하기만 하면 됩니다. " -"기본적으로 SuperLink 컨테이너는 사용자 ID가 ``49999``인 ``app``이라는 루트가 " -"아닌 사용자로 실행됩니다. 마운트된 디렉터리에 적절한 권한이 있는지 " -"확인하려면 새 디렉터리를 생성하고 디렉터리의 사용자 ID를 ``49999``로 " -"변경하는 것이 좋습니다. 나중에 디렉터리를 삭제하려면 ``sudo chown -R $USER:$(" -"id -gn) state``를 실행하여 사용자 ID를 현재 사용자 ID로 다시 변경할 수 " -"있습니다." +"If you want to persist the state of the SuperLink on your host system, all " +"you need to do is specify a directory where you want to save the file on " +"your host system and a name for the database file. By default, the SuperLink " +"container runs with a non-root user called ``app`` with the user ID " +"``49999``. It is recommended to create new directory and change the user ID " +"of the directory to ``49999`` to ensure the mounted directory has the proper " +"permissions. If you later want to delete the directory, you can change the " +"user ID back to the current user ID by running ``sudo chown -R $USER:$(id -" +"gn) state``." +msgstr "" +"호스트 시스템에서 SuperLink의 상태를 유지하려면 호스트 시스템에서 파일을 저장" +"할 디렉터리와 데이터베이스 파일의 이름을 지정하기만 하면 됩니다. 기본적으로 " +"SuperLink 컨테이너는 사용자 ID가 ``49999``인 ``app``이라는 루트가 아닌 사용자" +"로 실행됩니다. 마운트된 디렉터리에 적절한 권한이 있는지 확인하려면 새 디렉터" +"리를 생성하고 디렉터리의 사용자 ID를 ``49999``로 변경하는 것이 좋습니다. 나중" +"에 디렉터리를 삭제하려면 ``sudo chown -R $USER:$(id -gn) state``를 실행하여 " +"사용자 ID를 현재 사용자 ID로 다시 변경할 수 있습니다." #: ../../source/how-to-run-flower-using-docker.rst:82 msgid "" -"In the example below, we create a new directory, change the user ID and " -"tell Docker via the flag ``--volume`` to mount the local ``state`` " -"directory into the ``/app/state`` directory of the container. " -"Furthermore, we use the flag ``--database`` to specify the name of the " -"database file." +"In the example below, we create a new directory, change the user ID and tell " +"Docker via the flag ``--volume`` to mount the local ``state`` directory into " +"the ``/app/state`` directory of the container. Furthermore, we use the flag " +"``--database`` to specify the name of the database file." msgstr "" -"아래 예에서는 새 디렉터리를 생성하고, 사용자 ID를 변경하고, 플래그 " -"``--volume``을 통해 Docker에게 로컬 ``state`` 디렉터리를 컨테이너의 ``/app/" -"state`` 디렉터리에 마운트하도록 지시합니다. 또한 ``--database`` 플래그를 " -"사용하여 데이터베이스 파일의 이름을 지정합니다." +"아래 예에서는 새 디렉터리를 생성하고, 사용자 ID를 변경하고, 플래그 ``--" +"volume``을 통해 Docker에게 로컬 ``state`` 디렉터리를 컨테이너의 ``/app/" +"state`` 디렉터리에 마운트하도록 지시합니다. 또한 ``--database`` 플래그를 사용" +"하여 데이터베이스 파일의 이름을 지정합니다." #: ../../source/how-to-run-flower-using-docker.rst:95 msgid "" "As soon as the SuperLink starts, the file ``state.db`` is created in the " "``state`` directory on your host system. If the file already exists, the " -"SuperLink tries to restore the state from the file. To start the " -"SuperLink with an empty database, simply remove the ``state.db`` file." +"SuperLink tries to restore the state from the file. To start the SuperLink " +"with an empty database, simply remove the ``state.db`` file." msgstr "" -"SuperLink가 시작되자마자 호스트 시스템의 ``state`` 디렉터리에 ``state.db`` " -"파일이 생성됩니다. 파일이 이미 존재하는 경우 SuperLink는 파일에서 상태를 " -"복원하려고 시도합니다. 빈 데이터베이스로 SuperLink를 시작하려면 ``state.db`` " -"파일을 제거하면 됩니다." +"SuperLink가 시작되자마자 호스트 시스템의 ``state`` 디렉터리에 ``state.db`` 파" +"일이 생성됩니다. 파일이 이미 존재하는 경우 SuperLink는 파일에서 상태를 복원하" +"려고 시도합니다. 빈 데이터베이스로 SuperLink를 시작하려면 ``state.db`` 파일" +"을 제거하면 됩니다." #: ../../source/how-to-run-flower-using-docker.rst:100 #: ../../source/how-to-run-flower-using-docker.rst:281 @@ -5773,18 +5826,18 @@ msgstr "보안 연결을 위한 SSL 사용 설정" #: ../../source/how-to-run-flower-using-docker.rst:102 msgid "" -"To enable SSL, you will need a PEM-encoded root certificate, a PEM-" -"encoded private key and a PEM-encoded certificate chain." +"To enable SSL, you will need a PEM-encoded root certificate, a PEM-encoded " +"private key and a PEM-encoded certificate chain." msgstr "" "SSL을 사용하려면 PEM으로 인코딩된 루트 인증서, PEM으로 인코딩된 개인 키 및 " "PEM으로 인코딩된 인증서 체인이 필요합니다." #: ../../source/how-to-run-flower-using-docker.rst:106 msgid "" -"For testing purposes, you can generate your own self-signed certificates." -" The `Enable SSL connections `__ page contains a section that" -" will guide you through the process." +"For testing purposes, you can generate your own self-signed certificates. " +"The `Enable SSL connections `__ page contains a section that will " +"guide you through the process." msgstr "" "테스트 목적으로 자체 서명된 인증서를 생성할 수 있습니다. 'SSL 연결 사용 " "`__ is already installed " -"in the ``flwr/supernode`` base image, so you only need to include other " -"package dependencies in your ``requirements.txt``, such as ``torch``, " +"Note that `flwr `__ is already installed in " +"the ``flwr/supernode`` base image, so you only need to include other package " +"dependencies in your ``requirements.txt``, such as ``torch``, " "``tensorflow``, etc." msgstr "" -"`flwr `__ 는 이미 ``flwr/supernode`` 기본 " -"이미지에 설치되어 있으므로, ``torch``, ``tensorflow`` 등과 같은 다른 패키지 " +"`flwr `__ 는 이미 ``flwr/supernode`` 기본 이" +"미지에 설치되어 있으므로, ``torch``, ``tensorflow`` 등과 같은 다른 패키지 " "dependencies만 ``requirements.txt``에 포함시키면 됩니다." #: ../../source/how-to-run-flower-using-docker.rst:200 msgid "" -"Next, we create a Dockerfile. If you use the ``quickstart-pytorch`` " -"example, create a new file called ``Dockerfile.supernode`` in ``examples" -"/quickstart-pytorch``." +"Next, we create a Dockerfile. If you use the ``quickstart-pytorch`` example, " +"create a new file called ``Dockerfile.supernode`` in ``examples/quickstart-" +"pytorch``." msgstr "" -"다음으로, Dockerfile을 생성합니다.``quickstart-pytorch`` 예제를 사용하는 " -"경우 ``examples/quickstart-pytorch``에 ``Dockerfile.supernode``라는 새 " -"파일을 생성합니다." +"다음으로, Dockerfile을 생성합니다.``quickstart-pytorch`` 예제를 사용하는 경" +"우 ``examples/quickstart-pytorch``에 ``Dockerfile.supernode``라는 새 파일을 " +"생성합니다." #: ../../source/how-to-run-flower-using-docker.rst:203 msgid "" "The ``Dockerfile.supernode`` contains the instructions that assemble the " "SuperNode image." -msgstr "``Dockerfile.supernode``에는 SuperNode 이미지를 조립하는 지침이 포함되어 " -"있습니다." +msgstr "" +"``Dockerfile.supernode``에는 SuperNode 이미지를 조립하는 지침이 포함되어 있습" +"니다." #: ../../source/how-to-run-flower-using-docker.rst:217 msgid "" -"In the first two lines, we instruct Docker to use the SuperNode image " -"tagged ``nightly`` as a base image and set our working directory to " -"``/app``. The following instructions will now be executed in the ``/app``" -" directory. Next, we install the ClientApp dependencies by copying the " -"``requirements.txt`` file into the image and run ``pip install``. In the " -"last two lines, we copy the ``client.py`` module into the image and set " -"the entry point to ``flower-client-app`` with the argument " -"``client:app``. The argument is the object reference of the ClientApp " -"(``:``) that will be run inside the ClientApp." -msgstr "" -"처음 두 줄에서는 ``nightly`` 태그가 붙은 SuperNode 이미지를 기본 이미지로 " -"사용하고 작업 디렉터리를 ``/app``로 설정하도록 Docker에 지시합니다. 이제 " -"``/app`` 디렉토리에서 다음 명령이 실행됩니다. 다음으로, ``requirements.txt`` " -"파일을 이미지에 복사하여 ClientApp dependencies 요소를 설치하고 ``pip " -"install``을 실행합니다. 마지막 두 줄에서 ``client.py`` 모듈을 이미지에 " -"복사하고 ``client:app`` 인수를 사용하여 진입점을 ``flower-client-app``로 " -"설정합니다. 인수는 클라이언트앱 내부에서 실행될 클라이언트앱의 객체 참조 " -"(``:``) 입니다." +"In the first two lines, we instruct Docker to use the SuperNode image tagged " +"``nightly`` as a base image and set our working directory to ``/app``. The " +"following instructions will now be executed in the ``/app`` directory. Next, " +"we install the ClientApp dependencies by copying the ``requirements.txt`` " +"file into the image and run ``pip install``. In the last two lines, we copy " +"the ``client.py`` module into the image and set the entry point to ``flower-" +"client-app`` with the argument ``client:app``. The argument is the object " +"reference of the ClientApp (``:``) that will be run " +"inside the ClientApp." +msgstr "" +"처음 두 줄에서는 ``nightly`` 태그가 붙은 SuperNode 이미지를 기본 이미지로 사" +"용하고 작업 디렉터리를 ``/app``로 설정하도록 Docker에 지시합니다. 이제 ``/" +"app`` 디렉토리에서 다음 명령이 실행됩니다. 다음으로, ``requirements.txt`` 파" +"일을 이미지에 복사하여 ClientApp dependencies 요소를 설치하고 ``pip install``" +"을 실행합니다. 마지막 두 줄에서 ``client.py`` 모듈을 이미지에 복사하고 " +"``client:app`` 인수를 사용하여 진입점을 ``flower-client-app``로 설정합니다. " +"인수는 클라이언트앱 내부에서 실행될 클라이언트앱의 객체 참조 (``:" +"``) 입니다." #: ../../source/how-to-run-flower-using-docker.rst:226 msgid "Building the SuperNode Docker image" @@ -5946,11 +5999,11 @@ msgstr "SuperNode Docker 이미지 빌드" #: ../../source/how-to-run-flower-using-docker.rst:228 msgid "" -"Next, we build the SuperNode Docker image by running the following " -"command in the directory where Dockerfile and ClientApp code are located." +"Next, we build the SuperNode Docker image by running the following command " +"in the directory where Dockerfile and ClientApp code are located." msgstr "" -"다음으로, Dockerfile 및 ClientApp 코드가 있는 디렉터리에서 다음 명령을 " -"실행하여 SuperNode Docker 이미지를 빌드합니다." +"다음으로, Dockerfile 및 ClientApp 코드가 있는 디렉터리에서 다음 명령을 실행하" +"여 SuperNode Docker 이미지를 빌드합니다." #: ../../source/how-to-run-flower-using-docker.rst:235 msgid "" @@ -5958,9 +6011,9 @@ msgid "" "Remember that the here chosen values only serve as an example. You can " "change them to your needs." msgstr "" -"이미지에 ``flwr_supernode``라는 이름을 붙이고 ``0.0.1`` 태그를 붙였습니다. " -"여기서 선택한 값은 예시일 뿐이라는 점을 기억하세요. 필요에 따라 변경할 수 " -"있습니다." +"이미지에 ``flwr_supernode``라는 이름을 붙이고 ``0.0.1`` 태그를 붙였습니다. 여" +"기서 선택한 값은 예시일 뿐이라는 점을 기억하세요. 필요에 따라 변경할 수 있습" +"니다." #: ../../source/how-to-run-flower-using-docker.rst:240 msgid "Running the SuperNode Docker image" @@ -5983,9 +6036,10 @@ msgstr "``docker run``: 새 Docker 컨테이너를 실행하는 명령입니다. #: ../../source/how-to-run-flower-using-docker.rst:253 #: ../../source/how-to-run-flower-using-docker.rst:370 msgid "" -"``--rm``: This option specifies that the container should be " -"automatically removed when it stops." -msgstr "``--rm``: 이 옵션은 컨테이너가 중지될 때 자동으로 제거되도록 지정합니다." +"``--rm``: This option specifies that the container should be automatically " +"removed when it stops." +msgstr "" +"``--rm``: 이 옵션은 컨테이너가 중지될 때 자동으로 제거되도록 지정합니다." #: ../../source/how-to-run-flower-using-docker.rst:254 msgid "``flwr_supernode:0.0.1``: The name the tag of the Docker image to use." @@ -5998,26 +6052,28 @@ msgstr "``--insecure``: 이 옵션은 보안되지 않은 통신을 활성화합 #: ../../source/how-to-run-flower-using-docker.rst msgid "" -"``--superlink 192.168.1.100:9092``: This option specifies the address of " -"the SuperLinks Fleet" -msgstr "``--superlink 192.168.1.100:9092``: 이 옵션은 SuperLinks Fleet의 주소를 " -"지정합니다" +"``--superlink 192.168.1.100:9092``: This option specifies the address of the " +"SuperLinks Fleet" +msgstr "" +"``--superlink 192.168.1.100:9092``: 이 옵션은 SuperLinks Fleet의 주소를 지정" +"합니다" #: ../../source/how-to-run-flower-using-docker.rst msgid "API to connect to. Remember to update it with your SuperLink IP." -msgstr "API에 연결할 수 있습니다. SuperLink IP로 업데이트하는 것을 잊지 마세요." +msgstr "" +"API에 연결할 수 있습니다. SuperLink IP로 업데이트하는 것을 잊지 마세요." #: ../../source/how-to-run-flower-using-docker.rst:269 msgid "" -"To test running Flower locally, you can create a `bridge network " -"`__, use the ``--network`` argument and pass the " -"name of the Docker network to run your SuperNodes." +"To test running Flower locally, you can create a `bridge network `__, use the ``--network`` argument and pass the name of the Docker " +"network to run your SuperNodes." msgstr "" "로컬에서 Flower를 실행하는 것을 테스트하려면 `bridge network `__를 생성하고 ``--network`` argument를 사용하고 SuperNodes를 " -"실행할 Docker 네트워크의 이름을 전달하면 됩니다." +"networks>`__를 생성하고 ``--network`` argument를 사용하고 SuperNodes를 실행" +"할 Docker 네트워크의 이름을 전달하면 됩니다." #: ../../source/how-to-run-flower-using-docker.rst:273 msgid "" @@ -6031,21 +6087,21 @@ msgstr "" msgid "" "To enable SSL, we will need to mount a PEM-encoded root certificate into " "your SuperNode container." -msgstr "SSL을 사용하려면 PEM 인코딩된 루트 인증서를 SuperNode 컨테이너에 마운트해야 " +msgstr "" +"SSL을 사용하려면 PEM 인코딩된 루트 인증서를 SuperNode 컨테이너에 마운트해야 " "합니다." #: ../../source/how-to-run-flower-using-docker.rst:285 msgid "" -"Assuming the certificate already exists locally, we can use the flag " -"``--volume`` to mount the local certificate into the container's " -"``/app/`` directory. This allows the SuperNode to access the certificate " -"within the container. Use the ``--root-certificates`` flag when starting " -"the container." +"Assuming the certificate already exists locally, we can use the flag ``--" +"volume`` to mount the local certificate into the container's ``/app/`` " +"directory. This allows the SuperNode to access the certificate within the " +"container. Use the ``--root-certificates`` flag when starting the container." msgstr "" -"인증서가 이미 로컬에 존재한다고 가정하면, ``--volume`` 플래그를 사용하여 " -"로컬 인증서를 컨테이너의 ``/app/`` 디렉터리에 마운트할 수 있습니다. 이렇게 " -"하면 SuperNode가 컨테이너 내의 인증서에 액세스할 수 있습니다. 컨테이너를 " -"시작할 때 ``--root-certificates`` 플래그를 사용하세요." +"인증서가 이미 로컬에 존재한다고 가정하면, ``--volume`` 플래그를 사용하여 로" +"컬 인증서를 컨테이너의 ``/app/`` 디렉터리에 마운트할 수 있습니다. 이렇게 하" +"면 SuperNode가 컨테이너 내의 인증서에 액세스할 수 있습니다. 컨테이너를 시작" +"할 때 ``--root-certificates`` 플래그를 사용하세요." #: ../../source/how-to-run-flower-using-docker.rst:297 msgid "Flower ServerApp" @@ -6053,29 +6109,30 @@ msgstr "Flower 서버앱" #: ../../source/how-to-run-flower-using-docker.rst:299 msgid "" -"The procedure for building and running a ServerApp image is almost " -"identical to the SuperNode image." -msgstr "ServerApp 이미지를 빌드하고 실행하는 절차는 SuperNode 이미지와 거의 " -"동일합니다." +"The procedure for building and running a ServerApp image is almost identical " +"to the SuperNode image." +msgstr "" +"ServerApp 이미지를 빌드하고 실행하는 절차는 SuperNode 이미지와 거의 동일합니" +"다." #: ../../source/how-to-run-flower-using-docker.rst:301 msgid "" -"Similar to the SuperNode image, the ServerApp Docker image comes with a " -"pre-installed version of Flower and serves as a base for building your " -"own ServerApp image." +"Similar to the SuperNode image, the ServerApp Docker image comes with a pre-" +"installed version of Flower and serves as a base for building your own " +"ServerApp image." msgstr "" "SuperNode 이미지와 마찬가지로 ServerApp Docker 이미지는 Flower의 사전 설치된 " -"버전과 함께 제공되며, 자체 ServerApp 이미지를 구축하기 위한 기본 역할을 " -"합니다." +"버전과 함께 제공되며, 자체 ServerApp 이미지를 구축하기 위한 기본 역할을 합니" +"다." #: ../../source/how-to-run-flower-using-docker.rst:304 msgid "" -"We will use the same ``quickstart-pytorch`` example as we do in the " -"Flower SuperNode section. If you have not already done so, please follow " -"the `SuperNode Prerequisites`_ before proceeding." +"We will use the same ``quickstart-pytorch`` example as we do in the Flower " +"SuperNode section. If you have not already done so, please follow the " +"`SuperNode Prerequisites`_ before proceeding." msgstr "" -"여기서는 Flower SuperNode 섹션에서와 동일한`quickstart-pytorch`` 예제를 " -"사용하겠습니다. 아직 수행하지 않았다면 계속 진행하기 전에 `SuperNode " +"여기서는 Flower SuperNode 섹션에서와 동일한`quickstart-pytorch`` 예제를 사용" +"하겠습니다. 아직 수행하지 않았다면 계속 진행하기 전에 `SuperNode " "Prerequisites`_ 을 따르세요." #: ../../source/how-to-run-flower-using-docker.rst:309 @@ -6086,8 +6143,8 @@ msgstr "ServerApp Dockerfile 만들기" msgid "" "First, we need to create a Dockerfile in the directory where the " "``ServerApp`` code is located. If you use the ``quickstart-pytorch`` " -"example, create a new file called ``Dockerfile.serverapp`` in ``examples" -"/quickstart-pytorch``." +"example, create a new file called ``Dockerfile.serverapp`` in ``examples/" +"quickstart-pytorch``." msgstr "" "먼저, ``ServerApp`` 코드가 있는 디렉토리에 Docker파일을 생성해야 합니다. " "``quickstart-pytorch`` 예제를 사용하는 경우 ``examples/quickstart-pytorch``" @@ -6097,24 +6154,24 @@ msgstr "" msgid "" "The ``Dockerfile.serverapp`` contains the instructions that assemble the " "ServerApp image." -msgstr "``Dockerfile.serverapp``에는 ServerApp 이미지를 합치는 지침이 포함되어 " -"있습니다." +msgstr "" +"``Dockerfile.serverapp``에는 ServerApp 이미지를 합치는 지침이 포함되어 있습니" +"다." #: ../../source/how-to-run-flower-using-docker.rst:335 msgid "" -"In the first two lines, we instruct Docker to use the ServerApp image " -"tagged ``1.8.0`` as a base image and set our working directory to " -"``/app``. The following instructions will now be executed in the ``/app``" -" directory. In the last two lines, we copy the ``server.py`` module into " -"the image and set the entry point to ``flower-server-app`` with the " -"argument ``server:app``. The argument is the object reference of the " -"ServerApp (``:``) that will be run inside the " -"ServerApp container." -msgstr "" -"처음 두 줄에서는 ``1.8.0`` 태그가 붙은 ServerApp 이미지를 기본 이미지로 " -"사용하고 작업 디렉터리를 ``/app``로 설정하도록 Docker에 지시합니다. 이제 " -"``/app`` 디렉토리에서 다음 명령이 실행됩니다. 마지막 두 줄에서는 ``server." -"py`` 모듈을 이미지에 복사하고 ``server:app`` argument를 사용하여 진입점을 " +"In the first two lines, we instruct Docker to use the ServerApp image tagged " +"``1.8.0`` as a base image and set our working directory to ``/app``. The " +"following instructions will now be executed in the ``/app`` directory. In " +"the last two lines, we copy the ``server.py`` module into the image and set " +"the entry point to ``flower-server-app`` with the argument ``server:app``. " +"The argument is the object reference of the ServerApp (``:" +"``) that will be run inside the ServerApp container." +msgstr "" +"처음 두 줄에서는 ``1.8.0`` 태그가 붙은 ServerApp 이미지를 기본 이미지로 사용" +"하고 작업 디렉터리를 ``/app``로 설정하도록 Docker에 지시합니다. 이제 ``/" +"app`` 디렉토리에서 다음 명령이 실행됩니다. 마지막 두 줄에서는 ``server.py`` " +"모듈을 이미지에 복사하고 ``server:app`` argument를 사용하여 진입점을 " "``flower-server-app``로 설정합니다. 인수는 ServerApp 컨테이너 내에서 실행될 " "ServerApp의 객체 참조(``:``)입니다." @@ -6124,11 +6181,11 @@ msgstr "ServerApp Docker 이미지 빌드" #: ../../source/how-to-run-flower-using-docker.rst:345 msgid "" -"Next, we build the ServerApp Docker image by running the following " -"command in the directory where Dockerfile and ServerApp code are located." +"Next, we build the ServerApp Docker image by running the following command " +"in the directory where Dockerfile and ServerApp code are located." msgstr "" -"다음으로, Docker파일과 ServerApp 코드가 있는 디렉터리에서 다음 명령을 " -"실행하여 ServerApp Docker 이미지를 빌드합니다." +"다음으로, Docker파일과 ServerApp 코드가 있는 디렉터리에서 다음 명령을 실행하" +"여 ServerApp Docker 이미지를 빌드합니다." #: ../../source/how-to-run-flower-using-docker.rst:352 msgid "" @@ -6136,453 +6193,600 @@ msgid "" "Remember that the here chosen values only serve as an example. You can " "change them to your needs." msgstr "" +"이미지에``flwr_serverapp``이라는 이름을 붙이고 ``0.0.1``이라는 태그를 붙였습" +"니다. 여기서 선택한 값은 예시일 뿐이라는 점을 기억하세요. 필요에 따라 변경할 " +"수 있습니다." #: ../../source/how-to-run-flower-using-docker.rst:357 msgid "Running the ServerApp Docker image" -msgstr "" +msgstr "ServerApp Docker 이미지 실행" #: ../../source/how-to-run-flower-using-docker.rst:359 msgid "Now that we have built the ServerApp image, we can finally run it." -msgstr "" +msgstr "이제 ServerApp 이미지를 빌드했으니 이제 실행할 수 있습니다." #: ../../source/how-to-run-flower-using-docker.rst:371 msgid "``flwr_serverapp:0.0.1``: The name the tag of the Docker image to use." -msgstr "" +msgstr "``flwr_serverapp:0.0.1``: 사용할 Docker 이미지의 태그 이름입니다." #: ../../source/how-to-run-flower-using-docker.rst msgid "" -"``--superlink 192.168.1.100:9091``: This option specifies the address of " -"the SuperLinks Driver" +"``--superlink 192.168.1.100:9091``: This option specifies the address of the " +"SuperLinks Driver" msgstr "" +"``--superlink 192.168.1.100:9091``: 이 옵션은 SuperLinks 드라이버의 주소를 지" +"정합니다" #: ../../source/how-to-run-flower-using-docker.rst:385 msgid "" -"To test running Flower locally, you can create a `bridge network " -"`__, use the ``--network`` argument and pass the " -"name of the Docker network to run your ServerApps." +"To test running Flower locally, you can create a `bridge network `__, use the ``--network`` argument and pass the name of the Docker " +"network to run your ServerApps." msgstr "" +"로컬에서 Flower를 실행하는 것을 테스트하려면 `bridge network `__,를 생성하고 ``--network`` argument를 사용하여 ServerApp을 실행" +"할 Docker 네트워크의 이름을 전달하면 됩니다." #: ../../source/how-to-run-flower-using-docker.rst:389 msgid "" "Any argument that comes after the tag is passed to the Flower ServerApp " "binary. To see all available flags that the ServerApp supports, run:" msgstr "" +"태그 뒤에 오는 모든 argument는 Flower ServerApp 바이너리에 전달됩니다. " +"ServerApp에서 지원하는 사용 가능한 모든 플래그를 보려면 실행하세요:" #: ../../source/how-to-run-flower-using-docker.rst:399 msgid "" "To enable SSL, we will need to mount a PEM-encoded root certificate into " "your ServerApp container." msgstr "" +"SSL을 사용하려면 PEM 인코딩된 루트 인증서를 ServerApp 컨테이너에 마운트해야 " +"합니다." #: ../../source/how-to-run-flower-using-docker.rst:401 msgid "" -"Assuming the certificate already exists locally, we can use the flag " -"``--volume`` to mount the local certificate into the container's " -"``/app/`` directory. This allows the ServerApp to access the certificate " -"within the container. Use the ``--root-certificates`` flags when starting" -" the container." +"Assuming the certificate already exists locally, we can use the flag ``--" +"volume`` to mount the local certificate into the container's ``/app/`` " +"directory. This allows the ServerApp to access the certificate within the " +"container. Use the ``--root-certificates`` flags when starting the container." msgstr "" +"인증서가 이미 로컬에 존재한다고 가정하면, ``--volume`` 플래그를 사용하여 로" +"컬 인증서를 컨테이너의 ``/app/`` 디렉터리에 마운트할 수 있습니다. 이렇게 하" +"면 ServerApp이 컨테이너 내의 인증서에 액세스할 수 있습니다. 컨테이너를 시작" +"할 때 ``--root-certificates`` 플래그를 사용하세요." #: ../../source/how-to-run-flower-using-docker.rst:412 msgid "Advanced Docker options" -msgstr "" +msgstr "고급 Docker 옵션" #: ../../source/how-to-run-flower-using-docker.rst:415 msgid "Run with root user privileges" -msgstr "" +msgstr "루트 사용자 권한으로 실행" #: ../../source/how-to-run-flower-using-docker.rst:417 msgid "" -"Flower Docker images, by default, run with a non-root user " -"(username/groupname: ``app``, UID/GID: ``49999``). Using root user is not" -" recommended unless it is necessary for specific tasks during the build " -"process. Always make sure to run the container as a non-root user in " -"production to maintain security best practices." +"Flower Docker images, by default, run with a non-root user (username/" +"groupname: ``app``, UID/GID: ``49999``). Using root user is not recommended " +"unless it is necessary for specific tasks during the build process. Always " +"make sure to run the container as a non-root user in production to maintain " +"security best practices." msgstr "" +"기본적으로 Flower Docker 이미지는 루트 사용자가 아닌 사용자(사용자명/그룹명:" +"``app``, UID/GID: ``49999``)로 실행됩니다. 빌드 프로세스 중 특정 작업에 필요" +"한 경우가 아니라면 루트 사용자를 사용하지 않는 것이 좋습니다. 보안 모범 사례" +"를 유지하려면 항상 프로덕션 환경에서 루트 사용자가 아닌 사용자로 컨테이너를 " +"실행해야 합니다." #: ../../source/how-to-run-flower-using-docker.rst:422 msgid "**Run a container with root user privileges**" -msgstr "" +msgstr "**루트 사용자 권한으로 컨테이너 실행하기**" #: ../../source/how-to-run-flower-using-docker.rst:424 msgid "" "Run the Docker image with the ``-u`` flag and specify ``root`` as the " "username:" msgstr "" +"``-u`` 플래그를 사용하여 Docker 이미지를 실행하고 사용자 이름으로 ``root``를 " +"지정합니다:" #: ../../source/how-to-run-flower-using-docker.rst:430 msgid "This command will run the Docker container with root user privileges." -msgstr "" +msgstr "이 명령은 루트 사용자 권한으로 Docker 컨테이너를 실행합니다." #: ../../source/how-to-run-flower-using-docker.rst:432 msgid "**Run the build process with root user privileges**" -msgstr "" +msgstr "**루트 사용자 권한으로 빌드 프로세스를 실행합니다**" #: ../../source/how-to-run-flower-using-docker.rst:434 msgid "" "If you want to switch to the root user during the build process of the " -"Docker image to install missing system dependencies, you can use the " -"``USER root`` directive within your Dockerfile." +"Docker image to install missing system dependencies, you can use the ``USER " +"root`` directive within your Dockerfile." msgstr "" +"Docker 이미지 빌드 과정에서 루트 사용자로 전환하여 누락된 시스템 의존성을 " +"설치하려면 Dockerfile 내에서 ``USER root`` 지시어를 사용할 수 있습니다." #: ../../source/how-to-run-flower-using-docker.rst:454 msgid "Using a different Flower version" -msgstr "" +msgstr "다른 Flower 버전 사용" #: ../../source/how-to-run-flower-using-docker.rst:456 msgid "" "If you want to use a different version of Flower, for example Flower " -"nightly, you can do so by changing the tag. All available versions are on" -" `Docker Hub `__." +"nightly, you can do so by changing the tag. All available versions are on " +"`Docker Hub `__." msgstr "" +"다른 버전의 Flower를 사용하려면 태그를 변경하여 사용할 수 있습니다(예: " +"Flower nightly). 사용 가능한 모든 버전은 `Docker Hub `__에 있습니다." #: ../../source/how-to-run-flower-using-docker.rst:460 msgid "Pinning a Docker image to a specific version" -msgstr "" +msgstr "특정 버전에 Docker 이미지 고정하기" #: ../../source/how-to-run-flower-using-docker.rst:462 msgid "" "It may happen that we update the images behind the tags. Such updates " "usually include security updates of system dependencies that should not " -"change the functionality of Flower. However, if you want to ensure that " -"you always use the same image, you can specify the hash of the image " -"instead of the tag." +"change the functionality of Flower. However, if you want to ensure that you " +"always use the same image, you can specify the hash of the image instead of " +"the tag." msgstr "" +"태그 뒤에 있는 이미지가 업데이트될 수 있습니다. 이러한 업데이트에는 " +"일반적으로 Flower의 기능을 변경해서는 안 되는 시스템 의존성에 대한 보안 " +"업데이트가 포함됩니다. 그러나 항상 동일한 이미지를 사용하려면 태그 대신 " +"이미지의 해시를 지정할 수 있습니다." #: ../../source/how-to-run-flower-using-docker.rst:467 msgid "" "The following command returns the current image hash referenced by the " "``superlink:1.8.0`` tag:" msgstr "" +"다음 명령은 ``superlink:1.8.0`` 태그가 참조하는 현재 이미지 해시를 반환합니" +"다:" #: ../../source/how-to-run-flower-using-docker.rst:474 msgid "Next, we can pin the hash when running a new SuperLink container:" -msgstr "" +msgstr "다음으로, 새 SuperLink 컨테이너를 실행할 때 해시를 고정할 수 있습니다:" #: ../../source/how-to-run-flower-using-docker.rst:483 msgid "Setting environment variables" -msgstr "" +msgstr "환경 변수 설정" #: ../../source/how-to-run-flower-using-docker.rst:485 msgid "" "To set a variable inside a Docker container, you can use the ``-e " "=`` flag." msgstr "" +"Docker 컨테이너 내에서 변수를 설정하려면 ``-e =`` 플래그를 사용" +"하면 됩니다." #: ../../source/how-to-run-simulations.rst:2 msgid "Run simulations" -msgstr "" +msgstr "시뮬레이션 실행" #: ../../source/how-to-run-simulations.rst:8 msgid "" "Simulating Federated Learning workloads is useful for a multitude of use-" -"cases: you might want to run your workload on a large cohort of clients " -"but without having to source, configure and mange a large number of " -"physical devices; you might want to run your FL workloads as fast as " -"possible on the compute systems you have access to without having to go " -"through a complex setup process; you might want to validate your " -"algorithm on different scenarios at varying levels of data and system " -"heterogeneity, client availability, privacy budgets, etc. These are among" -" some of the use-cases where simulating FL workloads makes sense. Flower " -"can accommodate these scenarios by means of its `VirtualClientEngine " -"`_ or " -"VCE." -msgstr "" +"cases: you might want to run your workload on a large cohort of clients but " +"without having to source, configure and mange a large number of physical " +"devices; you might want to run your FL workloads as fast as possible on the " +"compute systems you have access to without having to go through a complex " +"setup process; you might want to validate your algorithm on different " +"scenarios at varying levels of data and system heterogeneity, client " +"availability, privacy budgets, etc. These are among some of the use-cases " +"where simulating FL workloads makes sense. Flower can accommodate these " +"scenarios by means of its `VirtualClientEngine `_ or VCE." +msgstr "" +"Federated 학습 워크로드 시뮬레이션은 다양한 사용 사례에 유용합니다. 대규모 클" +"라이언트 집단에서 워크로드를 실행하되 많은 수의 물리적 장치를 소싱, 구성 및 " +"관리할 필요가 없는 경우, 복잡한 설정 과정을 거치지 않고도 액세스 가능한 컴퓨" +"팅 시스템에서 최대한 빠르게 FL 워크로드를 실행하려는 경우, 다양한 수준의 데이" +"터 및 시스템 이질성, 클라이언트 가용성, 개인정보 예산 등의 다양한 시나리오에" +"서 알고리즘을 검증하려는 경우 등 여러 가지 사용 사례에 유용합니다. 이러한 사" +"례는 FL 워크로드 시뮬레이션이 적합한 사용 사례 중 일부입니다. Flower는 " +"`VirtualClientEngine `_ 또는 VCE를 통해 이러한 시나리오를 수용할 수 있습니다." #: ../../source/how-to-run-simulations.rst:10 msgid "" -"The :code:`VirtualClientEngine` schedules, launches and manages `virtual`" -" clients. These clients are identical to `non-virtual` clients (i.e. the " -"ones you launch via the command `flwr.client.start_client `_) in the sense that they can be configure by " -"creating a class inheriting, for example, from `flwr.client.NumPyClient " -"`_ and therefore behave in an " -"identical way. In addition to that, clients managed by the " -":code:`VirtualClientEngine` are:" -msgstr "" +"The :code:`VirtualClientEngine` schedules, launches and manages `virtual` " +"clients. These clients are identical to `non-virtual` clients (i.e. the ones " +"you launch via the command `flwr.client.start_client `_) in the sense that they can be configure by creating a " +"class inheriting, for example, from `flwr.client.NumPyClient `_ and therefore behave in an identical way. In " +"addition to that, clients managed by the :code:`VirtualClientEngine` are:" +msgstr "" +":code:`VirtualClientEngine`은 `virtual` 클라이언트를 예약, 실행 및 관리합니" +"다. 이러한 클라이언트는 `non-virtual` 클라이언트(예: `flwr.client." +"start_client `_ 명령을 통해 실행하는 클라이언" +"트)와 동일하며, `flwr.client.NumPyClient `_에서 상속하는 클래스 생성으로 구성될 수 있으므로 동일한 방식으" +"로 동작합니다. 그 외에도 :code:`VirtualClientEngine`에 의해 관리되는 클라이언" +"트는 다음과 같습니다:" #: ../../source/how-to-run-simulations.rst:12 msgid "" -"resource-aware: this means that each client gets assigned a portion of " -"the compute and memory on your system. You as a user can control this at " -"the beginning of the simulation and allows you to control the degree of " +"resource-aware: this means that each client gets assigned a portion of the " +"compute and memory on your system. You as a user can control this at the " +"beginning of the simulation and allows you to control the degree of " "parallelism of your Flower FL simulation. The fewer the resources per " "client, the more clients can run concurrently on the same hardware." msgstr "" +"resource-aware: 이는 각 클라이언트가 시스템에서 컴퓨팅 및 메모리의 일부를 할" +"당받는다는 것을 의미합니다. 사용자는 시뮬레이션을 시작할 때 이를 제어할 수 있" +"으며, 이를 통해 Flower FL 시뮬레이션의 병렬 처리 정도를 제어할 수 있습니다. " +"클라이언트당 리소스가 적을수록 동일한 하드웨어에서 더 많은 클라이언트를 동시" +"에 실행할 수 있습니다." #: ../../source/how-to-run-simulations.rst:13 msgid "" -"self-managed: this means that you as a user do not need to launch clients" -" manually, instead this gets delegated to :code:`VirtualClientEngine`'s " +"self-managed: this means that you as a user do not need to launch clients " +"manually, instead this gets delegated to :code:`VirtualClientEngine`'s " "internals." msgstr "" +"self-managed: 이는 사용자가 클라이언트를 수동으로 실행할 필요가 없으며, 대" +"신 :code:`VirtualClientEngine`의 내부에 위임된다는 의미입니다." #: ../../source/how-to-run-simulations.rst:14 msgid "" -"ephemeral: this means that a client is only materialized when it is " -"required in the FL process (e.g. to do `fit() `_). The object is destroyed afterwards," -" releasing the resources it was assigned and allowing in this way other " -"clients to participate." +"ephemeral: this means that a client is only materialized when it is required " +"in the FL process (e.g. to do `fit() `_). The object is destroyed afterwards, releasing the resources it was " +"assigned and allowing in this way other clients to participate." msgstr "" +"ephemeral: 이는 클라이언트가 FL 프로세스에서 필요할 때만 구체화됨을 의미합니" +"다(예: `fit() `_을 수행하기 위해). " +"객체는 나중에 소멸되어 할당된 리소스를 해제하고 다른 클라이언트가 참여할 수 " +"있도록 허용합니다." #: ../../source/how-to-run-simulations.rst:16 msgid "" "The :code:`VirtualClientEngine` implements `virtual` clients using `Ray " "`_, an open-source framework for scalable Python " -"workloads. In particular, Flower's :code:`VirtualClientEngine` makes use " -"of `Actors `_ to " -"spawn `virtual` clients and run their workload." +"workloads. In particular, Flower's :code:`VirtualClientEngine` makes use of " +"`Actors `_ to spawn " +"`virtual` clients and run their workload." msgstr "" +":code:`VirtualClientEngine`은 확장 가능한 파이썬 워크로드를 위한 오픈 소스 프" +"레임워크인 `Ray `_를 사용하여 `virtual` 클라이언트를 구" +"현합니다. 특히 Flower의 :code:`VirtualClientEngine`은 `Actors `_를 사용하여 `virtual` 클라이언트를 생" +"성하고 해당 워크로드를 실행합니다." #: ../../source/how-to-run-simulations.rst:20 msgid "Launch your Flower simulation" -msgstr "" +msgstr "Flower 시뮬레이션 시작" #: ../../source/how-to-run-simulations.rst:22 msgid "" -"Running Flower simulations still require you to define your client class," -" a strategy, and utility functions to download and load (and potentially " -"partition) your dataset. With that out of the way, launching your " -"simulation is done with `start_simulation `_ and a minimal example looks" -" as follows:" +"Running Flower simulations still require you to define your client class, a " +"strategy, and utility functions to download and load (and potentially " +"partition) your dataset. With that out of the way, launching your simulation " +"is done with `start_simulation `_ and a minimal example looks as follows:" msgstr "" +"Flower 시뮬레이션을 실행하려면 여전히 클라이언트 클래스, 전략 및 유틸리티 함" +"수를 정의하여 데이터 세트를 다운로드하고 로드(및 파티션)해야 합니다. 이 작업" +"을 마친 후 시뮬레이션을 시작하려면 `start_simulation `_을 사용하면 되며, 최소한의 예시는 다음과 같습니" +"다:" #: ../../source/how-to-run-simulations.rst:44 msgid "VirtualClientEngine resources" -msgstr "" +msgstr "VirtualClientEngine 리소스" #: ../../source/how-to-run-simulations.rst:45 msgid "" -"By default the VCE has access to all system resources (i.e. all CPUs, all" -" GPUs, etc) since that is also the default behavior when starting Ray. " -"However, in some settings you might want to limit how many of your system" -" resources are used for simulation. You can do this via the " -":code:`ray_init_args` input argument to :code:`start_simulation` which " -"the VCE internally passes to Ray's :code:`ray.init` command. For a " -"complete list of settings you can configure check the `ray.init " -"`_" -" documentation. Do not set :code:`ray_init_args` if you want the VCE to " -"use all your system's CPUs and GPUs." -msgstr "" +"By default the VCE has access to all system resources (i.e. all CPUs, all " +"GPUs, etc) since that is also the default behavior when starting Ray. " +"However, in some settings you might want to limit how many of your system " +"resources are used for simulation. You can do this via the :code:" +"`ray_init_args` input argument to :code:`start_simulation` which the VCE " +"internally passes to Ray's :code:`ray.init` command. For a complete list of " +"settings you can configure check the `ray.init `_ documentation. Do not set :" +"code:`ray_init_args` if you want the VCE to use all your system's CPUs and " +"GPUs." +msgstr "" +"기본적으로 VCE는 모든 시스템 리소스(예: 모든 CPU, 모든 GPU 등)에 액세스할 수 " +"있으며, 이는 Ray를 시작할 때의 기본 동작이기도 합니다. 그러나 일부 설정에서" +"는 시뮬레이션에 사용되는 시스템 리소스의 수를 제한하고 싶을 수 있습니다. 이 " +"설정은 VCE가 내부적으로 Ray의 :code:`ray.init` 명령에 전달하는 :code:" +"`start_simulation`에 대한 :code:`ray_init_args` 입력 인수를 통해 수행할 수 있" +"습니다. 구성할 수 있는 전체 설정 목록은 `ray.init `_ 설명서를 확인하세요. VCE가 " +"시스템의 모든 CPU와 GPU를 사용하도록 하려면 :code:`ray_init_args`를 설정하지 " +"마세요." #: ../../source/how-to-run-simulations.rst:62 msgid "Assigning client resources" -msgstr "" +msgstr "클라이언트 리소스 할당" #: ../../source/how-to-run-simulations.rst:63 msgid "" -"By default the :code:`VirtualClientEngine` assigns a single CPU core (and" -" nothing else) to each virtual client. This means that if your system has" -" 10 cores, that many virtual clients can be concurrently running." +"By default the :code:`VirtualClientEngine` assigns a single CPU core (and " +"nothing else) to each virtual client. This means that if your system has 10 " +"cores, that many virtual clients can be concurrently running." msgstr "" +"기본적으로 :code:`VirtualClientEngine`은 각 가상 클라이언트에 단일 CPU 코어" +"를 할당합니다(그 외에는 아무것도 할당하지 않음). 즉, 시스템에 코어가 10개인 " +"경우 그만큼 많은 가상 클라이언트를 동시에 실행할 수 있습니다." #: ../../source/how-to-run-simulations.rst:65 msgid "" -"More often than not, you would probably like to adjust the resources your" -" clients get assigned based on the complexity (i.e. compute and memory " -"footprint) of your FL workload. You can do so when starting your " -"simulation by setting the argument `client_resources` to " -"`start_simulation `_." -" Two keys are internally used by Ray to schedule and spawn workloads (in " -"our case Flower clients):" +"More often than not, you would probably like to adjust the resources your " +"clients get assigned based on the complexity (i.e. compute and memory " +"footprint) of your FL workload. You can do so when starting your simulation " +"by setting the argument `client_resources` to `start_simulation `_. Two keys are internally used " +"by Ray to schedule and spawn workloads (in our case Flower clients):" msgstr "" +"대부분의 경우 FL 워크로드의 복잡성(즉, 컴퓨팅 및 메모리 사용량)에 따라 클라이" +"언트에 할당되는 리소스를 조정하고 싶을 것입니다. 시뮬레이션을 시작할 때 " +"`client_resources` argument를 `start_simulation `_로 설정하여 이를 수행할 수 있습니다. Ray는 내부" +"적으로 두 개의 키를 사용하여 워크로드(이 경우 Flower 클라이언트)를 스케줄링하" +"고 스폰합니다:" #: ../../source/how-to-run-simulations.rst:67 msgid ":code:`num_cpus` indicates the number of CPU cores a client would get." msgstr "" +":code:`num_cpus`는 클라이언트에서 사용할 수 있는 CPU 코어 수를 나타냅니다." #: ../../source/how-to-run-simulations.rst:68 msgid "" ":code:`num_gpus` indicates the **ratio** of GPU memory a client gets " "assigned." msgstr "" +":code:`num_gpus`는 클라이언트에 할당되는 GPU 메모리의 **비율**을 나타냅니다." #: ../../source/how-to-run-simulations.rst:70 msgid "Let's see a few examples:" -msgstr "" +msgstr "몇 가지 예를 살펴보겠습니다:" #: ../../source/how-to-run-simulations.rst:89 msgid "" "While the :code:`client_resources` can be used to control the degree of " "concurrency in your FL simulation, this does not stop you from running " -"dozens, hundreds or even thousands of clients in the same round and " -"having orders of magnitude more `dormant` (i.e. not participating in a " -"round) clients. Let's say you want to have 100 clients per round but your" -" system can only accommodate 8 clients concurrently. The " -":code:`VirtualClientEngine` will schedule 100 jobs to run (each " -"simulating a client sampled by the strategy) and then will execute them " -"in a resource-aware manner in batches of 8." -msgstr "" +"dozens, hundreds or even thousands of clients in the same round and having " +"orders of magnitude more `dormant` (i.e. not participating in a round) " +"clients. Let's say you want to have 100 clients per round but your system " +"can only accommodate 8 clients concurrently. The :code:`VirtualClientEngine` " +"will schedule 100 jobs to run (each simulating a client sampled by the " +"strategy) and then will execute them in a resource-aware manner in batches " +"of 8." +msgstr "" +"code:`client_resources`를 사용하여 FL 시뮬레이션의 동시성 정도를 제어할 수 있" +"지만, 동일한 라운드에서 수십, 수백 또는 수천 개의 클라이언트를 실행하고 훨씬 " +"더 많은 '휴면'(즉, 라운드에 참여하지 않는) 클라이언트를 보유하는 것을 막을 수" +"는 없습니다. 라운드당 100명의 클라이언트를 받고 싶지만 시스템이 동시에 8명의 " +"클라이언트만 수용할 수 있다고 가정해 봅시다. code:`VirtualClientEngine`은 실" +"행할 100개의 작업(각각 전략에서 샘플링한 클라이언트를 시뮬레이션)을 예약한 다" +"음 리소스 인식 방식으로 8개씩 일괄적으로 실행합니다." #: ../../source/how-to-run-simulations.rst:91 msgid "" "To understand all the intricate details on how resources are used to " -"schedule FL clients and how to define custom resources, please take a " -"look at the `Ray documentation `_." +"schedule FL clients and how to define custom resources, please take a look " +"at the `Ray documentation `_." msgstr "" +"리소스가 FL 클라이언트를 예약하는 데 사용되는 방법과 사용자 지정 리소스를 정" +"의하는 방법에 대한 모든 복잡한 세부 사항을 이해하려면 'Ray 문서 '를 참조하세요." #: ../../source/how-to-run-simulations.rst:94 msgid "Simulation examples" -msgstr "" +msgstr "시뮬레이션 예제" #: ../../source/how-to-run-simulations.rst:96 msgid "" -"A few ready-to-run complete examples for Flower simulation in " -"Tensorflow/Keras and PyTorch are provided in the `Flower repository " -"`_. You can run them on Google Colab too:" +"A few ready-to-run complete examples for Flower simulation in Tensorflow/" +"Keras and PyTorch are provided in the `Flower repository `_. You can run them on Google Colab too:" msgstr "" +"Tensorflow/Keras와 파이토치에서 바로 실행할 수 있는 몇 가지 Flower 시뮬레이" +"션 예제는 `Flower 레포지토리 `_에서 제공됩니" +"다. Google Colab에서도 실행할 수 있습니다:" #: ../../source/how-to-run-simulations.rst:98 msgid "" -"`Tensorflow/Keras Simulation " -"`_: 100 clients collaboratively train a MLP model on MNIST." +"`Tensorflow/Keras Simulation `_: 100 clients collaboratively train a MLP " +"model on MNIST." msgstr "" +"`Tensorflow/Keras 시뮬레이션 `_: 100개의 클라이언트가 공동으로 MNIST에서 " +"MLP 모델을 훈련합니다." #: ../../source/how-to-run-simulations.rst:99 msgid "" -"`PyTorch Simulation `_: 100 clients collaboratively train a CNN model on " +"`PyTorch Simulation `_: 100 clients collaboratively train a CNN model on " "MNIST." msgstr "" +"파이토치 시뮬레이션 `_: 100개의 클라이언트가 공동으로 MNIST에서 CNN 모델을 훈" +"련합니다." #: ../../source/how-to-run-simulations.rst:104 msgid "Multi-node Flower simulations" -msgstr "" +msgstr "멀티 노드 Flower 시뮬레이션" #: ../../source/how-to-run-simulations.rst:106 msgid "" -"Flower's :code:`VirtualClientEngine` allows you to run FL simulations " -"across multiple compute nodes. Before starting your multi-node simulation" -" ensure that you:" +"Flower's :code:`VirtualClientEngine` allows you to run FL simulations across " +"multiple compute nodes. Before starting your multi-node simulation ensure " +"that you:" msgstr "" +"Flower의 :code:`VirtualClientEngine`을 사용하면 여러 컴퓨팅 노드에서 FL 시뮬" +"레이션을 실행할 수 있습니다. 멀티 노드 시뮬레이션을 시작하기 전에 다음 사항" +"을 확인하세요:" #: ../../source/how-to-run-simulations.rst:108 msgid "Have the same Python environment in all nodes." -msgstr "" +msgstr "모든 노드에서 동일한 Python 환경을 유지합니다." #: ../../source/how-to-run-simulations.rst:109 msgid "Have a copy of your code (e.g. your entire repo) in all nodes." -msgstr "" +msgstr "모든 노드에 코드 사본(예: 전체 레포지토리)을 보관하세요." #: ../../source/how-to-run-simulations.rst:110 msgid "" -"Have a copy of your dataset in all nodes (more about this in " -":ref:`simulation considerations `)" +"Have a copy of your dataset in all nodes (more about this in :ref:" +"`simulation considerations `)" msgstr "" +"모든 노드에 데이터 세트의 사본을 보유하세요(자세한 내용은 :ref:`simulation " +"considerations `에서 확인하세요)" #: ../../source/how-to-run-simulations.rst:111 msgid "" -"Pass :code:`ray_init_args={\"address\"=\"auto\"}` to `start_simulation " -"`_ so the " -":code:`VirtualClientEngine` attaches to a running Ray instance." +"Pass :code:`ray_init_args={\"address\"=\"auto\"}` to `start_simulation `_ so the :code:" +"`VirtualClientEngine` attaches to a running Ray instance." msgstr "" +":code:`ray_init_args={\"address\"=\"auto\"}`를 `start_simulation `_에 전달하여 :code:" +"`VirtualClientEngine`이 실행 중인 Ray 인스턴스에 연결되도록 합니다." #: ../../source/how-to-run-simulations.rst:112 msgid "" -"Start Ray on you head node: on the terminal type :code:`ray start " -"--head`. This command will print a few lines, one of which indicates how " -"to attach other nodes to the head node." +"Start Ray on you head node: on the terminal type :code:`ray start --head`. " +"This command will print a few lines, one of which indicates how to attach " +"other nodes to the head node." msgstr "" +"헤드 노드에서 Ray 시작: 터미널에서 :code:`ray start --head`를 입력합니다. 이 " +"명령은 몇 줄을 출력하며, 그 중 하나는 다른 노드를 헤드 노드에 연결하는 방법" +"을 나타냅니다." #: ../../source/how-to-run-simulations.rst:113 msgid "" -"Attach other nodes to the head node: copy the command shown after " -"starting the head and execute it on terminal of a new node: for example " -":code:`ray start --address='192.168.1.132:6379'`" +"Attach other nodes to the head node: copy the command shown after starting " +"the head and execute it on terminal of a new node: for example :code:`ray " +"start --address='192.168.1.132:6379'`" msgstr "" +"헤드 노드에 다른 노드 연결: 헤드를 시작한 후 표시된 명령어을 복사하여 새 노드" +"의 터미널에서 실행합니다: 예: :code:`ray start --" +"address='192.168.1.132:6379'`" #: ../../source/how-to-run-simulations.rst:115 msgid "" "With all the above done, you can run your code from the head node as you " "would if the simulation was running on a single node." msgstr "" +"위의 모든 작업이 완료되면 단일 노드에서 시뮬레이션을 실행할 때와 마찬가지로 " +"헤드 노드에서 코드를 실행할 수 있습니다." #: ../../source/how-to-run-simulations.rst:117 msgid "" -"Once your simulation is finished, if you'd like to dismantle your cluster" -" you simply need to run the command :code:`ray stop` in each node's " -"terminal (including the head node)." +"Once your simulation is finished, if you'd like to dismantle your cluster " +"you simply need to run the command :code:`ray stop` in each node's terminal " +"(including the head node)." msgstr "" +"시뮬레이션이 완료되면 클러스터를 해체하려면 각 노드(헤드 노드 포함)의 터미널" +"에서 :code:`ray stop` 명령을 실행하기만 하면 됩니다." #: ../../source/how-to-run-simulations.rst:120 msgid "Multi-node simulation good-to-know" -msgstr "" +msgstr "멀티 노드 시뮬레이션에 대해 알아두면 좋은 사항" #: ../../source/how-to-run-simulations.rst:122 msgid "" "Here we list a few interesting functionality when running multi-node FL " "simulations:" msgstr "" +"여기에서는 멀티 노드 FL 시뮬레이션을 실행할 때 흥미로운 몇 가지 기능을 나열합" +"니다:" #: ../../source/how-to-run-simulations.rst:124 msgid "" -"User :code:`ray status` to check all nodes connected to your head node as" -" well as the total resources available to the " -":code:`VirtualClientEngine`." +"User :code:`ray status` to check all nodes connected to your head node as " +"well as the total resources available to the :code:`VirtualClientEngine`." msgstr "" +"사용자는 :code:`ray status`를 통해 헤드 노드에 연결된 모든 노드와 :code:" +"`VirtualClientEngine`에 사용 가능한 총 리소스를 확인할 수 있습니다." #: ../../source/how-to-run-simulations.rst:126 msgid "" -"When attaching a new node to the head, all its resources (i.e. all CPUs, " -"all GPUs) will be visible by the head node. This means that the " -":code:`VirtualClientEngine` can schedule as many `virtual` clients as " -"that node can possible run. In some settings you might want to exclude " -"certain resources from the simulation. You can do this by appending " -"`--num-cpus=` and/or `--num-" -"gpus=` in any :code:`ray start` command (including " -"when starting the head)" -msgstr "" +"When attaching a new node to the head, all its resources (i.e. all CPUs, all " +"GPUs) will be visible by the head node. This means that the :code:" +"`VirtualClientEngine` can schedule as many `virtual` clients as that node " +"can possible run. In some settings you might want to exclude certain " +"resources from the simulation. You can do this by appending `--num-" +"cpus=` and/or `--num-gpus=` in any :" +"code:`ray start` command (including when starting the head)" +msgstr "" +"새 노드를 헤드에 연결하면 해당 노드의 모든 리소스(즉, 모든 CPU, 모든 GPU)가 " +"헤드 노드에 표시됩니다. 즉, :code:`VirtualClientEngine`은 해당 노드가 실행할 " +"수 있는 만큼의 `가상` 클라이언트를 예약할 수 있습니다. 일부 설정에서는 시뮬레" +"이션에서 특정 리소스를 제외하고 싶을 수 있습니다. 모든 :code:`ray start` 명령" +"(헤드 시작 시 포함)에 `--num-cpus=` 및/또는 `--num-" +"gpus=`를 추가하여 이 작업을 수행하면 됩니다" #: ../../source/how-to-run-simulations.rst:132 msgid "Considerations for simulations" -msgstr "" +msgstr "시뮬레이션 시 고려 사항" #: ../../source/how-to-run-simulations.rst:135 msgid "" -"We are actively working on these fronts so to make it trivial to run any " -"FL workload with Flower simulation." +"We are actively working on these fronts so to make it trivial to run any FL " +"workload with Flower simulation." msgstr "" +"Flower 시뮬레이션으로 모든 FL 워크로드를 간편하게 실행할 수 있도록 이러한 측" +"면에서 적극적으로 노력하고 있습니다." #: ../../source/how-to-run-simulations.rst:138 msgid "" -"The current VCE allows you to run Federated Learning workloads in " -"simulation mode whether you are prototyping simple scenarios on your " -"personal laptop or you want to train a complex FL pipeline across " -"multiple high-performance GPU nodes. While we add more capabilities to " -"the VCE, the points below highlight some of the considerations to keep in" -" mind when designing your FL pipeline with Flower. We also highlight a " -"couple of current limitations in our implementation." +"The current VCE allows you to run Federated Learning workloads in simulation " +"mode whether you are prototyping simple scenarios on your personal laptop or " +"you want to train a complex FL pipeline across multiple high-performance GPU " +"nodes. While we add more capabilities to the VCE, the points below highlight " +"some of the considerations to keep in mind when designing your FL pipeline " +"with Flower. We also highlight a couple of current limitations in our " +"implementation." msgstr "" +"현재 VCE를 사용하면 개인 노트북에서 간단한 시나리오를 프로토타이핑하든, 여러 " +"고성능 GPU 노드에서 복잡한 FL 파이프라인을 훈련하든 상관없이 시뮬레이션 모드" +"에서 Federated 학습 워크로드를 실행할 수 있습니다. VCE에 더 많은 기능을 추가" +"하는 동안, 아래에서는 Flower로 FL 파이프라인을 설계할 때 염두에 두어야 할 몇 " +"가지 사항을 강조합니다. 또한 현재 구현에서 몇 가지 제한 사항을 강조합니다." #: ../../source/how-to-run-simulations.rst:141 msgid "GPU resources" -msgstr "" +msgstr "GPU 리소스" #: ../../source/how-to-run-simulations.rst:143 msgid "" -"The VCE assigns a share of GPU memory to a client that specifies the key " -":code:`num_gpus` in :code:`client_resources`. This being said, Ray (used " +"The VCE assigns a share of GPU memory to a client that specifies the key :" +"code:`num_gpus` in :code:`client_resources`. This being said, Ray (used " "internally by the VCE) is by default:" msgstr "" +"VCE는 :code:`client_resources`에서 :code:`num_gpus` 키를 지정하는 클라이언트" +"에 GPU 메모리 공유를 할당합니다. 즉, (VCE에서 내부적으로 사용하는) Ray가 기본" +"적으로 사용됩니다:" #: ../../source/how-to-run-simulations.rst:146 msgid "" -"not aware of the total VRAM available on the GPUs. This means that if you" -" set :code:`num_gpus=0.5` and you have two GPUs in your system with " -"different (e.g. 32GB and 8GB) VRAM amounts, they both would run 2 clients" -" concurrently." +"not aware of the total VRAM available on the GPUs. This means that if you " +"set :code:`num_gpus=0.5` and you have two GPUs in your system with different " +"(e.g. 32GB and 8GB) VRAM amounts, they both would run 2 clients concurrently." msgstr "" +"GPU에서 사용 가능한 총 VRAM을 인식하지 못합니다. 즉, 시스템에 서로 다른(예: " +"32GB와 8GB) VRAM 용량을 가진 두 개의 GPU가 있고 :code:`num_gpus=0.5`를 설정하" +"면 둘 다 동시에 2개의 클라이언트를 실행하게 됩니다." #: ../../source/how-to-run-simulations.rst:147 msgid "" "not aware of other unrelated (i.e. not created by the VCE) workloads are " "running on the GPU. Two takeaways from this are:" msgstr "" +"관련 없는(즉, VCE에 의해 생성되지 않은) 다른 워크로드가 GPU에서 실행되고 있는" +"지 알지 못합니다. 여기서 두 가지 시사점을 얻을 수 있습니다:" #: ../../source/how-to-run-simulations.rst:149 msgid "" @@ -6590,178 +6794,237 @@ msgid "" "aggregation (by instance when making use of the `evaluate method `_)" msgstr "" +"집계 후 '글로벌 모델'을 평가하려면 Flower 서버에 GPU가 필요할 수 있습니다" +"(예: `evaluate method `_를 사용할 때)" #: ../../source/how-to-run-simulations.rst:150 msgid "" "If you want to run several independent Flower simulations on the same " -"machine you need to mask-out your GPUs with " -":code:`CUDA_VISIBLE_DEVICES=\"\"` when launching your " -"experiment." +"machine you need to mask-out your GPUs with :code:" +"`CUDA_VISIBLE_DEVICES=\"\"` when launching your experiment." msgstr "" +"동일한 머신에서 여러 개의 독립적인 Flower 시뮬레이션을 실행하려면, 실험을 시" +"작할 때 :code:`CUDA_VISIBLE_DEVICES=\"\"`로 GPU를 마스킹해야 합니다." #: ../../source/how-to-run-simulations.rst:153 msgid "" -"In addition, the GPU resource limits passed to :code:`client_resources` " -"are not `enforced` (i.e. they can be exceeded) which can result in the " -"situation of client using more VRAM than the ratio specified when " -"starting the simulation." +"In addition, the GPU resource limits passed to :code:`client_resources` are " +"not `enforced` (i.e. they can be exceeded) which can result in the situation " +"of client using more VRAM than the ratio specified when starting the " +"simulation." msgstr "" +"또한 :code:`client_resources`에 전달된 GPU 리소스 제한이 '강제'되지 않아(즉, " +"초과할 수 있음) 클라이언트가 시뮬레이션을 시작할 때 지정된 비율보다 더 많은 " +"VRAM을 사용하는 상황이 발생할 수 있습니다." #: ../../source/how-to-run-simulations.rst:156 msgid "TensorFlow with GPUs" -msgstr "" +msgstr "GPU를 사용한 TensorFlow" #: ../../source/how-to-run-simulations.rst:158 msgid "" -"When `using a GPU with TensorFlow " -"`_ nearly your entire GPU memory of" -" all your GPUs visible to the process will be mapped. This is done by " -"TensorFlow for optimization purposes. However, in settings such as FL " -"simulations where we want to split the GPU into multiple `virtual` " -"clients, this is not a desirable mechanism. Luckily we can disable this " -"default behavior by `enabling memory growth " -"`_." -msgstr "" +"When `using a GPU with TensorFlow `_ " +"nearly your entire GPU memory of all your GPUs visible to the process will " +"be mapped. This is done by TensorFlow for optimization purposes. However, in " +"settings such as FL simulations where we want to split the GPU into multiple " +"`virtual` clients, this is not a desirable mechanism. Luckily we can disable " +"this default behavior by `enabling memory growth `_." +msgstr "" +"`TensorFlow와 함께 GPU를 사용 `_하면 프" +"로세스에 보이는 모든 GPU의 거의 전체 GPU 메모리가 매핑됩니다. 이는 최적화 목" +"적으로 TensorFlow에서 수행됩니다. 그러나 GPU를 여러 개의 '가상' 클라이언트로 " +"분할하려는 FL 시뮬레이션과 같은 설정에서는 이는 바람직한 메커니즘이 아닙니" +"다. 다행히도 '메모리 증가 활성화 `_'를 통해 이 기본 동작을 비활성화할 수 있습니" +"다." #: ../../source/how-to-run-simulations.rst:160 msgid "" -"This would need to be done in the main process (which is where the server" -" would run) and in each Actor created by the VCE. By means of " -":code:`actor_kwargs` we can pass the reserved key `\"on_actor_init_fn\"` " -"in order to specify a function to be executed upon actor initialization. " -"In this case, to enable GPU growth for TF workloads. It would look as " -"follows:" +"This would need to be done in the main process (which is where the server " +"would run) and in each Actor created by the VCE. By means of :code:" +"`actor_kwargs` we can pass the reserved key `\"on_actor_init_fn\"` in order " +"to specify a function to be executed upon actor initialization. In this " +"case, to enable GPU growth for TF workloads. It would look as follows:" msgstr "" +"이 작업은 메인 프로세스(서버가 실행되는 곳)와 VCE에서 생성한 각 액터에서 수행" +"해야 합니다. :code:`actor_kwargs`를 통해 예약 키 `\"on_actor_init_fn\"`을 전" +"달하여 액터 초기화 시 실행할 함수를 지정할 수 있습니다. 이 경우 TF 워크로드" +"에 대한 GPU 증가를 활성화합니다. 다음과 같이 보입니다:" #: ../../source/how-to-run-simulations.rst:179 msgid "" "This is precisely the mechanism used in `Tensorflow/Keras Simulation " -"`_ example." +"`_ " +"example." msgstr "" +"이것이 바로`Tensorflow/Keras Simulation `_ 예제에서 사용된 메커니즘입니다." #: ../../source/how-to-run-simulations.rst:183 msgid "Multi-node setups" -msgstr "" +msgstr "멀티 노드 설정" #: ../../source/how-to-run-simulations.rst:185 msgid "" -"The VCE does not currently offer a way to control on which node a " -"particular `virtual` client is executed. In other words, if more than a " -"single node have the resources needed by a client to run, then any of " -"those nodes could get the client workload scheduled onto. Later in the FL" -" process (i.e. in a different round) the same client could be executed by" -" a different node. Depending on how your clients access their datasets, " -"this might require either having a copy of all dataset partitions on all " -"nodes or a dataset serving mechanism (e.g. using nfs, a database) to " -"circumvent data duplication." -msgstr "" +"The VCE does not currently offer a way to control on which node a particular " +"`virtual` client is executed. In other words, if more than a single node " +"have the resources needed by a client to run, then any of those nodes could " +"get the client workload scheduled onto. Later in the FL process (i.e. in a " +"different round) the same client could be executed by a different node. " +"Depending on how your clients access their datasets, this might require " +"either having a copy of all dataset partitions on all nodes or a dataset " +"serving mechanism (e.g. using nfs, a database) to circumvent data " +"duplication." +msgstr "" +"VCE는 현재 특정 '가상' 클라이언트를 어느 노드에서 실행할지 제어하는 방법을 제" +"공하지 않습니다. 즉, 클라이언트가 실행하는 데 필요한 리소스가 하나 이상의 노" +"드에 있는 경우 해당 노드 중 어느 노드에나 클라이언트 워크로드가 예약될 수 있" +"습니다. FL 프로세스 후반부(즉, 다른 라운드에서)에는 동일한 클라이언트가 다른 " +"노드에서 실행될 수 있습니다. 클라이언트가 데이터 세트에 액세스하는 방식에 따" +"라 모든 노드에 모든 데이터 세트 파티션의 복사본을 보유하거나 데이터 중복을 피" +"하기 위해 데이터 세트 제공 메커니즘(예: nfs, 데이터베이스 사용)을 사용해야 " +"할 수 있습니다." #: ../../source/how-to-run-simulations.rst:187 msgid "" -"By definition virtual clients are `stateless` due to their ephemeral " -"nature. A client state can be implemented as part of the Flower client " -"class but users need to ensure this saved to persistent storage (e.g. a " -"database, disk) and that can be retrieve later by the same client " -"regardless on which node it is running from. This is related to the point" -" above also since, in some way, the client's dataset could be seen as a " -"type of `state`." +"By definition virtual clients are `stateless` due to their ephemeral nature. " +"A client state can be implemented as part of the Flower client class but " +"users need to ensure this saved to persistent storage (e.g. a database, " +"disk) and that can be retrieve later by the same client regardless on which " +"node it is running from. This is related to the point above also since, in " +"some way, the client's dataset could be seen as a type of `state`." msgstr "" +"정의상 가상 클라이언트는 임시적 특성으로 인해 '상태 없음'입니다. 클라이언트 " +"상태는 Flower 클라이언트 클래스의 일부로 구현할 수 있지만, 사용자는 이를 영" +"구 저장소(예: 데이터베이스, 디스크)에 저장하여 나중에 실행 중인 노드와 관계없" +"이 동일한 클라이언트가 검색할 수 있도록 해야 합니다. 이는 어떤 식으로든 클라" +"이언트의 데이터 세트가 일종의 '상태'로 볼 수 있기 때문에 위의 요점과도 관련" +"이 있습니다." #: ../../source/how-to-save-and-load-model-checkpoints.rst:2 msgid "Save and load model checkpoints" -msgstr "" +msgstr "모델 체크포인트 저장 및 로드" #: ../../source/how-to-save-and-load-model-checkpoints.rst:4 msgid "" -"Flower does not automatically save model updates on the server-side. This" -" how-to guide describes the steps to save (and load) model checkpoints in" -" Flower." +"Flower does not automatically save model updates on the server-side. This " +"how-to guide describes the steps to save (and load) model checkpoints in " +"Flower." msgstr "" +"Flower는 서버 측에서 모델 업데이트를 자동으로 저장하지 않습니다. 이 사용법 가" +"이드에서는 Flower에서 모델 체크포인트를 저장(및 로드)하는 단계에 대해 설명합" +"니다." #: ../../source/how-to-save-and-load-model-checkpoints.rst:8 msgid "Model checkpointing" -msgstr "" +msgstr "모델 체크포인트" #: ../../source/how-to-save-and-load-model-checkpoints.rst:10 msgid "" -"Model updates can be persisted on the server-side by customizing " -":code:`Strategy` methods. Implementing custom strategies is always an " -"option, but for many cases it may be more convenient to simply customize " -"an existing strategy. The following code example defines a new " -":code:`SaveModelStrategy` which customized the existing built-in " -":code:`FedAvg` strategy. In particular, it customizes " -":code:`aggregate_fit` by calling :code:`aggregate_fit` in the base class " -"(:code:`FedAvg`). It then continues to save returned (aggregated) weights" -" before it returns those aggregated weights to the caller (i.e., the " -"server):" -msgstr "" +"Model updates can be persisted on the server-side by customizing :code:" +"`Strategy` methods. Implementing custom strategies is always an option, but " +"for many cases it may be more convenient to simply customize an existing " +"strategy. The following code example defines a new :code:`SaveModelStrategy` " +"which customized the existing built-in :code:`FedAvg` strategy. In " +"particular, it customizes :code:`aggregate_fit` by calling :code:" +"`aggregate_fit` in the base class (:code:`FedAvg`). It then continues to " +"save returned (aggregated) weights before it returns those aggregated " +"weights to the caller (i.e., the server):" +msgstr "" +":code:`Strategy` 메소드를 사용자 지정하여 서버 측에서 모델 업데이트를 지속할 " +"수 있습니다. 사용자 지정 전략을 구현하는 것은 항상 옵션이지만 대부분의 경우 " +"기존 전략을 간단히 사용자 지정하는 것이 더 편리할 수 있습니다. 다음 코드 예시" +"는 기존의 기본 제공 :code:`FedAvg` 전략을 사용자 지정한 새로운 :code:" +"`SaveModelStrategy`를 정의합니다. 특히, 기본 클래스(:code:`FedAvg`)에서 :" +"code:`aggregate_fit`을 호출하여 :code:`aggregate_fit`을 사용자 지정합니다. 그" +"런 다음 호출자(즉, 서버)에게 집계된 가중치를 반환하기 전에 반환된(집계된) 가" +"중치를 계속 저장합니다:" #: ../../source/how-to-save-and-load-model-checkpoints.rst:47 msgid "Save and load PyTorch checkpoints" -msgstr "" +msgstr "파이토치 체크포인트 저장 및 로드" #: ../../source/how-to-save-and-load-model-checkpoints.rst:49 msgid "" -"Similar to the previous example but with a few extra steps, we'll show " -"how to store a PyTorch checkpoint we'll use the ``torch.save`` function. " -"Firstly, ``aggregate_fit`` returns a ``Parameters`` object that has to be" -" transformed into a list of NumPy ``ndarray``'s, then those are " -"transformed into the PyTorch ``state_dict`` following the ``OrderedDict``" -" class structure." +"Similar to the previous example but with a few extra steps, we'll show how " +"to store a PyTorch checkpoint we'll use the ``torch.save`` function. " +"Firstly, ``aggregate_fit`` returns a ``Parameters`` object that has to be " +"transformed into a list of NumPy ``ndarray``'s, then those are transformed " +"into the PyTorch ``state_dict`` following the ``OrderedDict`` class " +"structure." msgstr "" +"이전 예제와 비슷하지만 몇 가지 단계가 추가되어 ``torch.save`` 함수를 사용하" +"여 파이토치 체크포인트를 저장하는 방법을 보여드리겠습니다. 먼저, " +"``aggregate_fit``은 ``Parameters`` 객체를 반환하는데, 이 객체는 NumPy " +"``ndarray``의 목록으로 변환되어야 하며, ``OrderedDict`` 클래스 구조에 따라 파" +"이토치 ``state_dict``로 변환됩니다." #: ../../source/how-to-save-and-load-model-checkpoints.rst:85 msgid "" -"To load your progress, you simply append the following lines to your " -"code. Note that this will iterate over all saved checkpoints and load the" -" latest one:" +"To load your progress, you simply append the following lines to your code. " +"Note that this will iterate over all saved checkpoints and load the latest " +"one:" msgstr "" +"진행 상황을 로드하려면 코드에 다음 줄을 추가하기만 하면 됩니다. 이렇게 하면 " +"저장된 모든 체크포인트를 반복하고 최신 체크포인트를 로드합니다:" #: ../../source/how-to-save-and-load-model-checkpoints.rst:97 msgid "" -"Return/use this object of type ``Parameters`` wherever necessary, such as" -" in the ``initial_parameters`` when defining a ``Strategy``." +"Return/use this object of type ``Parameters`` wherever necessary, such as in " +"the ``initial_parameters`` when defining a ``Strategy``." msgstr "" +"``전략``을 정의할 때 ``초기_파라미터``와 같이 필요한 경우 ``파라미터`` 유형" +"의 이 객체를 반환/사용합니다." #: ../../source/how-to-upgrade-to-flower-1.0.rst:2 msgid "Upgrade to Flower 1.0" -msgstr "" +msgstr "Flower 1.0으로 업그레이드" #: ../../source/how-to-upgrade-to-flower-1.0.rst:4 msgid "" -"Flower 1.0 is here. Along with new features, Flower 1.0 provides a stable" -" foundation for future growth. Compared to Flower 0.19 (and other 0.x " -"series releases), there are a few breaking changes that make it necessary" -" to change the code of existing 0.x-series projects." +"Flower 1.0 is here. Along with new features, Flower 1.0 provides a stable " +"foundation for future growth. Compared to Flower 0.19 (and other 0.x series " +"releases), there are a few breaking changes that make it necessary to change " +"the code of existing 0.x-series projects." msgstr "" +"Flower 1.0이 출시되었습니다. 새로운 기능과 함께 Flower 1.0은 향후 성장을 위" +"한 안정적인 기반을 제공합니다. Flower 0.19(및 다른 0.x 시리즈 릴리스)와 비교" +"했을 때 기존 0.x 시리즈 프로젝트의 코드를 변경해야 하는 몇 가지 획기적인 변" +"경 사항이 있습니다." #: ../../source/how-to-upgrade-to-flower-1.0.rst:8 #: ../../source/how-to-upgrade-to-flower-next.rst:43 msgid "Install update" -msgstr "" +msgstr "업데이트 설치" #: ../../source/how-to-upgrade-to-flower-1.0.rst:10 msgid "" -"Here's how to update an existing installation to Flower 1.0 using either " -"pip or Poetry:" +"Here's how to update an existing installation to Flower 1.0 using either pip " +"or Poetry:" msgstr "" +"다음은 pip 또는 Poetry를 사용하여 기존 설치를 Flower 1.0으로 업데이트하는 방" +"법입니다:" #: ../../source/how-to-upgrade-to-flower-1.0.rst:12 msgid "pip: add ``-U`` when installing." -msgstr "" +msgstr "pip: 설치할 때 ``-U``를 추가합니다." #: ../../source/how-to-upgrade-to-flower-1.0.rst:14 msgid "" "``python -m pip install -U flwr`` (when using ``start_server`` and " "``start_client``)" msgstr "" +"``python -m pip install -U flwr``(``start_server`` 및 ``start_client``를 사용" +"하는 경우)" #: ../../source/how-to-upgrade-to-flower-1.0.rst:15 msgid "" "``python -m pip install -U flwr[simulation]`` (when using " "``start_simulation``)" msgstr "" +"``python -m pip install -U flwr[simulation]``(``start_simulation`` 사용 시)" #: ../../source/how-to-upgrade-to-flower-1.0.rst:17 msgid "" @@ -6769,140 +7032,170 @@ msgid "" "reinstall (don't forget to delete ``poetry.lock`` via ``rm poetry.lock`` " "before running ``poetry install``)." msgstr "" +"Poetry: ``pyproject.toml``에서 ``flwr`` dependency을 업데이트한 다음 다시 설" +"치하세요(``poetry 설치``를 실행하기 전에 ``rm poetry.lock``을 통해 ``poetry." +"lock``을 삭제하는 것을 잊지 마세요)." #: ../../source/how-to-upgrade-to-flower-1.0.rst:19 -msgid "``flwr = \"^1.0.0\"`` (when using ``start_server`` and ``start_client``)" -msgstr "" +msgid "" +"``flwr = \"^1.0.0\"`` (when using ``start_server`` and ``start_client``)" +msgstr "``flwr = \"^1.0.0\"``(``start_server`` 및 ``start_client`` 사용 시)" #: ../../source/how-to-upgrade-to-flower-1.0.rst:20 msgid "" -"``flwr = { version = \"^1.0.0\", extras = [\"simulation\"] }`` (when " -"using ``start_simulation``)" +"``flwr = { version = \"^1.0.0\", extras = [\"simulation\"] }`` (when using " +"``start_simulation``)" msgstr "" +"``flwr = { version = \"^1.0.0\", extras = [\"simulation\"] }`` " +"(``start_simulation`` 사용 시)" #: ../../source/how-to-upgrade-to-flower-1.0.rst:24 #: ../../source/how-to-upgrade-to-flower-next.rst:100 msgid "Required changes" -msgstr "" +msgstr "필수 변경 사항" #: ../../source/how-to-upgrade-to-flower-1.0.rst:26 msgid "The following breaking changes require manual updates." -msgstr "" +msgstr "다음과 같은 주요 변경 사항에는 수동 업데이트가 필요합니다." #: ../../source/how-to-upgrade-to-flower-1.0.rst:29 msgid "General" -msgstr "" +msgstr "일반" #: ../../source/how-to-upgrade-to-flower-1.0.rst:31 msgid "" "Pass all arguments as keyword arguments (not as positional arguments). " "Here's an example:" -msgstr "" +msgstr "모든 전달인자를 위치 전달인자가 아닌 키워드 전달인자로 전달합니다. 다음은 " +"예시입니다:" #: ../../source/how-to-upgrade-to-flower-1.0.rst:33 msgid "" "Flower 0.19 (positional arguments): ``start_client(\"127.0.0.1:8080\", " "FlowerClient())``" msgstr "" +"Flower 0.19 (위치 전달인자): ``start_client(\"127.0.0.1:8080\", " +"FlowerClient())``" #: ../../source/how-to-upgrade-to-flower-1.0.rst:34 msgid "" "Flower 1.0 (keyword arguments): " -"``start_client(server_address=\"127.0.0.1:8080\", " -"client=FlowerClient())``" +"``start_client(server_address=\"127.0.0.1:8080\", client=FlowerClient())``" msgstr "" +"Flower 1.0 (키워드 전달인자): ``start_client(server_address=\"127.0.0.1:" +"8080\", client=FlowerClient())``" #: ../../source/how-to-upgrade-to-flower-1.0.rst:37 #: ../../source/ref-api/flwr.client.Client.rst:2 msgid "Client" -msgstr "" +msgstr "클라이언트" #: ../../source/how-to-upgrade-to-flower-1.0.rst:39 msgid "" "Subclasses of ``NumPyClient``: change ``def get_parameters(self):``` to " "``def get_parameters(self, config):``" msgstr "" +"``NumPyClient``의 서브클래스: ``def get_parameters(self):``를 ``def " +"get_parameters(self, config):``로 변경합니다" #: ../../source/how-to-upgrade-to-flower-1.0.rst:40 msgid "" "Subclasses of ``Client``: change ``def get_parameters(self):``` to ``def " "get_parameters(self, ins: GetParametersIns):``" msgstr "" +"``클라이언트``의 서브클래스: ``def get_parameters(self):``를 ``def " +"get_parameters(self, ins: GetParametersIns):``로 변경합니다" #: ../../source/how-to-upgrade-to-flower-1.0.rst:43 msgid "Strategies / ``start_server`` / ``start_simulation``" -msgstr "" +msgstr "전략 / ``start_server`` / ``start_simulation``" #: ../../source/how-to-upgrade-to-flower-1.0.rst:45 msgid "" "Pass ``ServerConfig`` (instead of a dictionary) to ``start_server`` and " "``start_simulation``. Here's an example:" msgstr "" +"Dictionary 대신 ``ServerConfig``를 ``start_server`` 및 ``start_simulation``" +"에 전달합니다. 다음은 예제입니다:" #: ../../source/how-to-upgrade-to-flower-1.0.rst:47 msgid "" "Flower 0.19: ``start_server(..., config={\"num_rounds\": 3, " "\"round_timeout\": 600.0}, ...)``" msgstr "" +"Flower 0.19: ``start_server(..., config={\"num_rounds\": 3, " +"\"round_timeout\": 600.0}, ...)``" #: ../../source/how-to-upgrade-to-flower-1.0.rst:48 msgid "" -"Flower 1.0: ``start_server(..., " -"config=flwr.server.ServerConfig(num_rounds=3, round_timeout=600.0), " -"...)``" +"Flower 1.0: ``start_server(..., config=flwr.server." +"ServerConfig(num_rounds=3, round_timeout=600.0), ...)``" msgstr "" +"Flower 1.0: ``start_server(..., config=flwr.server." +"ServerConfig(num_rounds=3, round_timeout=600.0), ...)``" #: ../../source/how-to-upgrade-to-flower-1.0.rst:50 msgid "" "Replace ``num_rounds=1`` in ``start_simulation`` with the new " "``config=ServerConfig(...)`` (see previous item)" msgstr "" +"``start_simulation``의 ``num_rounds=1``을 새로운 ``config=ServerConfig(...)``" +"로 바꿉니다(이전 항목 참조)" #: ../../source/how-to-upgrade-to-flower-1.0.rst:51 msgid "" "Remove ``force_final_distributed_eval`` parameter from calls to " -"``start_server``. Distributed evaluation on all clients can be enabled by" -" configuring the strategy to sample all clients for evaluation after the " -"last round of training." +"``start_server``. Distributed evaluation on all clients can be enabled by " +"configuring the strategy to sample all clients for evaluation after the last " +"round of training." msgstr "" +"'start_server`` 호출에서 ``force_final_distributed_eval`` 매개변수를 제거합니" +"다. 모든 클라이언트에 대한 분산 평가는 마지막 훈련 라운드 후 평가를 위해 모" +"든 클라이언트를 샘플링하도록 전략을 구성하여 활성화할 수 있습니다." #: ../../source/how-to-upgrade-to-flower-1.0.rst:52 msgid "Rename parameter/ndarray conversion functions:" -msgstr "" +msgstr "매개변수/ndarray 변환 함수의 이름을 바꿉니다:" #: ../../source/how-to-upgrade-to-flower-1.0.rst:54 msgid "``parameters_to_weights`` --> ``parameters_to_ndarrays``" -msgstr "" +msgstr "``parameters_to_weights`` --> ``parameters_to_ndarrays``" #: ../../source/how-to-upgrade-to-flower-1.0.rst:55 msgid "``weights_to_parameters`` --> ``ndarrays_to_parameters``" -msgstr "" +msgstr "``weights_to_parameters`` --> ``ndarrays_to_parameters``" #: ../../source/how-to-upgrade-to-flower-1.0.rst:57 msgid "" -"Strategy initialization: if the strategy relies on the default values for" -" ``fraction_fit`` and ``fraction_evaluate``, set ``fraction_fit`` and " +"Strategy initialization: if the strategy relies on the default values for " +"``fraction_fit`` and ``fraction_evaluate``, set ``fraction_fit`` and " "``fraction_evaluate`` manually to ``0.1``. Projects that do not manually " "create a strategy (by calling ``start_server`` or ``start_simulation`` " -"without passing a strategy instance) should now manually initialize " -"FedAvg with ``fraction_fit`` and ``fraction_evaluate`` set to ``0.1``." +"without passing a strategy instance) should now manually initialize FedAvg " +"with ``fraction_fit`` and ``fraction_evaluate`` set to ``0.1``." msgstr "" +"전략 초기화: 전략이 ``fraction_fit`` 및 ``fraction_evaluate``의 기본값에 의존" +"하는 경우 ``fraction_fit`` 및 ``fraction_evaluate``를 ``0.1``로 수동 설정합니" +"다. 전략을 수동으로 생성하지 않는 프로젝트(전략 인스턴스를 전달하지 않고 " +"``start_server`` 또는 ``start_simulation``을 호출하여)는 이제 " +"``fraction_fit`` 및 ``fraction_evaluate``를 ``0.1``로 설정하여 FedAvg를 수동" +"으로 초기화해야 합니다." #: ../../source/how-to-upgrade-to-flower-1.0.rst:58 msgid "Rename built-in strategy parameters (e.g., ``FedAvg``):" -msgstr "" +msgstr "기본 제공 전략 매개변수의 이름을 바꿉니다(예: ``FedAvg``):" #: ../../source/how-to-upgrade-to-flower-1.0.rst:60 msgid "``fraction_eval`` --> ``fraction_evaluate``" -msgstr "" +msgstr "``fraction_eval`` --> ``fraction_evaluate``" #: ../../source/how-to-upgrade-to-flower-1.0.rst:61 msgid "``min_eval_clients`` --> ``min_evaluate_clients``" -msgstr "" +msgstr "``min_eval_clients`` --> ``min_evaluate_clients``" #: ../../source/how-to-upgrade-to-flower-1.0.rst:62 msgid "``eval_fn`` --> ``evaluate_fn``" -msgstr "" +msgstr "``eval_fn`` --> ``evaluate_fn``" #: ../../source/how-to-upgrade-to-flower-1.0.rst:64 msgid "" @@ -6910,72 +7203,90 @@ msgid "" "functions, for example, ``configure_fit``, ``aggregate_fit``, " "``configure_evaluate``, ``aggregate_evaluate``, and ``evaluate_fn``." msgstr "" +"``rnd``의 이름을 ``server_round``로 바꿉니다. 이는 여러 메서드 및 함수(예: " +"``configure_fit``, ``aggregate_fit``, ``configure_evaluate``, " +"``aggregate_evaluate`` 및 ``evaluate_fn``)에 영향을 미칩니다." #: ../../source/how-to-upgrade-to-flower-1.0.rst:65 msgid "Add ``server_round`` and ``config`` to ``evaluate_fn``:" -msgstr "" +msgstr "``server_round`` 및 ``config``를 ``evaluate_fn``에 추가합니다:" #: ../../source/how-to-upgrade-to-flower-1.0.rst:67 msgid "" -"Flower 0.19: ``def evaluate(parameters: NDArrays) -> " -"Optional[Tuple[float, Dict[str, Scalar]]]:``" +"Flower 0.19: ``def evaluate(parameters: NDArrays) -> Optional[Tuple[float, " +"Dict[str, Scalar]]]:``" msgstr "" +"Flower 0.19: ``def evaluate(parameters: NDArrays) -> Optional[Tuple[float, " +"Dict[str, Scalar]]]:``" #: ../../source/how-to-upgrade-to-flower-1.0.rst:68 msgid "" -"Flower 1.0: ``def evaluate(server_round: int, parameters: NDArrays, " -"config: Dict[str, Scalar]) -> Optional[Tuple[float, Dict[str, " -"Scalar]]]:``" +"Flower 1.0: ``def evaluate(server_round: int, parameters: NDArrays, config: " +"Dict[str, Scalar]) -> Optional[Tuple[float, Dict[str, Scalar]]]:``" msgstr "" +"Flower 1.0: ``def evaluate(server_round: int, parameters: NDArrays, config: " +"Dict[str, Scalar]) -> Optional[Tuple[float, Dict[str, Scalar]]]:``" #: ../../source/how-to-upgrade-to-flower-1.0.rst:71 msgid "Custom strategies" -msgstr "" +msgstr "사용자 정의 전략" #: ../../source/how-to-upgrade-to-flower-1.0.rst:73 msgid "" -"The type of parameter ``failures`` has changed from " -"``List[BaseException]`` to ``List[Union[Tuple[ClientProxy, FitRes], " -"BaseException]]`` (in ``aggregate_fit``) and " -"``List[Union[Tuple[ClientProxy, EvaluateRes], BaseException]]`` (in " -"``aggregate_evaluate``)" +"The type of parameter ``failures`` has changed from ``List[BaseException]`` " +"to ``List[Union[Tuple[ClientProxy, FitRes], BaseException]]`` (in " +"``aggregate_fit``) and ``List[Union[Tuple[ClientProxy, EvaluateRes], " +"BaseException]]`` (in ``aggregate_evaluate``)" msgstr "" +"매개변수 ``failures``의 유형이 ``List[BaseException]``에서 " +"``List[Union[Tuple[ClientProxy], FitRes], BaseException]]``(``aggregate_fit``" +"에서) 및 ``List[Union[Tuple[ClientProxy], EvaluateRes], " +"BaseException]]``(``aggregate_evaluate``)로 변경되었습니다" #: ../../source/how-to-upgrade-to-flower-1.0.rst:74 msgid "" "The ``Strategy`` method ``evaluate`` now receives the current round of " "federated learning/evaluation as the first parameter:" msgstr "" +"이제 ``Strategy`` 메서드 ``evaluate``는 현재 federated 학습/평가 라운드를 첫 " +"번째 파라미터로 받습니다:" #: ../../source/how-to-upgrade-to-flower-1.0.rst:76 msgid "" "Flower 0.19: ``def evaluate(self, parameters: Parameters) -> " "Optional[Tuple[float, Dict[str, Scalar]]]:``" msgstr "" +"Flower 0.19: ``def evaluate(self, parameters: Parameters) -> " +"Optional[Tuple[float, Dict[str, Scalar]]]:``" #: ../../source/how-to-upgrade-to-flower-1.0.rst:77 msgid "" -"Flower 1.0: ``def evaluate(self, server_round: int, parameters: " -"Parameters) -> Optional[Tuple[float, Dict[str, Scalar]]]:``" +"Flower 1.0: ``def evaluate(self, server_round: int, parameters: Parameters) -" +"> Optional[Tuple[float, Dict[str, Scalar]]]:``" msgstr "" +"Flower 1.0: ``def evaluate(self, server_round: int, parameters: Parameters) -" +"> Optional[Tuple[float, Dict[str, Scalar]]]:``" #: ../../source/how-to-upgrade-to-flower-1.0.rst:80 msgid "Optional improvements" -msgstr "" +msgstr "선택적 개선 사항" #: ../../source/how-to-upgrade-to-flower-1.0.rst:82 msgid "" "Along with the necessary changes above, there are a number of potential " "improvements that just became possible:" msgstr "" +"위의 필수 변경 사항과 함께 방금 가능한 여러 가지 잠재적 개선 사항이 있습니다:" #: ../../source/how-to-upgrade-to-flower-1.0.rst:84 msgid "" "Remove \"placeholder\" methods from subclasses of ``Client`` or " -"``NumPyClient``. If you, for example, use server-side evaluation, then " -"empty placeholder implementations of ``evaluate`` are no longer " -"necessary." +"``NumPyClient``. If you, for example, use server-side evaluation, then empty " +"placeholder implementations of ``evaluate`` are no longer necessary." msgstr "" +"``Client`` 또는 ``NumPyClient``의 서브 클래스에서 \"placeholder\" 메서드를 제" +"거합니다. 예를 들어 서버 측 평가를 사용하는 경우 ``evaluate``의 빈 자리 표시" +"자 구현은 더 이상 필요하지 않습니다." #: ../../source/how-to-upgrade-to-flower-1.0.rst:85 msgid "" @@ -6983,69 +7294,84 @@ msgid "" "``start_simulation(..., config=flwr.server.ServerConfig(num_rounds=3, " "round_timeout=600.0), ...)``" msgstr "" +"``start_simulation``을 통해 라운드 타임아웃을 구성합니다: " +"``start_simulation(..., config=flwr.server.ServerConfig(num_rounds=3, " +"round_timeout=600.0), ...)``" #: ../../source/how-to-upgrade-to-flower-1.0.rst:89 #: ../../source/how-to-upgrade-to-flower-next.rst:317 msgid "Further help" -msgstr "" +msgstr "추가 도움말" #: ../../source/how-to-upgrade-to-flower-1.0.rst:91 msgid "" -"Most official `Flower code examples " -"`_ are already updated" -" to Flower 1.0, they can serve as a reference for using the Flower 1.0 " -"API. If there are further questions, `join the Flower Slack " -"`_ and use the channel ``#questions``." +"Most official `Flower code examples `_ are already updated to Flower 1.0, they can serve as a " +"reference for using the Flower 1.0 API. If there are further questions, " +"`join the Flower Slack `_ and use the channel " +"``#questions``." msgstr "" +"대부분의 공식 ``Flower code 예제 `_는 이미 Flower 1.0으로 업데이트되어 있으며, Flower 1.0 API를 사용" +"하기 위한 참고 자료로 사용할 수 있습니다. 더 궁금한 점이 있다면 ``플라워 슬" +"랙 `_에 가입하여 ``#questions`` 채널을 이용하" +"세요." #: ../../source/how-to-upgrade-to-flower-next.rst:2 msgid "Upgrade to Flower Next" -msgstr "" +msgstr "Flower Next 업그레이드" #: ../../source/how-to-upgrade-to-flower-next.rst:4 msgid "" -"Welcome to the migration guide for updating Flower to Flower Next! " -"Whether you're a seasoned user or just getting started, this guide will " -"help you smoothly transition your existing setup to take advantage of the" -" latest features and improvements in Flower Next, starting from version " -"1.8." +"Welcome to the migration guide for updating Flower to Flower Next! Whether " +"you're a seasoned user or just getting started, this guide will help you " +"smoothly transition your existing setup to take advantage of the latest " +"features and improvements in Flower Next, starting from version 1.8." msgstr "" +"Flower에서 Flower Next로의 업데이트를 위한 이동 가이드에 오신 것을 환영합니" +"다! 이 가이드는 숙련된 사용자든 이제 막 시작한 사용자든 상관없이 기존 설정을 " +"원활하게 전환하여 버전 1.8부터 Flower Next의 최신 기능 및 개선 사항을 활용할 " +"수 있도록 도와드립니다." #: ../../source/how-to-upgrade-to-flower-next.rst:9 msgid "" "This guide shows how to reuse pre-``1.8`` Flower code with minimum code " -"changes by using the *compatibility layer* in Flower Next. In another " -"guide, we will show how to run Flower Next end-to-end with pure Flower " -"Next APIs." +"changes by using the *compatibility layer* in Flower Next. In another guide, " +"we will show how to run Flower Next end-to-end with pure Flower Next APIs." msgstr "" +"이 가이드에서는 Flower Next의 *호환성 레이어*를 사용하여 최소한의 코드 변경으" +"로 ``1.8`` 이전의 Flower 코드를 재사용하는 방법을 보여줍니다. 다른 가이드에서" +"는 순수한 Flower Next API로 Flower Next를 end-to-end로 실행하는 방법을 보여드" +"리겠습니다." #: ../../source/how-to-upgrade-to-flower-next.rst:13 msgid "Let's dive in!" -msgstr "" +msgstr "자세히 알아봅시다!" #: ../../source/how-to-upgrade-to-flower-next.rst:48 msgid "" -"Here's how to update an existing installation of Flower to Flower Next " -"with ``pip``:" +"Here's how to update an existing installation of Flower to Flower Next with " +"``pip``:" msgstr "" +"기존에 설치된 Flower to Flower Next를 ``pip``으로 업데이트하는 방법은 다음과 " +"같습니다:" #: ../../source/how-to-upgrade-to-flower-next.rst:54 msgid "or if you need Flower Next with simulation:" -msgstr "" +msgstr "또는 시뮬레이션이 포함된 Flower Next가 필요한 경우:" #: ../../source/how-to-upgrade-to-flower-next.rst:61 msgid "" -"Ensure you set the following version constraint in your " -"``requirements.txt``" -msgstr "" +"Ensure you set the following version constraint in your ``requirements.txt``" +msgstr "``requirements.txt``에서 다음 버전 제약 조건을 설정했는지 확인하세요" #: ../../source/how-to-upgrade-to-flower-next.rst:71 msgid "or ``pyproject.toml``:" -msgstr "" +msgstr "또는 ``pyproject.toml``:" #: ../../source/how-to-upgrade-to-flower-next.rst:82 msgid "Using Poetry" -msgstr "" +msgstr "Poetry 사용" #: ../../source/how-to-upgrade-to-flower-next.rst:84 msgid "" @@ -7053,122 +7379,155 @@ msgid "" "(don't forget to delete ``poetry.lock`` via ``rm poetry.lock`` before " "running ``poetry install``)." msgstr "" +"``pyproject.toml``에서 ``flwr`` 의존성를 업데이트한 다음 다시 설치하세요(``" +"poetry install``을 실행하기 전에 ``rm poetry.lock``을 통해 ``poetry.lock``을 " +"삭제하는 것을 잊지 마세요)." #: ../../source/how-to-upgrade-to-flower-next.rst:86 msgid "" -"Ensure you set the following version constraint in your " -"``pyproject.toml``:" -msgstr "" +"Ensure you set the following version constraint in your ``pyproject.toml``:" +msgstr "``pyproject.toml``에 다음 버전 제약 조건을 설정했는지 확인하세요:" #: ../../source/how-to-upgrade-to-flower-next.rst:102 msgid "" "In Flower Next, the *infrastructure* and *application layers* have been " -"decoupled. Instead of starting a client in code via ``start_client()``, " -"you create a |clientapp_link|_ and start it via the command line. Instead" -" of starting a server in code via ``start_server()``, you create a " -"|serverapp_link|_ and start it via the command line. The long-running " +"decoupled. Instead of starting a client in code via ``start_client()``, you " +"create a |clientapp_link|_ and start it via the command line. Instead of " +"starting a server in code via ``start_server()``, you create a |" +"serverapp_link|_ and start it via the command line. The long-running " "components of server and client are called SuperLink and SuperNode. The " -"following non-breaking changes that require manual updates and allow you " -"to run your project both in the traditional way and in the Flower Next " -"way:" +"following non-breaking changes that require manual updates and allow you to " +"run your project both in the traditional way and in the Flower Next way:" msgstr "" +"Flower Next에서는 *infrastructure*와 *application layers*가 분리되었습니다. " +"코드에서 ``start_client()``를 통해 클라이언트를 시작하는 대신, 명령줄을 통해 " +"|clientapp_link|_를 생성하여 시작합니다. 코드에서 ``start_server()``를 통해 " +"서버를 시작하는 대신 |serverapp_link|_를 생성하고 명령줄을 통해 서버를 시작합" +"니다. 서버와 클라이언트의 장기 실행 컴포넌트를 SuperLink와 SuperNode라고 합니" +"다. 수동 업데이트가 필요하지 않고 기존 방식과 Flower Next 방식 모두에서 프로" +"젝트를 실행할 수 있는 non-breaking 변경 사항은 다음과 같습니다:" #: ../../source/how-to-upgrade-to-flower-next.rst:109 msgid "|clientapp_link|_" -msgstr "" +msgstr "|clientapp_link|_" #: ../../source/how-to-upgrade-to-flower-next.rst:110 msgid "" -"Wrap your existing client with |clientapp_link|_ instead of launching it " -"via |startclient_link|_. Here's an example:" +"Wrap your existing client with |clientapp_link|_ instead of launching it via " +"|startclient_link|_. Here's an example:" msgstr "" +"|clientapp_link|_를 통해 실행하는 대신 기존 클라이언트를 |clientapp_link|_로 " +"래핑하세요. 다음은 예시입니다:" #: ../../source/how-to-upgrade-to-flower-next.rst:132 msgid "|serverapp_link|_" -msgstr "" +msgstr "|serverapp_link|_" #: ../../source/how-to-upgrade-to-flower-next.rst:133 msgid "" -"Wrap your existing strategy with |serverapp_link|_ instead of starting " -"the server via |startserver_link|_. Here's an example:" +"Wrap your existing strategy with |serverapp_link|_ instead of starting the " +"server via |startserver_link|_. Here's an example:" msgstr "" +"서버를 시작하려면 |startserver_link|_를 통해 서버를 시작하는 대신 기존 전략" +"을 |serverapp_link|_로 래핑하세요. 다음은 예시입니다:" #: ../../source/how-to-upgrade-to-flower-next.rst:154 msgid "Deployment" -msgstr "" +msgstr "배포" #: ../../source/how-to-upgrade-to-flower-next.rst:155 msgid "" -"Run the ``SuperLink`` using |flowernext_superlink_link|_ before running, " -"in sequence, |flowernext_clientapp_link|_ (2x) and " -"|flowernext_serverapp_link|_. There is no need to execute `client.py` and" -" `server.py` as Python scripts." +"Run the ``SuperLink`` using |flowernext_superlink_link|_ before running, in " +"sequence, |flowernext_clientapp_link|_ (2x) and |flowernext_serverapp_link|" +"_. There is no need to execute `client.py` and `server.py` as Python scripts." msgstr "" +"실행하기 전에 |flowernext_superlink_link|_를 사용하여 ``SuperLink``를 실행한 " +"후 |flowernext_clientapp_link|_(2회) 및 |flowernext_serverapp_link|_를 " +"순서대로 실행합니다. 'client.py'와 'server.py'를 Python 스크립트로 실행할 " +"필요는 없습니다." #: ../../source/how-to-upgrade-to-flower-next.rst:158 msgid "" -"Here's an example to start the server without HTTPS (only for " -"prototyping):" +"Here's an example to start the server without HTTPS (only for prototyping):" msgstr "" +"다음은 HTTPS 없이 서버를 시작하는 예제입니다(프로토타이핑용으로만 사용):" #: ../../source/how-to-upgrade-to-flower-next.rst:174 msgid "" -"Here's another example to start with HTTPS. Use the ``--ssl-ca-" -"certfile``, ``--ssl-certfile``, and ``--ssl-keyfile`` command line " -"options to pass paths to (CA certificate, server certificate, and server " -"private key)." +"Here's another example to start with HTTPS. Use the ``--ssl-ca-certfile``, " +"``--ssl-certfile``, and ``--ssl-keyfile`` command line options to pass paths " +"to (CA certificate, server certificate, and server private key)." msgstr "" +"다음은 HTTPS로 시작하는 또 다른 예제입니다. '`--ssl-ca-certfile``, '`--ssl-" +"certfile``, '`--ssl-keyfile`` 명령줄 옵션을 사용하여 (CA 인증서, 서버 인증서 " +"및 서버 개인 키)의 경로를 전달합니다." #: ../../source/how-to-upgrade-to-flower-next.rst:201 msgid "Simulation in CLI" -msgstr "" +msgstr "CLI 시뮬레이션" #: ../../source/how-to-upgrade-to-flower-next.rst:202 msgid "" -"Wrap your existing client and strategy with |clientapp_link|_ and " -"|serverapp_link|_, respectively. There is no need to use |startsim_link|_" -" anymore. Here's an example:" +"Wrap your existing client and strategy with |clientapp_link|_ and |" +"serverapp_link|_, respectively. There is no need to use |startsim_link|_ " +"anymore. Here's an example:" msgstr "" +"기존 클라이언트와 전략을 각각 |clientapp_link|_와 |serverapp_link|_로 래핑하" +"세요. 더 이상 |startsim_link|_를 사용할 필요가 없습니다. 다음은 예시입니다:" #: ../../source/how-to-upgrade-to-flower-next.rst:232 msgid "" "Run |flower_simulation_link|_ in CLI and point to the ``server_app`` / " -"``client_app`` object in the code instead of executing the Python script." -" Here's an example (assuming the ``server_app`` and ``client_app`` " -"objects are in a ``sim.py`` module):" +"``client_app`` object in the code instead of executing the Python script. " +"Here's an example (assuming the ``server_app`` and ``client_app`` objects " +"are in a ``sim.py`` module):" msgstr "" +"CLI에서 |flower_simulation_link|_를 실행하고 Python 스크립트를 실행하는 대신 " +"코드에서 ``server_app`` / ``client_app`` 개체를 가리키세요. 다음은 예제입니다" +"(``server_app`` 및 ``client_app`` 객체가 ``sim.py`` 모듈에 있다고 가정):" #: ../../source/how-to-upgrade-to-flower-next.rst:249 msgid "" "Set default resources for each |clientapp_link|_ using the ``--backend-" -"config`` command line argument instead of setting the " -"``client_resources`` argument in |startsim_link|_. Here's an example:" +"config`` command line argument instead of setting the ``client_resources`` " +"argument in |startsim_link|_. Here's an example:" msgstr "" +"|startsim_link|_에서 ``client_resources`` 인수를 설정하는 대신 ``--backend-" +"config`` 명령줄 인수를 사용하여 각 |clientapp_link|_에 대한 기본 리소스를 설" +"정하세요. 다음은 예시입니다:" #: ../../source/how-to-upgrade-to-flower-next.rst:275 msgid "Simulation in a Notebook" -msgstr "" +msgstr "Notebook에서 시뮬레이션" #: ../../source/how-to-upgrade-to-flower-next.rst:276 msgid "" -"Run |runsim_link|_ in your notebook instead of |startsim_link|_. Here's " -"an example:" +"Run |runsim_link|_ in your notebook instead of |startsim_link|_. Here's an " +"example:" msgstr "" +"notebook에서 |startsim_link|_ 대신 |runsim_link|_를 실행하세요. 다음은 예시입" +"니다:" #: ../../source/how-to-upgrade-to-flower-next.rst:319 msgid "" -"Some official `Flower code examples `_ " -"are already updated to Flower Next so they can serve as a reference for " -"using the Flower Next API. If there are further questions, `join the " -"Flower Slack `_ and use the channel " -"``#questions``. You can also `participate in Flower Discuss " -"`_ where you can find us answering questions," -" or share and learn from others about migrating to Flower Next." -msgstr "" +"Some official `Flower code examples `_ are " +"already updated to Flower Next so they can serve as a reference for using " +"the Flower Next API. If there are further questions, `join the Flower Slack " +"`_ and use the channel ``#questions``. You " +"can also `participate in Flower Discuss `_ where " +"you can find us answering questions, or share and learn from others about " +"migrating to Flower Next." +msgstr "" +"일부 공식 ``Flower 코드 예제 `_는 이미 플라" +"워 넥스트에 업데이트되어 있으므로 플라워 넥스트 API를 사용하는 데 참고할 수 " +"있습니다. 더 궁금한 점이 있다면 ``플라워 슬랙 `_에 가입하고 ``#questions`` 채널을 이용하세요. 또한, ``Flower Discuss " +"`_에 참여하여 질문에 대한 답변을 확인하거나 다른 " +"사람들과 Flower Next로의 이동에 대해 공유하고 배울 수 있습니다." #: ../../source/how-to-upgrade-to-flower-next.rst:325 msgid "Important" -msgstr "" +msgstr "중요" #: ../../source/how-to-upgrade-to-flower-next.rst:328 msgid "" @@ -7176,322 +7535,399 @@ msgid "" "periodically updating this guide. Please feel free to share any feedback " "with us!" msgstr "" +"Flower Next는 빠른 속도로 지속적으로 개선되고 있으므로 이 가이드는 주기적으" +"로 업데이트될 예정입니다. 피드백이 있으면 언제든지 공유해 주세요!" #: ../../source/how-to-upgrade-to-flower-next.rst:334 msgid "Happy migrating! 🚀" -msgstr "" +msgstr "행복한 마이그레이션! 🚀" #: ../../source/how-to-use-built-in-mods.rst:2 msgid "Use Built-in Mods" -msgstr "" +msgstr "기본 제공 모드 사용" #: ../../source/how-to-use-built-in-mods.rst:4 msgid "" -"**Note: This tutorial covers experimental features. The functionality and" -" interfaces may change in future versions.**" +"**Note: This tutorial covers experimental features. The functionality and " +"interfaces may change in future versions.**" msgstr "" +"**참고: 이 튜토리얼은 실험적인 기능을 다룹니다. 기능 및 인터페이스는 향후 버" +"전에서 변경될 수 있습니다.**" #: ../../source/how-to-use-built-in-mods.rst:6 msgid "" -"In this tutorial, we will learn how to utilize built-in mods to augment " -"the behavior of a ``ClientApp``. Mods (sometimes also called Modifiers) " -"allow us to perform operations before and after a task is processed in " -"the ``ClientApp``." +"In this tutorial, we will learn how to utilize built-in mods to augment the " +"behavior of a ``ClientApp``. Mods (sometimes also called Modifiers) allow us " +"to perform operations before and after a task is processed in the " +"``ClientApp``." msgstr "" +"이 튜토리얼에서는 내장 모드를 활용하여 ``ClientApp``의 동작을 보강하는 방법" +"을 배우겠습니다. Mods(Modifiers라고도 함)를 사용하면 ``ClientApp``에서 작업" +"이 처리되기 전과 후에 작업을 수행할 수 있습니다." #: ../../source/how-to-use-built-in-mods.rst:9 msgid "What are Mods?" -msgstr "" +msgstr "Mods란 무엇인가요?" #: ../../source/how-to-use-built-in-mods.rst:11 msgid "" -"A Mod is a callable that wraps around a ``ClientApp``. It can manipulate " -"or inspect the incoming ``Message`` and the resulting outgoing " -"``Message``. The signature for a ``Mod`` is as follows:" +"A Mod is a callable that wraps around a ``ClientApp``. It can manipulate or " +"inspect the incoming ``Message`` and the resulting outgoing ``Message``. The " +"signature for a ``Mod`` is as follows:" msgstr "" +"Mod는 ``ClientApp``을 감싸는 콜러블입니다. 들어오는 ``Message``와 그 결과로 " +"나가는 ``Message``를 조작하거나 검사할 수 있습니다. ``Mod``의 시그니처는 다음" +"과 같습니다:" #: ../../source/how-to-use-built-in-mods.rst:18 msgid "A typical mod function might look something like this:" -msgstr "" +msgstr "일반적인 mod 함수는 다음과 같은 모습일 수 있습니다:" #: ../../source/how-to-use-built-in-mods.rst:31 msgid "Using Mods" -msgstr "" +msgstr "Mods 사용" #: ../../source/how-to-use-built-in-mods.rst:33 msgid "To use mods in your ``ClientApp``, you can follow these steps:" -msgstr "" +msgstr "``ClientApp``에서 mods를 사용하려면 다음 단계를 따르세요:" #: ../../source/how-to-use-built-in-mods.rst:36 msgid "1. Import the required mods" -msgstr "" +msgstr "1. 필요한 mods를 가져옵니다" #: ../../source/how-to-use-built-in-mods.rst:38 msgid "First, import the built-in mod you intend to use:" -msgstr "" +msgstr "먼저 사용하려는 기본 제공 mod를 가져옵니다:" #: ../../source/how-to-use-built-in-mods.rst:46 msgid "2. Define your client function" -msgstr "" +msgstr "2. 클라이언트 기능 정의" #: ../../source/how-to-use-built-in-mods.rst:48 msgid "" "Define your client function (``client_fn``) that will be wrapped by the " "mod(s):" -msgstr "" +msgstr "mod(s)로 래핑할 클라이언트 함수('``client_fn``)를 정의합니다:" #: ../../source/how-to-use-built-in-mods.rst:57 msgid "3. Create the ``ClientApp`` with mods" -msgstr "" +msgstr "3. mods로 ``ClientApp``을 생성합니다" #: ../../source/how-to-use-built-in-mods.rst:59 msgid "" "Create your ``ClientApp`` and pass the mods as a list to the ``mods`` " "argument. The order in which you provide the mods matters:" msgstr "" +"``ClientApp``을 생성하고 mods를 ``mods`` argument에 목록으로 전달합니다. mods" +"를 제공하는 순서가 중요합니다:" #: ../../source/how-to-use-built-in-mods.rst:72 msgid "Order of execution" -msgstr "" +msgstr "실행 순서" #: ../../source/how-to-use-built-in-mods.rst:74 msgid "" "When the ``ClientApp`` runs, the mods are executed in the order they are " "provided in the list:" -msgstr "" +msgstr "``ClientApp``이 실행되면 목록에 제공된 순서대로 모드가 실행됩니다:" #: ../../source/how-to-use-built-in-mods.rst:76 msgid "``example_mod_1`` (outermost mod)" -msgstr "" +msgstr "``example_mod_1``(가장 바깥쪽 mod)" #: ../../source/how-to-use-built-in-mods.rst:77 msgid "``example_mod_2`` (next mod)" -msgstr "" +msgstr "``example_mod_2`` (다음 mod)" #: ../../source/how-to-use-built-in-mods.rst:78 msgid "" "Message handler (core function that handles the incoming ``Message`` and " "returns the outgoing ``Message``)" msgstr "" +"Message handler(들어오는 ``Message``를 처리하고 나가는 ``Message``를 반환하" +"는 핵심 함수)" #: ../../source/how-to-use-built-in-mods.rst:79 msgid "``example_mod_2`` (on the way back)" -msgstr "" +msgstr "``example_mod_2``(돌아가는 방법)" #: ../../source/how-to-use-built-in-mods.rst:80 msgid "``example_mod_1`` (outermost mod on the way back)" -msgstr "" +msgstr "``example_mod_1``(돌아가는 방법에 가장 바깥쪽 모드)" #: ../../source/how-to-use-built-in-mods.rst:82 msgid "" -"Each mod has a chance to inspect and modify the incoming ``Message`` " -"before passing it to the next mod, and likewise with the outgoing " -"``Message`` before returning it up the stack." +"Each mod has a chance to inspect and modify the incoming ``Message`` before " +"passing it to the next mod, and likewise with the outgoing ``Message`` " +"before returning it up the stack." msgstr "" +"각 mod는 다음 mod로 전달하기 전에 들어오는 ``Message``를 검사하고 수정할 기회" +"가 있으며, 스택 위로 반환하기 전에 나가는 ``Message``도 마찬가지로 검사하고 " +"수정할 수 있습니다." #: ../../source/how-to-use-built-in-mods.rst:87 msgid "" "By following this guide, you have learned how to effectively use mods to " -"enhance your ``ClientApp``'s functionality. Remember that the order of " -"mods is crucial and affects how the input and output are processed." +"enhance your ``ClientApp``'s functionality. Remember that the order of mods " +"is crucial and affects how the input and output are processed." msgstr "" +"이 가이드를 따라 mods를 효과적으로 사용하여 ``ClientApp``의 기능을 향상시키" +"는 방법을 배웠습니다. mods 순서는 매우 중요하며 입력과 출력이 처리되는 방식" +"에 영향을 미친다는 점을 기억하세요." #: ../../source/how-to-use-built-in-mods.rst:89 msgid "Enjoy building a more robust and flexible ``ClientApp`` with mods!" -msgstr "" +msgstr "Mods를 통해 더욱 강력하고 유연한 ``ClientApp``을 구축해 보세요!" #: ../../source/how-to-use-differential-privacy.rst:2 msgid "Use Differential Privacy" -msgstr "" +msgstr "차분 개인정보 보호 사용" #: ../../source/how-to-use-differential-privacy.rst:3 msgid "" -"This guide explains how you can utilize differential privacy in the " -"Flower framework. If you are not yet familiar with differential privacy, " -"you can refer to :doc:`explanation-differential-privacy`." +"This guide explains how you can utilize differential privacy in the Flower " +"framework. If you are not yet familiar with differential privacy, you can " +"refer to :doc:`explanation-differential-privacy`." msgstr "" +"이 가이드에서는 Flower 프레임워크에서 차분 개인정보 보호 기능을 활용하는 방법" +"을 설명합니다. 차분 개인정보 보호에 대해 아직 익숙하지 않은 경우 :doc:" +"`explanation-differential-privacy`를 참조하세요." #: ../../source/how-to-use-differential-privacy.rst:7 msgid "" "Differential Privacy in Flower is in a preview phase. If you plan to use " -"these features in a production environment with sensitive data, feel free" -" contact us to discuss your requirements and to receive guidance on how " -"to best use these features." +"these features in a production environment with sensitive data, feel free " +"contact us to discuss your requirements and to receive guidance on how to " +"best use these features." msgstr "" +"Flower의 차분 개인정보 보호는 현재 프리뷰 단계에 있습니다. 민감한 데이터가 있" +"는 프로덕션 환경에서 이러한 기능을 사용할 계획이라면 언제든지 문의하여 요구 " +"사항을 논의하고 이러한 기능을 가장 잘 사용하는 방법에 대한 안내를 받으세요." #: ../../source/how-to-use-differential-privacy.rst:12 msgid "" -"This approach consists of two seprate phases: clipping of the updates and" -" adding noise to the aggregated model. For the clipping phase, Flower " -"framework has made it possible to decide whether to perform clipping on " -"the server side or the client side." +"This approach consists of two seprate phases: clipping of the updates and " +"adding noise to the aggregated model. For the clipping phase, Flower " +"framework has made it possible to decide whether to perform clipping on the " +"server side or the client side." msgstr "" +"이 접근 방식은 업데이트 클리핑과 집계된 모델에 노이즈 추가라는 두 가지 단계" +"로 구성됩니다. 클리핑 단계의 경우, Flower 프레임워크는 클리핑을 서버 측에서 " +"수행할지 클라이언트 측에서 수행할지 결정할 수 있도록 했습니다." #: ../../source/how-to-use-differential-privacy.rst:15 msgid "" "**Server-side Clipping**: This approach has the advantage of the server " "enforcing uniform clipping across all clients' updates and reducing the " "communication overhead for clipping values. However, it also has the " -"disadvantage of increasing the computational load on the server due to " -"the need to perform the clipping operation for all clients." +"disadvantage of increasing the computational load on the server due to the " +"need to perform the clipping operation for all clients." msgstr "" +"**Server-side Clipping**: 이 방식은 서버가 모든 클라이언트의 업데이트에 대해 " +"균일한 클리핑을 적용하고 클리핑 값에 대한 통신 오버헤드를 줄일 수 있다는 장점" +"이 있습니다. 하지만 모든 클라이언트에 대해 클리핑 작업을 수행해야 하기 때문" +"에 서버의 계산 부하가 증가한다는 단점도 있습니다." #: ../../source/how-to-use-differential-privacy.rst:16 msgid "" -"**Client-side Clipping**: This approach has the advantage of reducing the" -" computational overhead on the server. However, it also has the " -"disadvantage of lacking centralized control, as the server has less " -"control over the clipping process." +"**Client-side Clipping**: This approach has the advantage of reducing the " +"computational overhead on the server. However, it also has the disadvantage " +"of lacking centralized control, as the server has less control over the " +"clipping process." msgstr "" +"**Client-side Clipping**: 이 방식은 서버의 계산 오버헤드를 줄일 수 있다는 장" +"점이 있습니다. 하지만 서버가 클리핑 프로세스에 대한 통제력이 떨어지기 때문에 " +"centralized 제어가 부족하다는 단점도 있습니다." #: ../../source/how-to-use-differential-privacy.rst:21 msgid "Server-side Clipping" -msgstr "" +msgstr "서버 측 클리핑" #: ../../source/how-to-use-differential-privacy.rst:22 msgid "" "For central DP with server-side clipping, there are two :code:`Strategy` " "classes that act as wrappers around the actual :code:`Strategy` instance " -"(for example, :code:`FedAvg`). The two wrapper classes are " -":code:`DifferentialPrivacyServerSideFixedClipping` and " -":code:`DifferentialPrivacyServerSideAdaptiveClipping` for fixed and " -"adaptive clipping." +"(for example, :code:`FedAvg`). The two wrapper classes are :code:" +"`DifferentialPrivacyServerSideFixedClipping` and :code:" +"`DifferentialPrivacyServerSideAdaptiveClipping` for fixed and adaptive " +"clipping." msgstr "" +"서버 측 클리핑이 있는 중앙 DP의 경우, 실제 :code:`Strategy` 인스턴스를 감싸" +"는 래퍼 역할을 하는 두 개의 :code:`Strategy` 클래스가 있습니다(예: :code:" +"`FedAvg`). 두 개의 래퍼 클래스는 고정 및 적응형 클리핑을 위한 :code:" +"`DifferentialPrivacyServerSideFixedClipping`과 :code:" +"`DifferentialPrivacyServerSideAdaptiveClipping`입니다." #: ../../source/how-to-use-differential-privacy.rst:-1 msgid "server side clipping" -msgstr "" +msgstr "서버 측 클리핑" #: ../../source/how-to-use-differential-privacy.rst:31 msgid "" -"The code sample below enables the :code:`FedAvg` strategy to use server-" -"side fixed clipping using the " -":code:`DifferentialPrivacyServerSideFixedClipping` wrapper class. The " -"same approach can be used with " -":code:`DifferentialPrivacyServerSideAdaptiveClipping` by adjusting the " +"The code sample below enables the :code:`FedAvg` strategy to use server-side " +"fixed clipping using the :code:`DifferentialPrivacyServerSideFixedClipping` " +"wrapper class. The same approach can be used with :code:" +"`DifferentialPrivacyServerSideAdaptiveClipping` by adjusting the " "corresponding input parameters." msgstr "" +"아래 코드 샘플은 :code:`FedAvg` 전략이 :code:" +"`DifferentialPrivacyServerSideFixedClipping` 래퍼 클래스를 사용하여 서버 측 " +"고정 클리핑을 사용할 수 있도록 합니다. 해당 입력 매개변수를 조정하여 :code:" +"`DifferentialPrivacyServerSideAdaptiveClipping`과 동일한 접근 방식을 사용할 " +"수 있습니다." #: ../../source/how-to-use-differential-privacy.rst:52 msgid "Client-side Clipping" -msgstr "" +msgstr "클라이언트 측 클리핑" #: ../../source/how-to-use-differential-privacy.rst:53 msgid "" "For central DP with client-side clipping, the server sends the clipping " -"value to selected clients on each round. Clients can use existing Flower " -":code:`Mods` to perform the clipping. Two mods are available for fixed " -"and adaptive client-side clipping: :code:`fixedclipping_mod` and " -":code:`adaptiveclipping_mod` with corresponding server-side wrappers " -":code:`DifferentialPrivacyClientSideFixedClipping` and " -":code:`DifferentialPrivacyClientSideAdaptiveClipping`." -msgstr "" +"value to selected clients on each round. Clients can use existing Flower :" +"code:`Mods` to perform the clipping. Two mods are available for fixed and " +"adaptive client-side clipping: :code:`fixedclipping_mod` and :code:" +"`adaptiveclipping_mod` with corresponding server-side wrappers :code:" +"`DifferentialPrivacyClientSideFixedClipping` and :code:" +"`DifferentialPrivacyClientSideAdaptiveClipping`." +msgstr "" +"클라이언트 측 클리핑이 있는 중앙 DP의 경우 서버는 각 라운드마다 선택한 클라이" +"언트에 클리핑 값을 보냅니다. 클라이언트는 기존 Flower :code:`Mods`를 사용하" +"여 클리핑을 수행할 수 있습니다. 고정 및 적응형 클라이언트 측 클리핑에는 두 가" +"지 모드를 사용할 수 있습니다: :code:`fixedclipping_mod` 및 :code:" +"`adaptiveclipping_mod`와 해당 서버 측 래퍼 :code:" +"`DifferentialPrivacyClientSideFixedClipping` 및 :code:" +"`DifferentialPrivacyClientSideAdaptiveClipping`이 있습니다." #: ../../source/how-to-use-differential-privacy.rst:-1 msgid "client side clipping" -msgstr "" +msgstr "클라이언트 측 클리핑" #: ../../source/how-to-use-differential-privacy.rst:63 msgid "" "The code sample below enables the :code:`FedAvg` strategy to use " -"differential privacy with client-side fixed clipping using both the " -":code:`DifferentialPrivacyClientSideFixedClipping` wrapper class and, on " -"the client, :code:`fixedclipping_mod`:" +"differential privacy with client-side fixed clipping using both the :code:" +"`DifferentialPrivacyClientSideFixedClipping` wrapper class and, on the " +"client, :code:`fixedclipping_mod`:" msgstr "" +"아래 코드 샘플은 :code:`FedAvg` 전략이 클라이언트 측 고정 클리핑과 함께 차분 " +"프라이버시를 사용할 수 있도록 :code:" +"`DifferentialPrivacyClientSideFixedClipping` 래퍼 클래스와 클라이언트에서 :" +"code:`fixedclipping_mod`를 모두 사용하도록 합니다:" #: ../../source/how-to-use-differential-privacy.rst:80 msgid "" -"In addition to the server-side strategy wrapper, the :code:`ClientApp` " -"needs to configure the matching :code:`fixedclipping_mod` to perform the " -"client-side clipping:" +"In addition to the server-side strategy wrapper, the :code:`ClientApp` needs " +"to configure the matching :code:`fixedclipping_mod` to perform the client-" +"side clipping:" msgstr "" +"서버 측 전략 래퍼 외에도 클라이언트 측 클리핑을 수행하려면 :code:`ClientApp`" +"이 일치하는 :code:`fixedclipping_mod`를 구성해야 합니다:" #: ../../source/how-to-use-differential-privacy.rst:97 msgid "" -"To utilize local differential privacy (DP) and add noise to the client " -"model parameters before transmitting them to the server in Flower, you " -"can use the `LocalDpMod`. The following hyperparameters need to be set: " -"clipping norm value, sensitivity, epsilon, and delta." +"To utilize local differential privacy (DP) and add noise to the client model " +"parameters before transmitting them to the server in Flower, you can use the " +"`LocalDpMod`. The following hyperparameters need to be set: clipping norm " +"value, sensitivity, epsilon, and delta." msgstr "" +"로컬 차분 프라이버시(DP)를 활용하고 클라이언트 모델 파라미터를 서버로 전송하" +"기 전에 노이즈를 추가하려면 `LocalDpMod`를 사용하면 됩니다. 클리핑 노멀 값, " +"감도, 엡실론, 델타 등의 하이퍼파라미터를 설정해야 합니다." #: ../../source/how-to-use-differential-privacy.rst:-1 msgid "local DP mod" -msgstr "" +msgstr "로컬 DP mod" #: ../../source/how-to-use-differential-privacy.rst:104 msgid "Below is a code example that shows how to use :code:`LocalDpMod`:" -msgstr "" +msgstr "다음은 :code:`LocalDpMod`를 사용하는 방법을 보여주는 코드 예시입니다:" #: ../../source/how-to-use-differential-privacy.rst:122 msgid "" -"Please note that the order of mods, especially those that modify " -"parameters, is important when using multiple modifiers. Typically, " -"differential privacy (DP) modifiers should be the last to operate on " -"parameters." +"Please note that the order of mods, especially those that modify parameters, " +"is important when using multiple modifiers. Typically, differential privacy " +"(DP) modifiers should be the last to operate on parameters." msgstr "" +"여러 개의 수정자를 사용할 때는 수정자, 특히 매개변수를 수정하는 수정자의 순서" +"가 중요하다는 점에 유의하세요. 일반적으로 차분 프라이버시(DP) 수정자는 매개변" +"수에서 가장 마지막에 작동해야 합니다." #: ../../source/how-to-use-differential-privacy.rst:125 msgid "Local Training using Privacy Engines" -msgstr "" +msgstr "Privacy Engines을 사용한 로컬 훈련" #: ../../source/how-to-use-differential-privacy.rst:126 msgid "" -"For ensuring data instance-level privacy during local model training on " -"the client side, consider leveraging privacy engines such as Opacus and " -"TensorFlow Privacy. For examples of using Flower with these engines, " -"please refer to the Flower examples directory (`Opacus " -"`_, `Tensorflow" -" Privacy `_)." +"For ensuring data instance-level privacy during local model training on the " +"client side, consider leveraging privacy engines such as Opacus and " +"TensorFlow Privacy. For examples of using Flower with these engines, please " +"refer to the Flower examples directory (`Opacus `_, `Tensorflow Privacy `_)." msgstr "" +"클라이언트 측에서 로컬 모델을 훈련하는 동안 데이터 인스턴스 수준의 개인 정보 " +"보호를 보장하려면 Opacus 및 TensorFlow Privacy와 같은 개인 정보 보호 엔진을 " +"활용하는 것을 고려하세요. 이러한 엔진과 함께 Flower를 사용하는 예제는 Flower " +"examples directory (`Opacus `_, `Tensorflow Privacy `_)를 참조하세요." #: ../../source/how-to-use-strategies.rst:2 msgid "Use strategies" -msgstr "" +msgstr "전략 사용하기" #: ../../source/how-to-use-strategies.rst:4 msgid "" -"Flower allows full customization of the learning process through the " -":code:`Strategy` abstraction. A number of built-in strategies are " -"provided in the core framework." +"Flower allows full customization of the learning process through the :code:" +"`Strategy` abstraction. A number of built-in strategies are provided in the " +"core framework." msgstr "" +"Flower는 :code:`Strategy` abstraction를 통해 학습 과정을 완전히 사용자 정의" +"할 수 있습니다. 핵심 프레임워크에는 여러 가지 기본 제공 전략이 제공됩니다." #: ../../source/how-to-use-strategies.rst:6 msgid "" -"There are three ways to customize the way Flower orchestrates the " -"learning process on the server side:" +"There are three ways to customize the way Flower orchestrates the learning " +"process on the server side:" msgstr "" +"서버 측에서 Flower가 학습 과정을 조율하는 방식을 사용자 지정하는 방법에는 세 " +"가지가 있습니다:" #: ../../source/how-to-use-strategies.rst:8 msgid "Use an existing strategy, for example, :code:`FedAvg`" -msgstr "" +msgstr "기존 전략(예: :code:`FedAvg`)을 사용합니다" #: ../../source/how-to-use-strategies.rst:9 #: ../../source/how-to-use-strategies.rst:40 msgid "Customize an existing strategy with callback functions" -msgstr "" +msgstr "콜백 함수로 기존 전략 사용자 지정" #: ../../source/how-to-use-strategies.rst:10 #: ../../source/how-to-use-strategies.rst:87 msgid "Implement a novel strategy" -msgstr "" +msgstr "새로운 전략 구현" #: ../../source/how-to-use-strategies.rst:14 msgid "Use an existing strategy" -msgstr "" +msgstr "기존 전략 사용" #: ../../source/how-to-use-strategies.rst:16 msgid "" -"Flower comes with a number of popular federated learning strategies " -"built-in. A built-in strategy can be instantiated as follows:" +"Flower comes with a number of popular federated learning strategies built-" +"in. A built-in strategy can be instantiated as follows:" msgstr "" +"Flower에는 여러 가지 인기 있는 연합 학습 전략이 기본으로 제공됩니다. 기본 " +"제공 전략은 다음과 같이 인스턴스화할 수 있습니다:" #: ../../source/how-to-use-strategies.rst:25 msgid "" -"This creates a strategy with all parameters left at their default values " -"and passes it to the :code:`start_server` function. It is usually " -"recommended to adjust a few parameters during instantiation:" +"This creates a strategy with all parameters left at their default values and " +"passes it to the :code:`start_server` function. It is usually recommended to " +"adjust a few parameters during instantiation:" msgstr "" +"이렇게 하면 모든 매개변수가 기본값으로 유지된 전략이 생성되어 :code:" +"`start_server` 함수에 전달됩니다. 일반적으로 인스턴스화 중에 몇 가지 매개변수" +"를 조정하는 것이 좋습니다:" #: ../../source/how-to-use-strategies.rst:42 msgid "" @@ -7499,118 +7935,138 @@ msgid "" "Callback functions allow strategies to call user-provided code during " "execution." msgstr "" +"기존 전략은 동작을 사용자 지정하는 여러 가지 방법을 제공합니다. 콜백 함수를 " +"사용하면 전략이 실행 중에 사용자가 제공한 코드를 호출할 수 있습니다." #: ../../source/how-to-use-strategies.rst:45 msgid "Configuring client fit and client evaluate" -msgstr "" +msgstr "클라이언트 적합성 및 클라이언트 평가 구성" #: ../../source/how-to-use-strategies.rst:47 msgid "" "The server can pass new configuration values to the client each round by " -"providing a function to :code:`on_fit_config_fn`. The provided function " -"will be called by the strategy and must return a dictionary of " -"configuration key values pairs that will be sent to the client. It must " -"return a dictionary of arbitrary configuration values :code:`client.fit`" -" and :code:`client.evaluate` functions during each round of federated " -"learning." -msgstr "" +"providing a function to :code:`on_fit_config_fn`. The provided function will " +"be called by the strategy and must return a dictionary of configuration key " +"values pairs that will be sent to the client. It must return a dictionary of " +"arbitrary configuration values :code:`client.fit` and :code:`client." +"evaluate` functions during each round of federated learning." +msgstr "" +"서버는 매 라운드마다 새로운 설정 값을 클라이언트에 전달하기 위해 " +":code:`on_fit_config_fn`에 함수를 제공할 수 있습니다. 제공된 함수는 전략에 " +"의해 호출되며 클라이언트에 전송될 구성 키 값 쌍의 dictionary를 반환해야 " +"합니다. 연합 학습의 각 라운드 동안 임의의 구성 값 dictionary인 :code:`client." +"fit` 및 :code:`client.evaluate` 함수를 반환해야 합니다." #: ../../source/how-to-use-strategies.rst:75 msgid "" "The :code:`on_fit_config_fn` can be used to pass arbitrary configuration " "values from server to client, and poetentially change these values each " -"round, for example, to adjust the learning rate. The client will receive " -"the dictionary returned by the :code:`on_fit_config_fn` in its own " -":code:`client.fit()` function." +"round, for example, to adjust the learning rate. The client will receive the " +"dictionary returned by the :code:`on_fit_config_fn` in its own :code:`client." +"fit()` function." msgstr "" +":code:`on_fit_config_fn`은 서버에서 클라이언트로 임의의 구성 값을 전달하고, " +"예를 들어 학습 속도를 조정하기 위해 매 라운드마다 이 값을 잠재적으로 변경하" +"는 데 사용할 수 있습니다. 클라이언트는 자체 :code:`client.fit()` 함수에서 :" +"code:`on_fit_config_fn`이 반환한 dictionary를 받습니다." #: ../../source/how-to-use-strategies.rst:78 msgid "" -"Similar to :code:`on_fit_config_fn`, there is also " -":code:`on_evaluate_config_fn` to customize the configuration sent to " -":code:`client.evaluate()`" +"Similar to :code:`on_fit_config_fn`, there is also :code:" +"`on_evaluate_config_fn` to customize the configuration sent to :code:`client." +"evaluate()`" msgstr "" +":code:`on_fit_config_fn`과 유사하게, :code:`client.evaluate()`로 전송되는 구" +"성을 사용자 지정하는 :code:`on_evaluate_config_fn`도 있습니다" #: ../../source/how-to-use-strategies.rst:81 msgid "Configuring server-side evaluation" -msgstr "" +msgstr "서버 측 평가 구성" #: ../../source/how-to-use-strategies.rst:83 msgid "" -"Server-side evaluation can be enabled by passing an evaluation function " -"to :code:`evaluate_fn`." +"Server-side evaluation can be enabled by passing an evaluation function to :" +"code:`evaluate_fn`." msgstr "" +"서버 측 평가는 :code:`evaluate_fn`에 평가 함수를 전달하여 활성화할 수 있습니" +"다." #: ../../source/how-to-use-strategies.rst:89 msgid "" -"Writing a fully custom strategy is a bit more involved, but it provides " -"the most flexibility. Read the `Implementing Strategies `_ guide to learn more." +"Writing a fully custom strategy is a bit more involved, but it provides the " +"most flexibility. Read the `Implementing Strategies `_ guide to learn more." msgstr "" +"완전한 사용자 지정 전략을 작성하는 것은 조금 더 복잡하지만 유연성이 가장 뛰어" +"납니다. 자세한 내용은 `Implementing Strategies `_ 가이드를 참조하세요." #: ../../source/index.rst:34 msgid "Tutorial" -msgstr "" +msgstr "튜토리얼" #: ../../source/index.rst:44 msgid "Quickstart tutorials" -msgstr "" +msgstr "빠른 시작 튜토리얼" #: ../../source/index.rst:74 ../../source/index.rst:78 msgid "How-to guides" -msgstr "" +msgstr "사용 방법 가이드" #: ../../source/index.rst:99 msgid "Legacy example guides" -msgstr "" +msgstr "레거시 예제 가이드" #: ../../source/index.rst:108 ../../source/index.rst:112 msgid "Explanations" -msgstr "" +msgstr "설명" #: None:-1 msgid "API reference" -msgstr "" +msgstr "API 참조" #: ../../source/index.rst:137 msgid "Reference docs" -msgstr "" +msgstr "참조 문서" #: ../../source/index.rst:153 msgid "Contributor tutorials" -msgstr "" +msgstr "기여자 튜토리얼" #: ../../source/index.rst:160 msgid "Contributor how-to guides" -msgstr "" +msgstr "기여자 사용법 가이드" #: ../../source/index.rst:172 msgid "Contributor explanations" -msgstr "" +msgstr "기여자 설명" #: ../../source/index.rst:178 msgid "Contributor references" -msgstr "" +msgstr "기여자 참조" #: ../../source/index.rst:-1 msgid "" "Check out the documentation of the main Flower Framework enabling easy " "Python development for Federated Learning." -msgstr "" +msgstr "연합 학습을 위한 Python 개발을 쉽게 할 수 있는 주요 Flower 프레임워크의 " +"설명서를 확인하세요." #: ../../source/index.rst:2 msgid "Flower Framework Documentation" -msgstr "" +msgstr "플라워 프레임워크 문서" #: ../../source/index.rst:7 msgid "" "Welcome to Flower's documentation. `Flower `_ is a " "friendly federated learning framework." msgstr "" +"Flower 문서에 오신 것을 환영합니다. Flower `_는 편한 연합 " +"학습 프레임워크입니다." #: ../../source/index.rst:11 msgid "Join the Flower Community" -msgstr "" +msgstr "Flower 커뮤니티 가입하기" #: ../../source/index.rst:13 msgid "" @@ -7618,158 +8074,175 @@ msgid "" "researchers, engineers, students, professionals, academics, and other " "enthusiasts." msgstr "" +"Flower 커뮤니티는 연구원, 엔지니어, 학생, 전문가, 학자 및 기타 애호가들로 구" +"성된 편한 그룹으로 빠르게 성장하고 있습니다." #: ../../source/index.rst:15 msgid "Join us on Slack" -msgstr "" +msgstr "Slack에 가입하세요" #: ../../source/index.rst:23 msgid "Flower Framework" -msgstr "" +msgstr "Flower 프레임워크" #: ../../source/index.rst:25 msgid "" "The user guide is targeted at researchers and developers who want to use " "Flower to bring existing machine learning workloads into a federated " -"setting. One of Flower's design goals was to make this simple. Read on to" -" learn more." +"setting. One of Flower's design goals was to make this simple. Read on to " +"learn more." msgstr "" +"이 사용자 가이드는 Flower를 사용해 기존 머신 러닝 워크로드를 연합된 환경으로 " +"가져오고자 하는 연구자와 개발자를 대상으로 합니다. Flower의 설계 목표 중 하나" +"는 이를 간단하게 만드는 것이었습니다. 자세히 알아보려면 계속 읽어보세요." #: ../../source/index.rst:30 msgid "Tutorials" -msgstr "" +msgstr "튜토리얼" #: ../../source/index.rst:32 msgid "" -"A learning-oriented series of federated learning tutorials, the best " -"place to start." -msgstr "" +"A learning-oriented series of federated learning tutorials, the best place " +"to start." +msgstr "학습 중심의 연합 학습 튜토리얼 시리즈로, 시작하기에 가장 좋은 곳입니다." #: ../../source/index.rst:61 msgid "" -"QUICKSTART TUTORIALS: :doc:`PyTorch ` | " -":doc:`TensorFlow ` | :doc:`🤗 Transformers" -" ` | :doc:`JAX ` | :doc:`Pandas ` | :doc:`fastai " -"` | :doc:`PyTorch Lightning ` | :doc:`scikit-learn ` | :doc:`XGBoost ` | " -":doc:`Android ` | :doc:`iOS `" -msgstr "" +"QUICKSTART TUTORIALS: :doc:`PyTorch ` | :doc:" +"`TensorFlow ` | :doc:`🤗 Transformers " +"` | :doc:`JAX ` | :" +"doc:`Pandas ` | :doc:`fastai ` | :doc:`PyTorch Lightning ` | :doc:`scikit-learn ` | :doc:" +"`XGBoost ` | :doc:`Android ` | :doc:`iOS `" +msgstr "" +"QUICKSTART TUTORIALS: :doc:`PyTorch ` | :doc:" +"`TensorFlow ` | :doc:`🤗 Transformers " +"` | :doc:`JAX ` | :" +"doc:`Pandas ` | :doc:`fastai ` | :doc:`PyTorch Lightning ` | :doc:`scikit-learn ` | :doc:" +"`XGBoost ` | :doc:`Android ` | :doc:`iOS `" #: ../../source/index.rst:63 msgid "We also made video tutorials for PyTorch:" -msgstr "" +msgstr "파이토치용 동영상 튜토리얼도 만들었습니다:" #: ../../source/index.rst:68 msgid "And TensorFlow:" -msgstr "" +msgstr "그리고 TensorFlow도:" #: ../../source/index.rst:76 msgid "" -"Problem-oriented how-to guides show step-by-step how to achieve a " -"specific goal." +"Problem-oriented how-to guides show step-by-step how to achieve a specific " +"goal." msgstr "" +"문제 중심의 방법 가이드는 특정 목표를 달성하는 방법을 단계별로 보여줍니다." #: ../../source/index.rst:110 msgid "" "Understanding-oriented concept guides explain and discuss key topics and " "underlying ideas behind Flower and collaborative AI." msgstr "" +"이해 중심의 개념 가이드에서는 Flower와 협업 AI의 주요 주제와 기본 아이디어를 " +"설명하고 토론합니다." #: ../../source/index.rst:120 msgid "References" -msgstr "" +msgstr "참조" #: ../../source/index.rst:122 msgid "Information-oriented API reference and other reference material." -msgstr "" +msgstr "정보 지향 API 참조 및 기타 참고 자료." #: ../../source/index.rst:131::1 msgid ":py:obj:`flwr `\\" -msgstr "" +msgstr ":py:obj:`flwr `\\" #: ../../source/index.rst:131::1 flwr:1 of msgid "Flower main package." -msgstr "" +msgstr "Flower 메인 패키지." #: ../../source/index.rst:148 msgid "Contributor docs" -msgstr "" +msgstr "기여자 문서" #: ../../source/index.rst:150 msgid "" -"The Flower community welcomes contributions. The following docs are " -"intended to help along the way." +"The Flower community welcomes contributions. The following docs are intended " +"to help along the way." msgstr "" +"Flower 커뮤니티는 여러분의 기여를 환영합니다. 다음 문서는 그 과정에서 도움을 " +"드리기 위한 문서입니다." #: ../../source/ref-api-cli.rst:2 msgid "Flower CLI reference" -msgstr "" +msgstr "Flower CLI 참조" #: ../../source/ref-api-cli.rst:7 msgid "flower-simulation" -msgstr "" +msgstr "flower 시뮬레이션" #: ../../source/ref-api-cli.rst:17 msgid "flower-superlink" -msgstr "" +msgstr "flower 초연결" #: ../../source/ref-api-cli.rst:27 msgid "flower-client-app" -msgstr "" +msgstr "flower 클라이언트 앱" #: ../../source/ref-api-cli.rst:37 msgid "flower-server-app" -msgstr "" +msgstr "flower 서버 프로그램" #: ../../source/ref-api/flwr.rst:2 msgid "flwr" -msgstr "" +msgstr "flwr" #: ../../source/ref-api/flwr.client.rst:45 ../../source/ref-api/flwr.rst:25 #: ../../source/ref-api/flwr.server.rst:49 msgid "Modules" -msgstr "" +msgstr "Modules" #: ../../source/ref-api/flwr.rst:35::1 msgid ":py:obj:`flwr.client `\\" -msgstr "" +msgstr ":py:obj:`flwr.client `\\" #: ../../source/ref-api/flwr.rst:35::1 flwr.client:1 of msgid "Flower client." -msgstr "" +msgstr "Flower 클라이언트." #: ../../source/ref-api/flwr.rst:35::1 msgid ":py:obj:`flwr.common `\\" -msgstr "" +msgstr ":py:obj:`flwr.common `\\" #: ../../source/ref-api/flwr.rst:35::1 flwr.common:1 of msgid "Common components shared between server and client." -msgstr "" +msgstr "서버와 클라이언트 간에 공유되는 공통 구성 요소입니다." #: ../../source/ref-api/flwr.rst:35::1 msgid ":py:obj:`flwr.server `\\" -msgstr "" +msgstr ":py:obj:`flwr.server `\\" #: ../../source/ref-api/flwr.rst:35::1 #: ../../source/ref-api/flwr.server.rst:38::1 flwr.server:1 #: flwr.server.server.Server:1 of msgid "Flower server." -msgstr "" +msgstr "Flower 서버." #: ../../source/ref-api/flwr.rst:35::1 msgid ":py:obj:`flwr.simulation `\\" -msgstr "" +msgstr ":py:obj:`flwr.simulation `\\" #: ../../source/ref-api/flwr.rst:35::1 flwr.simulation:1 of msgid "Flower simulation." -msgstr "" +msgstr "Flower 시뮬레이션." #: ../../source/ref-api/flwr.client.rst:2 msgid "client" -msgstr "" +msgstr "클라이언트" #: ../../source/ref-api/flwr.client.mod.rst:13 #: ../../source/ref-api/flwr.client.rst:13 @@ -7777,47 +8250,51 @@ msgstr "" #: ../../source/ref-api/flwr.server.rst:13 #: ../../source/ref-api/flwr.simulation.rst:13 msgid "Functions" -msgstr "" +msgstr "함수" #: ../../source/ref-api/flwr.client.rst:25::1 msgid ":py:obj:`run_client_app `\\ \\(\\)" -msgstr "" +msgstr ":py:obj:`run_client_app `\\ \\(\\)" #: ../../source/ref-api/flwr.client.rst:25::1 #: flwr.client.supernode.app.run_client_app:1 of msgid "Run Flower client app." -msgstr "" +msgstr "Flower 클라이언트 앱을 실행합니다." #: ../../source/ref-api/flwr.client.rst:25::1 msgid ":py:obj:`run_supernode `\\ \\(\\)" -msgstr "" +msgstr ":py:obj:`run_supernode `\\ \\(\\)" #: ../../source/ref-api/flwr.client.rst:25::1 #: flwr.client.supernode.app.run_supernode:1 of msgid "Run Flower SuperNode." -msgstr "" +msgstr "Flower SuperNode를 실행합니다." #: ../../source/ref-api/flwr.client.rst:25::1 msgid "" ":py:obj:`start_client `\\ \\(\\*\\, " "server\\_address\\[\\, client\\_fn\\, ...\\]\\)" msgstr "" +":py:obj:`start_client `\\ \\(\\*\\, " +"server\\_address\\[\\, client\\_fn\\, ...\\]\\)" #: ../../source/ref-api/flwr.client.rst:25::1 #: flwr.client.app.start_client:1 of msgid "Start a Flower client node which connects to a Flower server." -msgstr "" +msgstr "Flower 서버에 연결되는 Flower 클라이언트 노드를 시작합니다." #: ../../source/ref-api/flwr.client.rst:25::1 msgid "" -":py:obj:`start_numpy_client `\\ \\(\\*\\," -" server\\_address\\, client\\)" +":py:obj:`start_numpy_client `\\ \\(\\*\\, " +"server\\_address\\, client\\)" msgstr "" +":py:obj:`start_numpy_client `\\ \\(\\*\\, " +"server\\_address\\, client\\)" #: ../../source/ref-api/flwr.client.rst:25::1 #: flwr.client.app.start_numpy_client:1 of msgid "Start a Flower NumPyClient which connects to a gRPC server." -msgstr "" +msgstr "gRPC 서버에 연결되는 Flower NumPyClient를 시작합니다." #: ../../source/ref-api/flwr.client.mod.rst:30 #: ../../source/ref-api/flwr.client.rst:27 @@ -7826,51 +8303,51 @@ msgstr "" #: ../../source/ref-api/flwr.server.strategy.rst:17 #: ../../source/ref-api/flwr.server.workflow.rst:17 msgid "Classes" -msgstr "" +msgstr "클래스" #: ../../source/ref-api/flwr.client.rst:34::1 msgid ":py:obj:`Client `\\ \\(\\)" -msgstr "" +msgstr ":py:obj:`Client `\\ \\(\\)" #: ../../source/ref-api/flwr.client.rst:34::1 #: flwr.client.client.Client:1 of msgid "Abstract base class for Flower clients." -msgstr "" +msgstr "Flower 클라이언트를 위한 추상 베이스 클래스입니다." #: ../../source/ref-api/flwr.client.rst:34::1 msgid "" -":py:obj:`ClientApp `\\ \\(\\[client\\_fn\\, " -"mods\\]\\)" +":py:obj:`ClientApp `\\ \\(\\[client\\_fn\\, mods\\]\\)" msgstr "" +":py:obj:`ClientApp `\\ \\(\\[client\\_fn\\, mods\\]\\)" #: ../../source/ref-api/flwr.client.rst:34::1 #: flwr.client.client_app.ClientApp:1 of msgid "Flower ClientApp." -msgstr "" +msgstr "Flower ClientApp." #: ../../source/ref-api/flwr.client.rst:34::1 msgid ":py:obj:`NumPyClient `\\ \\(\\)" -msgstr "" +msgstr ":py:obj:`NumPyClient `\\ \\(\\)" #: ../../source/ref-api/flwr.client.rst:34::1 #: flwr.client.numpy_client.NumPyClient:1 of msgid "Abstract base class for Flower clients using NumPy." -msgstr "" +msgstr "NumPy를 사용하는 Flower 클라이언트를 위한 추상 베이스 클래스입니다." #: ../../source/ref-api/flwr.client.rst:52::1 msgid ":py:obj:`flwr.client.mod `\\" -msgstr "" +msgstr ":py:obj:`flwr.client.mod `\\" #: ../../source/ref-api/flwr.client.rst:52::1 flwr.client.mod:1 of msgid "Flower Built-in Mods." -msgstr "" +msgstr "Flower 내장 모드." #: flwr.client.client.Client:1 flwr.client.numpy_client.NumPyClient:1 #: flwr.server.client_manager.ClientManager:1 #: flwr.server.driver.driver.Driver:1 flwr.server.strategy.strategy.Strategy:1 #: of msgid "Bases: :py:class:`~abc.ABC`" -msgstr "" +msgstr "Bases: :py:class:`~abc.ABC`" #: ../../source/ref-api/flwr.client.Client.rst:15 #: ../../source/ref-api/flwr.client.ClientApp.rst:15 @@ -7938,78 +8415,82 @@ msgstr "" #: ../../source/ref-api/flwr.server.workflow.SecAggPlusWorkflow.rst:15 #: ../../source/ref-api/flwr.server.workflow.SecAggWorkflow.rst:15 msgid "Methods" -msgstr "" +msgstr "메소드" #: ../../source/ref-api/flwr.client.Client.rst:44::1 msgid ":py:obj:`evaluate `\\ \\(ins\\)" -msgstr "" +msgstr ":py:obj:`evaluate `\\ \\(ins\\)" #: ../../source/ref-api/flwr.client.Client.rst:44::1 #: ../../source/ref-api/flwr.client.NumPyClient.rst:44::1 #: flwr.client.client.Client.evaluate:1 #: flwr.client.numpy_client.NumPyClient.evaluate:1 of msgid "Evaluate the provided parameters using the locally held dataset." -msgstr "" +msgstr "로컬로 보유한 데이터 세트를 사용하여 제공된 매개변수를 평가합니다." #: ../../source/ref-api/flwr.client.Client.rst:44::1 msgid ":py:obj:`fit `\\ \\(ins\\)" -msgstr "" +msgstr ":py:obj:`fit `\\ \\(ins\\)" #: ../../source/ref-api/flwr.client.Client.rst:44::1 #: flwr.client.client.Client.fit:1 of msgid "Refine the provided parameters using the locally held dataset." -msgstr "" +msgstr "로컬로 보유한 데이터 세트를 사용하여 제공된 매개변수를 구체화합니다." #: ../../source/ref-api/flwr.client.Client.rst:44::1 msgid ":py:obj:`get_context `\\ \\(\\)" -msgstr "" +msgstr ":py:obj:`get_context `\\ \\(\\)" #: ../../source/ref-api/flwr.client.Client.rst:44::1 #: ../../source/ref-api/flwr.client.NumPyClient.rst:44::1 #: flwr.client.client.Client.get_context:1 #: flwr.client.numpy_client.NumPyClient.get_context:1 of msgid "Get the run context from this client." -msgstr "" +msgstr "이 클라이언트에서 실행 컨텍스트를 가져옵니다." #: ../../source/ref-api/flwr.client.Client.rst:44::1 -msgid ":py:obj:`get_parameters `\\ \\(ins\\)" +msgid "" +":py:obj:`get_parameters `\\ \\(ins\\)" msgstr "" +":py:obj:`get_parameters `\\ \\(ins\\)" #: ../../source/ref-api/flwr.client.Client.rst:44::1 #: ../../source/ref-api/flwr.client.NumPyClient.rst:44::1 #: flwr.client.client.Client.get_parameters:1 #: flwr.client.numpy_client.NumPyClient.get_parameters:1 of msgid "Return the current local model parameters." -msgstr "" +msgstr "현재 로컬 모델 파라미터를 반환합니다." #: ../../source/ref-api/flwr.client.Client.rst:44::1 -msgid ":py:obj:`get_properties `\\ \\(ins\\)" +msgid "" +":py:obj:`get_properties `\\ \\(ins\\)" msgstr "" +":py:obj:`get_properties `\\ \\(ins\\)" #: ../../source/ref-api/flwr.client.Client.rst:44::1 #: flwr.client.client.Client.get_properties:1 of msgid "Return set of client's properties." -msgstr "" +msgstr "클라이언트의 속성 집합을 반환합니다." #: ../../source/ref-api/flwr.client.Client.rst:44::1 msgid ":py:obj:`set_context `\\ \\(context\\)" -msgstr "" +msgstr ":py:obj:`set_context `\\ \\(context\\)" #: ../../source/ref-api/flwr.client.Client.rst:44::1 #: ../../source/ref-api/flwr.client.NumPyClient.rst:44::1 #: flwr.client.client.Client.set_context:1 #: flwr.client.numpy_client.NumPyClient.set_context:1 of msgid "Apply a run context to this client." -msgstr "" +msgstr "이 클라이언트에 실행 컨텍스트를 적용합니다." #: ../../source/ref-api/flwr.client.Client.rst:44::1 msgid ":py:obj:`to_client `\\ \\(\\)" -msgstr "" +msgstr ":py:obj:`to_client `\\ \\(\\)" #: ../../source/ref-api/flwr.client.Client.rst:44::1 #: flwr.client.client.Client.to_client:1 of msgid "Return client (itself)." -msgstr "" +msgstr "클라이언트(자체)를 반환합니다." #: ../../source/ref-api/flwr.client.Client.rst:46 #: ../../source/ref-api/flwr.client.NumPyClient.rst:46 @@ -8040,11 +8521,11 @@ msgstr "" #: ../../source/ref-api/flwr.server.LegacyContext.rst:25 #: ../../source/ref-api/flwr.server.ServerConfig.rst:25 msgid "Attributes" -msgstr "" +msgstr "속성" #: flwr.client.client.Client.evaluate:1::1 of msgid ":py:obj:`context `\\" -msgstr "" +msgstr ":py:obj:`context `\\" #: ../../source/ref-api/flwr.common.Parameters.rst:2 #: flwr.client.app.start_client flwr.client.app.start_numpy_client @@ -8094,14 +8575,16 @@ msgstr "" #: flwr.simulation.app.start_simulation #: flwr.simulation.run_simulation.run_simulation of msgid "Parameters" -msgstr "" +msgstr "매개변수" #: flwr.client.client.Client.evaluate:3 of msgid "" -"The evaluation instructions containing (global) model parameters received" -" from the server and a dictionary of configuration values used to " -"customize the local evaluation process." +"The evaluation instructions containing (global) model parameters received " +"from the server and a dictionary of configuration values used to customize " +"the local evaluation process." msgstr "" +"서버에서 받은 (전역) 모델 파라미터와 로컬 평가 프로세스를 사용자 지정하는 데 " +"사용되는 구성 값 사전이 포함된 평가 지침입니다." #: flwr.client.client.Client.evaluate flwr.client.client.Client.fit #: flwr.client.client.Client.get_parameters @@ -8130,13 +8613,15 @@ msgstr "" #: flwr.server.strategy.strategy.Strategy.initialize_parameters #: flwr.simulation.app.start_simulation of msgid "Returns" -msgstr "" +msgstr "반환" #: flwr.client.client.Client.evaluate:8 of msgid "" "The evaluation result containing the loss on the local dataset and other " "details such as the number of local data examples used for evaluation." msgstr "" +"로컬 데이터 세트의 손실 및 평가에 사용된 로컬 데이터 예제 수와 같은 기타 세" +"부 정보가 포함된 평가 결과입니다." #: flwr.client.client.Client.evaluate flwr.client.client.Client.fit #: flwr.client.client.Client.get_parameters @@ -8163,44 +8648,49 @@ msgstr "" #: flwr.server.strategy.strategy.Strategy.initialize_parameters #: flwr.simulation.app.start_simulation of msgid "Return type" -msgstr "" +msgstr "반환 타입" #: flwr.client.client.Client.fit:3 of msgid "" -"The training instructions containing (global) model parameters received " -"from the server and a dictionary of configuration values used to " -"customize the local training process." +"The training instructions containing (global) model parameters received from " +"the server and a dictionary of configuration values used to customize the " +"local training process." msgstr "" +"서버에서 받은 (전역) 모델 파라미터와 로컬 학습 프로세스를 사용자 지정하는 데 " +"사용되는 구성 값 사전이 포함된 학습 지침입니다." #: flwr.client.client.Client.fit:8 of msgid "" -"The training result containing updated parameters and other details such " -"as the number of local training examples used for training." +"The training result containing updated parameters and other details such as " +"the number of local training examples used for training." msgstr "" +"업데이트된 매개변수와 훈련에 사용된 로컬 훈련 예제 수와 같은 기타 세부 정보" +"가 포함된 훈련 결과입니다." #: flwr.client.client.Client.get_parameters:3 of msgid "" "The get parameters instructions received from the server containing a " "dictionary of configuration values." msgstr "" +"구성 값 dictionary이 포함된 서버에서 받은 매개변수 가져오기 명령어입니다." #: flwr.client.client.Client.get_parameters:7 of msgid "The current local model parameters." -msgstr "" +msgstr "현재 로컬 모델 파라미터입니다." #: flwr.client.client.Client.get_properties:3 of msgid "" "The get properties instructions received from the server containing a " "dictionary of configuration values." -msgstr "" +msgstr "구성 값 dictionary이 포함된 서버로부터 받은 속성 가져오기 명령입니다." #: flwr.client.client.Client.get_properties:7 of msgid "The current client properties." -msgstr "" +msgstr "현재 클라이언트 속성입니다." #: ../../source/ref-api/flwr.client.ClientApp.rst:2 msgid "ClientApp" -msgstr "" +msgstr "클라이언트앱" #: flwr.client.client_app.ClientApp:1 flwr.client.mod.localdp_mod.LocalDpMod:1 #: flwr.common.constant.MessageType:1 flwr.common.constant.MessageTypeLegacy:1 @@ -8221,7 +8711,7 @@ msgstr "" #: flwr.server.workflow.secure_aggregation.secaggplus_workflow.SecAggPlusWorkflow:1 #: of msgid "Bases: :py:class:`object`" -msgstr "" +msgstr "Bases: :py:class:`object`" #: flwr.client.app.start_client:41 flwr.client.app.start_numpy_client:36 #: flwr.client.client_app.ClientApp:4 @@ -8236,112 +8726,127 @@ msgstr "" #: flwr.server.strategy.dp_fixed_clipping.DifferentialPrivacyServerSideFixedClipping:14 #: of msgid "Examples" -msgstr "" +msgstr "예시" #: flwr.client.client_app.ClientApp:5 of msgid "" "Assuming a typical `Client` implementation named `FlowerClient`, you can " "wrap it in a `ClientApp` as follows:" msgstr "" +"일반적인 `Client` 구현의 이름이 `FlowerClient`라고 가정하면, 다음과 같이 " +"`ClientApp`으로 래핑할 수 있습니다:" #: flwr.client.client_app.ClientApp:16 of msgid "" -"If the above code is in a Python module called `client`, it can be " -"started as follows:" +"If the above code is in a Python module called `client`, it can be started " +"as follows:" msgstr "" +"위의 코드가 'client'라는 Python 모듈에 있는 경우 다음과 같이 시작할 수 있습니" +"다:" #: flwr.client.client_app.ClientApp:21 of msgid "" -"In this `client:app` example, `client` refers to the Python module " -"`client.py` in which the previous code lives in and `app` refers to the " -"global attribute `app` that points to an object of type `ClientApp`." +"In this `client:app` example, `client` refers to the Python module `client." +"py` in which the previous code lives in and `app` refers to the global " +"attribute `app` that points to an object of type `ClientApp`." msgstr "" +"이 `client:app` 예제에서 `client`는 이전 코드가 있는 Python 모듈 `client.py`" +"를 가리키고 `app`는 `ClientApp` 유형의 객체를 가리키는 전역 속성 `app`을 가리" +"킵니다." #: flwr.client.client_app.ClientApp.evaluate:1::1 of msgid ":py:obj:`evaluate `\\ \\(\\)" -msgstr "" +msgstr ":py:obj:`evaluate `\\ \\(\\)" #: flwr.client.client_app.ClientApp.evaluate:1 #: flwr.client.client_app.ClientApp.evaluate:1::1 of msgid "Return a decorator that registers the evaluate fn with the client app." -msgstr "" +msgstr "클라이언트 앱에 평가함수를 등록하는 데코레이터를 반환합니다." #: flwr.client.client_app.ClientApp.evaluate:1::1 of msgid ":py:obj:`query `\\ \\(\\)" -msgstr "" +msgstr ":py:obj:`query `\\ \\(\\)" #: flwr.client.client_app.ClientApp.evaluate:1::1 #: flwr.client.client_app.ClientApp.query:1 of msgid "Return a decorator that registers the query fn with the client app." -msgstr "" +msgstr "클라이언트 앱에 query fn을 등록하는 데코레이터를 반환합니다." #: flwr.client.client_app.ClientApp.evaluate:1::1 of msgid ":py:obj:`train `\\ \\(\\)" -msgstr "" +msgstr ":py:obj:`train `\\ \\(\\)" #: flwr.client.client_app.ClientApp.evaluate:1::1 #: flwr.client.client_app.ClientApp.train:1 of msgid "Return a decorator that registers the train fn with the client app." -msgstr "" +msgstr "클라이언트 앱에 train fn을 등록하는 데코레이터를 반환합니다." #: ../../source/ref-api/flwr.client.NumPyClient.rst:2 msgid "NumPyClient" -msgstr "" +msgstr "NumPyClient" #: ../../source/ref-api/flwr.client.NumPyClient.rst:44::1 msgid "" ":py:obj:`evaluate `\\ \\(parameters\\, " "config\\)" msgstr "" +":py:obj:`evaluate `\\ \\(parameters\\, " +"config\\)" #: ../../source/ref-api/flwr.client.NumPyClient.rst:44::1 -msgid ":py:obj:`fit `\\ \\(parameters\\, config\\)" +msgid "" +":py:obj:`fit `\\ \\(parameters\\, config\\)" msgstr "" +":py:obj:`fit `\\ \\(parameters\\, config\\)" #: ../../source/ref-api/flwr.client.NumPyClient.rst:44::1 #: flwr.client.numpy_client.NumPyClient.fit:1 of msgid "Train the provided parameters using the locally held dataset." -msgstr "" +msgstr "로컬로 보유한 데이터 세트를 사용하여 제공된 파라미터를 학습합니다." #: ../../source/ref-api/flwr.client.NumPyClient.rst:44::1 msgid ":py:obj:`get_context `\\ \\(\\)" -msgstr "" +msgstr ":py:obj:`get_context `\\ \\(\\)" #: ../../source/ref-api/flwr.client.NumPyClient.rst:44::1 msgid "" ":py:obj:`get_parameters `\\ " "\\(config\\)" msgstr "" +":py:obj:`get_parameters `\\ " +"\\(config\\)" #: ../../source/ref-api/flwr.client.NumPyClient.rst:44::1 msgid "" ":py:obj:`get_properties `\\ " "\\(config\\)" msgstr "" +":py:obj:`get_properties `\\ " +"\\(config\\)" #: ../../source/ref-api/flwr.client.NumPyClient.rst:44::1 #: flwr.client.numpy_client.NumPyClient.get_properties:1 of msgid "Return a client's set of properties." -msgstr "" +msgstr "클라이언트의 속성 집합을 반환합니다." #: ../../source/ref-api/flwr.client.NumPyClient.rst:44::1 msgid "" -":py:obj:`set_context `\\ " -"\\(context\\)" +":py:obj:`set_context `\\ \\(context\\)" msgstr "" +":py:obj:`set_context `\\ \\(context\\)" #: ../../source/ref-api/flwr.client.NumPyClient.rst:44::1 msgid ":py:obj:`to_client `\\ \\(\\)" -msgstr "" +msgstr ":py:obj:`to_client `\\ \\(\\)" #: ../../source/ref-api/flwr.client.NumPyClient.rst:44::1 #: flwr.client.numpy_client.NumPyClient.to_client:1 of msgid "Convert to object to Client type and return it." -msgstr "" +msgstr "객체를 클라이언트 유형으로 변환하고 반환합니다." #: flwr.client.numpy_client.NumPyClient.evaluate:1::1 of msgid ":py:obj:`context `\\" -msgstr "" +msgstr ":py:obj:`context `\\" #: flwr.client.numpy_client.NumPyClient.evaluate:3 #: flwr.client.numpy_client.NumPyClient.fit:3 @@ -8351,262 +8856,311 @@ msgstr "" #: flwr.server.strategy.strategy.Strategy.configure_fit:5 #: flwr.server.strategy.strategy.Strategy.evaluate:8 of msgid "The current (global) model parameters." -msgstr "" +msgstr "현재(전역) 모델 매개변수입니다." #: flwr.client.numpy_client.NumPyClient.evaluate:5 of msgid "" -"Configuration parameters which allow the server to influence evaluation " -"on the client. It can be used to communicate arbitrary values from the " -"server to the client, for example, to influence the number of examples " -"used for evaluation." +"Configuration parameters which allow the server to influence evaluation on " +"the client. It can be used to communicate arbitrary values from the server " +"to the client, for example, to influence the number of examples used for " +"evaluation." msgstr "" +"서버가 클라이언트의 평가에 영향을 줄 수 있는 구성 매개변수입니다. 예를 들어 " +"평가에 사용되는 예제 수에 영향을 주기 위해 서버에서 클라이언트로 임의의 값을 " +"전달하는 데 사용할 수 있습니다." #: flwr.client.numpy_client.NumPyClient.evaluate:11 of msgid "" "* **loss** (*float*) -- The evaluation loss of the model on the local " "dataset. * **num_examples** (*int*) -- The number of examples used for " "evaluation. * **metrics** (*Dict[str, Scalar]*) -- A dictionary mapping " -"arbitrary string keys to values of type bool, bytes, float, int, or " -"str. It can be used to communicate arbitrary values back to the server." +"arbitrary string keys to values of type bool, bytes, float, int, or str. " +"It can be used to communicate arbitrary values back to the server." msgstr "" +"* **loss** (*float*) - 로컬 데이터 세트에서 모델의 평가 손실입니다. * " +"**num_examples** (*int*) -- 평가에 사용된 예제 수입니다. * **metrics** " +"(*Dict[str, Scalar]*) -- 임의의 문자열 키를 부울, 바이트, float, int 또는 " +"str 유형의 값에 매핑하는 dictionary입니다. 임의의 값을 서버에 다시 전달하는 " +"데 사용할 수 있습니다." #: flwr.client.numpy_client.NumPyClient.evaluate:11 of msgid "" -"**loss** (*float*) -- The evaluation loss of the model on the local " -"dataset." -msgstr "" +"**loss** (*float*) -- The evaluation loss of the model on the local dataset." +msgstr "**loss** (*float*) -- 로컬 데이터 세트에서 모델의 평가 손실입니다." #: flwr.client.numpy_client.NumPyClient.evaluate:12 of msgid "**num_examples** (*int*) -- The number of examples used for evaluation." -msgstr "" +msgstr "**num_examples** (*int*) - 평가에 사용된 예제 수입니다." #: flwr.client.numpy_client.NumPyClient.evaluate:13 #: flwr.client.numpy_client.NumPyClient.fit:13 of msgid "" -"**metrics** (*Dict[str, Scalar]*) -- A dictionary mapping arbitrary " -"string keys to values of type bool, bytes, float, int, or str. It can be " -"used to communicate arbitrary values back to the server." +"**metrics** (*Dict[str, Scalar]*) -- A dictionary mapping arbitrary string " +"keys to values of type bool, bytes, float, int, or str. It can be used to " +"communicate arbitrary values back to the server." msgstr "" +"**metrics** (*Dict[str, Scalar]*) - 임의의 문자열 키를 bool, bytes, float, " +"int 또는 str 타입의 값에 매핑하는 dictionary입니다. 임의의 값을 서버에 다시 " +"전달하는 데 사용할 수 있습니다." #: flwr.client.numpy_client.NumPyClient.evaluate:19 of msgid "" -"The previous return type format (int, float, float) and the extended " -"format (int, float, float, Dict[str, Scalar]) have been deprecated and " -"removed since Flower 0.19." +"The previous return type format (int, float, float) and the extended format " +"(int, float, float, Dict[str, Scalar]) have been deprecated and removed " +"since Flower 0.19." msgstr "" +"이전 반환 유형 형식(int, float, float)과 확장 형식(int, float, float, " +"Dict[str, Scalar])은 Flower 0.19부터 더 이상 사용되지 않으며 제거되었습니다." #: flwr.client.numpy_client.NumPyClient.fit:5 of msgid "" -"Configuration parameters which allow the server to influence training on " -"the client. It can be used to communicate arbitrary values from the " -"server to the client, for example, to set the number of (local) training " -"epochs." +"Configuration parameters which allow the server to influence training on the " +"client. It can be used to communicate arbitrary values from the server to " +"the client, for example, to set the number of (local) training epochs." msgstr "" +"서버가 클라이언트의 훈련에 영향을 줄 수 있는 구성 매개변수입니다. 예를 들어 " +"(로컬) 트레이닝 에포크 수를 설정하는 등 서버에서 클라이언트로 임의의 값을 전" +"달하는 데 사용할 수 있습니다." #: flwr.client.numpy_client.NumPyClient.fit:11 of msgid "" "* **parameters** (*NDArrays*) -- The locally updated model parameters. * " "**num_examples** (*int*) -- The number of examples used for training. * " -"**metrics** (*Dict[str, Scalar]*) -- A dictionary mapping arbitrary " -"string keys to values of type bool, bytes, float, int, or str. It can " -"be used to communicate arbitrary values back to the server." +"**metrics** (*Dict[str, Scalar]*) -- A dictionary mapping arbitrary string " +"keys to values of type bool, bytes, float, int, or str. It can be used to " +"communicate arbitrary values back to the server." msgstr "" +"* **parameters** (*NDArrays*) - 로컬로 업데이트된 모델 파라미터입니다. * " +"**num_examples** (*int*) -- 학습에 사용된 예제 수입니다. * **metrics** " +"(*Dict[str, Scalar]*) - 임의의 문자열 키를 bool, bytes, float, int,또는 str " +"타입의 값에 매핑하는 dictionary입니다. 임의의 값을 서버에 다시 전달하는 데 사" +"용할 수 있습니다." #: flwr.client.numpy_client.NumPyClient.fit:11 of msgid "**parameters** (*NDArrays*) -- The locally updated model parameters." -msgstr "" +msgstr "**parameters** (*NDArrays*) - 로컬로 업데이트된 모델 파라미터입니다." #: flwr.client.numpy_client.NumPyClient.fit:12 of msgid "**num_examples** (*int*) -- The number of examples used for training." -msgstr "" +msgstr "**num_examples** (*int*) - 트레이닝에 사용된 예제 수입니다." #: flwr.client.numpy_client.NumPyClient.get_parameters:3 of msgid "" -"Configuration parameters requested by the server. This can be used to " -"tell the client which parameters are needed along with some Scalar " -"attributes." +"Configuration parameters requested by the server. This can be used to tell " +"the client which parameters are needed along with some Scalar attributes." msgstr "" +"서버에서 요청한 구성 매개변수입니다. 이는 일부 스칼라 속성과 함께 어떤 매개변" +"수가 필요한지 클라이언트에게 알려주는 데 사용할 수 있습니다." #: flwr.client.numpy_client.NumPyClient.get_parameters:8 of -msgid "**parameters** -- The local model parameters as a list of NumPy ndarrays." -msgstr "" +msgid "" +"**parameters** -- The local model parameters as a list of NumPy ndarrays." +msgstr "**parameters** -- 로컬 모델 파라미터를 NumPy 배열 목록으로 표시합니다." #: flwr.client.numpy_client.NumPyClient.get_properties:3 of msgid "" -"Configuration parameters requested by the server. This can be used to " -"tell the client which properties are needed along with some Scalar " -"attributes." +"Configuration parameters requested by the server. This can be used to tell " +"the client which properties are needed along with some Scalar attributes." msgstr "" +"서버에서 요청하는 구성 매개변수입니다. 이는 일부 스칼라 속성과 함께 어떤 속성" +"이 필요한지 클라이언트에게 알려주는 데 사용할 수 있습니다." #: flwr.client.numpy_client.NumPyClient.get_properties:8 of msgid "" -"**properties** -- A dictionary mapping arbitrary string keys to values of" -" type bool, bytes, float, int, or str. It can be used to communicate " +"**properties** -- A dictionary mapping arbitrary string keys to values of " +"type bool, bytes, float, int, or str. It can be used to communicate " "arbitrary property values back to the server." msgstr "" +"**properties** -- 임의의 문자열 키를 bool, bytes, float, int 또는 str 타입의 " +"값에 매핑하는 dictionary입니다. 임의의 속성 값을 서버에 다시 전달하는 데 사용" +"할 수 있습니다." #: ../../source/ref-api/flwr.client.mod.rst:2 msgid "mod" -msgstr "" +msgstr "mod" #: ../../source/ref-api/flwr.client.mod.rst:28::1 msgid "" ":py:obj:`adaptiveclipping_mod `\\ " "\\(msg\\, ctxt\\, call\\_next\\)" msgstr "" +":py:obj:`adaptiveclipping_mod `\\ " +"\\(msg\\, ctxt\\, call\\_next\\)" #: ../../source/ref-api/flwr.client.mod.rst:28::1 #: flwr.client.mod.centraldp_mods.adaptiveclipping_mod:1 of msgid "Client-side adaptive clipping modifier." -msgstr "" +msgstr "클라이언트 측 적응형 클리핑 수정자." #: ../../source/ref-api/flwr.client.mod.rst:28::1 msgid "" -":py:obj:`fixedclipping_mod `\\ " -"\\(msg\\, ctxt\\, call\\_next\\)" +":py:obj:`fixedclipping_mod `\\ \\(msg\\, " +"ctxt\\, call\\_next\\)" msgstr "" +":py:obj:`fixedclipping_mod `\\ \\(msg\\, " +"ctxt\\, call\\_next\\)" #: ../../source/ref-api/flwr.client.mod.rst:28::1 #: flwr.client.mod.centraldp_mods.fixedclipping_mod:1 of msgid "Client-side fixed clipping modifier." -msgstr "" +msgstr "클라이언트 측 고정 클리핑 수정자." #: ../../source/ref-api/flwr.client.mod.rst:28::1 msgid ":py:obj:`make_ffn `\\ \\(ffn\\, mods\\)" -msgstr "" +msgstr ":py:obj:`make_ffn `\\ \\(ffn\\, mods\\)" #: ../../source/ref-api/flwr.client.mod.rst:28::1 #: flwr.client.mod.utils.make_ffn:1 of msgid "." -msgstr "" +msgstr "." #: ../../source/ref-api/flwr.client.mod.rst:28::1 msgid "" ":py:obj:`secagg_mod `\\ \\(msg\\, ctxt\\, " "call\\_next\\)" msgstr "" +":py:obj:`secagg_mod `\\ \\(msg\\, ctxt\\, " +"call\\_next\\)" #: ../../source/ref-api/flwr.client.mod.rst:28::1 #: flwr.client.mod.secure_aggregation.secagg_mod.secagg_mod:1 of -msgid "Handle incoming message and return results, following the SecAgg protocol." -msgstr "" +msgid "" +"Handle incoming message and return results, following the SecAgg protocol." +msgstr "SecAgg 프로토콜에 따라 수신 메시지를 처리하고 결과를 반환합니다." #: ../../source/ref-api/flwr.client.mod.rst:28::1 msgid "" ":py:obj:`secaggplus_mod `\\ \\(msg\\, " "ctxt\\, call\\_next\\)" msgstr "" +":py:obj:`secaggplus_mod `\\ \\(msg\\, " +"ctxt\\, call\\_next\\)" #: ../../source/ref-api/flwr.client.mod.rst:28::1 #: flwr.client.mod.secure_aggregation.secaggplus_mod.secaggplus_mod:1 of msgid "" -"Handle incoming message and return results, following the SecAgg+ " -"protocol." -msgstr "" +"Handle incoming message and return results, following the SecAgg+ protocol." +msgstr "SecAgg+ 프로토콜에 따라 수신 메시지를 처리하고 결과를 반환합니다." #: ../../source/ref-api/flwr.client.mod.rst:28::1 msgid "" -":py:obj:`message_size_mod `\\ \\(msg\\," -" ctxt\\, call\\_next\\)" +":py:obj:`message_size_mod `\\ \\(msg\\, " +"ctxt\\, call\\_next\\)" msgstr "" +":py:obj:`message_size_mod `\\ \\(msg\\, " +"ctxt\\, call\\_next\\)" #: ../../source/ref-api/flwr.client.mod.rst:28::1 #: flwr.client.mod.comms_mods.message_size_mod:1 of msgid "Message size mod." -msgstr "" +msgstr "메시지 크기 수정." #: ../../source/ref-api/flwr.client.mod.rst:28::1 msgid "" ":py:obj:`parameters_size_mod `\\ " "\\(msg\\, ctxt\\, call\\_next\\)" msgstr "" +":py:obj:`parameters_size_mod `\\ " +"\\(msg\\, ctxt\\, call\\_next\\)" #: ../../source/ref-api/flwr.client.mod.rst:28::1 #: flwr.client.mod.comms_mods.parameters_size_mod:1 of msgid "Parameters size mod." -msgstr "" +msgstr "매개변수 크기 mod." #: ../../source/ref-api/flwr.client.mod.rst:35::1 msgid "" -":py:obj:`LocalDpMod `\\ \\(clipping\\_norm\\," -" sensitivity\\, ...\\)" +":py:obj:`LocalDpMod `\\ \\(clipping\\_norm\\, " +"sensitivity\\, ...\\)" msgstr "" +":py:obj:`LocalDpMod `\\ \\(clipping\\_norm\\, " +"sensitivity\\, ...\\)" #: ../../source/ref-api/flwr.client.mod.rst:35::1 #: flwr.client.mod.localdp_mod.LocalDpMod:1 of msgid "Modifier for local differential privacy." -msgstr "" +msgstr "로컬 차분 프라이버시를 위한 수정자." #: ../../source/ref-api/flwr.client.mod.LocalDpMod.rst:2 msgid "LocalDpMod" -msgstr "" +msgstr "LocalDpMod" #: flwr.client.mod.localdp_mod.LocalDpMod:3 of msgid "" -"This mod clips the client model updates and adds noise to the params " -"before sending them to the server." +"This mod clips the client model updates and adds noise to the params before " +"sending them to the server." msgstr "" +"이 모드는 클라이언트 모델 업데이트를 클립하고 서버로 보내기 전에 파라미터에 " +"노이즈를 추가합니다." #: flwr.client.mod.centraldp_mods.adaptiveclipping_mod:12 #: flwr.client.mod.centraldp_mods.fixedclipping_mod:10 #: flwr.client.mod.localdp_mod.LocalDpMod:6 of msgid "It operates on messages of type `MessageType.TRAIN`." -msgstr "" +msgstr "이 함수는 `MessageType.TRAIN` 유형의 메시지에 대해 작동합니다." #: flwr.client.mod.localdp_mod.LocalDpMod:8 #: flwr.server.strategy.dp_fixed_clipping.DifferentialPrivacyClientSideFixedClipping:15 #: flwr.server.strategy.dp_fixed_clipping.DifferentialPrivacyServerSideFixedClipping:8 #: of msgid "The value of the clipping norm." -msgstr "" +msgstr "클리핑 기준값입니다." #: flwr.client.mod.localdp_mod.LocalDpMod:10 of msgid "The sensitivity of the client model." -msgstr "" +msgstr "클라이언트 모델의 민감도입니다." #: flwr.client.mod.localdp_mod.LocalDpMod:12 of msgid "" "The privacy budget. Smaller value of epsilon indicates a higher level of " "privacy protection." msgstr "" +"개인정보 보호 예산. 엡실론 값이 작을수록 개인정보 보호 수준이 높음을 나타냅니" +"다." #: flwr.client.mod.localdp_mod.LocalDpMod:15 of msgid "" -"The failure probability. The probability that the privacy mechanism fails" -" to provide the desired level of privacy. A smaller value of delta " -"indicates a stricter privacy guarantee." +"The failure probability. The probability that the privacy mechanism fails to " +"provide the desired level of privacy. A smaller value of delta indicates a " +"stricter privacy guarantee." msgstr "" +"실패 확률입니다. 프라이버시 메커니즘이 원하는 수준의 프라이버시를 제공하지 못" +"할 확률입니다. 델타 값이 작을수록 프라이버시가 더 엄격하게 보장된다는 의미입" +"니다." #: flwr.client.mod.localdp_mod.LocalDpMod:23 of -msgid "Create an instance of the local DP mod and add it to the client-side mods:" -msgstr "" +msgid "" +"Create an instance of the local DP mod and add it to the client-side mods:" +msgstr "로컬 DP 모드의 인스턴스를 생성하고 클라이언트 측 모드에 추가합니다:" #: ../../source/ref-api/flwr.client.mod.adaptiveclipping_mod.rst:2 msgid "adaptiveclipping\\_mod" -msgstr "" +msgstr "adaptiveclipping\\_mod" #: flwr.client.mod.centraldp_mods.adaptiveclipping_mod:3 of msgid "" "This mod needs to be used with the " -"DifferentialPrivacyClientSideAdaptiveClipping server-side strategy " -"wrapper." +"DifferentialPrivacyClientSideAdaptiveClipping server-side strategy wrapper." msgstr "" +"이 모드는 서버 측 전략 래퍼인 차분 프라이버시 클라이언트 측 적응형 클리핑과 " +"함께 사용해야 합니다." #: flwr.client.mod.centraldp_mods.adaptiveclipping_mod:6 #: flwr.client.mod.centraldp_mods.fixedclipping_mod:6 of msgid "The wrapper sends the clipping_norm value to the client." -msgstr "" +msgstr "래퍼는 클라이언트에 clipping_norm 값을 전송합니다." #: flwr.client.mod.centraldp_mods.adaptiveclipping_mod:8 #: flwr.client.mod.centraldp_mods.fixedclipping_mod:8 of -msgid "This mod clips the client model updates before sending them to the server." -msgstr "" +msgid "" +"This mod clips the client model updates before sending them to the server." +msgstr "이 모드는 클라이언트 모델 업데이트를 서버로 보내기 전에 클립합니다." #: flwr.client.mod.centraldp_mods.adaptiveclipping_mod:10 of msgid "" "It also sends KEY_NORM_BIT to the server for computing the new clipping " "value." -msgstr "" +msgstr "또한 새 클리핑 값을 계산하기 위해 서버로 KEY_NORM_BIT을 전송합니다." #: flwr.client.mod.centraldp_mods.adaptiveclipping_mod:15 #: flwr.client.mod.centraldp_mods.fixedclipping_mod:13 @@ -8615,240 +9169,280 @@ msgstr "" #: flwr.server.workflow.secure_aggregation.secaggplus_workflow.SecAggPlusWorkflow:60 #: of msgid "Notes" -msgstr "" +msgstr "참고" #: flwr.client.mod.centraldp_mods.adaptiveclipping_mod:16 #: flwr.client.mod.centraldp_mods.fixedclipping_mod:14 of msgid "Consider the order of mods when using multiple." -msgstr "" +msgstr "여러 개를 사용할 때는 모드의 순서를 고려하세요." #: flwr.client.mod.centraldp_mods.adaptiveclipping_mod:18 of -msgid "Typically, adaptiveclipping_mod should be the last to operate on params." +msgid "" +"Typically, adaptiveclipping_mod should be the last to operate on params." msgstr "" +"일반적으로 adaptiveclipping_mod는 매개변수에서 가장 마지막으로 작동해야 합니" +"다." #: ../../source/ref-api/flwr.client.mod.fixedclipping_mod.rst:2 msgid "fixedclipping\\_mod" -msgstr "" +msgstr "fixedclipping\\_mod" #: flwr.client.mod.centraldp_mods.fixedclipping_mod:3 of msgid "" "This mod needs to be used with the " "DifferentialPrivacyClientSideFixedClipping server-side strategy wrapper." msgstr "" +"이 모드는 서버 측 전략 래퍼인 DifferentialPrivacyClientSideFixedClipping과 함" +"께 사용해야 합니다." #: flwr.client.mod.centraldp_mods.fixedclipping_mod:16 of msgid "Typically, fixedclipping_mod should be the last to operate on params." msgstr "" +"일반적으로 fixedclipping_mod는 매개변수에서 가장 마지막으로 작동해야 합니다." #: ../../source/ref-api/flwr.client.mod.make_ffn.rst:2 msgid "make\\_ffn" -msgstr "" +msgstr "make\\_ffn" #: ../../source/ref-api/flwr.client.mod.message_size_mod.rst:2 msgid "message\\_size\\_mod" -msgstr "" +msgstr "message\\_size\\_mod" #: flwr.client.mod.comms_mods.message_size_mod:3 of msgid "This mod logs the size in bytes of the message being transmited." -msgstr "" +msgstr "이 모드는 전송되는 메시지의 크기를 바이트 단위로 기록합니다." #: ../../source/ref-api/flwr.client.mod.parameters_size_mod.rst:2 msgid "parameters\\_size\\_mod" -msgstr "" +msgstr "parameters\\_size\\_mod" #: flwr.client.mod.comms_mods.parameters_size_mod:3 of msgid "" -"This mod logs the number of parameters transmitted in the message as well" -" as their size in bytes." +"This mod logs the number of parameters transmitted in the message as well as " +"their size in bytes." msgstr "" +"이 모드는 메시지에서 전송된 매개변수의 수와 그 크기를 바이트 단위로 기록합니" +"다." #: ../../source/ref-api/flwr.client.mod.secagg_mod.rst:2 msgid "secagg\\_mod" -msgstr "" +msgstr "secagg\\_mod" #: ../../source/ref-api/flwr.client.mod.secaggplus_mod.rst:2 msgid "secaggplus\\_mod" -msgstr "" +msgstr "secaggplus\\_mod" #: ../../source/ref-api/flwr.client.run_client_app.rst:2 msgid "run\\_client\\_app" -msgstr "" +msgstr "run\\_client\\_app" #: ../../source/ref-api/flwr.client.run_supernode.rst:2 msgid "run\\_supernode" -msgstr "" +msgstr "run\\_supernode" #: ../../source/ref-api/flwr.client.start_client.rst:2 msgid "start\\_client" -msgstr "" +msgstr "start\\_client" #: flwr.client.app.start_client:3 flwr.client.app.start_numpy_client:9 of msgid "" "The IPv4 or IPv6 address of the server. If the Flower server runs on the " -"same machine on port 8080, then `server_address` would be " -"`\"[::]:8080\"`." +"same machine on port 8080, then `server_address` would be `\"[::]:8080\"`." msgstr "" +"서버의 IPv4 또는 IPv6 주소입니다. Flower 서버가 포트 8080의 동일한 컴퓨터에" +"서 실행되는 경우 `서버_주소`는 `\"[::]:8080\"`이 됩니다." #: flwr.client.app.start_client:7 of msgid "A callable that instantiates a Client. (default: None)" -msgstr "" +msgstr "클라이언트를 인스턴스화하는 호출 가능 항목입니다. (기본값: None)" #: flwr.client.app.start_client:9 of msgid "" -"An implementation of the abstract base class `flwr.client.Client` " -"(default: None)" -msgstr "" +"An implementation of the abstract base class `flwr.client.Client` (default: " +"None)" +msgstr "추상 베이스 클래스 `flwr.client.Client`의 구현(기본값: None)" #: flwr.client.app.start_client:12 flwr.client.app.start_numpy_client:15 of msgid "" -"The maximum length of gRPC messages that can be exchanged with the Flower" -" server. The default should be sufficient for most models. Users who " -"train very large models might need to increase this value. Note that the " -"Flower server needs to be started with the same value (see " -"`flwr.server.start_server`), otherwise it will not know about the " -"increased limit and block larger messages." +"The maximum length of gRPC messages that can be exchanged with the Flower " +"server. The default should be sufficient for most models. Users who train " +"very large models might need to increase this value. Note that the Flower " +"server needs to be started with the same value (see `flwr.server." +"start_server`), otherwise it will not know about the increased limit and " +"block larger messages." msgstr "" +"Flower 서버와 교환할 수 있는 gRPC 메시지의 최대 길이입니다. 기본값은 대부분" +"의 모델에 충분합니다. 매우 큰 모델을 훈련하는 사용자는 이 값을 늘려야 할 수" +"도 있습니다. Flower 서버는 동일한 값으로 시작해야 하며(`flwr.server." +"start_server` 참조), 그렇지 않으면 증가된 제한을 알지 못해 더 큰 메시지를 차" +"단합니다." #: flwr.client.app.start_client:19 flwr.client.app.start_numpy_client:22 of msgid "" "The PEM-encoded root certificates as a byte string or a path string. If " -"provided, a secure connection using the certificates will be established " -"to an SSL-enabled Flower server." +"provided, a secure connection using the certificates will be established to " +"an SSL-enabled Flower server." msgstr "" +"바이트 문자열 또는 경로 문자열로 PEM 인코딩된 루트 인증서. 제공하면 인증서를 " +"사용하여 SSL이 활성화된 Flower 서버에 보안 연결이 설정됩니다." #: flwr.client.app.start_client:23 flwr.client.app.start_numpy_client:26 of msgid "" -"Starts an insecure gRPC connection when True. Enables HTTPS connection " -"when False, using system certificates if `root_certificates` is None." +"Starts an insecure gRPC connection when True. Enables HTTPS connection when " +"False, using system certificates if `root_certificates` is None." msgstr "" +"True일 경우 안전하지 않은 gRPC 연결을 시작합니다. root_certificates`가 None" +"인 경우 시스템 인증서를 사용하여 False일 때 HTTPS 연결을 활성화합니다." #: flwr.client.app.start_client:26 flwr.client.app.start_numpy_client:29 of msgid "" "Configure the transport layer. Allowed values: - 'grpc-bidi': gRPC, " -"bidirectional streaming - 'grpc-rere': gRPC, request-response " -"(experimental) - 'rest': HTTP (experimental)" +"bidirectional streaming - 'grpc-rere': gRPC, request-response (experimental) " +"- 'rest': HTTP (experimental)" msgstr "" +"전송 계층을 구성합니다. 허용되는 값입니다: - 'grpc-bidi': gRPC, 양방향 스트리" +"밍 - 'grpc-rere': gRPC, 요청-응답(실험적) - 'rest': HTTP(실험적)" #: flwr.client.app.start_client:31 of msgid "" "The maximum number of times the client will try to connect to the server " -"before giving up in case of a connection error. If set to None, there is " -"no limit to the number of tries." +"before giving up in case of a connection error. If set to None, there is no " +"limit to the number of tries." msgstr "" +"연결 오류 발생 시 클라이언트가 서버 연결을 포기하기 전에 시도하는 최대 횟수입" +"니다. None으로 설정하면 시도 횟수에 제한이 없습니다." #: flwr.client.app.start_client:35 of msgid "" -"The maximum duration before the client stops trying to connect to the " -"server in case of connection error. If set to None, there is no limit to " -"the total time." +"The maximum duration before the client stops trying to connect to the server " +"in case of connection error. If set to None, there is no limit to the total " +"time." msgstr "" +"연결 오류 발생 시 클라이언트가 서버에 대한 연결을 시도하지 않는 최대 기간입니" +"다. None으로 설정하면 총 시간에는 제한이 없습니다." #: flwr.client.app.start_client:42 flwr.client.app.start_numpy_client:37 of msgid "Starting a gRPC client with an insecure server connection:" -msgstr "" +msgstr "안전하지 않은 서버 연결로 gRPC 클라이언트 시작하기:" #: flwr.client.app.start_client:49 flwr.client.app.start_numpy_client:44 of msgid "Starting an SSL-enabled gRPC client using system certificates:" -msgstr "" +msgstr "시스템 인증서를 사용하여 SSL 사용 gRPC 클라이언트를 시작합니다:" #: flwr.client.app.start_client:60 flwr.client.app.start_numpy_client:52 of msgid "Starting an SSL-enabled gRPC client using provided certificates:" -msgstr "" +msgstr "제공된 인증서를 사용하여 SSL 지원 gRPC 클라이언트를 시작합니다:" #: ../../source/ref-api/flwr.client.start_numpy_client.rst:2 msgid "start\\_numpy\\_client" -msgstr "" +msgstr "start\\_numpy\\_client" #: flwr.client.app.start_numpy_client:5 of msgid "" -"This function is deprecated since 1.7.0. Use " -":code:`flwr.client.start_client` instead and first convert your " -":code:`NumPyClient` to type :code:`flwr.client.Client` by executing its " -":code:`to_client()` method." +"This function is deprecated since 1.7.0. Use :code:`flwr.client." +"start_client` instead and first convert your :code:`NumPyClient` to type :" +"code:`flwr.client.Client` by executing its :code:`to_client()` method." msgstr "" +"이 함수는 1.7.0부터 더 이상 사용되지 않습니다. 대신 :code:`flwr.client." +"start_client`를 사용하고 먼저 :code:`to_client()` 메서드를 실행하여 :code:" +"`NumPyClient`를 :code:`flwr.client.Client` 유형으로 변환합니다." #: flwr.client.app.start_numpy_client:13 of msgid "An implementation of the abstract base class `flwr.client.NumPyClient`." -msgstr "" +msgstr "추상 베이스 클래스 `flwr.client.NumPyClient`의 구현입니다." #: ../../source/ref-api/flwr.common.rst:2 msgid "common" -msgstr "" +msgstr "공통" #: ../../source/ref-api/flwr.common.rst:30::1 -msgid ":py:obj:`array_from_numpy `\\ \\(ndarray\\)" +msgid "" +":py:obj:`array_from_numpy `\\ \\(ndarray\\)" msgstr "" +":py:obj:`array_from_numpy `\\ \\(ndarray\\)" #: ../../source/ref-api/flwr.common.rst:30::1 #: flwr.common.record.conversion_utils.array_from_numpy:1 of msgid "Create Array from NumPy ndarray." -msgstr "" +msgstr "NumPy에서 배열을 만듭니다." #: ../../source/ref-api/flwr.common.rst:30::1 -msgid ":py:obj:`bytes_to_ndarray `\\ \\(tensor\\)" +msgid "" +":py:obj:`bytes_to_ndarray `\\ \\(tensor\\)" msgstr "" +":py:obj:`bytes_to_ndarray `\\ \\(tensor\\)" #: ../../source/ref-api/flwr.common.rst:30::1 #: flwr.common.parameter.bytes_to_ndarray:1 of msgid "Deserialize NumPy ndarray from bytes." -msgstr "" +msgstr "바이트에서 NumPy를 역직렬화합니다." #: ../../source/ref-api/flwr.common.rst:30::1 msgid "" ":py:obj:`configure `\\ \\(identifier\\[\\, " "filename\\, host\\]\\)" msgstr "" +":py:obj:`configure `\\ \\(identifier\\[\\, " +"filename\\, host\\]\\)" #: ../../source/ref-api/flwr.common.rst:30::1 #: flwr.common.logger.configure:1 of msgid "Configure logging to file and/or remote log server." -msgstr "" +msgstr "파일 및/또는 원격 로그 서버에 로깅을 구성합니다." #: ../../source/ref-api/flwr.common.rst:30::1 msgid "" ":py:obj:`event `\\ \\(event\\_type\\[\\, " "event\\_details\\]\\)" msgstr "" +":py:obj:`event `\\ \\(event\\_type\\[\\, " +"event\\_details\\]\\)" #: ../../source/ref-api/flwr.common.rst:30::1 #: flwr.common.telemetry.event:1 of msgid "Submit create_event to ThreadPoolExecutor to avoid blocking." -msgstr "" +msgstr "차단을 피하기 위해 create_event를 ThreadPoolExecutor에 제출합니다." #: ../../source/ref-api/flwr.common.rst:30::1 msgid "" ":py:obj:`log `\\ \\(level\\, msg\\, \\*args\\, " "\\*\\*kwargs\\)" msgstr "" +":py:obj:`log `\\ \\(level\\, msg\\, \\*args\\, " +"\\*\\*kwargs\\)" #: ../../source/ref-api/flwr.common.rst:30::1 logging.Logger.log:1 #: of msgid "Log 'msg % args' with the integer severity 'level'." -msgstr "" +msgstr "정수 심각도 'level'과 함께 'msg % args'를 기록합니다." #: ../../source/ref-api/flwr.common.rst:30::1 -msgid ":py:obj:`ndarray_to_bytes `\\ \\(ndarray\\)" +msgid "" +":py:obj:`ndarray_to_bytes `\\ \\(ndarray\\)" msgstr "" +":py:obj:`ndarray_to_bytes `\\ \\(ndarray\\)" #: ../../source/ref-api/flwr.common.rst:30::1 #: flwr.common.parameter.ndarray_to_bytes:1 of msgid "Serialize NumPy ndarray to bytes." -msgstr "" +msgstr "NumPy와 배열을 바이트열로 직렬화합니다." #: ../../source/ref-api/flwr.common.rst:30::1 msgid ":py:obj:`now `\\ \\(\\)" -msgstr "" +msgstr ":py:obj:`now `\\ \\(\\)" #: ../../source/ref-api/flwr.common.rst:30::1 #: flwr.common.date.now:1 of msgid "Construct a datetime from time.time() with time zone set to UTC." -msgstr "" +msgstr "표준 시간대를 UTC로 설정하여 time.time()에서 날짜 시간을 생성합니다." #: ../../source/ref-api/flwr.common.rst:30::1 msgid "" ":py:obj:`ndarrays_to_parameters `\\ " "\\(ndarrays\\)" msgstr "" +":py:obj:`ndarrays_to_parameters `\\ " +"\\(ndarrays\\)" #: ../../source/ref-api/flwr.common.rst:30::1 #: flwr.common.parameter.ndarrays_to_parameters:1 @@ -8856,1333 +9450,1485 @@ msgstr "" #: flwr.server.strategy.fedavg_android.FedAvgAndroid.ndarrays_to_parameters:1 #: of msgid "Convert NumPy ndarrays to parameters object." -msgstr "" +msgstr "NumPy 배열을 매개변수 객체로 변환합니다." #: ../../source/ref-api/flwr.common.rst:30::1 msgid "" ":py:obj:`parameters_to_ndarrays `\\ " "\\(parameters\\)" msgstr "" +":py:obj:`parameters_to_ndarrays `\\ " +"\\(parameters\\)" #: ../../source/ref-api/flwr.common.rst:30::1 #: flwr.common.parameter.parameters_to_ndarrays:1 of msgid "Convert parameters object to NumPy ndarrays." -msgstr "" +msgstr "매개변수 객체를 NumPy 배열로 변환합니다." #: ../../source/ref-api/flwr.common.rst:64::1 msgid "" -":py:obj:`Array `\\ \\(dtype\\, shape\\, stype\\, " -"data\\)" +":py:obj:`Array `\\ \\(dtype\\, shape\\, stype\\, data\\)" msgstr "" +":py:obj:`Array `\\ \\(dtype\\, shape\\, stype\\, data\\)" #: ../../source/ref-api/flwr.common.rst:64::1 #: flwr.common.record.parametersrecord.Array:1 of msgid "Array type." -msgstr "" +msgstr "배열 유형." #: ../../source/ref-api/flwr.common.rst:64::1 msgid "" ":py:obj:`ClientMessage `\\ " "\\(\\[get\\_properties\\_res\\, ...\\]\\)" msgstr "" +":py:obj:`ClientMessage `\\ " +"\\(\\[get\\_properties\\_res\\, ...\\]\\)" #: ../../source/ref-api/flwr.common.rst:64::1 #: flwr.common.typing.ClientMessage:1 of msgid "ClientMessage is a container used to hold one result message." msgstr "" +"ClientMessage는 하나의 결과 메시지를 저장하는 데 사용되는 컨테이너입니다." #: ../../source/ref-api/flwr.common.rst:64::1 msgid ":py:obj:`Code `\\ \\(value\\)" -msgstr "" +msgstr ":py:obj:`Code `\\ \\(value\\)" #: ../../source/ref-api/flwr.common.rst:64::1 #: flwr.common.typing.Code:1 of msgid "Client status codes." -msgstr "" +msgstr "클라이언트 상태 코드." #: ../../source/ref-api/flwr.common.rst:64::1 msgid "" ":py:obj:`ConfigsRecord `\\ " "\\(\\[configs\\_dict\\, keep\\_input\\]\\)" msgstr "" +":py:obj:`ConfigsRecord `\\ " +"\\(\\[configs\\_dict\\, keep\\_input\\]\\)" #: ../../source/ref-api/flwr.common.rst:64::1 #: flwr.common.record.configsrecord.ConfigsRecord:1 of msgid "Configs record." -msgstr "" +msgstr "레코드를 설정합니다." #: ../../source/ref-api/flwr.common.rst:64::1 msgid ":py:obj:`Context `\\ \\(state\\)" -msgstr "" +msgstr ":py:obj:`Context `\\ \\(state\\)" #: ../../source/ref-api/flwr.common.rst:64::1 #: flwr.common.context.Context:1 of msgid "State of your run." -msgstr "" +msgstr "실행 상태." #: ../../source/ref-api/flwr.common.rst:64::1 msgid ":py:obj:`DisconnectRes `\\ \\(reason\\)" -msgstr "" +msgstr ":py:obj:`DisconnectRes `\\ \\(reason\\)" #: ../../source/ref-api/flwr.common.rst:64::1 #: flwr.common.typing.DisconnectRes:1 of msgid "DisconnectRes message from client to server." -msgstr "" +msgstr "클라이언트에서 서버로 연결 해제 메시지를 보냅니다." #: ../../source/ref-api/flwr.common.rst:64::1 msgid "" -":py:obj:`EvaluateIns `\\ \\(parameters\\, " -"config\\)" +":py:obj:`EvaluateIns `\\ \\(parameters\\, config\\)" msgstr "" +":py:obj:`EvaluateIns `\\ \\(parameters\\, config\\)" #: ../../source/ref-api/flwr.common.rst:64::1 #: flwr.common.typing.EvaluateIns:1 of msgid "Evaluate instructions for a client." -msgstr "" +msgstr "클라이언트에 대한 지침을 평가합니다." #: ../../source/ref-api/flwr.common.rst:64::1 msgid "" ":py:obj:`EvaluateRes `\\ \\(status\\, loss\\, " "num\\_examples\\, metrics\\)" msgstr "" +":py:obj:`EvaluateRes `\\ \\(status\\, loss\\, " +"num\\_examples\\, metrics\\)" #: ../../source/ref-api/flwr.common.rst:64::1 #: flwr.common.typing.EvaluateRes:1 of msgid "Evaluate response from a client." -msgstr "" +msgstr "클라이언트의 응답을 평가합니다." #: ../../source/ref-api/flwr.common.rst:64::1 msgid ":py:obj:`EventType `\\ \\(value\\)" -msgstr "" +msgstr ":py:obj:`EventType `\\ \\(value\\)" #: ../../source/ref-api/flwr.common.rst:64::1 #: flwr.common.telemetry.EventType:1 of msgid "Types of telemetry events." -msgstr "" +msgstr "원격 분석 이벤트의 유형." #: ../../source/ref-api/flwr.common.rst:64::1 msgid ":py:obj:`FitIns `\\ \\(parameters\\, config\\)" -msgstr "" +msgstr ":py:obj:`FitIns `\\ \\(parameters\\, config\\)" #: ../../source/ref-api/flwr.common.rst:64::1 #: flwr.common.typing.FitIns:1 of msgid "Fit instructions for a client." -msgstr "" +msgstr "고객을 위한 맞춤 지침." #: ../../source/ref-api/flwr.common.rst:64::1 msgid "" ":py:obj:`FitRes `\\ \\(status\\, parameters\\, " "num\\_examples\\, metrics\\)" msgstr "" +":py:obj:`FitRes `\\ \\(status\\, parameters\\, " +"num\\_examples\\, metrics\\)" #: ../../source/ref-api/flwr.common.rst:64::1 #: flwr.common.typing.FitRes:1 of msgid "Fit response from a client." -msgstr "" +msgstr "클라이언트의 적합성 응답." #: ../../source/ref-api/flwr.common.rst:64::1 msgid ":py:obj:`Error `\\ \\(code\\[\\, reason\\]\\)" -msgstr "" +msgstr ":py:obj:`Error `\\ \\(code\\[\\, reason\\]\\)" #: ../../source/ref-api/flwr.common.rst:64::1 #: flwr.common.message.Error:1 of msgid "A dataclass that stores information about an error that occurred." -msgstr "" +msgstr "발생한 오류에 대한 정보를 저장하는 데이터 클래스입니다." #: ../../source/ref-api/flwr.common.rst:64::1 -msgid ":py:obj:`GetParametersIns `\\ \\(config\\)" +msgid "" +":py:obj:`GetParametersIns `\\ \\(config\\)" msgstr "" +":py:obj:`GetParametersIns `\\ \\(config\\)" #: ../../source/ref-api/flwr.common.rst:64::1 #: flwr.common.typing.GetParametersIns:1 of msgid "Parameters request for a client." -msgstr "" +msgstr "클라이언트에 대한 매개변수 요청입니다." #: ../../source/ref-api/flwr.common.rst:64::1 msgid "" ":py:obj:`GetParametersRes `\\ \\(status\\, " "parameters\\)" msgstr "" +":py:obj:`GetParametersRes `\\ \\(status\\, " +"parameters\\)" #: ../../source/ref-api/flwr.common.rst:64::1 #: flwr.common.typing.GetParametersRes:1 of msgid "Response when asked to return parameters." -msgstr "" +msgstr "매개변수 반환 요청 시 응답합니다." #: ../../source/ref-api/flwr.common.rst:64::1 -msgid ":py:obj:`GetPropertiesIns `\\ \\(config\\)" +msgid "" +":py:obj:`GetPropertiesIns `\\ \\(config\\)" msgstr "" +":py:obj:`GetPropertiesIns `\\ \\(config\\)" #: ../../source/ref-api/flwr.common.rst:64::1 #: flwr.common.typing.GetPropertiesIns:1 of msgid "Properties request for a client." -msgstr "" +msgstr "클라이언트에 대한 속성 요청." #: ../../source/ref-api/flwr.common.rst:64::1 msgid "" ":py:obj:`GetPropertiesRes `\\ \\(status\\, " "properties\\)" msgstr "" +":py:obj:`GetPropertiesRes `\\ \\(status\\, " +"properties\\)" #: ../../source/ref-api/flwr.common.rst:64::1 #: flwr.common.typing.GetPropertiesRes:1 of msgid "Properties response from a client." -msgstr "" +msgstr "클라이언트의 속성 응답을 확인합니다." #: ../../source/ref-api/flwr.common.rst:64::1 msgid "" ":py:obj:`Message `\\ \\(metadata\\[\\, content\\, " "error\\]\\)" msgstr "" +":py:obj:`Message `\\ \\(metadata\\[\\, content\\, " +"error\\]\\)" #: ../../source/ref-api/flwr.common.rst:64::1 #: flwr.common.message.Message:1 of msgid "State of your application from the viewpoint of the entity using it." -msgstr "" +msgstr "애플리케이션을 사용하는 엔티티의 관점에서 애플리케이션의 상태입니다." #: ../../source/ref-api/flwr.common.rst:64::1 msgid ":py:obj:`MessageType `\\ \\(\\)" -msgstr "" +msgstr ":py:obj:`MessageType `\\ \\(\\)" #: ../../source/ref-api/flwr.common.rst:64::1 #: flwr.common.constant.MessageType:1 of msgid "Message type." -msgstr "" +msgstr "메시지 타입." #: ../../source/ref-api/flwr.common.rst:64::1 msgid ":py:obj:`MessageTypeLegacy `\\ \\(\\)" -msgstr "" +msgstr ":py:obj:`MessageTypeLegacy `\\ \\(\\)" #: ../../source/ref-api/flwr.common.rst:64::1 #: flwr.common.constant.MessageTypeLegacy:1 of msgid "Legacy message type." -msgstr "" +msgstr "레거시 메시지 타입." #: ../../source/ref-api/flwr.common.rst:64::1 msgid "" -":py:obj:`Metadata `\\ \\(run\\_id\\, " -"message\\_id\\, src\\_node\\_id\\, ...\\)" +":py:obj:`Metadata `\\ \\(run\\_id\\, message\\_id\\, " +"src\\_node\\_id\\, ...\\)" msgstr "" +":py:obj:`Metadata `\\ \\(run\\_id\\, message\\_id\\, " +"src\\_node\\_id\\, ...\\)" #: ../../source/ref-api/flwr.common.rst:64::1 #: flwr.common.message.Metadata:1 of msgid "A dataclass holding metadata associated with the current message." -msgstr "" +msgstr "현재 메시지와 관련된 메타데이터를 보유한 데이터 클래스입니다." #: ../../source/ref-api/flwr.common.rst:64::1 msgid "" ":py:obj:`MetricsRecord `\\ " "\\(\\[metrics\\_dict\\, keep\\_input\\]\\)" msgstr "" +":py:obj:`MetricsRecord `\\ " +"\\(\\[metrics\\_dict\\, keep\\_input\\]\\)" #: ../../source/ref-api/flwr.common.rst:64::1 #: flwr.common.record.metricsrecord.MetricsRecord:1 of msgid "Metrics record." -msgstr "" +msgstr "메트릭 기록." #: ../../source/ref-api/flwr.common.rst:64::1 msgid ":py:obj:`NDArray `\\" -msgstr "" +msgstr ":py:obj:`NDArray `\\" #: ../../source/ref-api/flwr.common.rst:64::1 msgid "" -"alias of :py:class:`~numpy.ndarray`\\ [:py:obj:`~typing.Any`, " -":py:class:`~numpy.dtype`\\ [:py:obj:`~typing.Any`]]" +"alias of :py:class:`~numpy.ndarray`\\ [:py:obj:`~typing.Any`, :py:class:" +"`~numpy.dtype`\\ [:py:obj:`~typing.Any`]]" msgstr "" +"alias of :py:class:`~numpy.ndarray`\\ [:py:obj:`~typing.Any`, :py:class:" +"`~numpy.dtype`\\ [:py:obj:`~typing.Any`]]" #: ../../source/ref-api/flwr.common.rst:64::1 msgid "" ":py:obj:`Parameters `\\ \\(tensors\\, " "tensor\\_type\\)" msgstr "" +":py:obj:`Parameters `\\ \\(tensors\\, " +"tensor\\_type\\)" #: ../../source/ref-api/flwr.common.rst:64::1 #: flwr.common.typing.Parameters:1 of msgid "Model parameters." -msgstr "" +msgstr "모델 매개변수." #: ../../source/ref-api/flwr.common.rst:64::1 msgid "" ":py:obj:`ParametersRecord `\\ " "\\(\\[array\\_dict\\, keep\\_input\\]\\)" msgstr "" +":py:obj:`ParametersRecord `\\ " +"\\(\\[array\\_dict\\, keep\\_input\\]\\)" #: ../../source/ref-api/flwr.common.rst:64::1 #: flwr.common.record.parametersrecord.ParametersRecord:1 of msgid "Parameters record." -msgstr "" +msgstr "매개변수 기록." #: ../../source/ref-api/flwr.common.rst:64::1 msgid ":py:obj:`ReconnectIns `\\ \\(seconds\\)" -msgstr "" +msgstr ":py:obj:`ReconnectIns `\\ \\(seconds\\)" #: ../../source/ref-api/flwr.common.rst:64::1 #: flwr.common.typing.ReconnectIns:1 of msgid "ReconnectIns message from server to client." -msgstr "" +msgstr "서버에서 클라이언트로 메시지를 다시 연결합니다." #: ../../source/ref-api/flwr.common.rst:64::1 msgid "" ":py:obj:`RecordSet `\\ " "\\(\\[parameters\\_records\\, ...\\]\\)" msgstr "" +":py:obj:`RecordSet `\\ " +"\\(\\[parameters\\_records\\, ...\\]\\)" #: ../../source/ref-api/flwr.common.rst:64::1 #: flwr.common.record.recordset.RecordSet:1 of msgid "RecordSet stores groups of parameters, metrics and configs." -msgstr "" +msgstr "RecordSet은 매개변수, 메트릭 및 설정 그룹을 저장합니다." #: ../../source/ref-api/flwr.common.rst:64::1 msgid "" ":py:obj:`ServerMessage `\\ " "\\(\\[get\\_properties\\_ins\\, ...\\]\\)" msgstr "" +":py:obj:`ServerMessage `\\ " +"\\(\\[get\\_properties\\_ins\\, ...\\]\\)" #: ../../source/ref-api/flwr.common.rst:64::1 #: flwr.common.typing.ServerMessage:1 of msgid "ServerMessage is a container used to hold one instruction message." msgstr "" +"ServerMessage는 하나의 instruction 메시지를 저장하는 데 사용되는 컨테이너입니" +"다." #: ../../source/ref-api/flwr.common.rst:64::1 msgid ":py:obj:`Status `\\ \\(code\\, message\\)" -msgstr "" +msgstr ":py:obj:`Status `\\ \\(code\\, message\\)" #: ../../source/ref-api/flwr.common.rst:64::1 #: flwr.common.typing.Status:1 of msgid "Client status." -msgstr "" +msgstr "클라이언트 상태." #: ../../source/ref-api/flwr.common.Array.rst:2 msgid "Array" -msgstr "" +msgstr "배열" #: flwr.common.record.parametersrecord.Array:3 of msgid "" "A dataclass containing serialized data from an array-like or tensor-like " "object along with some metadata about it." msgstr "" +"배열형 또는 텐서형 객체의 직렬화된 데이터와 그에 대한 일부 메타데이터를 포함" +"하는 데이터 클래스입니다." #: flwr.common.record.parametersrecord.Array:6 of msgid "" -"A string representing the data type of the serialised object (e.g. " -"`np.float32`)" -msgstr "" +"A string representing the data type of the serialised object (e.g. `np." +"float32`)" +msgstr "직렬화된 객체의 데이터 유형을 나타내는 문자열(예: `np.float32`)" #: flwr.common.record.parametersrecord.Array:8 of msgid "" -"A list representing the shape of the unserialized array-like object. This" -" is used to deserialize the data (depending on the serialization method) " -"or simply as a metadata field." +"A list representing the shape of the unserialized array-like object. This is " +"used to deserialize the data (depending on the serialization method) or " +"simply as a metadata field." msgstr "" +"직렬화되지 않은 배열과 같은 객체의 모양을 나타내는 목록입니다. 직렬화 방법에 " +"따라 데이터를 역직렬화하는 데 사용되거나 단순히 메타데이터 필드로 사용됩니다." #: flwr.common.record.parametersrecord.Array:12 of msgid "" -"A string indicating the type of serialisation mechanism used to generate " -"the bytes in `data` from an array-like or tensor-like object." +"A string indicating the type of serialisation mechanism used to generate the " +"bytes in `data` from an array-like or tensor-like object." msgstr "" +"배열형 또는 텐서형 객체에서 `데이터`의 바이트를 생성하는 데 사용되는 직렬화 " +"메커니즘의 유형을 나타내는 문자열입니다." #: flwr.common.record.parametersrecord.Array:15 of msgid "A buffer of bytes containing the data." -msgstr "" +msgstr "데이터를 포함하는 바이트 버퍼입니다." #: ../../source/ref-api/flwr.common.Array.rst:26::1 msgid ":py:obj:`numpy `\\ \\(\\)" -msgstr "" +msgstr ":py:obj:`numpy `\\ \\(\\)" #: ../../source/ref-api/flwr.common.Array.rst:26::1 #: flwr.common.record.parametersrecord.Array.numpy:1 of msgid "Return the array as a NumPy array." -msgstr "" +msgstr "배열을 NumPy 배열로 반환합니다." #: flwr.common.record.parametersrecord.Array.numpy:1::1 of msgid ":py:obj:`dtype `\\" -msgstr "" +msgstr ":py:obj:`dtype `\\" #: flwr.common.record.parametersrecord.Array.numpy:1::1 of msgid ":py:obj:`shape `\\" -msgstr "" +msgstr ":py:obj:`shape `\\" #: flwr.common.record.parametersrecord.Array.numpy:1::1 of msgid ":py:obj:`stype `\\" -msgstr "" +msgstr ":py:obj:`stype `\\" #: flwr.common.record.parametersrecord.Array.numpy:1::1 of msgid ":py:obj:`data `\\" -msgstr "" +msgstr ":py:obj:`data `\\" #: ../../source/ref-api/flwr.common.ClientMessage.rst:2 msgid "ClientMessage" -msgstr "" +msgstr "클라이언트 메시지" #: ../../source/ref-api/flwr.common.ClientMessage.rst:31::1 msgid ":py:obj:`evaluate_res `\\" -msgstr "" +msgstr ":py:obj:`evaluate_res `\\" #: ../../source/ref-api/flwr.common.ClientMessage.rst:31::1 msgid ":py:obj:`fit_res `\\" -msgstr "" +msgstr ":py:obj:`fit_res `\\" #: ../../source/ref-api/flwr.common.ClientMessage.rst:31::1 msgid "" -":py:obj:`get_parameters_res " -"`\\" +":py:obj:`get_parameters_res `\\" msgstr "" +":py:obj:`get_parameters_res `\\" #: ../../source/ref-api/flwr.common.ClientMessage.rst:31::1 msgid "" -":py:obj:`get_properties_res " -"`\\" +":py:obj:`get_properties_res `\\" msgstr "" +":py:obj:`get_properties_res `\\" #: ../../source/ref-api/flwr.common.Code.rst:2 msgid "Code" -msgstr "" +msgstr "코드" #: flwr.common.typing.Code:1 of msgid "Bases: :py:class:`~enum.Enum`" -msgstr "" +msgstr "Bases: :py:class:`~enum.Enum`" #: ../../source/ref-api/flwr.common.Code.rst:26::1 msgid ":py:obj:`OK `\\" -msgstr "" +msgstr ":py:obj:`OK `\\" #: ../../source/ref-api/flwr.common.Code.rst:26::1 msgid "" -":py:obj:`GET_PROPERTIES_NOT_IMPLEMENTED " -"`\\" +":py:obj:`GET_PROPERTIES_NOT_IMPLEMENTED `\\" msgstr "" +":py:obj:`GET_PROPERTIES_NOT_IMPLEMENTED `\\" #: ../../source/ref-api/flwr.common.Code.rst:26::1 msgid "" -":py:obj:`GET_PARAMETERS_NOT_IMPLEMENTED " -"`\\" +":py:obj:`GET_PARAMETERS_NOT_IMPLEMENTED `\\" msgstr "" +":py:obj:`GET_PARAMETERS_NOT_IMPLEMENTED `\\" #: ../../source/ref-api/flwr.common.Code.rst:26::1 msgid ":py:obj:`FIT_NOT_IMPLEMENTED `\\" -msgstr "" +msgstr ":py:obj:`FIT_NOT_IMPLEMENTED `\\" #: ../../source/ref-api/flwr.common.Code.rst:26::1 msgid "" -":py:obj:`EVALUATE_NOT_IMPLEMENTED " -"`\\" +":py:obj:`EVALUATE_NOT_IMPLEMENTED `\\" msgstr "" +":py:obj:`EVALUATE_NOT_IMPLEMENTED `\\" #: ../../source/ref-api/flwr.common.ConfigsRecord.rst:2 msgid "ConfigsRecord" -msgstr "" +msgstr "컨피그 레코드" #: flwr.common.record.configsrecord.ConfigsRecord:1 of msgid "" -"Bases: :py:class:`~flwr.common.record.typeddict.TypedDict`\\ " -"[:py:class:`str`, :py:class:`int` | :py:class:`float` | :py:class:`str` |" -" :py:class:`bytes` | :py:class:`bool` | :py:class:`~typing.List`\\ " -"[:py:class:`int`] | :py:class:`~typing.List`\\ [:py:class:`float`] | " -":py:class:`~typing.List`\\ [:py:class:`str`] | :py:class:`~typing.List`\\" -" [:py:class:`bytes`] | :py:class:`~typing.List`\\ [:py:class:`bool`]]" +"Bases: :py:class:`~flwr.common.record.typeddict.TypedDict`\\ [:py:class:" +"`str`, :py:class:`int` | :py:class:`float` | :py:class:`str` | :py:class:" +"`bytes` | :py:class:`bool` | :py:class:`~typing.List`\\ [:py:class:`int`] | :" +"py:class:`~typing.List`\\ [:py:class:`float`] | :py:class:`~typing.List`\\ [:" +"py:class:`str`] | :py:class:`~typing.List`\\ [:py:class:`bytes`] | :py:class:" +"`~typing.List`\\ [:py:class:`bool`]]" msgstr "" +"Bases: :py:class:`~flwr.common.record.typeddict.TypedDict`\\ [:py:class:`str`" +", :py:class:`int` | :py:class:`float` | :py:class:`str` | :py:class:`bytes` |" +" :py:class:`bool` | :py:class:`~typing.List`\\ [:py:class:`int`] | " +":py:class:`~typing.List`\\ [:py:class:`float`] | :py:class:`~typing.List`\\ " +"[:py:class:`str`] | :py:class:`~typing.List`\\ [:py:class:`bytes`] | " +":py:class:`~typing.List`\\ [:py:class:`bool`]]" #: flwr.common.record.typeddict.TypedDict.clear:1::1 of msgid ":py:obj:`clear `\\ \\(\\)" -msgstr "" +msgstr ":py:obj:`clear `\\ \\(\\)" #: flwr.common.record.typeddict.TypedDict.clear:1 #: flwr.common.record.typeddict.TypedDict.clear:1::1 of msgid "Remove all items from R." -msgstr "" +msgstr "R에서 모든 항목을 제거합니다." #: flwr.common.record.typeddict.TypedDict.clear:1::1 of msgid ":py:obj:`count_bytes `\\ \\(\\)" -msgstr "" +msgstr ":py:obj:`count_bytes `\\ \\(\\)" #: flwr.common.record.configsrecord.ConfigsRecord.count_bytes:1 #: flwr.common.record.metricsrecord.MetricsRecord.count_bytes:1 #: flwr.common.record.parametersrecord.ParametersRecord.count_bytes:1 #: flwr.common.record.typeddict.TypedDict.clear:1::1 of msgid "Return number of Bytes stored in this object." -msgstr "" +msgstr "이 객체에 저장된 바이트 수를 반환합니다." #: flwr.common.record.typeddict.TypedDict.clear:1::1 of msgid ":py:obj:`get `\\ \\(k\\[\\,d\\]\\)" -msgstr "" +msgstr ":py:obj:`get `\\ \\(k\\[\\,d\\]\\)" #: flwr.common.record.typeddict.TypedDict.clear:1::1 #: flwr.common.record.typeddict.TypedDict.get:1 of msgid "d defaults to None." -msgstr "" +msgstr "d는 기본값이 None입니다." #: flwr.common.record.typeddict.TypedDict.clear:1::1 of msgid ":py:obj:`items `\\ \\(\\)" -msgstr "" +msgstr ":py:obj:`items `\\ \\(\\)" #: flwr.common.record.typeddict.TypedDict.clear:1::1 of msgid ":py:obj:`keys `\\ \\(\\)" -msgstr "" +msgstr ":py:obj:`keys `\\ \\(\\)" #: flwr.common.record.typeddict.TypedDict.clear:1::1 of msgid ":py:obj:`pop `\\ \\(k\\[\\,d\\]\\)" -msgstr "" +msgstr ":py:obj:`pop `\\ \\(k\\[\\,d\\]\\)" #: flwr.common.record.typeddict.TypedDict.clear:1::1 #: flwr.common.record.typeddict.TypedDict.pop:1 of -msgid "If key is not found, d is returned if given, otherwise KeyError is raised." -msgstr "" +msgid "" +"If key is not found, d is returned if given, otherwise KeyError is raised." +msgstr "키를 찾을 수 없으면 주어진 경우 d가 반환되고, 그렇지 않으면 KeyError가 " +"발생합니다." #: flwr.common.record.typeddict.TypedDict.clear:1::1 of msgid "" ":py:obj:`update `\\ \\(\\[E\\, " "\\]\\*\\*F\\)" msgstr "" +":py:obj:`update `\\ \\(\\[E\\, \\]\\*\\*F\\" +")" #: flwr.common.record.typeddict.TypedDict.clear:1::1 #: flwr.common.record.typeddict.TypedDict.update:1 of msgid "Update R from dict/iterable E and F." -msgstr "" +msgstr "dict/iterable E 및 F에서 R을 업데이트합니다." #: flwr.common.record.typeddict.TypedDict.clear:1::1 of msgid ":py:obj:`values `\\ \\(\\)" -msgstr "" +msgstr ":py:obj:`values `\\ \\(\\)" #: flwr.common.record.configsrecord.ConfigsRecord.count_bytes:3 of msgid "This function counts booleans as occupying 1 Byte." -msgstr "" +msgstr "이 함수는 booleans을 1바이트를 차지하는 것으로 계산합니다." #: ../../source/ref-api/flwr.common.Context.rst:2 msgid "Context" -msgstr "" +msgstr "컨텍스트" #: flwr.common.context.Context:3 of msgid "" -"Holds records added by the entity in a given run and that will stay " -"local. This means that the data it holds will never leave the system it's" -" running from. This can be used as an intermediate storage or scratchpad " -"when executing mods. It can also be used as a memory to access at " -"different points during the lifecycle of this entity (e.g. across " -"multiple rounds)" +"Holds records added by the entity in a given run and that will stay local. " +"This means that the data it holds will never leave the system it's running " +"from. This can be used as an intermediate storage or scratchpad when " +"executing mods. It can also be used as a memory to access at different " +"points during the lifecycle of this entity (e.g. across multiple rounds)" msgstr "" +"특정 실행에서 엔티티가 추가한 레코드를 보유하며 로컬에 유지됩니다. 즉, " +"저장된 데이터는 실행 중인 시스템을 벗어나지 않습니다. 모드를 실행할 때 중간 " +"저장소나 스크래치 패드로 사용할 수 있습니다. 또한 이 엔티티의 수명 주기 동안 " +"다른 시점에서 액세스하기 위한 메모리로도 사용할 수 있습니다(예: 여러 " +"라운드에 걸쳐)" #: ../../source/ref-api/flwr.common.Context.rst:28::1 msgid ":py:obj:`state `\\" -msgstr "" +msgstr ":py:obj:`state `\\" #: ../../source/ref-api/flwr.common.DisconnectRes.rst:2 msgid "DisconnectRes" -msgstr "" +msgstr "연결 해제" #: ../../source/ref-api/flwr.common.DisconnectRes.rst:28::1 msgid ":py:obj:`reason `\\" -msgstr "" +msgstr ":py:obj:`reason `\\" #: ../../source/ref-api/flwr.common.Error.rst:2 msgid "Error" -msgstr "" +msgstr "오류" #: flwr.common.message.Error:3 of msgid "An identifier for the error." -msgstr "" +msgstr "오류 식별자입니다." #: flwr.common.message.Error:5 of msgid "A reason for why the error arose (e.g. an exception stack-trace)" -msgstr "" +msgstr "오류가 발생한 이유(예: 예외 스택 추적)" #: flwr.common.Error.code:1::1 of msgid ":py:obj:`code `\\" -msgstr "" +msgstr ":py:obj:`code `\\" #: flwr.common.Error.code:1 flwr.common.Error.code:1::1 of msgid "Error code." -msgstr "" +msgstr "오류 코드." #: flwr.common.Error.code:1::1 of msgid ":py:obj:`reason `\\" -msgstr "" +msgstr ":py:obj:`reason `\\" #: flwr.common.Error.code:1::1 flwr.common.Error.reason:1 of msgid "Reason reported about the error." -msgstr "" +msgstr "오류에 대해 보고된 사유입니다." #: ../../source/ref-api/flwr.common.EvaluateIns.rst:2 msgid "EvaluateIns" -msgstr "" +msgstr "평가" #: ../../source/ref-api/flwr.common.EvaluateIns.rst:29::1 msgid ":py:obj:`parameters `\\" -msgstr "" +msgstr ":py:obj:`parameters `\\" #: ../../source/ref-api/flwr.common.EvaluateIns.rst:29::1 msgid ":py:obj:`config `\\" -msgstr "" +msgstr ":py:obj:`config `\\" #: ../../source/ref-api/flwr.common.EvaluateRes.rst:2 msgid "EvaluateRes" -msgstr "" +msgstr "EvaluateRes" #: ../../source/ref-api/flwr.common.EvaluateRes.rst:31::1 msgid ":py:obj:`status `\\" -msgstr "" +msgstr ":py:obj:`status `\\" #: ../../source/ref-api/flwr.common.EvaluateRes.rst:31::1 msgid ":py:obj:`loss `\\" -msgstr "" +msgstr ":py:obj:`loss `\\" #: ../../source/ref-api/flwr.common.EvaluateRes.rst:31::1 msgid ":py:obj:`num_examples `\\" -msgstr "" +msgstr ":py:obj:`num_examples `\\" #: ../../source/ref-api/flwr.common.EvaluateRes.rst:31::1 msgid ":py:obj:`metrics `\\" -msgstr "" +msgstr ":py:obj:`metrics `\\" #: ../../source/ref-api/flwr.common.EventType.rst:2 msgid "EventType" -msgstr "" +msgstr "이벤트 타입" #: flwr.common.telemetry.EventType:1 of msgid "Bases: :py:class:`str`, :py:class:`~enum.Enum`" -msgstr "" +msgstr "Bases: :py:class:`str`, :py:class:`~enum.Enum`" #: ../../source/ref-api/flwr.common.EventType.rst:163::1 msgid "" ":py:obj:`encode `\\ \\(\\[encoding\\, " "errors\\]\\)" msgstr "" +":py:obj:`encode `\\ \\(\\[encoding\\, errors\\]" +"\\)" #: ../../source/ref-api/flwr.common.EventType.rst:163::1 #: flwr.common.EventType.encode:1 of msgid "Encode the string using the codec registered for encoding." -msgstr "" +msgstr "인코딩용으로 등록된 코덱을 사용하여 문자열을 인코딩합니다." #: ../../source/ref-api/flwr.common.EventType.rst:163::1 msgid "" ":py:obj:`replace `\\ \\(old\\, new\\[\\, " "count\\]\\)" msgstr "" +":py:obj:`replace `\\ \\(old\\, new\\[\\, " +"count\\]\\)" #: ../../source/ref-api/flwr.common.EventType.rst:163::1 #: flwr.common.EventType.replace:1 of msgid "Return a copy with all occurrences of substring old replaced by new." -msgstr "" +msgstr "이전 하위 문자열이 모두 새 하위 문자열로 바뀐 사본을 반환합니다." #: ../../source/ref-api/flwr.common.EventType.rst:163::1 msgid "" -":py:obj:`split `\\ \\(\\[sep\\, " -"maxsplit\\]\\)" +":py:obj:`split `\\ \\(\\[sep\\, maxsplit\\]\\)" msgstr "" +":py:obj:`split `\\ \\(\\[sep\\, maxsplit\\]\\)" #: ../../source/ref-api/flwr.common.EventType.rst:163::1 #: flwr.common.EventType.rsplit:1 flwr.common.EventType.split:1 of msgid "" -"Return a list of the substrings in the string, using sep as the separator" -" string." -msgstr "" +"Return a list of the substrings in the string, using sep as the separator " +"string." +msgstr "sep를 구분 문자열로 사용하여 문자열의 하위 문자열 목록을 반환합니다." #: ../../source/ref-api/flwr.common.EventType.rst:163::1 msgid "" -":py:obj:`rsplit `\\ \\(\\[sep\\, " -"maxsplit\\]\\)" +":py:obj:`rsplit `\\ \\(\\[sep\\, maxsplit\\]\\)" msgstr "" +":py:obj:`rsplit `\\ \\(\\[sep\\, maxsplit\\]\\)" #: ../../source/ref-api/flwr.common.EventType.rst:163::1 msgid ":py:obj:`join `\\ \\(iterable\\, \\/\\)" -msgstr "" +msgstr ":py:obj:`join `\\ \\(iterable\\, \\/\\)" #: ../../source/ref-api/flwr.common.EventType.rst:163::1 #: flwr.common.EventType.join:1 of msgid "Concatenate any number of strings." -msgstr "" +msgstr "원하는 수의 문자열을 연결합니다." #: ../../source/ref-api/flwr.common.EventType.rst:163::1 msgid ":py:obj:`capitalize `\\ \\(\\)" -msgstr "" +msgstr ":py:obj:`capitalize `\\ \\(\\)" #: ../../source/ref-api/flwr.common.EventType.rst:163::1 #: flwr.common.EventType.capitalize:1 of msgid "Return a capitalized version of the string." -msgstr "" +msgstr "대문자로 된 문자열을 반환합니다." #: ../../source/ref-api/flwr.common.EventType.rst:163::1 msgid ":py:obj:`casefold `\\ \\(\\)" -msgstr "" +msgstr ":py:obj:`casefold `\\ \\(\\)" #: ../../source/ref-api/flwr.common.EventType.rst:163::1 #: flwr.common.EventType.casefold:1 of msgid "Return a version of the string suitable for caseless comparisons." -msgstr "" +msgstr "대소문자 구분 없는 비교에 적합한 문자열을 반환합니다." #: ../../source/ref-api/flwr.common.EventType.rst:163::1 msgid ":py:obj:`title `\\ \\(\\)" -msgstr "" +msgstr ":py:obj:`title `\\ \\(\\)" #: ../../source/ref-api/flwr.common.EventType.rst:163::1 #: flwr.common.EventType.title:1 of msgid "Return a version of the string where each word is titlecased." -msgstr "" +msgstr "각 단어의 제목이 대소문자로 구분된 문자열을 반환합니다." #: ../../source/ref-api/flwr.common.EventType.rst:163::1 msgid "" ":py:obj:`center `\\ \\(width\\[\\, " "fillchar\\]\\)" msgstr "" +":py:obj:`center `\\ \\(width\\[\\, fillchar\\]" +"\\)" #: ../../source/ref-api/flwr.common.EventType.rst:163::1 #: flwr.common.EventType.center:1 of msgid "Return a centered string of length width." -msgstr "" +msgstr "길이 너비의 가운데 문자열을 반환합니다." #: ../../source/ref-api/flwr.common.EventType.rst:163::1 msgid "" ":py:obj:`count `\\ \\(sub\\[\\, start\\[\\, " "end\\]\\]\\)" msgstr "" +":py:obj:`count `\\ \\(sub\\[\\, start\\[\\, " +"end\\]\\]\\)" #: ../../source/ref-api/flwr.common.EventType.rst:163::1 msgid "" -"Return the number of non-overlapping occurrences of substring sub in " -"string S[start:end]." -msgstr "" +"Return the number of non-overlapping occurrences of substring sub in string " +"S[start:end]." +msgstr "문자열 S[start:end]에서 하위 문자열 sub이 겹치지 않는 횟수를 반환합니다." #: ../../source/ref-api/flwr.common.EventType.rst:163::1 msgid "" -":py:obj:`expandtabs `\\ " -"\\(\\[tabsize\\]\\)" +":py:obj:`expandtabs `\\ \\(\\[tabsize\\]\\)" msgstr "" +":py:obj:`expandtabs `\\ \\(\\[tabsize\\]\\)" #: ../../source/ref-api/flwr.common.EventType.rst:163::1 #: flwr.common.EventType.expandtabs:1 of msgid "Return a copy where all tab characters are expanded using spaces." -msgstr "" +msgstr "모든 탭 문자가 공백을 사용하여 확장된 사본을 반환합니다." #: ../../source/ref-api/flwr.common.EventType.rst:163::1 msgid "" ":py:obj:`find `\\ \\(sub\\[\\, start\\[\\, " "end\\]\\]\\)" msgstr "" +":py:obj:`find `\\ \\(sub\\[\\, start\\[\\, end\\]" +"\\]\\)" #: ../../source/ref-api/flwr.common.EventType.rst:163::1 msgid "" -"Return the lowest index in S where substring sub is found, such that sub " -"is contained within S[start:end]." -msgstr "" +"Return the lowest index in S where substring sub is found, such that sub is " +"contained within S[start:end]." +msgstr "하위 문자열 sub이 발견되는 S에서 하위가 S[start:end] 내에 포함되는 가장 낮은 " +"인덱스를 반환합니다." #: ../../source/ref-api/flwr.common.EventType.rst:163::1 -msgid ":py:obj:`partition `\\ \\(sep\\, \\/\\)" +msgid "" +":py:obj:`partition `\\ \\(sep\\, \\/\\)" msgstr "" +":py:obj:`partition `\\ \\(sep\\, \\/\\)" #: ../../source/ref-api/flwr.common.EventType.rst:163::1 #: flwr.common.EventType.partition:1 flwr.common.EventType.rpartition:1 of msgid "Partition the string into three parts using the given separator." -msgstr "" +msgstr "지정된 구분 기호를 사용하여 문자열을 세 부분으로 분할합니다." #: ../../source/ref-api/flwr.common.EventType.rst:163::1 msgid "" ":py:obj:`index `\\ \\(sub\\[\\, start\\[\\, " "end\\]\\]\\)" msgstr "" +":py:obj:`index `\\ \\(sub\\[\\, start\\[\\, " +"end\\]\\]\\)" #: ../../source/ref-api/flwr.common.EventType.rst:163::1 msgid "" -":py:obj:`ljust `\\ \\(width\\[\\, " -"fillchar\\]\\)" +":py:obj:`ljust `\\ \\(width\\[\\, fillchar\\]\\)" msgstr "" +":py:obj:`ljust `\\ \\(width\\[\\, fillchar\\]\\)" #: ../../source/ref-api/flwr.common.EventType.rst:163::1 #: flwr.common.EventType.ljust:1 of msgid "Return a left-justified string of length width." -msgstr "" +msgstr "왼쪽으로 정렬된 길이의 문자열을 반환합니다." #: ../../source/ref-api/flwr.common.EventType.rst:163::1 msgid ":py:obj:`lower `\\ \\(\\)" -msgstr "" +msgstr ":py:obj:`lower `\\ \\(\\)" #: ../../source/ref-api/flwr.common.EventType.rst:163::1 #: flwr.common.EventType.lower:1 of msgid "Return a copy of the string converted to lowercase." -msgstr "" +msgstr "소문자로 변환된 문자열 사본을 반환합니다." #: ../../source/ref-api/flwr.common.EventType.rst:163::1 msgid ":py:obj:`lstrip `\\ \\(\\[chars\\]\\)" -msgstr "" +msgstr ":py:obj:`lstrip `\\ \\(\\[chars\\]\\)" #: ../../source/ref-api/flwr.common.EventType.rst:163::1 #: flwr.common.EventType.lstrip:1 of msgid "Return a copy of the string with leading whitespace removed." -msgstr "" +msgstr "선행 공백이 제거된 문자열의 복사본을 반환합니다." #: ../../source/ref-api/flwr.common.EventType.rst:163::1 msgid "" ":py:obj:`rfind `\\ \\(sub\\[\\, start\\[\\, " "end\\]\\]\\)" msgstr "" +":py:obj:`rfind `\\ \\(sub\\[\\, start\\[\\, " +"end\\]\\]\\)" #: ../../source/ref-api/flwr.common.EventType.rst:163::1 msgid "" -"Return the highest index in S where substring sub is found, such that sub" -" is contained within S[start:end]." -msgstr "" +"Return the highest index in S where substring sub is found, such that sub is " +"contained within S[start:end]." +msgstr "부분 문자열 sub이 발견되는 곳에서 sub이 S[start:end] 내에 포함되도록 S에서 " +"가장 높은 인덱스를 반환합니다." #: ../../source/ref-api/flwr.common.EventType.rst:163::1 msgid "" -":py:obj:`rindex `\\ \\(sub\\[\\, " -"start\\[\\, end\\]\\]\\)" +":py:obj:`rindex `\\ \\(sub\\[\\, start\\[\\, " +"end\\]\\]\\)" msgstr "" +":py:obj:`rindex `\\ \\(sub\\[\\, start\\[\\, " +"end\\]\\]\\)" #: ../../source/ref-api/flwr.common.EventType.rst:163::1 msgid "" -":py:obj:`rjust `\\ \\(width\\[\\, " -"fillchar\\]\\)" +":py:obj:`rjust `\\ \\(width\\[\\, fillchar\\]\\)" msgstr "" +":py:obj:`rjust `\\ \\(width\\[\\, fillchar\\]\\)" #: ../../source/ref-api/flwr.common.EventType.rst:163::1 #: flwr.common.EventType.rjust:1 of msgid "Return a right-justified string of length width." -msgstr "" +msgstr "길이 너비의 오른쪽 정렬된 문자열을 반환합니다." #: ../../source/ref-api/flwr.common.EventType.rst:163::1 msgid ":py:obj:`rstrip `\\ \\(\\[chars\\]\\)" -msgstr "" +msgstr ":py:obj:`rstrip `\\ \\(\\[chars\\]\\)" #: ../../source/ref-api/flwr.common.EventType.rst:163::1 #: flwr.common.EventType.rstrip:1 of msgid "Return a copy of the string with trailing whitespace removed." -msgstr "" +msgstr "후행 공백이 제거된 문자열의 복사본을 반환합니다." #: ../../source/ref-api/flwr.common.EventType.rst:163::1 -msgid ":py:obj:`rpartition `\\ \\(sep\\, \\/\\)" +msgid "" +":py:obj:`rpartition `\\ \\(sep\\, \\/\\)" msgstr "" +":py:obj:`rpartition `\\ \\(sep\\, \\/\\)" #: ../../source/ref-api/flwr.common.EventType.rst:163::1 msgid "" ":py:obj:`splitlines `\\ " "\\(\\[keepends\\]\\)" msgstr "" +":py:obj:`splitlines `\\ \\(\\[keepends\\]\\" +")" #: ../../source/ref-api/flwr.common.EventType.rst:163::1 #: flwr.common.EventType.splitlines:1 of msgid "Return a list of the lines in the string, breaking at line boundaries." -msgstr "" +msgstr "문자열의 줄 목록을 줄 경계에서 구분하여 반환합니다." #: ../../source/ref-api/flwr.common.EventType.rst:163::1 msgid ":py:obj:`strip `\\ \\(\\[chars\\]\\)" -msgstr "" +msgstr ":py:obj:`strip `\\ \\(\\[chars\\]\\)" #: ../../source/ref-api/flwr.common.EventType.rst:163::1 #: flwr.common.EventType.strip:1 of -msgid "Return a copy of the string with leading and trailing whitespace removed." -msgstr "" +msgid "" +"Return a copy of the string with leading and trailing whitespace removed." +msgstr "선행 및 후행 공백이 제거된 문자열 사본을 반환합니다." #: ../../source/ref-api/flwr.common.EventType.rst:163::1 msgid ":py:obj:`swapcase `\\ \\(\\)" -msgstr "" +msgstr ":py:obj:`swapcase `\\ \\(\\)" #: ../../source/ref-api/flwr.common.EventType.rst:163::1 #: flwr.common.EventType.swapcase:1 of msgid "" "Convert uppercase characters to lowercase and lowercase characters to " "uppercase." -msgstr "" +msgstr "대문자를 소문자로, 소문자를 대문자로 변환합니다." #: ../../source/ref-api/flwr.common.EventType.rst:163::1 -msgid ":py:obj:`translate `\\ \\(table\\, \\/\\)" +msgid "" +":py:obj:`translate `\\ \\(table\\, \\/\\)" msgstr "" +":py:obj:`translate `\\ \\(table\\, \\/\\)" #: ../../source/ref-api/flwr.common.EventType.rst:163::1 #: flwr.common.EventType.translate:1 of msgid "Replace each character in the string using the given translation table." -msgstr "" +msgstr "주어진 번역 테이블을 사용하여 문자열의 각 문자를 바꿉니다." #: ../../source/ref-api/flwr.common.EventType.rst:163::1 msgid ":py:obj:`upper `\\ \\(\\)" -msgstr "" +msgstr ":py:obj:`upper `\\ \\(\\)" #: ../../source/ref-api/flwr.common.EventType.rst:163::1 #: flwr.common.EventType.upper:1 of msgid "Return a copy of the string converted to uppercase." -msgstr "" +msgstr "Return a copy of the string converted to uppercase." #: ../../source/ref-api/flwr.common.EventType.rst:163::1 msgid "" -":py:obj:`startswith `\\ \\(prefix\\[\\," -" start\\[\\, end\\]\\]\\)" +":py:obj:`startswith `\\ \\(prefix\\[\\, " +"start\\[\\, end\\]\\]\\)" msgstr "" +":py:obj:`startswith `\\ \\(prefix\\[\\, " +"start\\[\\, end\\]\\]\\)" #: ../../source/ref-api/flwr.common.EventType.rst:163::1 msgid "Return True if S starts with the specified prefix, False otherwise." -msgstr "" +msgstr "S가 지정된 접두사로 시작하면 True를 반환하고, 그렇지 않으면 False를 " +"반환합니다." #: ../../source/ref-api/flwr.common.EventType.rst:163::1 msgid "" ":py:obj:`endswith `\\ \\(suffix\\[\\, " "start\\[\\, end\\]\\]\\)" msgstr "" +":py:obj:`endswith `\\ \\(suffix\\[\\, start\\" +"[\\, end\\]\\]\\)" #: ../../source/ref-api/flwr.common.EventType.rst:163::1 msgid "Return True if S ends with the specified suffix, False otherwise." -msgstr "" +msgstr "S가 지정된 접미사로 끝나면 True를 반환하고 그렇지 않으면 False을 반환합니다." #: ../../source/ref-api/flwr.common.EventType.rst:163::1 msgid "" -":py:obj:`removeprefix `\\ " -"\\(prefix\\, \\/\\)" +":py:obj:`removeprefix `\\ \\(prefix\\, " +"\\/\\)" msgstr "" +":py:obj:`removeprefix `\\ \\(prefix\\, \\" +"/\\)" #: ../../source/ref-api/flwr.common.EventType.rst:163::1 #: flwr.common.EventType.removeprefix:1 of msgid "Return a str with the given prefix string removed if present." -msgstr "" +msgstr "주어진 접두사 문자열이 있는 경우 제거된 문자열을 반환합니다." #: ../../source/ref-api/flwr.common.EventType.rst:163::1 msgid "" -":py:obj:`removesuffix `\\ " -"\\(suffix\\, \\/\\)" +":py:obj:`removesuffix `\\ \\(suffix\\, " +"\\/\\)" msgstr "" +":py:obj:`removesuffix `\\ \\(suffix\\, \\" +"/\\)" #: ../../source/ref-api/flwr.common.EventType.rst:163::1 #: flwr.common.EventType.removesuffix:1 of msgid "Return a str with the given suffix string removed if present." -msgstr "" +msgstr "주어진 접미사 문자열이 있는 경우 제거된 문자열을 반환합니다." #: ../../source/ref-api/flwr.common.EventType.rst:163::1 msgid ":py:obj:`isascii `\\ \\(\\)" -msgstr "" +msgstr ":py:obj:`isascii `\\ \\(\\)" #: ../../source/ref-api/flwr.common.EventType.rst:163::1 #: flwr.common.EventType.isascii:1 of msgid "Return True if all characters in the string are ASCII, False otherwise." -msgstr "" +msgstr "문자열의 모든 문자가 ASCII인 경우 True를 반환하고, 그렇지 않으면 False를 " +"반환합니다." #: ../../source/ref-api/flwr.common.EventType.rst:163::1 msgid ":py:obj:`islower `\\ \\(\\)" -msgstr "" +msgstr ":py:obj:`islower `\\ \\(\\)" #: ../../source/ref-api/flwr.common.EventType.rst:163::1 #: flwr.common.EventType.islower:1 of msgid "Return True if the string is a lowercase string, False otherwise." -msgstr "" +msgstr "문자열이 소문자 문자열이면 True를 반환하고, 그렇지 않으면 False를 반환합니다." #: ../../source/ref-api/flwr.common.EventType.rst:163::1 msgid ":py:obj:`isupper `\\ \\(\\)" -msgstr "" +msgstr ":py:obj:`isupper `\\ \\(\\)" #: ../../source/ref-api/flwr.common.EventType.rst:163::1 #: flwr.common.EventType.isupper:1 of msgid "Return True if the string is an uppercase string, False otherwise." -msgstr "" +msgstr "문자열이 대문자 문자열이면 True를 반환하고, 그렇지 않으면 False를 반환합니다." #: ../../source/ref-api/flwr.common.EventType.rst:163::1 msgid ":py:obj:`istitle `\\ \\(\\)" -msgstr "" +msgstr ":py:obj:`istitle `\\ \\(\\)" #: ../../source/ref-api/flwr.common.EventType.rst:163::1 #: flwr.common.EventType.istitle:1 of msgid "Return True if the string is a title-cased string, False otherwise." -msgstr "" +msgstr "문자열이 제목 대/소문자가 구분된 문자열이면 True를 반환하고, 그렇지 않으면 " +"False를 반환합니다." #: ../../source/ref-api/flwr.common.EventType.rst:163::1 msgid ":py:obj:`isspace `\\ \\(\\)" -msgstr "" +msgstr ":py:obj:`isspace `\\ \\(\\)" #: ../../source/ref-api/flwr.common.EventType.rst:163::1 #: flwr.common.EventType.isspace:1 of msgid "Return True if the string is a whitespace string, False otherwise." -msgstr "" +msgstr "문자열이 공백 문자열이면 True를 반환하고, 그렇지 않으면 False를 반환합니다." #: ../../source/ref-api/flwr.common.EventType.rst:163::1 msgid ":py:obj:`isdecimal `\\ \\(\\)" -msgstr "" +msgstr ":py:obj:`isdecimal `\\ \\(\\)" #: ../../source/ref-api/flwr.common.EventType.rst:163::1 #: flwr.common.EventType.isdecimal:1 of msgid "Return True if the string is a decimal string, False otherwise." -msgstr "" +msgstr "문자열이 10진수 문자열이면 True를 반환하고, 그렇지 않으면 False를 반환합니다." #: ../../source/ref-api/flwr.common.EventType.rst:163::1 msgid ":py:obj:`isdigit `\\ \\(\\)" -msgstr "" +msgstr ":py:obj:`isdigit `\\ \\(\\)" #: ../../source/ref-api/flwr.common.EventType.rst:163::1 #: flwr.common.EventType.isdigit:1 of msgid "Return True if the string is a digit string, False otherwise." -msgstr "" +msgstr "문자열이 숫자 문자열이면 True를 반환하고, 그렇지 않으면 False를 반환합니다." #: ../../source/ref-api/flwr.common.EventType.rst:163::1 msgid ":py:obj:`isnumeric `\\ \\(\\)" -msgstr "" +msgstr ":py:obj:`isnumeric `\\ \\(\\)" #: ../../source/ref-api/flwr.common.EventType.rst:163::1 #: flwr.common.EventType.isnumeric:1 of msgid "Return True if the string is a numeric string, False otherwise." -msgstr "" +msgstr "문자열이 숫자 문자열이면 True를 반환하고, 그렇지 않으면 False를 반환합니다." #: ../../source/ref-api/flwr.common.EventType.rst:163::1 msgid ":py:obj:`isalpha `\\ \\(\\)" -msgstr "" +msgstr ":py:obj:`isalpha `\\ \\(\\)" #: ../../source/ref-api/flwr.common.EventType.rst:163::1 #: flwr.common.EventType.isalpha:1 of msgid "Return True if the string is an alphabetic string, False otherwise." -msgstr "" +msgstr "문자열이 알파벳 문자열이면 True를 반환하고, 그렇지 않으면 False를 반환합니다." #: ../../source/ref-api/flwr.common.EventType.rst:163::1 msgid ":py:obj:`isalnum `\\ \\(\\)" -msgstr "" +msgstr ":py:obj:`isalnum `\\ \\(\\)" #: ../../source/ref-api/flwr.common.EventType.rst:163::1 #: flwr.common.EventType.isalnum:1 of msgid "Return True if the string is an alpha-numeric string, False otherwise." -msgstr "" +msgstr "문자열이 영-숫자 문자열이면 True를 반환하고, 그렇지 않으면 False를 " +"반환합니다." #: ../../source/ref-api/flwr.common.EventType.rst:163::1 msgid ":py:obj:`isidentifier `\\ \\(\\)" -msgstr "" +msgstr ":py:obj:`isidentifier `\\ \\(\\)" #: ../../source/ref-api/flwr.common.EventType.rst:163::1 #: flwr.common.EventType.isidentifier:1 of -msgid "Return True if the string is a valid Python identifier, False otherwise." -msgstr "" +msgid "" +"Return True if the string is a valid Python identifier, False otherwise." +msgstr "문자열이 유효한 파이썬 식별자인 경우 True를 반환하고, 그렇지 않으면 False를 " +"반환합니다." #: ../../source/ref-api/flwr.common.EventType.rst:163::1 msgid ":py:obj:`isprintable `\\ \\(\\)" -msgstr "" +msgstr ":py:obj:`isprintable `\\ \\(\\)" #: ../../source/ref-api/flwr.common.EventType.rst:163::1 #: flwr.common.EventType.isprintable:1 of msgid "Return True if the string is printable, False otherwise." -msgstr "" +msgstr "문자열을 인쇄할 수 있으면 True를 반환하고, 그렇지 않으면 False를 반환합니다." #: ../../source/ref-api/flwr.common.EventType.rst:163::1 msgid ":py:obj:`zfill `\\ \\(width\\, \\/\\)" -msgstr "" +msgstr ":py:obj:`zfill `\\ \\(width\\, \\/\\)" #: ../../source/ref-api/flwr.common.EventType.rst:163::1 #: flwr.common.EventType.zfill:1 of msgid "" -"Pad a numeric string with zeros on the left, to fill a field of the given" -" width." -msgstr "" +"Pad a numeric string with zeros on the left, to fill a field of the given " +"width." +msgstr "숫자 문자열을 왼쪽에 0으로 채워서 지정된 너비의 필드를 채웁니다." #: ../../source/ref-api/flwr.common.EventType.rst:163::1 msgid "" ":py:obj:`format `\\ \\(\\*args\\, " "\\*\\*kwargs\\)" msgstr "" +":py:obj:`format `\\ \\(\\*args\\, \\*\\*" +"kwargs\\)" #: ../../source/ref-api/flwr.common.EventType.rst:163::1 -msgid "Return a formatted version of S, using substitutions from args and kwargs." -msgstr "" +msgid "" +"Return a formatted version of S, using substitutions from args and kwargs." +msgstr "args와 kwarg의 치환을 사용하여 형식이 지정된 S를 반환합니다." #: ../../source/ref-api/flwr.common.EventType.rst:163::1 msgid ":py:obj:`format_map `\\ \\(mapping\\)" -msgstr "" +msgstr ":py:obj:`format_map `\\ \\(mapping\\)" #: ../../source/ref-api/flwr.common.EventType.rst:163::1 msgid "Return a formatted version of S, using substitutions from mapping." -msgstr "" +msgstr "매핑의 치환을 사용하여 형식이 지정된 S를 반환합니다." #: ../../source/ref-api/flwr.common.EventType.rst:163::1 msgid ":py:obj:`maketrans `\\" -msgstr "" +msgstr ":py:obj:`maketrans `\\" #: ../../source/ref-api/flwr.common.EventType.rst:163::1 #: flwr.common.EventType.maketrans:1 of msgid "Return a translation table usable for str.translate()." -msgstr "" +msgstr "str.translate()에 사용할 수 있는 번역 테이블을 반환합니다." #: flwr.common.EventType.capitalize:1::1 of msgid ":py:obj:`PING `\\" -msgstr "" +msgstr ":py:obj:`PING `\\" #: flwr.common.EventType.capitalize:1::1 of -msgid ":py:obj:`START_CLIENT_ENTER `\\" +msgid "" +":py:obj:`START_CLIENT_ENTER `\\" msgstr "" +":py:obj:`START_CLIENT_ENTER `\\" #: flwr.common.EventType.capitalize:1::1 of -msgid ":py:obj:`START_CLIENT_LEAVE `\\" +msgid "" +":py:obj:`START_CLIENT_LEAVE `\\" msgstr "" +":py:obj:`START_CLIENT_LEAVE `\\" #: flwr.common.EventType.capitalize:1::1 of -msgid ":py:obj:`START_SERVER_ENTER `\\" +msgid "" +":py:obj:`START_SERVER_ENTER `\\" msgstr "" +":py:obj:`START_SERVER_ENTER `\\" #: flwr.common.EventType.capitalize:1::1 of -msgid ":py:obj:`START_SERVER_LEAVE `\\" +msgid "" +":py:obj:`START_SERVER_LEAVE `\\" msgstr "" +":py:obj:`START_SERVER_LEAVE `\\" #: flwr.common.EventType.capitalize:1::1 of msgid "" -":py:obj:`RUN_DRIVER_API_ENTER " -"`\\" +":py:obj:`RUN_DRIVER_API_ENTER `\\" msgstr "" +":py:obj:`RUN_DRIVER_API_ENTER `\\" #: flwr.common.EventType.capitalize:1::1 of msgid "" -":py:obj:`RUN_DRIVER_API_LEAVE " -"`\\" +":py:obj:`RUN_DRIVER_API_LEAVE `\\" msgstr "" +":py:obj:`RUN_DRIVER_API_LEAVE `\\" #: flwr.common.EventType.capitalize:1::1 of msgid "" -":py:obj:`RUN_FLEET_API_ENTER " -"`\\" +":py:obj:`RUN_FLEET_API_ENTER `\\" msgstr "" +":py:obj:`RUN_FLEET_API_ENTER `\\" #: flwr.common.EventType.capitalize:1::1 of msgid "" -":py:obj:`RUN_FLEET_API_LEAVE " -"`\\" +":py:obj:`RUN_FLEET_API_LEAVE `\\" msgstr "" +":py:obj:`RUN_FLEET_API_LEAVE `\\" #: flwr.common.EventType.capitalize:1::1 of msgid "" -":py:obj:`RUN_SUPERLINK_ENTER " -"`\\" +":py:obj:`RUN_SUPERLINK_ENTER `\\" msgstr "" +":py:obj:`RUN_SUPERLINK_ENTER `\\" #: flwr.common.EventType.capitalize:1::1 of msgid "" -":py:obj:`RUN_SUPERLINK_LEAVE " -"`\\" +":py:obj:`RUN_SUPERLINK_LEAVE `\\" msgstr "" +":py:obj:`RUN_SUPERLINK_LEAVE `\\" #: flwr.common.EventType.capitalize:1::1 of msgid "" -":py:obj:`START_SIMULATION_ENTER " -"`\\" +":py:obj:`START_SIMULATION_ENTER `\\" msgstr "" +":py:obj:`START_SIMULATION_ENTER `\\" #: flwr.common.EventType.capitalize:1::1 of msgid "" -":py:obj:`START_SIMULATION_LEAVE " -"`\\" +":py:obj:`START_SIMULATION_LEAVE `\\" msgstr "" +":py:obj:`START_SIMULATION_LEAVE `\\" #: flwr.common.EventType.capitalize:1::1 of msgid ":py:obj:`DRIVER_CONNECT `\\" -msgstr "" +msgstr ":py:obj:`DRIVER_CONNECT `\\" #: flwr.common.EventType.capitalize:1::1 of msgid ":py:obj:`DRIVER_DISCONNECT `\\" -msgstr "" +msgstr ":py:obj:`DRIVER_DISCONNECT `\\" #: flwr.common.EventType.capitalize:1::1 of -msgid ":py:obj:`START_DRIVER_ENTER `\\" +msgid "" +":py:obj:`START_DRIVER_ENTER `\\" msgstr "" +":py:obj:`START_DRIVER_ENTER `\\" #: flwr.common.EventType.capitalize:1::1 of -msgid ":py:obj:`START_DRIVER_LEAVE `\\" +msgid "" +":py:obj:`START_DRIVER_LEAVE `\\" msgstr "" +":py:obj:`START_DRIVER_LEAVE `\\" #: flwr.common.EventType.capitalize:1::1 of msgid "" -":py:obj:`RUN_CLIENT_APP_ENTER " -"`\\" +":py:obj:`RUN_CLIENT_APP_ENTER `\\" msgstr "" +":py:obj:`RUN_CLIENT_APP_ENTER `\\" #: flwr.common.EventType.capitalize:1::1 of msgid "" -":py:obj:`RUN_CLIENT_APP_LEAVE " -"`\\" +":py:obj:`RUN_CLIENT_APP_LEAVE `\\" msgstr "" +":py:obj:`RUN_CLIENT_APP_LEAVE `\\" #: flwr.common.EventType.capitalize:1::1 of msgid "" -":py:obj:`RUN_SERVER_APP_ENTER " -"`\\" +":py:obj:`RUN_SERVER_APP_ENTER `\\" msgstr "" +":py:obj:`RUN_SERVER_APP_ENTER `\\" #: flwr.common.EventType.capitalize:1::1 of msgid "" -":py:obj:`RUN_SERVER_APP_LEAVE " -"`\\" +":py:obj:`RUN_SERVER_APP_LEAVE `\\" msgstr "" +":py:obj:`RUN_SERVER_APP_LEAVE `\\" #: flwr.common.EventType.capitalize:1::1 of msgid "" -":py:obj:`RUN_SUPERNODE_ENTER " -"`\\" +":py:obj:`RUN_SUPERNODE_ENTER `\\" msgstr "" +":py:obj:`RUN_SUPERNODE_ENTER `\\" #: flwr.common.EventType.capitalize:1::1 of msgid "" -":py:obj:`RUN_SUPERNODE_LEAVE " -"`\\" +":py:obj:`RUN_SUPERNODE_LEAVE `\\" msgstr "" +":py:obj:`RUN_SUPERNODE_LEAVE `\\" #: flwr.common.EventType.capitalize:1::1 of msgid "" -":py:obj:`RUN_SUPEREXEC_ENTER " -"`\\" +":py:obj:`RUN_SUPEREXEC_ENTER `\\" msgstr "" +":py:obj:`RUN_SUPEREXEC_ENTER `\\" #: flwr.common.EventType.capitalize:1::1 of msgid "" -":py:obj:`RUN_SUPEREXEC_LEAVE " -"`\\" +":py:obj:`RUN_SUPEREXEC_LEAVE `\\" msgstr "" +":py:obj:`RUN_SUPEREXEC_LEAVE `\\" #: flwr.common.EventType.capitalize:3 of msgid "" "More specifically, make the first character have upper case and the rest " "lower case." -msgstr "" +msgstr "보다 구체적으로, 첫 번째 문자는 대문자로, 나머지는 소문자로 만듭니다." #: flwr.common.EventType.center:3 flwr.common.EventType.ljust:3 #: flwr.common.EventType.rjust:3 of -msgid "Padding is done using the specified fill character (default is a space)." -msgstr "" +msgid "" +"Padding is done using the specified fill character (default is a space)." +msgstr "패딩은 지정된 채우기 문자를 사용하여 수행됩니다(기본값은 공백)." #: flwr.common.EventType.count:1 of msgid "" -"Return the number of non-overlapping occurrences of substring sub in " -"string S[start:end]. Optional arguments start and end are interpreted as" -" in slice notation." +"Return the number of non-overlapping occurrences of substring sub in string " +"S[start:end]. Optional arguments start and end are interpreted as in slice " +"notation." msgstr "" +"문자열 S[start:end]에서 부분 문자열 sub의 겹치지 않는 횟수를 반환합니다. " +"선택적 인자 start와 end는 슬라이스 표기법과 같이 해석됩니다." #: flwr.common.EventType.encode:3 of msgid "encoding" -msgstr "" +msgstr "인코딩" #: flwr.common.EventType.encode:4 of msgid "The encoding in which to encode the string." -msgstr "" +msgstr "문자열을 인코딩합니다." #: flwr.common.EventType.encode:9 of msgid "errors" -msgstr "" +msgstr "오류" #: flwr.common.EventType.encode:6 of msgid "" "The error handling scheme to use for encoding errors. The default is " "'strict' meaning that encoding errors raise a UnicodeEncodeError. Other " -"possible values are 'ignore', 'replace' and 'xmlcharrefreplace' as well " -"as any other name registered with codecs.register_error that can handle " +"possible values are 'ignore', 'replace' and 'xmlcharrefreplace' as well as " +"any other name registered with codecs.register_error that can handle " "UnicodeEncodeErrors." msgstr "" +"인코딩 오류에 사용할 오류 처리 방식입니다. 기본값은 'strict'로, 인코딩 " +"오류가 발생하면 UnicodeEncodeError를 발생시킵니다. 다른 가능한 값으로는 " +"'ignore', 'replace', 'xmlcharrefreplace', 그리고 UnicodeEncodeError를 처리할 " +"수 있는 codecs.register_error에 등록된 다른 이름도 사용할 수 있습니다." #: flwr.common.EventType.endswith:1 of msgid "" "Return True if S ends with the specified suffix, False otherwise. With " -"optional start, test S beginning at that position. With optional end, " -"stop comparing S at that position. suffix can also be a tuple of strings " -"to try." +"optional start, test S beginning at that position. With optional end, stop " +"comparing S at that position. suffix can also be a tuple of strings to try." msgstr "" +"S가 지정된 접미사로 끝나면 True를 반환하고, 그렇지 않으면 False를 " +"반환합니다. 시작 옵션을 사용하면 해당 위치부터 S를 테스트합니다. end 옵션을 " +"사용하면 해당 위치에서 S 비교를 중지합니다. 접미사는 시도할 문자열의 튜플일 " +"수도 있습니다." #: flwr.common.EventType.expandtabs:3 of msgid "If tabsize is not given, a tab size of 8 characters is assumed." -msgstr "" +msgstr "탭 크기를 지정하지 않으면 크기가 8로 지정됩니다." #: flwr.common.EventType.find:1 flwr.common.EventType.index:1 of msgid "" -"Return the lowest index in S where substring sub is found, such that sub " -"is contained within S[start:end]. Optional arguments start and end are " +"Return the lowest index in S where substring sub is found, such that sub is " +"contained within S[start:end]. Optional arguments start and end are " "interpreted as in slice notation." msgstr "" +"부분 문자열 sub가 발견되는 곳의 가장 낮은 인덱스를 반환하며, sub는 " +"S[start:end] 내에 포함되어야 합니다. 선택적 인자 start와 end는 슬라이스 " +"표기법과 같이 해석됩니다." #: flwr.common.EventType.find:5 flwr.common.EventType.rfind:5 of msgid "Return -1 on failure." -msgstr "" +msgstr "실패 시 -1을 반환합니다." #: flwr.common.EventType.format:1 of msgid "" -"Return a formatted version of S, using substitutions from args and " -"kwargs. The substitutions are identified by braces ('{' and '}')." -msgstr "" +"Return a formatted version of S, using substitutions from args and kwargs. " +"The substitutions are identified by braces ('{' and '}')." +msgstr "args와 kwargs의 치환을 사용하여 형식이 지정된 S를 반환합니다. 치환은 " +"중괄호('{' 및 '}')로 식별됩니다." #: flwr.common.EventType.format_map:1 of msgid "" "Return a formatted version of S, using substitutions from mapping. The " "substitutions are identified by braces ('{' and '}')." -msgstr "" +msgstr "매핑의 치환을 사용하여 형식이 지정된 S를 반환합니다. 치환은 중괄호('{' 및 " +"'}')로 식별됩니다." #: flwr.common.EventType.index:5 flwr.common.EventType.rindex:5 of msgid "Raises ValueError when the substring is not found." -msgstr "" +msgstr "부분 문자열을 찾을 수 없을 때 ValueError를 발생시킵니다." #: flwr.common.EventType.isalnum:3 of msgid "" -"A string is alpha-numeric if all characters in the string are alpha-" -"numeric and there is at least one character in the string." -msgstr "" +"A string is alpha-numeric if all characters in the string are alpha-numeric " +"and there is at least one character in the string." +msgstr "문자열의 모든 문자가 영숫자이고 문자열에 하나 이상의 문자가 있는 경우 " +"문자열은 영-숫자입니다." #: flwr.common.EventType.isalpha:3 of msgid "" -"A string is alphabetic if all characters in the string are alphabetic and" -" there is at least one character in the string." -msgstr "" +"A string is alphabetic if all characters in the string are alphabetic and " +"there is at least one character in the string." +msgstr "문자열의 모든 문자가 알파벳이고 문자열에 하나 이상의 문자가 있는 경우 " +"문자열은 알파벳입니다." #: flwr.common.EventType.isascii:3 of msgid "" -"ASCII characters have code points in the range U+0000-U+007F. Empty " -"string is ASCII too." -msgstr "" +"ASCII characters have code points in the range U+0000-U+007F. Empty string " +"is ASCII too." +msgstr "ASCII 문자는 U+0000-U+007F 범위의 코드 포인트가 있습니다. 빈 문자열도 " +"ASCII입니다." #: flwr.common.EventType.isdecimal:3 of msgid "" -"A string is a decimal string if all characters in the string are decimal " -"and there is at least one character in the string." -msgstr "" +"A string is a decimal string if all characters in the string are decimal and " +"there is at least one character in the string." +msgstr "문자열의 모든 문자가 10진수이고 문자열에 하나 이상의 문자가 있는 경우 " +"문자열은 10진수 문자열입니다." #: flwr.common.EventType.isdigit:3 of msgid "" -"A string is a digit string if all characters in the string are digits and" -" there is at least one character in the string." -msgstr "" +"A string is a digit string if all characters in the string are digits and " +"there is at least one character in the string." +msgstr "문자열의 모든 문자가 숫자이고 문자열에 하나 이상의 문자가 있는 경우 문자열은 " +"숫자 문자열입니다." #: flwr.common.EventType.isidentifier:3 of msgid "" -"Call keyword.iskeyword(s) to test whether string s is a reserved " -"identifier, such as \"def\" or \"class\"." +"Call keyword.iskeyword(s) to test whether string s is a reserved identifier, " +"such as \"def\" or \"class\"." msgstr "" +"keyword.iskeyword(s)를 호출하여 문자열 s가 \"def\" 또는 \"class\"와 같은 " +"예약 식별자인지 테스트합니다." #: flwr.common.EventType.islower:3 of msgid "" -"A string is lowercase if all cased characters in the string are lowercase" -" and there is at least one cased character in the string." -msgstr "" +"A string is lowercase if all cased characters in the string are lowercase " +"and there is at least one cased character in the string." +msgstr "문자열이 모두 소문자이고 문자열에 문자가 하나 이상 있는 경우 문자열은 " +"소문자입니다." #: flwr.common.EventType.isnumeric:3 of msgid "" -"A string is numeric if all characters in the string are numeric and there" -" is at least one character in the string." -msgstr "" +"A string is numeric if all characters in the string are numeric and there is " +"at least one character in the string." +msgstr "문자열의 모든 문자가 숫자이고 문자열에 하나 이상의 문자가 있는 경우 문자열은 " +"숫자입니다." #: flwr.common.EventType.isprintable:3 of msgid "" -"A string is printable if all of its characters are considered printable " -"in repr() or if it is empty." -msgstr "" +"A string is printable if all of its characters are considered printable in " +"repr() or if it is empty." +msgstr "문자열은 repr()에서 모든 문자가 인쇄 가능한 것으로 간주되거나 비어 있는 경우 " +"인쇄할 수 있습니다." #: flwr.common.EventType.isspace:3 of msgid "" -"A string is whitespace if all characters in the string are whitespace and" -" there is at least one character in the string." -msgstr "" +"A string is whitespace if all characters in the string are whitespace and " +"there is at least one character in the string." +msgstr "문자열의 모든 문자가 공백이고 문자열에 하나 이상의 문자가 있는 경우 문자열은 " +"공백입니다." #: flwr.common.EventType.istitle:3 of msgid "" -"In a title-cased string, upper- and title-case characters may only follow" -" uncased characters and lowercase characters only cased ones." -msgstr "" +"In a title-cased string, upper- and title-case characters may only follow " +"uncased characters and lowercase characters only cased ones." +msgstr "제목 대/소문자 문자열에서 대문자와 제목 대문자는 대소문자만, 소문자는 " +"대문자만 뒤에 올 수 있습니다." #: flwr.common.EventType.isupper:3 of msgid "" -"A string is uppercase if all cased characters in the string are uppercase" -" and there is at least one cased character in the string." -msgstr "" +"A string is uppercase if all cased characters in the string are uppercase " +"and there is at least one cased character in the string." +msgstr "문자열의 모든 문자가 대문자이고 문자열에 문자가 하나 이상 있는 경우 문자열은 " +"대문자입니다." #: flwr.common.EventType.join:3 of msgid "" -"The string whose method is called is inserted in between each given " -"string. The result is returned as a new string." -msgstr "" +"The string whose method is called is inserted in between each given string. " +"The result is returned as a new string." +msgstr "메서드가 호출되는 문자열은 주어진 각 문자열 사이에 삽입됩니다. 결과는 새 " +"문자열로 반환됩니다." #: flwr.common.EventType.join:6 of msgid "Example: '.'.join(['ab', 'pq', 'rs']) -> 'ab.pq.rs'" -msgstr "" +msgstr "Example: '.'.join(['ab', 'pq', 'rs']) -> 'ab.pq.rs'" #: flwr.common.EventType.lstrip:3 flwr.common.EventType.rstrip:3 #: flwr.common.EventType.strip:3 of msgid "If chars is given and not None, remove characters in chars instead." -msgstr "" +msgstr "None이 아닌 문자가 지정되면 대신 문자열에서 문자를 제거합니다." #: flwr.common.EventType.maketrans:3 of msgid "" @@ -10190,10 +10936,15 @@ msgid "" "ordinals (integers) or characters to Unicode ordinals, strings or None. " "Character keys will be then converted to ordinals. If there are two " "arguments, they must be strings of equal length, and in the resulting " -"dictionary, each character in x will be mapped to the character at the " -"same position in y. If there is a third argument, it must be a string, " -"whose characters will be mapped to None in the result." +"dictionary, each character in x will be mapped to the character at the same " +"position in y. If there is a third argument, it must be a string, whose " +"characters will be mapped to None in the result." msgstr "" +"argument이 하나만 있는 경우, 유니코드 서수(정수) 또는 문자를 유니코드 서수, " +"문자열 또는 None에 매핑하는 dictionary이어야 합니다. 그러면 문자 키가 서수로 " +"변환됩니다. 인수가 두 개이면 길이가 같은 문자열이어야 하며, 결과 " +"dictionary에서 x의 각 문자는 y의 같은 위치에 있는 문자에 매핑됩니다. 세 번째 " +"인수가 있으면 문자열이어야 하며, 그 문자는 결과에서 None에 매핑됩니다." #: flwr.common.EventType.partition:3 of msgid "" @@ -10201,18 +10952,23 @@ msgid "" "found, returns a 3-tuple containing the part before the separator, the " "separator itself, and the part after it." msgstr "" +"문자열에서 구분 기호를 검색합니다. 구분 기호가 발견되면 구분 기호 앞 부분, " +"구분 기호 자체, 구분 기호 뒤 부분을 포함하는 3-tuple을 반환합니다." #: flwr.common.EventType.partition:7 of msgid "" "If the separator is not found, returns a 3-tuple containing the original " "string and two empty strings." -msgstr "" +msgstr "구분 기호를 찾을 수 없으면 원래 문자열과 빈 문자열 2개를 포함하는 3-튜플을 " +"반환합니다." #: flwr.common.EventType.removeprefix:3 of msgid "" -"If the string starts with the prefix string, return string[len(prefix):]." -" Otherwise, return a copy of the original string." +"If the string starts with the prefix string, return string[len(prefix):]. " +"Otherwise, return a copy of the original string." msgstr "" +"문자열이 접두사 문자열로 시작하면 문자열[len(prefix):]을 반환합니다. 그렇지 " +"않으면 원본 문자열의 복사본을 반환합니다." #: flwr.common.EventType.removesuffix:3 of msgid "" @@ -10220,667 +10976,727 @@ msgid "" "return string[:-len(suffix)]. Otherwise, return a copy of the original " "string." msgstr "" +"문자열이 접미사 문자열로 끝나고 해당 접미사가 비어 있지 않으면 " +"문자열[:-len(suffix)]을 반환합니다. 그렇지 않으면 원본 문자열의 복사본을 " +"반환합니다." #: flwr.common.EventType.replace:5 of msgid "count" -msgstr "" +msgstr "카운트" #: flwr.common.EventType.replace:4 of msgid "" "Maximum number of occurrences to replace. -1 (the default value) means " "replace all occurrences." -msgstr "" +msgstr "대체할 최대 발생 횟수입니다. -1(기본값)은 모든 항목을 교체한다는 의미입니다." #: flwr.common.EventType.replace:7 of msgid "" -"If the optional argument count is given, only the first count occurrences" -" are replaced." -msgstr "" +"If the optional argument count is given, only the first count occurrences " +"are replaced." +msgstr "선택적 argument 개수를 지정하면 첫 번째 개수만 바뀝니다." #: flwr.common.EventType.rfind:1 flwr.common.EventType.rindex:1 of msgid "" -"Return the highest index in S where substring sub is found, such that sub" -" is contained within S[start:end]. Optional arguments start and end are " +"Return the highest index in S where substring sub is found, such that sub is " +"contained within S[start:end]. Optional arguments start and end are " "interpreted as in slice notation." msgstr "" +"부분 문자열 sub가 발견되는 곳의 가장 높은 인덱스를 반환하며, sub는 " +"S[start:end] 내에 포함되어야 합니다. 선택적 인자 start와 end는 슬라이스 " +"표기법과 같이 해석됩니다." #: flwr.common.EventType.rpartition:3 of msgid "" -"This will search for the separator in the string, starting at the end. If" -" the separator is found, returns a 3-tuple containing the part before the" -" separator, the separator itself, and the part after it." +"This will search for the separator in the string, starting at the end. If " +"the separator is found, returns a 3-tuple containing the part before the " +"separator, the separator itself, and the part after it." msgstr "" +"그러면 문자열에서 끝 부분부터 시작하여 구분 기호를 검색합니다. 구분 기호가 " +"발견되면 구분 기호 앞 부분, 구분 기호 자체, 구분 기호 뒤 부분을 포함하는 3-" +"tuple을 반환합니다." #: flwr.common.EventType.rpartition:7 of msgid "" "If the separator is not found, returns a 3-tuple containing two empty " "strings and the original string." -msgstr "" +msgstr "구분 기호를 찾을 수 없는 경우 빈 문자열 2개와 원래 문자열을 포함하는 3-" +"tuple을 반환합니다." #: flwr.common.EventType.rsplit:7 flwr.common.EventType.split:7 of msgid "sep" -msgstr "" +msgstr "sep" #: flwr.common.EventType.rsplit:4 flwr.common.EventType.split:4 of msgid "The separator used to split the string." -msgstr "" +msgstr "문자열을 분할하는 데 사용되는 구분 기호입니다." #: flwr.common.EventType.rsplit:6 flwr.common.EventType.split:6 of msgid "" -"When set to None (the default value), will split on any whitespace " -"character (including \\\\n \\\\r \\\\t \\\\f and spaces) and will discard" -" empty strings from the result." +"When set to None (the default value), will split on any whitespace character " +"(including \\\\n \\\\r \\\\t \\\\f and spaces) and will discard empty " +"strings from the result." msgstr "" +"None(기본값)으로 설정하면 모든 공백 문자(\\\\n" +" \\\\r \\\\t \\\\f 및 공백 포함)를 분할하고 결과에서 빈 문자열을 삭제합니다." #: flwr.common.EventType.rsplit:11 flwr.common.EventType.split:11 of msgid "maxsplit" -msgstr "" +msgstr "maxsplit" #: flwr.common.EventType.rsplit:10 flwr.common.EventType.split:10 of msgid "" -"Maximum number of splits (starting from the left). -1 (the default value)" -" means no limit." -msgstr "" +"Maximum number of splits (starting from the left). -1 (the default value) " +"means no limit." +msgstr "최대 분할 횟수(왼쪽부터 시작). -1(기본값)은 제한이 없음을 의미합니다." #: flwr.common.EventType.rsplit:13 of msgid "Splitting starts at the end of the string and works to the front." -msgstr "" +msgstr "분할은 문자열 끝에서 시작하여 앞쪽으로 진행됩니다." #: flwr.common.EventType.split:13 of msgid "" "Note, str.split() is mainly useful for data that has been intentionally " -"delimited. With natural text that includes punctuation, consider using " -"the regular expression module." +"delimited. With natural text that includes punctuation, consider using the " +"regular expression module." msgstr "" +"참고로 str.split()은 주로 의도적으로 구분된 데이터에 유용합니다. 구두점이 " +"포함된 자연 텍스트의 경우 정규식 모듈을 사용하는 것이 좋습니다." #: flwr.common.EventType.splitlines:3 of msgid "" -"Line breaks are not included in the resulting list unless keepends is " -"given and true." -msgstr "" +"Line breaks are not included in the resulting list unless keepends is given " +"and true." +msgstr "줄 바꿈은 keepends가 주어지고 참이 아니면 결과 목록에 포함되지 않습니다." #: flwr.common.EventType.startswith:1 of msgid "" "Return True if S starts with the specified prefix, False otherwise. With " -"optional start, test S beginning at that position. With optional end, " -"stop comparing S at that position. prefix can also be a tuple of strings " -"to try." +"optional start, test S beginning at that position. With optional end, stop " +"comparing S at that position. prefix can also be a tuple of strings to try." msgstr "" +"S가 지정된 접두사로 시작하면 True를 반환하고, 그렇지 않으면 False를 " +"반환합니다. 시작 옵션을 사용하면 해당 위치에서 시작되는 S를 테스트합니다. " +"선택적 end를 사용하면 해당 위치에서 S 비교를 중지합니다. 접두사는 시도할 " +"문자열의 튜플일 수도 있습니다." #: flwr.common.EventType.title:3 of msgid "" -"More specifically, words start with uppercased characters and all " -"remaining cased characters have lower case." -msgstr "" +"More specifically, words start with uppercased characters and all remaining " +"cased characters have lower case." +msgstr "보다 구체적으로, 단어는 대문자로 시작하고 나머지 모든 대소문자는 소문자로 " +"표기합니다." #: flwr.common.EventType.translate:5 of msgid "table" -msgstr "" +msgstr "table" #: flwr.common.EventType.translate:4 of msgid "" -"Translation table, which must be a mapping of Unicode ordinals to Unicode" -" ordinals, strings, or None." -msgstr "" +"Translation table, which must be a mapping of Unicode ordinals to Unicode " +"ordinals, strings, or None." +msgstr "유니코드 서수를 유니코드 서수, 문자열 또는 없음으로 매핑하는 번역 " +"테이블이어야 합니다." #: flwr.common.EventType.translate:7 of msgid "" "The table must implement lookup/indexing via __getitem__, for instance a " -"dictionary or list. If this operation raises LookupError, the character " -"is left untouched. Characters mapped to None are deleted." +"dictionary or list. If this operation raises LookupError, the character is " +"left untouched. Characters mapped to None are deleted." msgstr "" +"테이블은 사전이나 목록과 같이 __getitem__을 통해 조회/색인을 구현해야 " +"합니다. 이 작업에서 LookupError가 발생하면 문자는 그대로 유지됩니다. " +"없음으로 매핑된 문자는 삭제됩니다." #: flwr.common.EventType.zfill:3 of msgid "The string is never truncated." -msgstr "" +msgstr "문자열은 잘리지 않습니다." #: ../../source/ref-api/flwr.common.FitIns.rst:2 msgid "FitIns" -msgstr "" +msgstr "FitIns" #: ../../source/ref-api/flwr.common.FitIns.rst:29::1 msgid ":py:obj:`parameters `\\" -msgstr "" +msgstr ":py:obj:`parameters `\\" #: ../../source/ref-api/flwr.common.FitIns.rst:29::1 msgid ":py:obj:`config `\\" -msgstr "" +msgstr ":py:obj:`config `\\" #: ../../source/ref-api/flwr.common.FitRes.rst:2 msgid "FitRes" -msgstr "" +msgstr "FitRes" #: ../../source/ref-api/flwr.common.FitRes.rst:31::1 msgid ":py:obj:`status `\\" -msgstr "" +msgstr ":py:obj:`status `\\" #: ../../source/ref-api/flwr.common.FitRes.rst:31::1 msgid ":py:obj:`parameters `\\" -msgstr "" +msgstr ":py:obj:`parameters `\\" #: ../../source/ref-api/flwr.common.FitRes.rst:31::1 msgid ":py:obj:`num_examples `\\" -msgstr "" +msgstr ":py:obj:`num_examples `\\" #: ../../source/ref-api/flwr.common.FitRes.rst:31::1 msgid ":py:obj:`metrics `\\" -msgstr "" +msgstr ":py:obj:`metrics `\\" #: ../../source/ref-api/flwr.common.GetParametersIns.rst:2 msgid "GetParametersIns" -msgstr "" +msgstr "GetParametersIns" #: ../../source/ref-api/flwr.common.GetParametersIns.rst:28::1 msgid ":py:obj:`config `\\" -msgstr "" +msgstr ":py:obj:`config `\\" #: ../../source/ref-api/flwr.common.GetParametersRes.rst:2 msgid "GetParametersRes" -msgstr "" +msgstr "GetParametersRes" #: ../../source/ref-api/flwr.common.GetParametersRes.rst:29::1 msgid ":py:obj:`status `\\" -msgstr "" +msgstr ":py:obj:`status `\\" #: ../../source/ref-api/flwr.common.GetParametersRes.rst:29::1 msgid ":py:obj:`parameters `\\" -msgstr "" +msgstr ":py:obj:`parameters `\\" #: ../../source/ref-api/flwr.common.GetPropertiesIns.rst:2 msgid "GetPropertiesIns" -msgstr "" +msgstr "GetPropertiesIns" #: ../../source/ref-api/flwr.common.GetPropertiesIns.rst:28::1 msgid ":py:obj:`config `\\" -msgstr "" +msgstr ":py:obj:`config `\\" #: ../../source/ref-api/flwr.common.GetPropertiesRes.rst:2 msgid "GetPropertiesRes" -msgstr "" +msgstr "GetPropertiesRes" #: ../../source/ref-api/flwr.common.GetPropertiesRes.rst:29::1 msgid ":py:obj:`status `\\" -msgstr "" +msgstr ":py:obj:`status `\\" #: ../../source/ref-api/flwr.common.GetPropertiesRes.rst:29::1 msgid ":py:obj:`properties `\\" -msgstr "" +msgstr ":py:obj:`properties `\\" #: ../../source/ref-api/flwr.common.Message.rst:2 msgid "Message" -msgstr "" +msgstr "Message" #: flwr.common.Message.content:1::1 flwr.common.Message.metadata:1 #: flwr.common.message.Message:3 of msgid "A dataclass including information about the message to be executed." -msgstr "" +msgstr "실행할 메시지에 대한 정보를 포함한 데이터 클래스입니다." #: flwr.common.message.Message:5 of msgid "" -"Holds records either sent by another entity (e.g. sent by the server-side" -" logic to a client, or vice-versa) or that will be sent to it." -msgstr "" +"Holds records either sent by another entity (e.g. sent by the server-side " +"logic to a client, or vice-versa) or that will be sent to it." +msgstr "다른 엔터티(예: 서버 측 로직이 클라이언트로 전송하거나 그 반대로 전송하는 등)" +"가 전송했거나 전송할 레코드를 보유합니다." #: flwr.common.message.Message:8 of msgid "" -"A dataclass that captures information about an error that took place when" -" processing another message." -msgstr "" +"A dataclass that captures information about an error that took place when " +"processing another message." +msgstr "다른 메시지를 처리할 때 발생한 오류에 대한 정보를 캡처하는 데이터 " +"클래스입니다." #: ../../source/ref-api/flwr.common.Message.rst:35::1 msgid "" ":py:obj:`create_error_reply `\\ " "\\(error\\[\\, ttl\\]\\)" msgstr "" +":py:obj:`create_error_reply `\\ \\(" +"error\\[\\, ttl\\]\\)" #: ../../source/ref-api/flwr.common.Message.rst:35::1 #: flwr.common.message.Message.create_error_reply:1 of msgid "Construct a reply message indicating an error happened." -msgstr "" +msgstr "오류가 발생했음을 나타내는 답장 메시지를 작성합니다." #: ../../source/ref-api/flwr.common.Message.rst:35::1 msgid "" -":py:obj:`create_reply `\\ " -"\\(content\\[\\, ttl\\]\\)" +":py:obj:`create_reply `\\ \\(content\\[\\, " +"ttl\\]\\)" msgstr "" +":py:obj:`create_reply `\\ \\(content\\[\\, " +"ttl\\]\\)" #: ../../source/ref-api/flwr.common.Message.rst:35::1 #: flwr.common.message.Message.create_reply:1 of msgid "Create a reply to this message with specified content and TTL." -msgstr "" +msgstr "지정된 콘텐츠와 TTL을 사용하여 이 메시지에 대한 답글을 작성합니다." #: ../../source/ref-api/flwr.common.Message.rst:35::1 msgid ":py:obj:`has_content `\\ \\(\\)" -msgstr "" +msgstr ":py:obj:`has_content `\\ \\(\\)" #: ../../source/ref-api/flwr.common.Message.rst:35::1 #: flwr.common.message.Message.has_content:1 of msgid "Return True if message has content, else False." -msgstr "" +msgstr "메시지에 콘텐츠가 있으면 True을 반환하고, 그렇지 않으면 False을 반환합니다." #: ../../source/ref-api/flwr.common.Message.rst:35::1 msgid ":py:obj:`has_error `\\ \\(\\)" -msgstr "" +msgstr ":py:obj:`has_error `\\ \\(\\)" #: ../../source/ref-api/flwr.common.Message.rst:35::1 #: flwr.common.message.Message.has_error:1 of msgid "Return True if message has an error, else False." -msgstr "" +msgstr "메시지에 오류가 있으면 True을 반환하고, 그렇지 않으면 False을 반환합니다." #: flwr.common.Message.content:1::1 of msgid ":py:obj:`content `\\" -msgstr "" +msgstr ":py:obj:`content `\\" #: flwr.common.Message.content:1 flwr.common.Message.content:1::1 #: of msgid "The content of this message." -msgstr "" +msgstr "이 메시지의 내용입니다." #: flwr.common.Message.content:1::1 of msgid ":py:obj:`error `\\" -msgstr "" +msgstr ":py:obj:`error `\\" #: flwr.common.Message.content:1::1 flwr.common.Message.error:1 of msgid "Error captured by this message." -msgstr "" +msgstr "이 메시지가 캡처한 오류입니다." #: flwr.common.Message.content:1::1 of msgid ":py:obj:`metadata `\\" -msgstr "" +msgstr ":py:obj:`metadata `\\" #: flwr.common.message.Message.create_error_reply:3 of msgid "The error that was encountered." -msgstr "" +msgstr "오류가 발생했습니다." #: flwr.common.message.Message.create_error_reply:5 #: flwr.common.message.Message.create_reply:9 of msgid "" -"Time-to-live for this message in seconds. If unset, it will be set based " -"on the remaining time for the received message before it expires. This " -"follows the equation: ttl = msg.meta.ttl - (reply.meta.created_at - " -"msg.meta.created_at)" +"Time-to-live for this message in seconds. If unset, it will be set based on " +"the remaining time for the received message before it expires. This follows " +"the equation: ttl = msg.meta.ttl - (reply.meta.created_at - msg.meta." +"created_at)" msgstr "" +"이 메시지의 남은 시간(초)입니다. 설정하지 않으면 수신된 메시지가 만료되기 " +"전까지 남은 시간을 기준으로 설정됩니다. 이는 다음과 같은 공식을 따릅니다: " +"ttl = msg.meta.ttl - (reply.meta.created_at - msg.meta.created_at)" #: flwr.common.message.Message.create_error_reply:5 #: flwr.common.message.Message.create_reply:9 of msgid "" -"Time-to-live for this message in seconds. If unset, it will be set based " -"on the remaining time for the received message before it expires. This " -"follows the equation:" +"Time-to-live for this message in seconds. If unset, it will be set based on " +"the remaining time for the received message before it expires. This follows " +"the equation:" msgstr "" +"이 메시지의 남은 시간(초)입니다. 설정하지 않으면 수신된 메시지가 만료되기 " +"전까지 남은 시간을 기준으로 설정됩니다. 이는 다음 공식을 따릅니다:" #: flwr.common.message.Message.create_error_reply:9 #: flwr.common.message.Message.create_reply:13 of msgid "ttl = msg.meta.ttl - (reply.meta.created_at - msg.meta.created_at)" -msgstr "" +msgstr "ttl = msg.meta.ttl - (reply.meta.created_at - msg.meta.created_at)" #: flwr.common.message.Message.create_reply:3 of msgid "" -"The method generates a new `Message` as a reply to this message. It " -"inherits 'run_id', 'src_node_id', 'dst_node_id', and 'message_type' from " -"this message and sets 'reply_to_message' to the ID of this message." +"The method generates a new `Message` as a reply to this message. It inherits " +"'run_id', 'src_node_id', 'dst_node_id', and 'message_type' from this message " +"and sets 'reply_to_message' to the ID of this message." msgstr "" +"이 메서드는 이 메시지에 대한 응답으로 새로운 '메시지'를 생성합니다. 이 " +"메시지에서 'run_id', 'src_node_id', 'dst_node_id', 'message_type'을 상속하고 " +"'reply_to_message'를 이 메시지의 ID로 설정합니다." #: flwr.common.message.Message.create_reply:7 of msgid "The content for the reply message." -msgstr "" +msgstr "답장 메시지의 콘텐츠입니다." #: flwr.common.message.Message.create_reply:16 of msgid "A new `Message` instance representing the reply." -msgstr "" +msgstr "답장을 나타내는 새로운 `메시지` 인스턴스입니다." #: ../../source/ref-api/flwr.common.MessageType.rst:2 msgid "MessageType" -msgstr "" +msgstr "MessageType" #: ../../source/ref-api/flwr.common.MessageType.rst:30::1 msgid ":py:obj:`EVALUATE `\\" -msgstr "" +msgstr ":py:obj:`EVALUATE `\\" #: ../../source/ref-api/flwr.common.MessageType.rst:30::1 msgid ":py:obj:`QUERY `\\" -msgstr "" +msgstr ":py:obj:`QUERY `\\" #: ../../source/ref-api/flwr.common.MessageType.rst:30::1 msgid ":py:obj:`TRAIN `\\" -msgstr "" +msgstr ":py:obj:`TRAIN `\\" #: ../../source/ref-api/flwr.common.MessageTypeLegacy.rst:2 msgid "MessageTypeLegacy" -msgstr "" +msgstr "MessageTypeLegacy" #: ../../source/ref-api/flwr.common.MessageTypeLegacy.rst:29::1 -msgid ":py:obj:`GET_PARAMETERS `\\" +msgid "" +":py:obj:`GET_PARAMETERS `\\" msgstr "" +":py:obj:`GET_PARAMETERS `\\" #: ../../source/ref-api/flwr.common.MessageTypeLegacy.rst:29::1 -msgid ":py:obj:`GET_PROPERTIES `\\" +msgid "" +":py:obj:`GET_PROPERTIES `\\" msgstr "" +":py:obj:`GET_PROPERTIES `\\" #: flwr.common.Metadata.created_at:1::1 #: flwr.common.Metadata.run_id:1 flwr.common.message.Metadata:3 of msgid "An identifier for the current run." -msgstr "" +msgstr "현재 실행에 대한 식별자입니다." #: flwr.common.Metadata.created_at:1::1 #: flwr.common.Metadata.message_id:1 flwr.common.message.Metadata:5 of msgid "An identifier for the current message." -msgstr "" +msgstr "현재 메시지의 식별자입니다." #: flwr.common.Metadata.created_at:1::1 #: flwr.common.Metadata.src_node_id:1 flwr.common.message.Metadata:7 of msgid "An identifier for the node sending this message." -msgstr "" +msgstr "이 메시지를 보내는 노드의 식별자입니다." #: flwr.common.Metadata.created_at:1::1 #: flwr.common.Metadata.dst_node_id:1 flwr.common.message.Metadata:9 of msgid "An identifier for the node receiving this message." -msgstr "" +msgstr "이 메시지를 수신하는 노드의 식별자입니다." #: flwr.common.Metadata.created_at:1::1 #: flwr.common.Metadata.reply_to_message:1 flwr.common.message.Metadata:11 of msgid "An identifier for the message this message replies to." -msgstr "" +msgstr "이 메시지가 회신하는 메시지의 식별자입니다." #: flwr.common.message.Metadata:13 of msgid "" -"An identifier for grouping messages. In some settings, this is used as " -"the FL round." -msgstr "" +"An identifier for grouping messages. In some settings, this is used as the " +"FL round." +msgstr "메시지를 그룹화하기 위한 식별자입니다. 일부 설정에서는 FL 라운드로 " +"사용됩니다." #: flwr.common.message.Metadata:16 of msgid "Time-to-live for this message in seconds." -msgstr "" +msgstr "이 메시지의 유효 시간(초)입니다." #: flwr.common.Metadata.created_at:1::1 #: flwr.common.Metadata.message_type:1 flwr.common.message.Metadata:18 of msgid "A string that encodes the action to be executed on the receiving end." -msgstr "" +msgstr "수신 측에서 실행할 작업을 인코딩하는 문자열입니다." #: flwr.common.message.Metadata:21 of msgid "" -"An identifier that can be used when loading a particular data partition " -"for a ClientApp. Making use of this identifier is more relevant when " -"conducting simulations." +"An identifier that can be used when loading a particular data partition for " +"a ClientApp. Making use of this identifier is more relevant when conducting " +"simulations." msgstr "" +"클라이언트 앱의 특정 데이터 파티션을 로드할 때 사용할 수 있는 식별자입니다. " +"시뮬레이션을 수행할 때 이 식별자를 사용하는 것이 더 적절합니다." #: flwr.common.Metadata.created_at:1::1 of msgid ":py:obj:`created_at `\\" -msgstr "" +msgstr ":py:obj:`created_at `\\" #: flwr.common.Metadata.created_at:1 #: flwr.common.Metadata.created_at:1::1 of msgid "Unix timestamp when the message was created." -msgstr "" +msgstr "메시지가 생성된 때의 Unix timestamp입니다." #: flwr.common.Metadata.created_at:1::1 of msgid ":py:obj:`dst_node_id `\\" -msgstr "" +msgstr ":py:obj:`dst_node_id `\\" #: flwr.common.Metadata.created_at:1::1 of msgid ":py:obj:`group_id `\\" -msgstr "" +msgstr ":py:obj:`group_id `\\" #: flwr.common.Metadata.created_at:1::1 #: flwr.common.Metadata.group_id:1 of msgid "An identifier for grouping messages." -msgstr "" +msgstr "메시지를 그룹화하기 위한 식별자입니다." #: flwr.common.Metadata.created_at:1::1 of msgid ":py:obj:`message_id `\\" -msgstr "" +msgstr ":py:obj:`message_id `\\" #: flwr.common.Metadata.created_at:1::1 of msgid ":py:obj:`message_type `\\" -msgstr "" +msgstr ":py:obj:`message_type `\\" #: flwr.common.Metadata.created_at:1::1 of msgid ":py:obj:`partition_id `\\" -msgstr "" +msgstr ":py:obj:`partition_id `\\" #: flwr.common.Metadata.created_at:1::1 #: flwr.common.Metadata.partition_id:1 of msgid "An identifier telling which data partition a ClientApp should use." -msgstr "" +msgstr "클라이언트앱이 사용해야 하는 데이터 파티션을 알려주는 식별자입니다." #: flwr.common.Metadata.created_at:1::1 of msgid ":py:obj:`reply_to_message `\\" -msgstr "" +msgstr ":py:obj:`reply_to_message `\\" #: flwr.common.Metadata.created_at:1::1 of msgid ":py:obj:`run_id `\\" -msgstr "" +msgstr ":py:obj:`run_id `\\" #: flwr.common.Metadata.created_at:1::1 of msgid ":py:obj:`src_node_id `\\" -msgstr "" +msgstr ":py:obj:`src_node_id `\\" #: flwr.common.Metadata.created_at:1::1 of msgid ":py:obj:`ttl `\\" -msgstr "" +msgstr ":py:obj:`ttl `\\" #: flwr.common.Metadata.created_at:1::1 flwr.common.Metadata.ttl:1 #: of msgid "Time-to-live for this message." -msgstr "" +msgstr "이 메시지를 기다리는 시간입니다." #: ../../source/ref-api/flwr.common.MetricsRecord.rst:2 msgid "MetricsRecord" -msgstr "" +msgstr "MetricsRecord" #: flwr.common.record.metricsrecord.MetricsRecord:1 of msgid "" -"Bases: :py:class:`~flwr.common.record.typeddict.TypedDict`\\ " -"[:py:class:`str`, :py:class:`int` | :py:class:`float` | " -":py:class:`~typing.List`\\ [:py:class:`int`] | :py:class:`~typing.List`\\" -" [:py:class:`float`]]" +"Bases: :py:class:`~flwr.common.record.typeddict.TypedDict`\\ [:py:class:" +"`str`, :py:class:`int` | :py:class:`float` | :py:class:`~typing.List`\\ [:py:" +"class:`int`] | :py:class:`~typing.List`\\ [:py:class:`float`]]" msgstr "" +"Bases: :py:class:`~flwr.common.record.typeddict.TypedDict`\\ [:py:class:`str`" +", :py:class:`int` | :py:class:`float` | :py:class:`~typing.List`\\ " +"[:py:class:`int`] | :py:class:`~typing.List`\\ [:py:class:`float`]]" #: flwr.common.record.typeddict.TypedDict.clear:1::1 of msgid ":py:obj:`clear `\\ \\(\\)" -msgstr "" +msgstr ":py:obj:`clear `\\ \\(\\)" #: flwr.common.record.typeddict.TypedDict.clear:1::1 of msgid ":py:obj:`count_bytes `\\ \\(\\)" -msgstr "" +msgstr ":py:obj:`count_bytes `\\ \\(\\)" #: flwr.common.record.typeddict.TypedDict.clear:1::1 of msgid ":py:obj:`get `\\ \\(k\\[\\,d\\]\\)" -msgstr "" +msgstr ":py:obj:`get `\\ \\(k\\[\\,d\\]\\)" #: flwr.common.record.typeddict.TypedDict.clear:1::1 of msgid ":py:obj:`items `\\ \\(\\)" -msgstr "" +msgstr ":py:obj:`items `\\ \\(\\)" #: flwr.common.record.typeddict.TypedDict.clear:1::1 of msgid ":py:obj:`keys `\\ \\(\\)" -msgstr "" +msgstr ":py:obj:`keys `\\ \\(\\)" #: flwr.common.record.typeddict.TypedDict.clear:1::1 of msgid ":py:obj:`pop `\\ \\(k\\[\\,d\\]\\)" -msgstr "" +msgstr ":py:obj:`pop `\\ \\(k\\[\\,d\\]\\)" #: flwr.common.record.typeddict.TypedDict.clear:1::1 of msgid "" ":py:obj:`update `\\ \\(\\[E\\, " "\\]\\*\\*F\\)" msgstr "" +":py:obj:`update `\\ \\(\\[E\\, \\]\\*\\*F\\" +")" #: flwr.common.record.typeddict.TypedDict.clear:1::1 of msgid ":py:obj:`values `\\ \\(\\)" msgstr "" +":py:obj:`update `\\ \\(\\[E\\, \\]\\*\\*F\\" +")" #: ../../source/ref-api/flwr.common.NDArray.rst:2 msgid "NDArray" -msgstr "" +msgstr "NDArray" #: ../../source/ref-api/flwr.common.Parameters.rst:29::1 msgid ":py:obj:`tensors `\\" -msgstr "" +msgstr ":py:obj:`tensors `\\" #: ../../source/ref-api/flwr.common.Parameters.rst:29::1 msgid ":py:obj:`tensor_type `\\" -msgstr "" +msgstr ":py:obj:`tensor_type `\\" #: ../../source/ref-api/flwr.common.ParametersRecord.rst:2 msgid "ParametersRecord" -msgstr "" +msgstr "ParametersRecord" #: flwr.common.record.parametersrecord.ParametersRecord:1 of msgid "" -"Bases: :py:class:`~flwr.common.record.typeddict.TypedDict`\\ " -"[:py:class:`str`, :py:class:`~flwr.common.record.parametersrecord.Array`]" +"Bases: :py:class:`~flwr.common.record.typeddict.TypedDict`\\ [:py:class:" +"`str`, :py:class:`~flwr.common.record.parametersrecord.Array`]" msgstr "" +"Bases: :py:class:`~flwr.common.record.typeddict.TypedDict`\\ [:py:class:`str`" +", :py:class:`~flwr.common.record.parametersrecord.Array`]" #: flwr.common.record.parametersrecord.ParametersRecord:3 of msgid "" -"A dataclass storing named Arrays in order. This means that it holds " -"entries as an OrderedDict[str, Array]. ParametersRecord objects can be " -"viewed as an equivalent to PyTorch's state_dict, but holding serialised " -"tensors instead." +"A dataclass storing named Arrays in order. This means that it holds entries " +"as an OrderedDict[str, Array]. ParametersRecord objects can be viewed as an " +"equivalent to PyTorch's state_dict, but holding serialised tensors instead." msgstr "" +"Arrays라는 이름의 데이터 클래스를 순서대로 저장합니다. 즉, OrderedDict[str, " +"Array]로 항목을 보유합니다. ParametersRecord 객체는 파이토치의 state_dict와 " +"동등한 것으로 볼 수 있지만, 대신 직렬화된 텐서를 보유합니다." #: flwr.common.record.typeddict.TypedDict.clear:1::1 of msgid ":py:obj:`clear `\\ \\(\\)" -msgstr "" +msgstr ":py:obj:`clear `\\ \\(\\)" #: flwr.common.record.typeddict.TypedDict.clear:1::1 of -msgid ":py:obj:`count_bytes `\\ \\(\\)" +msgid "" +":py:obj:`count_bytes `\\ \\(\\)" msgstr "" +":py:obj:`count_bytes `\\ \\(\\)" #: flwr.common.record.typeddict.TypedDict.clear:1::1 of msgid ":py:obj:`get `\\ \\(k\\[\\,d\\]\\)" -msgstr "" +msgstr ":py:obj:`get `\\ \\(k\\[\\,d\\]\\)" #: flwr.common.record.typeddict.TypedDict.clear:1::1 of msgid ":py:obj:`items `\\ \\(\\)" -msgstr "" +msgstr ":py:obj:`items `\\ \\(\\)" #: flwr.common.record.typeddict.TypedDict.clear:1::1 of msgid ":py:obj:`keys `\\ \\(\\)" -msgstr "" +msgstr ":py:obj:`keys `\\ \\(\\)" #: flwr.common.record.typeddict.TypedDict.clear:1::1 of msgid ":py:obj:`pop `\\ \\(k\\[\\,d\\]\\)" -msgstr "" +msgstr ":py:obj:`pop `\\ \\(k\\[\\,d\\]\\)" #: flwr.common.record.typeddict.TypedDict.clear:1::1 of msgid "" ":py:obj:`update `\\ \\(\\[E\\, " "\\]\\*\\*F\\)" msgstr "" +":py:obj:`update `\\ \\(\\[E\\, \\]\\*\\*" +"F\\)" #: flwr.common.record.typeddict.TypedDict.clear:1::1 of msgid ":py:obj:`values `\\ \\(\\)" -msgstr "" +msgstr ":py:obj:`values `\\ \\(\\)" #: flwr.common.record.parametersrecord.ParametersRecord.count_bytes:3 of msgid "" -"Note that a small amount of Bytes might also be included in this counting" -" that correspond to metadata of the serialized object (e.g. of NumPy " -"array) needed for deseralization." -msgstr "" +"Note that a small amount of Bytes might also be included in this counting " +"that correspond to metadata of the serialized object (e.g. of NumPy array) " +"needed for deseralization." +msgstr "역직렬화에 필요한 직렬화된 객체의 메타데이터(예: NumPy 배열)에 해당하는 " +"소량의 바이트도 이 카운팅에 포함될 수 있습니다." #: ../../source/ref-api/flwr.common.ReconnectIns.rst:2 msgid "ReconnectIns" -msgstr "" +msgstr "ReconnectIns" #: ../../source/ref-api/flwr.common.ReconnectIns.rst:28::1 msgid ":py:obj:`seconds `\\" -msgstr "" +msgstr ":py:obj:`seconds `\\" #: ../../source/ref-api/flwr.common.RecordSet.rst:2 msgid "RecordSet" -msgstr "" +msgstr "RecordSet" #: flwr.common.RecordSet.configs_records:1::1 of msgid ":py:obj:`configs_records `\\" -msgstr "" +msgstr ":py:obj:`configs_records `\\" #: flwr.common.RecordSet.configs_records:1 #: flwr.common.RecordSet.configs_records:1::1 of msgid "Dictionary holding ConfigsRecord instances." -msgstr "" +msgstr "Dictionary holding ConfigsRecord instances." #: flwr.common.RecordSet.configs_records:1::1 of msgid ":py:obj:`metrics_records `\\" -msgstr "" +msgstr ":py:obj:`metrics_records `\\" #: flwr.common.RecordSet.configs_records:1::1 #: flwr.common.RecordSet.metrics_records:1 of msgid "Dictionary holding MetricsRecord instances." -msgstr "" +msgstr "Dictionary holding MetricsRecord instances." #: flwr.common.RecordSet.configs_records:1::1 of -msgid ":py:obj:`parameters_records `\\" +msgid "" +":py:obj:`parameters_records `\\" msgstr "" +":py:obj:`parameters_records `\\" #: flwr.common.RecordSet.configs_records:1::1 #: flwr.common.RecordSet.parameters_records:1 of msgid "Dictionary holding ParametersRecord instances." -msgstr "" +msgstr "Dictionary holding ParametersRecord instances." #: ../../source/ref-api/flwr.common.ServerMessage.rst:2 msgid "ServerMessage" -msgstr "" +msgstr "ServerMessage" #: ../../source/ref-api/flwr.common.ServerMessage.rst:31::1 msgid ":py:obj:`evaluate_ins `\\" -msgstr "" +msgstr ":py:obj:`evaluate_ins `\\" #: ../../source/ref-api/flwr.common.ServerMessage.rst:31::1 msgid ":py:obj:`fit_ins `\\" -msgstr "" +msgstr ":py:obj:`fit_ins `\\" #: ../../source/ref-api/flwr.common.ServerMessage.rst:31::1 msgid "" -":py:obj:`get_parameters_ins " -"`\\" +":py:obj:`get_parameters_ins `\\" msgstr "" +":py:obj:`get_parameters_ins `\\" #: ../../source/ref-api/flwr.common.ServerMessage.rst:31::1 msgid "" -":py:obj:`get_properties_ins " -"`\\" +":py:obj:`get_properties_ins `\\" msgstr "" +":py:obj:`get_properties_ins `\\" #: ../../source/ref-api/flwr.common.Status.rst:2 msgid "Status" -msgstr "" +msgstr "Status" #: ../../source/ref-api/flwr.common.Status.rst:29::1 msgid ":py:obj:`code `\\" -msgstr "" +msgstr ":py:obj:`code `\\" #: ../../source/ref-api/flwr.common.Status.rst:29::1 msgid ":py:obj:`message `\\" -msgstr "" +msgstr ":py:obj:`message `\\" #: ../../source/ref-api/flwr.common.array_from_numpy.rst:2 msgid "array\\_from\\_numpy" -msgstr "" +msgstr "array\\_from\\_numpy" #: ../../source/ref-api/flwr.common.bytes_to_ndarray.rst:2 msgid "bytes\\_to\\_ndarray" -msgstr "" +msgstr "bytes\\_to\\_ndarray" #: ../../source/ref-api/flwr.common.configure.rst:2 msgid "configure" -msgstr "" +msgstr "구성" #: ../../source/ref-api/flwr.common.event.rst:2 msgid "event" -msgstr "" +msgstr "이벤트" #: ../../source/ref-api/flwr.common.log.rst:2 msgid "log" -msgstr "" +msgstr "로그" #: logging.Logger.log:3 of msgid "" -"To pass exception information, use the keyword argument exc_info with a " -"true value, e.g." -msgstr "" +"To pass exception information, use the keyword argument exc_info with a true " +"value, e.g." +msgstr "예외 정보를 전달하려면 키워드 argument exc_info를 참 값과 함께 사용합니다." #: logging.Logger.log:6 of #, python-format @@ -10993,8 +11809,8 @@ msgstr "" #: ../../source/ref-api/flwr.server.rst:38::1 msgid "" -":py:obj:`ServerConfig `\\ \\(\\[num\\_rounds\\," -" round\\_timeout\\]\\)" +":py:obj:`ServerConfig `\\ \\(\\[num\\_rounds\\, " +"round\\_timeout\\]\\)" msgstr "" #: ../../source/ref-api/flwr.server.rst:38::1 @@ -11003,7 +11819,8 @@ msgid "Flower server config." msgstr "" #: ../../source/ref-api/flwr.server.rst:38::1 -msgid ":py:obj:`SimpleClientManager `\\ \\(\\)" +msgid "" +":py:obj:`SimpleClientManager `\\ \\(\\)" msgstr "" #: ../../source/ref-api/flwr.server.rst:38::1 @@ -11045,7 +11862,8 @@ msgid "Return all available clients." msgstr "" #: flwr.server.client_manager.ClientManager.all:1::1 of -msgid ":py:obj:`num_available `\\ \\(\\)" +msgid "" +":py:obj:`num_available `\\ \\(\\)" msgstr "" #: flwr.server.client_manager.ClientManager.all:1::1 @@ -11068,8 +11886,8 @@ msgstr "" #: flwr.server.client_manager.ClientManager.all:1::1 of msgid "" -":py:obj:`sample `\\ " -"\\(num\\_clients\\[\\, min\\_num\\_clients\\, criterion\\]\\)" +":py:obj:`sample `\\ \\(num\\_clients\\[\\, " +"min\\_num\\_clients\\, criterion\\]\\)" msgstr "" #: flwr.server.client_manager.ClientManager.all:1::1 @@ -11080,7 +11898,8 @@ msgid "Sample a number of Flower ClientProxy instances." msgstr "" #: flwr.server.client_manager.ClientManager.all:1::1 of -msgid ":py:obj:`unregister `\\ \\(client\\)" +msgid "" +":py:obj:`unregister `\\ \\(client\\)" msgstr "" #: flwr.server.client_manager.ClientManager.all:1::1 @@ -11112,8 +11931,7 @@ msgstr "" #: flwr.server.client_manager.SimpleClientManager.register:6 of msgid "" "**success** -- Indicating if registration was successful. False if " -"ClientProxy is already registered or can not be registered for any " -"reason." +"ClientProxy is already registered or can not be registered for any reason." msgstr "" #: flwr.server.client_manager.ClientManager.unregister:3 @@ -11127,8 +11945,8 @@ msgstr "" #: flwr.server.driver.driver.Driver.create_message:1::1 of msgid "" -":py:obj:`create_message `\\ " -"\\(content\\, message\\_type\\, ...\\[\\, ttl\\]\\)" +":py:obj:`create_message `\\ \\(content\\, " +"message\\_type\\, ...\\[\\, ttl\\]\\)" msgstr "" #: flwr.server.driver.driver.Driver.create_message:1 @@ -11158,8 +11976,7 @@ msgstr "" #: flwr.server.driver.driver.Driver.create_message:1::1 of msgid "" -":py:obj:`push_messages `\\ " -"\\(messages\\)" +":py:obj:`push_messages `\\ \\(messages\\)" msgstr "" #: flwr.server.driver.driver.Driver.create_message:1::1 @@ -11180,20 +11997,20 @@ msgstr "" #: flwr.server.driver.driver.Driver.create_message:3 of msgid "" -"This method constructs a new `Message` with given content and metadata. " -"The `run_id` and `src_node_id` will be set automatically." +"This method constructs a new `Message` with given content and metadata. The " +"`run_id` and `src_node_id` will be set automatically." msgstr "" #: flwr.server.driver.driver.Driver.create_message:6 of msgid "" -"The content for the new message. This holds records that are to be sent " -"to the destination node." +"The content for the new message. This holds records that are to be sent to " +"the destination node." msgstr "" #: flwr.server.driver.driver.Driver.create_message:9 of msgid "" -"The type of the message, defining the action to be executed on the " -"receiving end." +"The type of the message, defining the action to be executed on the receiving " +"end." msgstr "" #: flwr.server.driver.driver.Driver.create_message:12 of @@ -11202,17 +12019,16 @@ msgstr "" #: flwr.server.driver.driver.Driver.create_message:14 of msgid "" -"The ID of the group to which this message is associated. In some " -"settings, this is used as the FL round." +"The ID of the group to which this message is associated. In some settings, " +"this is used as the FL round." msgstr "" #: flwr.server.driver.driver.Driver.create_message:17 of msgid "" -"Time-to-live for the round trip of this message, i.e., the time from " -"sending this message to receiving a reply. It specifies in seconds the " -"duration for which the message and its potential reply are considered " -"valid. If unset, the default TTL (i.e., `common.DEFAULT_TTL`) will be " -"used." +"Time-to-live for the round trip of this message, i.e., the time from sending " +"this message to receiving a reply. It specifies in seconds the duration for " +"which the message and its potential reply are considered valid. If unset, " +"the default TTL (i.e., `common.DEFAULT_TTL`) will be used." msgstr "" #: flwr.server.driver.driver.Driver.create_message:23 of @@ -11223,12 +12039,13 @@ msgstr "" #: flwr.server.driver.driver.Driver.pull_messages:3 of msgid "" -"This method is used to collect messages from the SuperLink that " -"correspond to a set of given message IDs." +"This method is used to collect messages from the SuperLink that correspond " +"to a set of given message IDs." msgstr "" #: flwr.server.driver.driver.Driver.pull_messages:6 of -msgid "An iterable of message IDs for which reply messages are to be retrieved." +msgid "" +"An iterable of message IDs for which reply messages are to be retrieved." msgstr "" #: flwr.server.driver.driver.Driver.pull_messages:9 of @@ -11237,8 +12054,8 @@ msgstr "" #: flwr.server.driver.driver.Driver.push_messages:3 of msgid "" -"This method takes an iterable of messages and sends each message to the " -"node specified in `dst_node_id`." +"This method takes an iterable of messages and sends each message to the node " +"specified in `dst_node_id`." msgstr "" #: flwr.server.driver.driver.Driver.push_messages:6 @@ -11248,34 +12065,35 @@ msgstr "" #: flwr.server.driver.driver.Driver.push_messages:9 of msgid "" -"**message_ids** -- An iterable of IDs for the messages that were sent, " -"which can be used to pull replies." +"**message_ids** -- An iterable of IDs for the messages that were sent, which " +"can be used to pull replies." msgstr "" #: flwr.server.driver.driver.Driver.send_and_receive:3 of msgid "" -"This method sends a list of messages to their destination node IDs and " -"then waits for the replies. It continues to pull replies until either all" -" replies are received or the specified timeout duration is exceeded." +"This method sends a list of messages to their destination node IDs and then " +"waits for the replies. It continues to pull replies until either all replies " +"are received or the specified timeout duration is exceeded." msgstr "" #: flwr.server.driver.driver.Driver.send_and_receive:9 of msgid "" "The timeout duration in seconds. If specified, the method will wait for " -"replies for this duration. If `None`, there is no time limit and the " -"method will wait until replies for all messages are received." +"replies for this duration. If `None`, there is no time limit and the method " +"will wait until replies for all messages are received." msgstr "" #: flwr.server.driver.driver.Driver.send_and_receive:14 of -msgid "**replies** -- An iterable of reply messages received from the SuperLink." +msgid "" +"**replies** -- An iterable of reply messages received from the SuperLink." msgstr "" #: flwr.server.driver.driver.Driver.send_and_receive:19 of msgid "" -"This method uses `push_messages` to send the messages and `pull_messages`" -" to collect the replies. If `timeout` is set, the method may not return " -"replies for all sent messages. A message remains valid until its TTL, " -"which is not affected by `timeout`." +"This method uses `push_messages` to send the messages and `pull_messages` to " +"collect the replies. If `timeout` is set, the method may not return replies " +"for all sent messages. A message remains valid until its TTL, which is not " +"affected by `timeout`." msgstr "" #: ../../source/ref-api/flwr.server.History.rst:2 @@ -11284,9 +12102,8 @@ msgstr "" #: flwr.server.history.History.add_loss_centralized:1::1 of msgid "" -":py:obj:`add_loss_centralized " -"`\\ \\(server\\_round\\, " -"loss\\)" +":py:obj:`add_loss_centralized `\\ " +"\\(server\\_round\\, loss\\)" msgstr "" #: flwr.server.history.History.add_loss_centralized:1 @@ -11296,9 +12113,8 @@ msgstr "" #: flwr.server.history.History.add_loss_centralized:1::1 of msgid "" -":py:obj:`add_loss_distributed " -"`\\ \\(server\\_round\\, " -"loss\\)" +":py:obj:`add_loss_distributed `\\ " +"\\(server\\_round\\, loss\\)" msgstr "" #: flwr.server.history.History.add_loss_centralized:1::1 @@ -11308,9 +12124,8 @@ msgstr "" #: flwr.server.history.History.add_loss_centralized:1::1 of msgid "" -":py:obj:`add_metrics_centralized " -"`\\ \\(server\\_round\\, " -"metrics\\)" +":py:obj:`add_metrics_centralized `\\ \\(server\\_round\\, metrics\\)" msgstr "" #: flwr.server.history.History.add_loss_centralized:1::1 @@ -11320,9 +12135,8 @@ msgstr "" #: flwr.server.history.History.add_loss_centralized:1::1 of msgid "" -":py:obj:`add_metrics_distributed " -"`\\ \\(server\\_round\\, " -"metrics\\)" +":py:obj:`add_metrics_distributed `\\ \\(server\\_round\\, metrics\\)" msgstr "" #: flwr.server.history.History.add_loss_centralized:1::1 @@ -11332,9 +12146,8 @@ msgstr "" #: flwr.server.history.History.add_loss_centralized:1::1 of msgid "" -":py:obj:`add_metrics_distributed_fit " -"`\\ \\(server\\_round\\," -" ...\\)" +":py:obj:`add_metrics_distributed_fit `\\ \\(server\\_round\\, ...\\)" msgstr "" #: flwr.server.history.History.add_loss_centralized:1::1 @@ -11385,8 +12198,8 @@ msgstr "" #: flwr.server.server.Server.client_manager:1::1 of msgid "" -":py:obj:`disconnect_all_clients " -"`\\ \\(timeout\\)" +":py:obj:`disconnect_all_clients `\\ \\(timeout\\)" msgstr "" #: flwr.server.server.Server.client_manager:1::1 @@ -11416,8 +12229,8 @@ msgstr "" #: flwr.server.server.Server.client_manager:1::1 of msgid "" -":py:obj:`fit_round `\\ \\(server\\_round\\," -" timeout\\)" +":py:obj:`fit_round `\\ \\(server\\_round\\, " +"timeout\\)" msgstr "" #: flwr.server.server.Server.client_manager:1::1 @@ -11437,7 +12250,8 @@ msgid "Set the max_workers used by ThreadPoolExecutor." msgstr "" #: flwr.server.server.Server.client_manager:1::1 of -msgid ":py:obj:`set_strategy `\\ \\(strategy\\)" +msgid "" +":py:obj:`set_strategy `\\ \\(strategy\\)" msgstr "" #: flwr.server.server.Server.client_manager:1::1 @@ -11472,8 +12286,8 @@ msgstr "" #: flwr.server.server_config.ServerConfig:3 of msgid "" -"All attributes have default values which allows users to configure just " -"the ones they care about." +"All attributes have default values which allows users to configure just the " +"ones they care about." msgstr "" #: ../../source/ref-api/flwr.server.ServerConfig.rst:29::1 @@ -11498,14 +12312,13 @@ msgstr "" #: flwr.server.client_manager.SimpleClientManager.all:1::1 of msgid "" -":py:obj:`num_available `\\" -" \\(\\)" +":py:obj:`num_available `\\ " +"\\(\\)" msgstr "" #: flwr.server.client_manager.SimpleClientManager.all:1::1 of msgid "" -":py:obj:`register `\\ " -"\\(client\\)" +":py:obj:`register `\\ \\(client\\)" msgstr "" #: flwr.server.client_manager.SimpleClientManager.all:1::1 of @@ -11528,8 +12341,8 @@ msgstr "" #: flwr.server.client_manager.SimpleClientManager.wait_for:3 of msgid "" -"Blocks until the requested number of clients is available or until a " -"timeout is reached. Current timeout default: 1 day." +"Blocks until the requested number of clients is available or until a timeout " +"is reached. Current timeout default: 1 day." msgstr "" #: flwr.server.client_manager.SimpleClientManager.wait_for:6 of @@ -11570,8 +12383,8 @@ msgstr "" #: flwr.server.app.start_server:5 of msgid "" -"A server implementation, either `flwr.server.Server` or a subclass " -"thereof. If no instance is provided, then `start_server` will create one." +"A server implementation, either `flwr.server.Server` or a subclass thereof. " +"If no instance is provided, then `start_server` will create one." msgstr "" #: flwr.server.app.start_server:9 flwr.simulation.app.start_simulation:28 of @@ -11582,41 +12395,41 @@ msgstr "" #: flwr.server.app.start_server:12 of msgid "" -"An implementation of the abstract base class " -"`flwr.server.strategy.Strategy`. If no strategy is provided, then " -"`start_server` will use `flwr.server.strategy.FedAvg`." +"An implementation of the abstract base class `flwr.server.strategy." +"Strategy`. If no strategy is provided, then `start_server` will use `flwr." +"server.strategy.FedAvg`." msgstr "" #: flwr.server.app.start_server:16 of msgid "" -"An implementation of the abstract base class `flwr.server.ClientManager`." -" If no implementation is provided, then `start_server` will use " -"`flwr.server.client_manager.SimpleClientManager`." +"An implementation of the abstract base class `flwr.server.ClientManager`. If " +"no implementation is provided, then `start_server` will use `flwr.server." +"client_manager.SimpleClientManager`." msgstr "" #: flwr.server.app.start_server:21 of msgid "" -"The maximum length of gRPC messages that can be exchanged with the Flower" -" clients. The default should be sufficient for most models. Users who " -"train very large models might need to increase this value. Note that the " -"Flower clients need to be started with the same value (see " -"`flwr.client.start_client`), otherwise clients will not know about the " -"increased limit and block larger messages." +"The maximum length of gRPC messages that can be exchanged with the Flower " +"clients. The default should be sufficient for most models. Users who train " +"very large models might need to increase this value. Note that the Flower " +"clients need to be started with the same value (see `flwr.client." +"start_client`), otherwise clients will not know about the increased limit " +"and block larger messages." msgstr "" #: flwr.server.app.start_server:28 of msgid "" -"Tuple containing root certificate, server certificate, and private key to" -" start a secure SSL-enabled server. The tuple is expected to have three " -"bytes elements in the following order: * CA certificate. * " -"server certificate. * server private key." +"Tuple containing root certificate, server certificate, and private key to " +"start a secure SSL-enabled server. The tuple is expected to have three bytes " +"elements in the following order: * CA certificate. * server " +"certificate. * server private key." msgstr "" #: flwr.server.app.start_server:28 of msgid "" -"Tuple containing root certificate, server certificate, and private key to" -" start a secure SSL-enabled server. The tuple is expected to have three " -"bytes elements in the following order:" +"Tuple containing root certificate, server certificate, and private key to " +"start a secure SSL-enabled server. The tuple is expected to have three bytes " +"elements in the following order:" msgstr "" #: flwr.server.app.start_server:32 of @@ -11649,8 +12462,8 @@ msgstr "" #: ../../source/ref-api/flwr.server.strategy.rst:45::1 msgid "" -":py:obj:`Bulyan `\\ \\(\\*\\, " -"fraction\\_fit\\, fraction\\_evaluate\\, ...\\)" +":py:obj:`Bulyan `\\ \\(\\*\\, fraction\\_fit\\, " +"fraction\\_evaluate\\, ...\\)" msgstr "" #: ../../source/ref-api/flwr.server.strategy.rst:45::1 @@ -11682,9 +12495,8 @@ msgstr "" #: ../../source/ref-api/flwr.server.strategy.rst:45::1 msgid "" -":py:obj:`DifferentialPrivacyClientSideAdaptiveClipping " -"`\\ " -"\\(...\\)" +":py:obj:`DifferentialPrivacyClientSideAdaptiveClipping `\\ \\(...\\)" msgstr "" #: ../../source/ref-api/flwr.server.strategy.rst:45::1 @@ -11695,9 +12507,8 @@ msgstr "" #: ../../source/ref-api/flwr.server.strategy.rst:45::1 msgid "" -":py:obj:`DifferentialPrivacyServerSideAdaptiveClipping " -"`\\ " -"\\(...\\)" +":py:obj:`DifferentialPrivacyServerSideAdaptiveClipping `\\ \\(...\\)" msgstr "" #: ../../source/ref-api/flwr.server.strategy.rst:45::1 @@ -11708,9 +12519,8 @@ msgstr "" #: ../../source/ref-api/flwr.server.strategy.rst:45::1 msgid "" -":py:obj:`DifferentialPrivacyClientSideFixedClipping " -"`\\ " -"\\(...\\)" +":py:obj:`DifferentialPrivacyClientSideFixedClipping `\\ \\(...\\)" msgstr "" #: ../../source/ref-api/flwr.server.strategy.rst:45::1 @@ -11721,9 +12531,8 @@ msgstr "" #: ../../source/ref-api/flwr.server.strategy.rst:45::1 msgid "" -":py:obj:`DifferentialPrivacyServerSideFixedClipping " -"`\\ " -"\\(...\\)" +":py:obj:`DifferentialPrivacyServerSideFixedClipping `\\ \\(...\\)" msgstr "" #: ../../source/ref-api/flwr.server.strategy.rst:45::1 @@ -11768,8 +12577,8 @@ msgstr "" #: ../../source/ref-api/flwr.server.strategy.rst:45::1 msgid "" -":py:obj:`FedAvgAndroid `\\ " -"\\(\\*\\[\\, fraction\\_fit\\, ...\\]\\)" +":py:obj:`FedAvgAndroid `\\ \\(\\*\\[\\, " +"fraction\\_fit\\, ...\\]\\)" msgstr "" #: ../../source/ref-api/flwr.server.strategy.rst:45::1 @@ -11818,8 +12627,8 @@ msgstr "" #: ../../source/ref-api/flwr.server.strategy.rst:45::1 msgid "" -":py:obj:`FedTrimmedAvg `\\ " -"\\(\\*\\[\\, fraction\\_fit\\, ...\\]\\)" +":py:obj:`FedTrimmedAvg `\\ \\(\\*\\[\\, " +"fraction\\_fit\\, ...\\]\\)" msgstr "" #: ../../source/ref-api/flwr.server.strategy.rst:45::1 @@ -11873,9 +12682,8 @@ msgstr "" #: ../../source/ref-api/flwr.server.strategy.rst:45::1 msgid "" -":py:obj:`FaultTolerantFedAvg " -"`\\ \\(\\*\\[\\, " -"fraction\\_fit\\, ...\\]\\)" +":py:obj:`FaultTolerantFedAvg `\\ " +"\\(\\*\\[\\, fraction\\_fit\\, ...\\]\\)" msgstr "" #: ../../source/ref-api/flwr.server.strategy.rst:45::1 @@ -11885,8 +12693,8 @@ msgstr "" #: ../../source/ref-api/flwr.server.strategy.rst:45::1 msgid "" -":py:obj:`Krum `\\ \\(\\*\\[\\, " -"fraction\\_fit\\, fraction\\_evaluate\\, ...\\]\\)" +":py:obj:`Krum `\\ \\(\\*\\[\\, fraction\\_fit\\, " +"fraction\\_evaluate\\, ...\\]\\)" msgstr "" #: ../../source/ref-api/flwr.server.strategy.rst:45::1 @@ -11896,8 +12704,8 @@ msgstr "" #: ../../source/ref-api/flwr.server.strategy.rst:45::1 msgid "" -":py:obj:`QFedAvg `\\ \\(\\*\\[\\, " -"q\\_param\\, qffl\\_learning\\_rate\\, ...\\]\\)" +":py:obj:`QFedAvg `\\ \\(\\*\\[\\, q\\_param\\, " +"qffl\\_learning\\_rate\\, ...\\]\\)" msgstr "" #: ../../source/ref-api/flwr.server.strategy.rst:45::1 @@ -12065,8 +12873,8 @@ msgstr "" #: flwr.server.strategy.bulyan.Bulyan:27 of msgid "" -"Byzantine resilient aggregation rule that is used as the first step of " -"the Bulyan (e.g., Krum)" +"Byzantine resilient aggregation rule that is used as the first step of the " +"Bulyan (e.g., Krum)" msgstr "" #: flwr.server.strategy.bulyan.Bulyan:29 of @@ -12075,9 +12883,8 @@ msgstr "" #: flwr.server.strategy.fedavg.FedAvg.aggregate_evaluate:1::1 of msgid "" -":py:obj:`aggregate_evaluate " -"`\\ \\(server\\_round\\, " -"results\\, ...\\)" +":py:obj:`aggregate_evaluate `\\ \\(server\\_round\\, results\\, ...\\)" msgstr "" #: flwr.server.strategy.fault_tolerant_fedavg.FaultTolerantFedAvg.aggregate_evaluate:1 @@ -12104,9 +12911,8 @@ msgstr "" #: flwr.server.strategy.fedavg.FedAvg.aggregate_evaluate:1::1 of msgid "" -":py:obj:`configure_evaluate " -"`\\ \\(server\\_round\\, " -"parameters\\, ...\\)" +":py:obj:`configure_evaluate `\\ \\(server\\_round\\, parameters\\, ...\\)" msgstr "" #: flwr.server.strategy.dp_adaptive_clipping.DifferentialPrivacyClientSideAdaptiveClipping.aggregate_evaluate:1::1 @@ -12185,9 +12991,8 @@ msgstr "" #: flwr.server.strategy.fedavg.FedAvg.aggregate_evaluate:1::1 of msgid "" -":py:obj:`initialize_parameters " -"`\\ " -"\\(client\\_manager\\)" +":py:obj:`initialize_parameters `\\ \\(client\\_manager\\)" msgstr "" #: flwr.server.strategy.fault_tolerant_fedavg.FaultTolerantFedAvg.aggregate_evaluate:1::1 @@ -12204,9 +13009,8 @@ msgstr "" #: flwr.server.strategy.fedavg.FedAvg.aggregate_evaluate:1::1 of msgid "" -":py:obj:`num_evaluation_clients " -"`\\ " -"\\(num\\_available\\_clients\\)" +":py:obj:`num_evaluation_clients `\\ \\(num\\_available\\_clients\\)" msgstr "" #: flwr.server.strategy.fault_tolerant_fedavg.FaultTolerantFedAvg.aggregate_evaluate:1::1 @@ -12223,8 +13027,8 @@ msgstr "" #: flwr.server.strategy.fedavg.FedAvg.aggregate_evaluate:1::1 of msgid "" -":py:obj:`num_fit_clients `\\" -" \\(num\\_available\\_clients\\)" +":py:obj:`num_fit_clients `\\ " +"\\(num\\_available\\_clients\\)" msgstr "" #: flwr.server.strategy.fault_tolerant_fedavg.FaultTolerantFedAvg.aggregate_evaluate:1::1 @@ -12255,9 +13059,8 @@ msgstr "" #: flwr.server.strategy.dpfedavg_fixed.DPFedAvgFixed.aggregate_evaluate:1::1 #: of msgid "" -":py:obj:`aggregate_evaluate " -"`\\ " -"\\(server\\_round\\, results\\, ...\\)" +":py:obj:`aggregate_evaluate `\\ \\(server\\_round\\, results\\, ...\\)" msgstr "" #: flwr.server.strategy.dp_adaptive_clipping.DifferentialPrivacyClientSideAdaptiveClipping.aggregate_evaluate:1 @@ -12277,9 +13080,8 @@ msgstr "" #: flwr.server.strategy.dpfedavg_fixed.DPFedAvgFixed.aggregate_evaluate:1::1 #: of msgid "" -":py:obj:`aggregate_fit " -"`\\ " -"\\(server\\_round\\, results\\, failures\\)" +":py:obj:`aggregate_fit `\\ \\(server\\_round\\, results\\, failures\\)" msgstr "" #: flwr.server.strategy.dpfedavg_adaptive.DPFedAvgAdaptive.aggregate_fit:1 @@ -12291,9 +13093,8 @@ msgstr "" #: flwr.server.strategy.dpfedavg_fixed.DPFedAvgFixed.aggregate_evaluate:1::1 #: of msgid "" -":py:obj:`configure_evaluate " -"`\\ " -"\\(server\\_round\\, parameters\\, ...\\)" +":py:obj:`configure_evaluate `\\ \\(server\\_round\\, parameters\\, ...\\)" msgstr "" #: flwr.server.strategy.dpfedavg_fixed.DPFedAvgFixed.aggregate_evaluate:1::1 @@ -12304,9 +13105,8 @@ msgstr "" #: flwr.server.strategy.dpfedavg_fixed.DPFedAvgFixed.aggregate_evaluate:1::1 #: of msgid "" -":py:obj:`configure_fit " -"`\\ " -"\\(server\\_round\\, parameters\\, ...\\)" +":py:obj:`configure_fit `\\ \\(server\\_round\\, parameters\\, ...\\)" msgstr "" #: flwr.server.strategy.dpfedavg_fixed.DPFedAvgFixed.aggregate_evaluate:1::1 @@ -12326,15 +13126,15 @@ msgstr "" #: flwr.server.strategy.dp_fixed_clipping.DifferentialPrivacyServerSideFixedClipping.evaluate:1 #: flwr.server.strategy.dpfedavg_fixed.DPFedAvgFixed.aggregate_evaluate:1::1 #: flwr.server.strategy.dpfedavg_fixed.DPFedAvgFixed.evaluate:1 of -msgid "Evaluate model parameters using an evaluation function from the strategy." +msgid "" +"Evaluate model parameters using an evaluation function from the strategy." msgstr "" #: flwr.server.strategy.dpfedavg_fixed.DPFedAvgFixed.aggregate_evaluate:1::1 #: of msgid "" -":py:obj:`initialize_parameters " -"`\\ " -"\\(client\\_manager\\)" +":py:obj:`initialize_parameters `\\ \\(client\\_manager\\)" msgstr "" #: flwr.server.strategy.dp_adaptive_clipping.DifferentialPrivacyClientSideAdaptiveClipping.aggregate_evaluate:1::1 @@ -12373,9 +13173,9 @@ msgstr "" msgid "" "**evaluate_configuration** -- A list of tuples. Each tuple in the list " "identifies a `ClientProxy` and the `EvaluateIns` for this particular " -"`ClientProxy`. If a particular `ClientProxy` is not included in this " -"list, it means that this `ClientProxy` will not participate in the next " -"round of federated evaluation." +"`ClientProxy`. If a particular `ClientProxy` is not included in this list, " +"it means that this `ClientProxy` will not participate in the next round of " +"federated evaluation." msgstr "" #: ../../source/ref-api/flwr.server.strategy.DPFedAvgFixed.rst:2 @@ -12395,16 +13195,14 @@ msgstr "" #: flwr.server.strategy.dpfedavg_fixed.DPFedAvgFixed.aggregate_evaluate:1::1 #: of msgid "" -":py:obj:`aggregate_evaluate " -"`\\ " -"\\(server\\_round\\, results\\, ...\\)" +":py:obj:`aggregate_evaluate `\\ \\(server\\_round\\, results\\, ...\\)" msgstr "" #: flwr.server.strategy.dpfedavg_fixed.DPFedAvgFixed.aggregate_evaluate:1::1 #: of msgid "" -":py:obj:`aggregate_fit " -"`\\ " +":py:obj:`aggregate_fit `\\ " "\\(server\\_round\\, results\\, failures\\)" msgstr "" @@ -12416,24 +13214,21 @@ msgstr "" #: flwr.server.strategy.dpfedavg_fixed.DPFedAvgFixed.aggregate_evaluate:1::1 #: of msgid "" -":py:obj:`configure_evaluate " -"`\\ " -"\\(server\\_round\\, parameters\\, ...\\)" +":py:obj:`configure_evaluate `\\ \\(server\\_round\\, parameters\\, ...\\)" msgstr "" #: flwr.server.strategy.dpfedavg_fixed.DPFedAvgFixed.aggregate_evaluate:1::1 #: of msgid "" -":py:obj:`configure_fit " -"`\\ " +":py:obj:`configure_fit `\\ " "\\(server\\_round\\, parameters\\, ...\\)" msgstr "" #: flwr.server.strategy.dpfedavg_fixed.DPFedAvgFixed.aggregate_evaluate:1::1 #: flwr.server.strategy.dpfedavg_fixed.DPFedAvgFixed.configure_fit:1 of msgid "" -"Configure the next round of training incorporating Differential Privacy " -"(DP)." +"Configure the next round of training incorporating Differential Privacy (DP)." msgstr "" #: flwr.server.strategy.dpfedavg_fixed.DPFedAvgFixed.aggregate_evaluate:1::1 @@ -12446,25 +13241,23 @@ msgstr "" #: flwr.server.strategy.dpfedavg_fixed.DPFedAvgFixed.aggregate_evaluate:1::1 #: of msgid "" -":py:obj:`initialize_parameters " -"`\\ " -"\\(client\\_manager\\)" +":py:obj:`initialize_parameters `\\ \\(client\\_manager\\)" msgstr "" #: flwr.server.strategy.dpfedavg_fixed.DPFedAvgFixed.configure_fit:3 of msgid "" -"Configuration of the next training round includes information related to " -"DP, such as clip norm and noise stddev." +"Configuration of the next training round includes information related to DP, " +"such as clip norm and noise stddev." msgstr "" #: flwr.server.strategy.dpfedavg_fixed.DPFedAvgFixed.configure_fit:13 #: flwr.server.strategy.strategy.Strategy.configure_fit:10 of msgid "" -"**fit_configuration** -- A list of tuples. Each tuple in the list " -"identifies a `ClientProxy` and the `FitIns` for this particular " -"`ClientProxy`. If a particular `ClientProxy` is not included in this " -"list, it means that this `ClientProxy` will not participate in the next " -"round of federated learning." +"**fit_configuration** -- A list of tuples. Each tuple in the list identifies " +"a `ClientProxy` and the `FitIns` for this particular `ClientProxy`. If a " +"particular `ClientProxy` is not included in this list, it means that this " +"`ClientProxy` will not participate in the next round of federated learning." msgstr "" #: ../../source/ref-api/flwr.server.strategy.DifferentialPrivacyClientSideAdaptiveClipping.rst:2 @@ -12481,9 +13274,8 @@ msgstr "" msgid "" "In comparison to `DifferentialPrivacyServerSideAdaptiveClipping`, which " "performs clipping on the server-side, " -"`DifferentialPrivacyClientSideAdaptiveClipping` expects clipping to " -"happen on the client-side, usually by using the built-in " -"`adaptiveclipping_mod`." +"`DifferentialPrivacyClientSideAdaptiveClipping` expects clipping to happen " +"on the client-side, usually by using the built-in `adaptiveclipping_mod`." msgstr "" #: flwr.server.strategy.dp_adaptive_clipping.DifferentialPrivacyClientSideAdaptiveClipping:10 @@ -12519,22 +13311,23 @@ msgstr "" #: flwr.server.strategy.dp_adaptive_clipping.DifferentialPrivacyClientSideAdaptiveClipping:19 #: flwr.server.strategy.dp_adaptive_clipping.DifferentialPrivacyServerSideAdaptiveClipping:12 #: of -msgid "The desired quantile of updates which should be clipped. Defaults to 0.5." +msgid "" +"The desired quantile of updates which should be clipped. Defaults to 0.5." msgstr "" #: flwr.server.strategy.dp_adaptive_clipping.DifferentialPrivacyClientSideAdaptiveClipping:21 #: flwr.server.strategy.dp_adaptive_clipping.DifferentialPrivacyServerSideAdaptiveClipping:14 #: of msgid "" -"The learning rate for the clipping norm adaptation. Defaults to 0.2. " -"Andrew et al. recommends to set to 0.2." +"The learning rate for the clipping norm adaptation. Defaults to 0.2. Andrew " +"et al. recommends to set to 0.2." msgstr "" #: flwr.server.strategy.dp_adaptive_clipping.DifferentialPrivacyClientSideAdaptiveClipping:24 #: of msgid "" -"The stddev of the noise added to the count of updates currently below the" -" estimate. Andrew et al. recommends to set to `expected_num_records/20`" +"The stddev of the noise added to the count of updates currently below the " +"estimate. Andrew et al. recommends to set to `expected_num_records/20`" msgstr "" #: flwr.server.strategy.dp_adaptive_clipping.DifferentialPrivacyClientSideAdaptiveClipping:30 @@ -12548,8 +13341,8 @@ msgstr "" #: flwr.server.strategy.dp_adaptive_clipping.DifferentialPrivacyClientSideAdaptiveClipping:34 #: of msgid "" -"Wrap the strategy with the " -"`DifferentialPrivacyClientSideAdaptiveClipping` wrapper:" +"Wrap the strategy with the `DifferentialPrivacyClientSideAdaptiveClipping` " +"wrapper:" msgstr "" #: flwr.server.strategy.dp_adaptive_clipping.DifferentialPrivacyClientSideAdaptiveClipping:40 @@ -12560,17 +13353,17 @@ msgstr "" #: flwr.server.strategy.dp_adaptive_clipping.DifferentialPrivacyClientSideAdaptiveClipping.aggregate_evaluate:1::1 #: of msgid "" -":py:obj:`aggregate_evaluate " -"`\\" -" \\(server\\_round\\, results\\, ...\\)" +":py:obj:`aggregate_evaluate `\\ " +"\\(server\\_round\\, results\\, ...\\)" msgstr "" #: flwr.server.strategy.dp_adaptive_clipping.DifferentialPrivacyClientSideAdaptiveClipping.aggregate_evaluate:1::1 #: of msgid "" -":py:obj:`aggregate_fit " -"`\\" -" \\(server\\_round\\, results\\, failures\\)" +":py:obj:`aggregate_fit `\\ " +"\\(server\\_round\\, results\\, failures\\)" msgstr "" #: flwr.server.strategy.dp_adaptive_clipping.DifferentialPrivacyClientSideAdaptiveClipping.aggregate_evaluate:1::1 @@ -12584,33 +13377,33 @@ msgstr "" #: flwr.server.strategy.dp_adaptive_clipping.DifferentialPrivacyClientSideAdaptiveClipping.aggregate_evaluate:1::1 #: of msgid "" -":py:obj:`configure_evaluate " -"`\\" -" \\(server\\_round\\, parameters\\, ...\\)" +":py:obj:`configure_evaluate `\\ " +"\\(server\\_round\\, parameters\\, ...\\)" msgstr "" #: flwr.server.strategy.dp_adaptive_clipping.DifferentialPrivacyClientSideAdaptiveClipping.aggregate_evaluate:1::1 #: of msgid "" -":py:obj:`configure_fit " -"`\\" -" \\(server\\_round\\, parameters\\, ...\\)" +":py:obj:`configure_fit `\\ " +"\\(server\\_round\\, parameters\\, ...\\)" msgstr "" #: flwr.server.strategy.dp_adaptive_clipping.DifferentialPrivacyClientSideAdaptiveClipping.aggregate_evaluate:1::1 #: of msgid "" -":py:obj:`evaluate " -"`\\" -" \\(server\\_round\\, parameters\\)" +":py:obj:`evaluate `\\ " +"\\(server\\_round\\, parameters\\)" msgstr "" #: flwr.server.strategy.dp_adaptive_clipping.DifferentialPrivacyClientSideAdaptiveClipping.aggregate_evaluate:1::1 #: of msgid "" -":py:obj:`initialize_parameters " -"`\\" -" \\(client\\_manager\\)" +":py:obj:`initialize_parameters `\\ " +"\\(client\\_manager\\)" msgstr "" #: ../../source/ref-api/flwr.server.strategy.DifferentialPrivacyClientSideFixedClipping.rst:2 @@ -12627,16 +13420,16 @@ msgstr "" msgid "" "In comparison to `DifferentialPrivacyServerSideFixedClipping`, which " "performs clipping on the server-side, " -"`DifferentialPrivacyClientSideFixedClipping` expects clipping to happen " -"on the client-side, usually by using the built-in `fixedclipping_mod`." +"`DifferentialPrivacyClientSideFixedClipping` expects clipping to happen on " +"the client-side, usually by using the built-in `fixedclipping_mod`." msgstr "" #: flwr.server.strategy.dp_fixed_clipping.DifferentialPrivacyClientSideFixedClipping:12 #: flwr.server.strategy.dp_fixed_clipping.DifferentialPrivacyServerSideFixedClipping:5 #: of msgid "" -"The noise multiplier for the Gaussian mechanism for model updates. A " -"value of 1.0 or higher is recommended for strong privacy." +"The noise multiplier for the Gaussian mechanism for model updates. A value " +"of 1.0 or higher is recommended for strong privacy." msgstr "" #: flwr.server.strategy.dp_fixed_clipping.DifferentialPrivacyClientSideFixedClipping:26 @@ -12654,17 +13447,17 @@ msgstr "" #: flwr.server.strategy.dp_fixed_clipping.DifferentialPrivacyClientSideFixedClipping.aggregate_evaluate:1::1 #: of msgid "" -":py:obj:`aggregate_evaluate " -"`\\" -" \\(server\\_round\\, results\\, ...\\)" +":py:obj:`aggregate_evaluate `\\ " +"\\(server\\_round\\, results\\, ...\\)" msgstr "" #: flwr.server.strategy.dp_fixed_clipping.DifferentialPrivacyClientSideFixedClipping.aggregate_evaluate:1::1 #: of msgid "" -":py:obj:`aggregate_fit " -"`\\" -" \\(server\\_round\\, results\\, failures\\)" +":py:obj:`aggregate_fit `\\ " +"\\(server\\_round\\, results\\, failures\\)" msgstr "" #: flwr.server.strategy.dp_fixed_clipping.DifferentialPrivacyClientSideFixedClipping.aggregate_evaluate:1::1 @@ -12676,33 +13469,33 @@ msgstr "" #: flwr.server.strategy.dp_fixed_clipping.DifferentialPrivacyClientSideFixedClipping.aggregate_evaluate:1::1 #: of msgid "" -":py:obj:`configure_evaluate " -"`\\" -" \\(server\\_round\\, parameters\\, ...\\)" +":py:obj:`configure_evaluate `\\ " +"\\(server\\_round\\, parameters\\, ...\\)" msgstr "" #: flwr.server.strategy.dp_fixed_clipping.DifferentialPrivacyClientSideFixedClipping.aggregate_evaluate:1::1 #: of msgid "" -":py:obj:`configure_fit " -"`\\" -" \\(server\\_round\\, parameters\\, ...\\)" +":py:obj:`configure_fit `\\ " +"\\(server\\_round\\, parameters\\, ...\\)" msgstr "" #: flwr.server.strategy.dp_fixed_clipping.DifferentialPrivacyClientSideFixedClipping.aggregate_evaluate:1::1 #: of msgid "" -":py:obj:`evaluate " -"`\\" -" \\(server\\_round\\, parameters\\)" +":py:obj:`evaluate `\\ \\(server\\_round\\, " +"parameters\\)" msgstr "" #: flwr.server.strategy.dp_fixed_clipping.DifferentialPrivacyClientSideFixedClipping.aggregate_evaluate:1::1 #: of msgid "" -":py:obj:`initialize_parameters " -"`\\" -" \\(client\\_manager\\)" +":py:obj:`initialize_parameters `\\ " +"\\(client\\_manager\\)" msgstr "" #: ../../source/ref-api/flwr.server.strategy.DifferentialPrivacyServerSideAdaptiveClipping.rst:2 @@ -12712,9 +13505,8 @@ msgstr "" #: flwr.server.strategy.dp_adaptive_clipping.DifferentialPrivacyServerSideAdaptiveClipping:17 #: of msgid "" -"The standard deviation of the noise added to the count of updates below " -"the estimate. Andrew et al. recommends to set to " -"`expected_num_records/20`" +"The standard deviation of the noise added to the count of updates below the " +"estimate. Andrew et al. recommends to set to `expected_num_records/20`" msgstr "" #: flwr.server.strategy.dp_adaptive_clipping.DifferentialPrivacyServerSideAdaptiveClipping:27 @@ -12727,49 +13519,49 @@ msgstr "" #: flwr.server.strategy.dp_adaptive_clipping.DifferentialPrivacyServerSideAdaptiveClipping.aggregate_evaluate:1::1 #: of msgid "" -":py:obj:`aggregate_evaluate " -"`\\" -" \\(server\\_round\\, results\\, ...\\)" +":py:obj:`aggregate_evaluate `\\ " +"\\(server\\_round\\, results\\, ...\\)" msgstr "" #: flwr.server.strategy.dp_adaptive_clipping.DifferentialPrivacyServerSideAdaptiveClipping.aggregate_evaluate:1::1 #: of msgid "" -":py:obj:`aggregate_fit " -"`\\" -" \\(server\\_round\\, results\\, failures\\)" +":py:obj:`aggregate_fit `\\ " +"\\(server\\_round\\, results\\, failures\\)" msgstr "" #: flwr.server.strategy.dp_adaptive_clipping.DifferentialPrivacyServerSideAdaptiveClipping.aggregate_evaluate:1::1 #: of msgid "" -":py:obj:`configure_evaluate " -"`\\" -" \\(server\\_round\\, parameters\\, ...\\)" +":py:obj:`configure_evaluate `\\ " +"\\(server\\_round\\, parameters\\, ...\\)" msgstr "" #: flwr.server.strategy.dp_adaptive_clipping.DifferentialPrivacyServerSideAdaptiveClipping.aggregate_evaluate:1::1 #: of msgid "" -":py:obj:`configure_fit " -"`\\" -" \\(server\\_round\\, parameters\\, ...\\)" +":py:obj:`configure_fit `\\ " +"\\(server\\_round\\, parameters\\, ...\\)" msgstr "" #: flwr.server.strategy.dp_adaptive_clipping.DifferentialPrivacyServerSideAdaptiveClipping.aggregate_evaluate:1::1 #: of msgid "" -":py:obj:`evaluate " -"`\\" -" \\(server\\_round\\, parameters\\)" +":py:obj:`evaluate `\\ " +"\\(server\\_round\\, parameters\\)" msgstr "" #: flwr.server.strategy.dp_adaptive_clipping.DifferentialPrivacyServerSideAdaptiveClipping.aggregate_evaluate:1::1 #: of msgid "" -":py:obj:`initialize_parameters " -"`\\" -" \\(client\\_manager\\)" +":py:obj:`initialize_parameters `\\ " +"\\(client\\_manager\\)" msgstr "" #: ../../source/ref-api/flwr.server.strategy.DifferentialPrivacyServerSideFixedClipping.rst:2 @@ -12779,24 +13571,23 @@ msgstr "" #: flwr.server.strategy.dp_fixed_clipping.DifferentialPrivacyServerSideFixedClipping:19 #: of msgid "" -"Wrap the strategy with the DifferentialPrivacyServerSideFixedClipping " -"wrapper" +"Wrap the strategy with the DifferentialPrivacyServerSideFixedClipping wrapper" msgstr "" #: flwr.server.strategy.dp_fixed_clipping.DifferentialPrivacyServerSideFixedClipping.aggregate_evaluate:1::1 #: of msgid "" -":py:obj:`aggregate_evaluate " -"`\\" -" \\(server\\_round\\, results\\, ...\\)" +":py:obj:`aggregate_evaluate `\\ " +"\\(server\\_round\\, results\\, ...\\)" msgstr "" #: flwr.server.strategy.dp_fixed_clipping.DifferentialPrivacyServerSideFixedClipping.aggregate_evaluate:1::1 #: of msgid "" -":py:obj:`aggregate_fit " -"`\\" -" \\(server\\_round\\, results\\, failures\\)" +":py:obj:`aggregate_fit `\\ " +"\\(server\\_round\\, results\\, failures\\)" msgstr "" #: flwr.server.strategy.dp_fixed_clipping.DifferentialPrivacyServerSideFixedClipping.aggregate_evaluate:1::1 @@ -12808,33 +13599,33 @@ msgstr "" #: flwr.server.strategy.dp_fixed_clipping.DifferentialPrivacyServerSideFixedClipping.aggregate_evaluate:1::1 #: of msgid "" -":py:obj:`configure_evaluate " -"`\\" -" \\(server\\_round\\, parameters\\, ...\\)" +":py:obj:`configure_evaluate `\\ " +"\\(server\\_round\\, parameters\\, ...\\)" msgstr "" #: flwr.server.strategy.dp_fixed_clipping.DifferentialPrivacyServerSideFixedClipping.aggregate_evaluate:1::1 #: of msgid "" -":py:obj:`configure_fit " -"`\\" -" \\(server\\_round\\, parameters\\, ...\\)" +":py:obj:`configure_fit `\\ " +"\\(server\\_round\\, parameters\\, ...\\)" msgstr "" #: flwr.server.strategy.dp_fixed_clipping.DifferentialPrivacyServerSideFixedClipping.aggregate_evaluate:1::1 #: of msgid "" -":py:obj:`evaluate " -"`\\" -" \\(server\\_round\\, parameters\\)" +":py:obj:`evaluate `\\ \\(server\\_round\\, " +"parameters\\)" msgstr "" #: flwr.server.strategy.dp_fixed_clipping.DifferentialPrivacyServerSideFixedClipping.aggregate_evaluate:1::1 #: of msgid "" -":py:obj:`initialize_parameters " -"`\\" -" \\(client\\_manager\\)" +":py:obj:`initialize_parameters `\\ " +"\\(client\\_manager\\)" msgstr "" #: flwr.server.strategy.dp_fixed_clipping.DifferentialPrivacyServerSideFixedClipping.aggregate_fit:3 @@ -12849,17 +13640,15 @@ msgstr "" #: flwr.server.strategy.fault_tolerant_fedavg.FaultTolerantFedAvg.aggregate_evaluate:1::1 #: of msgid "" -":py:obj:`aggregate_evaluate " -"`\\ " -"\\(server\\_round\\, results\\, ...\\)" +":py:obj:`aggregate_evaluate `\\ \\(server\\_round\\, results\\, ...\\)" msgstr "" #: flwr.server.strategy.fault_tolerant_fedavg.FaultTolerantFedAvg.aggregate_evaluate:1::1 #: of msgid "" -":py:obj:`aggregate_fit " -"`\\ " -"\\(server\\_round\\, results\\, failures\\)" +":py:obj:`aggregate_fit `\\ \\(server\\_round\\, results\\, failures\\)" msgstr "" #: flwr.server.strategy.fault_tolerant_fedavg.FaultTolerantFedAvg.aggregate_evaluate:1::1 @@ -12881,17 +13670,15 @@ msgstr "" #: flwr.server.strategy.fault_tolerant_fedavg.FaultTolerantFedAvg.aggregate_evaluate:1::1 #: of msgid "" -":py:obj:`configure_evaluate " -"`\\ " -"\\(server\\_round\\, parameters\\, ...\\)" +":py:obj:`configure_evaluate `\\ \\(server\\_round\\, parameters\\, ...\\)" msgstr "" #: flwr.server.strategy.fault_tolerant_fedavg.FaultTolerantFedAvg.aggregate_evaluate:1::1 #: of msgid "" -":py:obj:`configure_fit " -"`\\ " -"\\(server\\_round\\, parameters\\, ...\\)" +":py:obj:`configure_fit `\\ \\(server\\_round\\, parameters\\, ...\\)" msgstr "" #: flwr.server.strategy.fault_tolerant_fedavg.FaultTolerantFedAvg.aggregate_evaluate:1::1 @@ -12904,25 +13691,22 @@ msgstr "" #: flwr.server.strategy.fault_tolerant_fedavg.FaultTolerantFedAvg.aggregate_evaluate:1::1 #: of msgid "" -":py:obj:`initialize_parameters " -"`\\ " -"\\(client\\_manager\\)" +":py:obj:`initialize_parameters `\\ \\(client\\_manager\\)" msgstr "" #: flwr.server.strategy.fault_tolerant_fedavg.FaultTolerantFedAvg.aggregate_evaluate:1::1 #: of msgid "" -":py:obj:`num_evaluation_clients " -"`\\ " -"\\(num\\_available\\_clients\\)" +":py:obj:`num_evaluation_clients `\\ \\(num\\_available\\_clients\\)" msgstr "" #: flwr.server.strategy.fault_tolerant_fedavg.FaultTolerantFedAvg.aggregate_evaluate:1::1 #: of msgid "" -":py:obj:`num_fit_clients " -"`\\ " -"\\(num\\_available\\_clients\\)" +":py:obj:`num_fit_clients `\\ \\(num\\_available\\_clients\\)" msgstr "" #: ../../source/ref-api/flwr.server.strategy.FedAdagrad.rst:2 @@ -12975,28 +13759,26 @@ msgstr "" #: flwr.server.strategy.fedavg.FedAvg.aggregate_evaluate:1::1 of msgid "" -":py:obj:`aggregate_evaluate " -"`\\ " -"\\(server\\_round\\, results\\, ...\\)" +":py:obj:`aggregate_evaluate `\\ \\(server\\_round\\, results\\, ...\\)" msgstr "" #: flwr.server.strategy.fedavg.FedAvg.aggregate_evaluate:1::1 of msgid "" -":py:obj:`aggregate_fit `\\" -" \\(server\\_round\\, results\\, failures\\)" +":py:obj:`aggregate_fit `\\ " +"\\(server\\_round\\, results\\, failures\\)" msgstr "" #: flwr.server.strategy.fedavg.FedAvg.aggregate_evaluate:1::1 of msgid "" -":py:obj:`configure_evaluate " -"`\\ " -"\\(server\\_round\\, parameters\\, ...\\)" +":py:obj:`configure_evaluate `\\ \\(server\\_round\\, parameters\\, ...\\)" msgstr "" #: flwr.server.strategy.fedavg.FedAvg.aggregate_evaluate:1::1 of msgid "" -":py:obj:`configure_fit `\\" -" \\(server\\_round\\, parameters\\, ...\\)" +":py:obj:`configure_fit `\\ " +"\\(server\\_round\\, parameters\\, ...\\)" msgstr "" #: flwr.server.strategy.fedavg.FedAvg.aggregate_evaluate:1::1 of @@ -13007,23 +13789,20 @@ msgstr "" #: flwr.server.strategy.fedavg.FedAvg.aggregate_evaluate:1::1 of msgid "" -":py:obj:`initialize_parameters " -"`\\ " -"\\(client\\_manager\\)" +":py:obj:`initialize_parameters `\\ \\(client\\_manager\\)" msgstr "" #: flwr.server.strategy.fedavg.FedAvg.aggregate_evaluate:1::1 of msgid "" -":py:obj:`num_evaluation_clients " -"`\\ " -"\\(num\\_available\\_clients\\)" +":py:obj:`num_evaluation_clients `\\ \\(num\\_available\\_clients\\)" msgstr "" #: flwr.server.strategy.fedavg.FedAvg.aggregate_evaluate:1::1 of msgid "" -":py:obj:`num_fit_clients " -"`\\ " -"\\(num\\_available\\_clients\\)" +":py:obj:`num_fit_clients `\\ \\(num\\_available\\_clients\\)" msgstr "" #: ../../source/ref-api/flwr.server.strategy.FedAdam.rst:2 @@ -13042,9 +13821,8 @@ msgstr "" #: flwr.server.strategy.fedavg.FedAvg.aggregate_evaluate:1::1 of msgid "" -":py:obj:`aggregate_evaluate " -"`\\ \\(server\\_round\\," -" results\\, ...\\)" +":py:obj:`aggregate_evaluate `\\ \\(server\\_round\\, results\\, ...\\)" msgstr "" #: flwr.server.strategy.fedavg.FedAvg.aggregate_evaluate:1::1 of @@ -13055,9 +13833,8 @@ msgstr "" #: flwr.server.strategy.fedavg.FedAvg.aggregate_evaluate:1::1 of msgid "" -":py:obj:`configure_evaluate " -"`\\ \\(server\\_round\\," -" parameters\\, ...\\)" +":py:obj:`configure_evaluate `\\ \\(server\\_round\\, parameters\\, ...\\)" msgstr "" #: flwr.server.strategy.fedavg.FedAvg.aggregate_evaluate:1::1 of @@ -13074,22 +13851,19 @@ msgstr "" #: flwr.server.strategy.fedavg.FedAvg.aggregate_evaluate:1::1 of msgid "" -":py:obj:`initialize_parameters " -"`\\ " -"\\(client\\_manager\\)" +":py:obj:`initialize_parameters `\\ \\(client\\_manager\\)" msgstr "" #: flwr.server.strategy.fedavg.FedAvg.aggregate_evaluate:1::1 of msgid "" -":py:obj:`num_evaluation_clients " -"`\\ " -"\\(num\\_available\\_clients\\)" +":py:obj:`num_evaluation_clients `\\ \\(num\\_available\\_clients\\)" msgstr "" #: flwr.server.strategy.fedavg.FedAvg.aggregate_evaluate:1::1 of msgid "" -":py:obj:`num_fit_clients " -"`\\ " +":py:obj:`num_fit_clients `\\ " "\\(num\\_available\\_clients\\)" msgstr "" @@ -13106,17 +13880,16 @@ msgstr "" #: of msgid "" "Fraction of clients used during training. In case `min_fit_clients` is " -"larger than `fraction_fit * available_clients`, `min_fit_clients` will " -"still be sampled. Defaults to 1.0." +"larger than `fraction_fit * available_clients`, `min_fit_clients` will still " +"be sampled. Defaults to 1.0." msgstr "" #: flwr.server.strategy.fedavg.FedAvg:9 flwr.server.strategy.fedprox.FedProx:41 #: of msgid "" -"Fraction of clients used during validation. In case " -"`min_evaluate_clients` is larger than `fraction_evaluate * " -"available_clients`, `min_evaluate_clients` will still be sampled. " -"Defaults to 1.0." +"Fraction of clients used during validation. In case `min_evaluate_clients` " +"is larger than `fraction_evaluate * available_clients`, " +"`min_evaluate_clients` will still be sampled. Defaults to 1.0." msgstr "" #: flwr.server.strategy.fedavg.FedAvg:33 of @@ -13125,9 +13898,8 @@ msgstr "" #: flwr.server.strategy.fedavg.FedAvg.aggregate_evaluate:1::1 of msgid "" -":py:obj:`aggregate_evaluate " -"`\\ \\(server\\_round\\, " -"results\\, ...\\)" +":py:obj:`aggregate_evaluate `\\ \\(server\\_round\\, results\\, ...\\)" msgstr "" #: flwr.server.strategy.fedavg.FedAvg.aggregate_evaluate:1::1 of @@ -13138,9 +13910,8 @@ msgstr "" #: flwr.server.strategy.fedavg.FedAvg.aggregate_evaluate:1::1 of msgid "" -":py:obj:`configure_evaluate " -"`\\ \\(server\\_round\\, " -"parameters\\, ...\\)" +":py:obj:`configure_evaluate `\\ \\(server\\_round\\, parameters\\, ...\\)" msgstr "" #: flwr.server.strategy.fedavg.FedAvg.aggregate_evaluate:1::1 of @@ -13157,22 +13928,20 @@ msgstr "" #: flwr.server.strategy.fedavg.FedAvg.aggregate_evaluate:1::1 of msgid "" -":py:obj:`initialize_parameters " -"`\\ " -"\\(client\\_manager\\)" +":py:obj:`initialize_parameters `\\ \\(client\\_manager\\)" msgstr "" #: flwr.server.strategy.fedavg.FedAvg.aggregate_evaluate:1::1 of msgid "" -":py:obj:`num_evaluation_clients " -"`\\ " -"\\(num\\_available\\_clients\\)" +":py:obj:`num_evaluation_clients `\\ \\(num\\_available\\_clients\\)" msgstr "" #: flwr.server.strategy.fedavg.FedAvg.aggregate_evaluate:1::1 of msgid "" -":py:obj:`num_fit_clients `\\" -" \\(num\\_available\\_clients\\)" +":py:obj:`num_fit_clients `\\ " +"\\(num\\_available\\_clients\\)" msgstr "" #: ../../source/ref-api/flwr.server.strategy.FedAvgAndroid.rst:2 @@ -13182,24 +13951,22 @@ msgstr "" #: flwr.server.strategy.fedavg_android.FedAvgAndroid.aggregate_evaluate:1::1 #: of msgid "" -":py:obj:`aggregate_evaluate " -"`\\ " -"\\(server\\_round\\, results\\, ...\\)" +":py:obj:`aggregate_evaluate `\\ \\(server\\_round\\, results\\, ...\\)" msgstr "" #: flwr.server.strategy.fedavg_android.FedAvgAndroid.aggregate_evaluate:1::1 #: of msgid "" -":py:obj:`aggregate_fit " -"`\\ " +":py:obj:`aggregate_fit `\\ " "\\(server\\_round\\, results\\, failures\\)" msgstr "" #: flwr.server.strategy.fedavg_android.FedAvgAndroid.aggregate_evaluate:1::1 #: of msgid "" -":py:obj:`bytes_to_ndarray " -"`\\ \\(tensor\\)" +":py:obj:`bytes_to_ndarray `\\ \\(tensor\\)" msgstr "" #: flwr.server.strategy.fedavg_android.FedAvgAndroid.aggregate_evaluate:1::1 @@ -13210,16 +13977,14 @@ msgstr "" #: flwr.server.strategy.fedavg_android.FedAvgAndroid.aggregate_evaluate:1::1 #: of msgid "" -":py:obj:`configure_evaluate " -"`\\ " -"\\(server\\_round\\, parameters\\, ...\\)" +":py:obj:`configure_evaluate `\\ \\(server\\_round\\, parameters\\, ...\\)" msgstr "" #: flwr.server.strategy.fedavg_android.FedAvgAndroid.aggregate_evaluate:1::1 #: of msgid "" -":py:obj:`configure_fit " -"`\\ " +":py:obj:`configure_fit `\\ " "\\(server\\_round\\, parameters\\, ...\\)" msgstr "" @@ -13233,16 +13998,15 @@ msgstr "" #: flwr.server.strategy.fedavg_android.FedAvgAndroid.aggregate_evaluate:1::1 #: of msgid "" -":py:obj:`initialize_parameters " -"`\\ " -"\\(client\\_manager\\)" +":py:obj:`initialize_parameters `\\ \\(client\\_manager\\)" msgstr "" #: flwr.server.strategy.fedavg_android.FedAvgAndroid.aggregate_evaluate:1::1 #: of msgid "" -":py:obj:`ndarray_to_bytes " -"`\\ \\(ndarray\\)" +":py:obj:`ndarray_to_bytes `\\ \\(ndarray\\)" msgstr "" #: flwr.server.strategy.fedavg_android.FedAvgAndroid.aggregate_evaluate:1::1 @@ -13253,33 +14017,29 @@ msgstr "" #: flwr.server.strategy.fedavg_android.FedAvgAndroid.aggregate_evaluate:1::1 #: of msgid "" -":py:obj:`ndarrays_to_parameters " -"`\\ " -"\\(ndarrays\\)" +":py:obj:`ndarrays_to_parameters `\\ \\(ndarrays\\)" msgstr "" #: flwr.server.strategy.fedavg_android.FedAvgAndroid.aggregate_evaluate:1::1 #: of msgid "" -":py:obj:`num_evaluation_clients " -"`\\ " -"\\(num\\_available\\_clients\\)" +":py:obj:`num_evaluation_clients `\\ \\(num\\_available\\_clients\\)" msgstr "" #: flwr.server.strategy.fedavg_android.FedAvgAndroid.aggregate_evaluate:1::1 #: of msgid "" -":py:obj:`num_fit_clients " -"`\\ " -"\\(num\\_available\\_clients\\)" +":py:obj:`num_fit_clients `\\ \\(num\\_available\\_clients\\)" msgstr "" #: flwr.server.strategy.fedavg_android.FedAvgAndroid.aggregate_evaluate:1::1 #: of msgid "" -":py:obj:`parameters_to_ndarrays " -"`\\ " -"\\(parameters\\)" +":py:obj:`parameters_to_ndarrays `\\ \\(parameters\\)" msgstr "" #: flwr.server.strategy.fedavg_android.FedAvgAndroid.aggregate_evaluate:1::1 @@ -13298,8 +14058,7 @@ msgstr "" #: flwr.server.strategy.fedavgm.FedAvgM:25 of msgid "" -"Server-side learning rate used in server-side optimization. Defaults to " -"1.0." +"Server-side learning rate used in server-side optimization. Defaults to 1.0." msgstr "" #: flwr.server.strategy.fedavgm.FedAvgM:28 of @@ -13308,9 +14067,8 @@ msgstr "" #: flwr.server.strategy.fedavg.FedAvg.aggregate_evaluate:1::1 of msgid "" -":py:obj:`aggregate_evaluate " -"`\\ \\(server\\_round\\," -" results\\, ...\\)" +":py:obj:`aggregate_evaluate `\\ \\(server\\_round\\, results\\, ...\\)" msgstr "" #: flwr.server.strategy.fedavg.FedAvg.aggregate_evaluate:1::1 of @@ -13321,9 +14079,8 @@ msgstr "" #: flwr.server.strategy.fedavg.FedAvg.aggregate_evaluate:1::1 of msgid "" -":py:obj:`configure_evaluate " -"`\\ \\(server\\_round\\," -" parameters\\, ...\\)" +":py:obj:`configure_evaluate `\\ \\(server\\_round\\, parameters\\, ...\\)" msgstr "" #: flwr.server.strategy.fedavg.FedAvg.aggregate_evaluate:1::1 of @@ -13340,22 +14097,19 @@ msgstr "" #: flwr.server.strategy.fedavg.FedAvg.aggregate_evaluate:1::1 of msgid "" -":py:obj:`initialize_parameters " -"`\\ " -"\\(client\\_manager\\)" +":py:obj:`initialize_parameters `\\ \\(client\\_manager\\)" msgstr "" #: flwr.server.strategy.fedavg.FedAvg.aggregate_evaluate:1::1 of msgid "" -":py:obj:`num_evaluation_clients " -"`\\ " -"\\(num\\_available\\_clients\\)" +":py:obj:`num_evaluation_clients `\\ \\(num\\_available\\_clients\\)" msgstr "" #: flwr.server.strategy.fedavg.FedAvg.aggregate_evaluate:1::1 of msgid "" -":py:obj:`num_fit_clients " -"`\\ " +":py:obj:`num_fit_clients `\\ " "\\(num\\_available\\_clients\\)" msgstr "" @@ -13365,9 +14119,8 @@ msgstr "" #: flwr.server.strategy.fedavg.FedAvg.aggregate_evaluate:1::1 of msgid "" -":py:obj:`aggregate_evaluate " -"`\\ " -"\\(server\\_round\\, results\\, ...\\)" +":py:obj:`aggregate_evaluate `\\ \\(server\\_round\\, results\\, ...\\)" msgstr "" #: flwr.server.strategy.fedavg.FedAvg.aggregate_evaluate:1::1 of @@ -13383,9 +14136,8 @@ msgstr "" #: flwr.server.strategy.fedavg.FedAvg.aggregate_evaluate:1::1 of msgid "" -":py:obj:`configure_evaluate " -"`\\ " -"\\(server\\_round\\, parameters\\, ...\\)" +":py:obj:`configure_evaluate `\\ \\(server\\_round\\, parameters\\, ...\\)" msgstr "" #: flwr.server.strategy.fedavg.FedAvg.aggregate_evaluate:1::1 of @@ -13402,22 +14154,19 @@ msgstr "" #: flwr.server.strategy.fedavg.FedAvg.aggregate_evaluate:1::1 of msgid "" -":py:obj:`initialize_parameters " -"`\\ " -"\\(client\\_manager\\)" +":py:obj:`initialize_parameters `\\ \\(client\\_manager\\)" msgstr "" #: flwr.server.strategy.fedavg.FedAvg.aggregate_evaluate:1::1 of msgid "" -":py:obj:`num_evaluation_clients " -"`\\ " -"\\(num\\_available\\_clients\\)" +":py:obj:`num_evaluation_clients `\\ \\(num\\_available\\_clients\\)" msgstr "" #: flwr.server.strategy.fedavg.FedAvg.aggregate_evaluate:1::1 of msgid "" -":py:obj:`num_fit_clients " -"`\\ " +":py:obj:`num_fit_clients `\\ " "\\(num\\_available\\_clients\\)" msgstr "" @@ -13435,9 +14184,8 @@ msgstr "" #: flwr.server.strategy.fedavg.FedAvg.aggregate_evaluate:1::1 of msgid "" -":py:obj:`aggregate_evaluate " -"`\\ \\(server\\_round\\, " -"results\\, ...\\)" +":py:obj:`aggregate_evaluate `\\ \\(server\\_round\\, results\\, ...\\)" msgstr "" #: flwr.server.strategy.fedavg.FedAvg.aggregate_evaluate:1::1 of @@ -13448,9 +14196,8 @@ msgstr "" #: flwr.server.strategy.fedavg.FedAvg.aggregate_evaluate:1::1 of msgid "" -":py:obj:`configure_evaluate " -"`\\ \\(server\\_round\\, " -"parameters\\, ...\\)" +":py:obj:`configure_evaluate `\\ \\(server\\_round\\, parameters\\, ...\\)" msgstr "" #: flwr.server.strategy.fedavg.FedAvg.aggregate_evaluate:1::1 of @@ -13467,22 +14214,20 @@ msgstr "" #: flwr.server.strategy.fedavg.FedAvg.aggregate_evaluate:1::1 of msgid "" -":py:obj:`initialize_parameters " -"`\\ " -"\\(client\\_manager\\)" +":py:obj:`initialize_parameters `\\ \\(client\\_manager\\)" msgstr "" #: flwr.server.strategy.fedavg.FedAvg.aggregate_evaluate:1::1 of msgid "" -":py:obj:`num_evaluation_clients " -"`\\ " -"\\(num\\_available\\_clients\\)" +":py:obj:`num_evaluation_clients `\\ \\(num\\_available\\_clients\\)" msgstr "" #: flwr.server.strategy.fedavg.FedAvg.aggregate_evaluate:1::1 of msgid "" -":py:obj:`num_fit_clients `\\" -" \\(num\\_available\\_clients\\)" +":py:obj:`num_fit_clients `\\ " +"\\(num\\_available\\_clients\\)" msgstr "" #: ../../source/ref-api/flwr.server.strategy.FedProx.rst:2 @@ -13495,9 +14240,9 @@ msgstr "" #: flwr.server.strategy.fedprox.FedProx:5 of msgid "" -"The strategy in itself will not be different than FedAvg, the client " -"needs to be adjusted. A proximal term needs to be added to the loss " -"function during the training:" +"The strategy in itself will not be different than FedAvg, the client needs " +"to be adjusted. A proximal term needs to be added to the loss function " +"during the training:" msgstr "" #: flwr.server.strategy.fedprox.FedProx:9 of @@ -13530,15 +14275,14 @@ msgstr "" msgid "" "The weight of the proximal term used in the optimization. 0.0 makes this " "strategy equivalent to FedAvg, and the higher the coefficient, the more " -"regularization will be used (that is, the client parameters will need to " -"be closer to the server parameters during training)." +"regularization will be used (that is, the client parameters will need to be " +"closer to the server parameters during training)." msgstr "" #: flwr.server.strategy.fedavg.FedAvg.aggregate_evaluate:1::1 of msgid "" -":py:obj:`aggregate_evaluate " -"`\\ \\(server\\_round\\," -" results\\, ...\\)" +":py:obj:`aggregate_evaluate `\\ \\(server\\_round\\, results\\, ...\\)" msgstr "" #: flwr.server.strategy.fedavg.FedAvg.aggregate_evaluate:1::1 of @@ -13549,9 +14293,8 @@ msgstr "" #: flwr.server.strategy.fedavg.FedAvg.aggregate_evaluate:1::1 of msgid "" -":py:obj:`configure_evaluate " -"`\\ \\(server\\_round\\," -" parameters\\, ...\\)" +":py:obj:`configure_evaluate `\\ \\(server\\_round\\, parameters\\, ...\\)" msgstr "" #: flwr.server.strategy.fedavg.FedAvg.aggregate_evaluate:1::1 of @@ -13568,22 +14311,19 @@ msgstr "" #: flwr.server.strategy.fedavg.FedAvg.aggregate_evaluate:1::1 of msgid "" -":py:obj:`initialize_parameters " -"`\\ " -"\\(client\\_manager\\)" +":py:obj:`initialize_parameters `\\ \\(client\\_manager\\)" msgstr "" #: flwr.server.strategy.fedavg.FedAvg.aggregate_evaluate:1::1 of msgid "" -":py:obj:`num_evaluation_clients " -"`\\ " -"\\(num\\_available\\_clients\\)" +":py:obj:`num_evaluation_clients `\\ \\(num\\_available\\_clients\\)" msgstr "" #: flwr.server.strategy.fedavg.FedAvg.aggregate_evaluate:1::1 of msgid "" -":py:obj:`num_fit_clients " -"`\\ " +":py:obj:`num_fit_clients `\\ " "\\(num\\_available\\_clients\\)" msgstr "" @@ -13605,15 +14345,13 @@ msgstr "" #: flwr.server.strategy.fedavg.FedAvg.aggregate_evaluate:1::1 of msgid "" -":py:obj:`aggregate_evaluate " -"`\\ " -"\\(server\\_round\\, results\\, ...\\)" +":py:obj:`aggregate_evaluate `\\ \\(server\\_round\\, results\\, ...\\)" msgstr "" #: flwr.server.strategy.fedavg.FedAvg.aggregate_evaluate:1::1 of msgid "" -":py:obj:`aggregate_fit " -"`\\ " +":py:obj:`aggregate_fit `\\ " "\\(server\\_round\\, results\\, failures\\)" msgstr "" @@ -13624,15 +14362,13 @@ msgstr "" #: flwr.server.strategy.fedavg.FedAvg.aggregate_evaluate:1::1 of msgid "" -":py:obj:`configure_evaluate " -"`\\ " -"\\(server\\_round\\, parameters\\, ...\\)" +":py:obj:`configure_evaluate `\\ \\(server\\_round\\, parameters\\, ...\\)" msgstr "" #: flwr.server.strategy.fedavg.FedAvg.aggregate_evaluate:1::1 of msgid "" -":py:obj:`configure_fit " -"`\\ " +":py:obj:`configure_fit `\\ " "\\(server\\_round\\, parameters\\, ...\\)" msgstr "" @@ -13644,23 +14380,20 @@ msgstr "" #: flwr.server.strategy.fedavg.FedAvg.aggregate_evaluate:1::1 of msgid "" -":py:obj:`initialize_parameters " -"`\\ " -"\\(client\\_manager\\)" +":py:obj:`initialize_parameters `\\ \\(client\\_manager\\)" msgstr "" #: flwr.server.strategy.fedavg.FedAvg.aggregate_evaluate:1::1 of msgid "" -":py:obj:`num_evaluation_clients " -"`\\ " -"\\(num\\_available\\_clients\\)" +":py:obj:`num_evaluation_clients `\\ \\(num\\_available\\_clients\\)" msgstr "" #: flwr.server.strategy.fedavg.FedAvg.aggregate_evaluate:1::1 of msgid "" -":py:obj:`num_fit_clients " -"`\\ " -"\\(num\\_available\\_clients\\)" +":py:obj:`num_fit_clients `\\ \\(num\\_available\\_clients\\)" msgstr "" #: ../../source/ref-api/flwr.server.strategy.FedXgbBagging.rst:2 @@ -13670,9 +14403,8 @@ msgstr "" #: flwr.server.strategy.fedxgb_bagging.FedXgbBagging.aggregate_evaluate:1::1 #: of msgid "" -":py:obj:`aggregate_evaluate " -"`\\ " -"\\(server\\_round\\, results\\, ...\\)" +":py:obj:`aggregate_evaluate `\\ \\(server\\_round\\, results\\, ...\\)" msgstr "" #: flwr.server.strategy.fedxgb_bagging.FedXgbBagging.aggregate_evaluate:1 @@ -13686,8 +14418,7 @@ msgstr "" #: flwr.server.strategy.fedxgb_bagging.FedXgbBagging.aggregate_evaluate:1::1 #: of msgid "" -":py:obj:`aggregate_fit " -"`\\ " +":py:obj:`aggregate_fit `\\ " "\\(server\\_round\\, results\\, failures\\)" msgstr "" @@ -13701,16 +14432,14 @@ msgstr "" #: flwr.server.strategy.fedxgb_bagging.FedXgbBagging.aggregate_evaluate:1::1 #: of msgid "" -":py:obj:`configure_evaluate " -"`\\ " -"\\(server\\_round\\, parameters\\, ...\\)" +":py:obj:`configure_evaluate `\\ \\(server\\_round\\, parameters\\, ...\\)" msgstr "" #: flwr.server.strategy.fedxgb_bagging.FedXgbBagging.aggregate_evaluate:1::1 #: of msgid "" -":py:obj:`configure_fit " -"`\\ " +":py:obj:`configure_fit `\\ " "\\(server\\_round\\, parameters\\, ...\\)" msgstr "" @@ -13724,25 +14453,22 @@ msgstr "" #: flwr.server.strategy.fedxgb_bagging.FedXgbBagging.aggregate_evaluate:1::1 #: of msgid "" -":py:obj:`initialize_parameters " -"`\\ " -"\\(client\\_manager\\)" +":py:obj:`initialize_parameters `\\ \\(client\\_manager\\)" msgstr "" #: flwr.server.strategy.fedxgb_bagging.FedXgbBagging.aggregate_evaluate:1::1 #: of msgid "" -":py:obj:`num_evaluation_clients " -"`\\ " -"\\(num\\_available\\_clients\\)" +":py:obj:`num_evaluation_clients `\\ \\(num\\_available\\_clients\\)" msgstr "" #: flwr.server.strategy.fedxgb_bagging.FedXgbBagging.aggregate_evaluate:1::1 #: of msgid "" -":py:obj:`num_fit_clients " -"`\\ " -"\\(num\\_available\\_clients\\)" +":py:obj:`num_fit_clients `\\ \\(num\\_available\\_clients\\)" msgstr "" #: ../../source/ref-api/flwr.server.strategy.FedXgbCyclic.rst:2 @@ -13752,33 +14478,29 @@ msgstr "" #: flwr.server.strategy.fedxgb_cyclic.FedXgbCyclic.aggregate_evaluate:1::1 #: of msgid "" -":py:obj:`aggregate_evaluate " -"`\\ " -"\\(server\\_round\\, results\\, ...\\)" +":py:obj:`aggregate_evaluate `\\ \\(server\\_round\\, results\\, ...\\)" msgstr "" #: flwr.server.strategy.fedxgb_cyclic.FedXgbCyclic.aggregate_evaluate:1::1 #: of msgid "" -":py:obj:`aggregate_fit " -"`\\ \\(server\\_round\\," -" results\\, failures\\)" +":py:obj:`aggregate_fit `\\ " +"\\(server\\_round\\, results\\, failures\\)" msgstr "" #: flwr.server.strategy.fedxgb_cyclic.FedXgbCyclic.aggregate_evaluate:1::1 #: of msgid "" -":py:obj:`configure_evaluate " -"`\\ " -"\\(server\\_round\\, parameters\\, ...\\)" +":py:obj:`configure_evaluate `\\ \\(server\\_round\\, parameters\\, ...\\)" msgstr "" #: flwr.server.strategy.fedxgb_cyclic.FedXgbCyclic.aggregate_evaluate:1::1 #: of msgid "" -":py:obj:`configure_fit " -"`\\ \\(server\\_round\\," -" parameters\\, ...\\)" +":py:obj:`configure_fit `\\ " +"\\(server\\_round\\, parameters\\, ...\\)" msgstr "" #: flwr.server.strategy.fedxgb_cyclic.FedXgbCyclic.aggregate_evaluate:1::1 @@ -13791,25 +14513,22 @@ msgstr "" #: flwr.server.strategy.fedxgb_cyclic.FedXgbCyclic.aggregate_evaluate:1::1 #: of msgid "" -":py:obj:`initialize_parameters " -"`\\ " -"\\(client\\_manager\\)" +":py:obj:`initialize_parameters `\\ \\(client\\_manager\\)" msgstr "" #: flwr.server.strategy.fedxgb_cyclic.FedXgbCyclic.aggregate_evaluate:1::1 #: of msgid "" -":py:obj:`num_evaluation_clients " -"`\\ " -"\\(num\\_available\\_clients\\)" +":py:obj:`num_evaluation_clients `\\ \\(num\\_available\\_clients\\)" msgstr "" #: flwr.server.strategy.fedxgb_cyclic.FedXgbCyclic.aggregate_evaluate:1::1 #: of msgid "" -":py:obj:`num_fit_clients " -"`\\ " -"\\(num\\_available\\_clients\\)" +":py:obj:`num_fit_clients `\\ \\(num\\_available\\_clients\\)" msgstr "" #: ../../source/ref-api/flwr.server.strategy.FedXgbNnAvg.rst:2 @@ -13819,36 +14538,31 @@ msgstr "" #: flwr.server.strategy.fedxgb_nn_avg.FedXgbNnAvg:5 of msgid "" "This strategy is deprecated, but a copy of it is available in Flower " -"Baselines: " -"https://github.com/adap/flower/tree/main/baselines/hfedxgboost." +"Baselines: https://github.com/adap/flower/tree/main/baselines/hfedxgboost." msgstr "" #: flwr.server.strategy.fedavg.FedAvg.aggregate_evaluate:1::1 of msgid "" -":py:obj:`aggregate_evaluate " -"`\\ " -"\\(server\\_round\\, results\\, ...\\)" +":py:obj:`aggregate_evaluate `\\ \\(server\\_round\\, results\\, ...\\)" msgstr "" #: flwr.server.strategy.fedavg.FedAvg.aggregate_evaluate:1::1 of msgid "" -":py:obj:`aggregate_fit " -"`\\ \\(server\\_round\\, " -"results\\, failures\\)" +":py:obj:`aggregate_fit `\\ " +"\\(server\\_round\\, results\\, failures\\)" msgstr "" #: flwr.server.strategy.fedavg.FedAvg.aggregate_evaluate:1::1 of msgid "" -":py:obj:`configure_evaluate " -"`\\ " -"\\(server\\_round\\, parameters\\, ...\\)" +":py:obj:`configure_evaluate `\\ \\(server\\_round\\, parameters\\, ...\\)" msgstr "" #: flwr.server.strategy.fedavg.FedAvg.aggregate_evaluate:1::1 of msgid "" -":py:obj:`configure_fit " -"`\\ \\(server\\_round\\, " -"parameters\\, ...\\)" +":py:obj:`configure_fit `\\ " +"\\(server\\_round\\, parameters\\, ...\\)" msgstr "" #: flwr.server.strategy.fedavg.FedAvg.aggregate_evaluate:1::1 of @@ -13859,23 +14573,20 @@ msgstr "" #: flwr.server.strategy.fedavg.FedAvg.aggregate_evaluate:1::1 of msgid "" -":py:obj:`initialize_parameters " -"`\\ " -"\\(client\\_manager\\)" +":py:obj:`initialize_parameters `\\ \\(client\\_manager\\)" msgstr "" #: flwr.server.strategy.fedavg.FedAvg.aggregate_evaluate:1::1 of msgid "" -":py:obj:`num_evaluation_clients " -"`\\ " -"\\(num\\_available\\_clients\\)" +":py:obj:`num_evaluation_clients `\\ \\(num\\_available\\_clients\\)" msgstr "" #: flwr.server.strategy.fedavg.FedAvg.aggregate_evaluate:1::1 of msgid "" -":py:obj:`num_fit_clients " -"`\\ " -"\\(num\\_available\\_clients\\)" +":py:obj:`num_fit_clients `\\ \\(num\\_available\\_clients\\)" msgstr "" #: ../../source/ref-api/flwr.server.strategy.FedYogi.rst:2 @@ -13896,9 +14607,8 @@ msgstr "" #: flwr.server.strategy.fedavg.FedAvg.aggregate_evaluate:1::1 of msgid "" -":py:obj:`aggregate_evaluate " -"`\\ \\(server\\_round\\," -" results\\, ...\\)" +":py:obj:`aggregate_evaluate `\\ \\(server\\_round\\, results\\, ...\\)" msgstr "" #: flwr.server.strategy.fedavg.FedAvg.aggregate_evaluate:1::1 of @@ -13909,9 +14619,8 @@ msgstr "" #: flwr.server.strategy.fedavg.FedAvg.aggregate_evaluate:1::1 of msgid "" -":py:obj:`configure_evaluate " -"`\\ \\(server\\_round\\," -" parameters\\, ...\\)" +":py:obj:`configure_evaluate `\\ \\(server\\_round\\, parameters\\, ...\\)" msgstr "" #: flwr.server.strategy.fedavg.FedAvg.aggregate_evaluate:1::1 of @@ -13928,22 +14637,19 @@ msgstr "" #: flwr.server.strategy.fedavg.FedAvg.aggregate_evaluate:1::1 of msgid "" -":py:obj:`initialize_parameters " -"`\\ " -"\\(client\\_manager\\)" +":py:obj:`initialize_parameters `\\ \\(client\\_manager\\)" msgstr "" #: flwr.server.strategy.fedavg.FedAvg.aggregate_evaluate:1::1 of msgid "" -":py:obj:`num_evaluation_clients " -"`\\ " -"\\(num\\_available\\_clients\\)" +":py:obj:`num_evaluation_clients `\\ \\(num\\_available\\_clients\\)" msgstr "" #: flwr.server.strategy.fedavg.FedAvg.aggregate_evaluate:1::1 of msgid "" -":py:obj:`num_fit_clients " -"`\\ " +":py:obj:`num_fit_clients `\\ " "\\(num\\_available\\_clients\\)" msgstr "" @@ -13957,15 +14663,14 @@ msgstr "" #: flwr.server.strategy.krum.Krum:17 of msgid "" -"Number of clients to keep before averaging (MultiKrum). Defaults to 0, in" -" that case classical Krum is applied." +"Number of clients to keep before averaging (MultiKrum). Defaults to 0, in " +"that case classical Krum is applied." msgstr "" #: flwr.server.strategy.fedavg.FedAvg.aggregate_evaluate:1::1 of msgid "" -":py:obj:`aggregate_evaluate " -"`\\ \\(server\\_round\\, " -"results\\, ...\\)" +":py:obj:`aggregate_evaluate `\\ \\(server\\_round\\, results\\, ...\\)" msgstr "" #: flwr.server.strategy.fedavg.FedAvg.aggregate_evaluate:1::1 of @@ -13981,9 +14686,8 @@ msgstr "" #: flwr.server.strategy.fedavg.FedAvg.aggregate_evaluate:1::1 of msgid "" -":py:obj:`configure_evaluate " -"`\\ \\(server\\_round\\, " -"parameters\\, ...\\)" +":py:obj:`configure_evaluate `\\ \\(server\\_round\\, parameters\\, ...\\)" msgstr "" #: flwr.server.strategy.fedavg.FedAvg.aggregate_evaluate:1::1 of @@ -14000,16 +14704,14 @@ msgstr "" #: flwr.server.strategy.fedavg.FedAvg.aggregate_evaluate:1::1 of msgid "" -":py:obj:`initialize_parameters " -"`\\ " -"\\(client\\_manager\\)" +":py:obj:`initialize_parameters `\\ \\(client\\_manager\\)" msgstr "" #: flwr.server.strategy.fedavg.FedAvg.aggregate_evaluate:1::1 of msgid "" -":py:obj:`num_evaluation_clients " -"`\\ " -"\\(num\\_available\\_clients\\)" +":py:obj:`num_evaluation_clients `\\ \\(num\\_available\\_clients\\)" msgstr "" #: flwr.server.strategy.fedavg.FedAvg.aggregate_evaluate:1::1 of @@ -14024,9 +14726,8 @@ msgstr "" #: flwr.server.strategy.qfedavg.QFedAvg.aggregate_evaluate:1::1 of msgid "" -":py:obj:`aggregate_evaluate " -"`\\ \\(server\\_round\\," -" results\\, ...\\)" +":py:obj:`aggregate_evaluate `\\ \\(server\\_round\\, results\\, ...\\)" msgstr "" #: flwr.server.strategy.qfedavg.QFedAvg.aggregate_evaluate:1::1 of @@ -14037,9 +14738,8 @@ msgstr "" #: flwr.server.strategy.qfedavg.QFedAvg.aggregate_evaluate:1::1 of msgid "" -":py:obj:`configure_evaluate " -"`\\ \\(server\\_round\\," -" parameters\\, ...\\)" +":py:obj:`configure_evaluate `\\ \\(server\\_round\\, parameters\\, ...\\)" msgstr "" #: flwr.server.strategy.qfedavg.QFedAvg.aggregate_evaluate:1::1 of @@ -14056,22 +14756,19 @@ msgstr "" #: flwr.server.strategy.qfedavg.QFedAvg.aggregate_evaluate:1::1 of msgid "" -":py:obj:`initialize_parameters " -"`\\ " -"\\(client\\_manager\\)" +":py:obj:`initialize_parameters `\\ \\(client\\_manager\\)" msgstr "" #: flwr.server.strategy.qfedavg.QFedAvg.aggregate_evaluate:1::1 of msgid "" -":py:obj:`num_evaluation_clients " -"`\\ " -"\\(num\\_available\\_clients\\)" +":py:obj:`num_evaluation_clients `\\ \\(num\\_available\\_clients\\)" msgstr "" #: flwr.server.strategy.qfedavg.QFedAvg.aggregate_evaluate:1::1 of msgid "" -":py:obj:`num_fit_clients " -"`\\ " +":py:obj:`num_fit_clients `\\ " "\\(num\\_available\\_clients\\)" msgstr "" @@ -14082,9 +14779,8 @@ msgstr "" #: flwr.server.strategy.strategy.Strategy.aggregate_evaluate:1::1 #: of msgid "" -":py:obj:`aggregate_evaluate " -"`\\ " -"\\(server\\_round\\, results\\, ...\\)" +":py:obj:`aggregate_evaluate `\\ \\(server\\_round\\, results\\, ...\\)" msgstr "" #: flwr.server.strategy.strategy.Strategy.aggregate_evaluate:1 @@ -14108,9 +14804,8 @@ msgstr "" #: flwr.server.strategy.strategy.Strategy.aggregate_evaluate:1::1 #: of msgid "" -":py:obj:`configure_evaluate " -"`\\ " -"\\(server\\_round\\, parameters\\, ...\\)" +":py:obj:`configure_evaluate `\\ \\(server\\_round\\, parameters\\, ...\\)" msgstr "" #: flwr.server.strategy.strategy.Strategy.aggregate_evaluate:1::1 @@ -14135,9 +14830,8 @@ msgstr "" #: flwr.server.strategy.strategy.Strategy.aggregate_evaluate:1::1 #: of msgid "" -":py:obj:`initialize_parameters " -"`\\ " -"\\(client\\_manager\\)" +":py:obj:`initialize_parameters `\\ \\(client\\_manager\\)" msgstr "" #: flwr.server.strategy.strategy.Strategy.aggregate_evaluate:1::1 @@ -14147,17 +14841,18 @@ msgstr "" #: flwr.server.strategy.strategy.Strategy.aggregate_evaluate:5 of msgid "" -"Successful updates from the previously selected and configured clients. " -"Each pair of `(ClientProxy, FitRes` constitutes a successful update from " -"one of the previously selected clients. Not that not all previously " -"selected clients are necessarily included in this list: a client might " -"drop out and not submit a result. For each client that did not submit an " -"update, there should be an `Exception` in `failures`." +"Successful updates from the previously selected and configured clients. Each " +"pair of `(ClientProxy, FitRes` constitutes a successful update from one of " +"the previously selected clients. Not that not all previously selected " +"clients are necessarily included in this list: a client might drop out and " +"not submit a result. For each client that did not submit an update, there " +"should be an `Exception` in `failures`." msgstr "" #: flwr.server.strategy.strategy.Strategy.aggregate_evaluate:13 #: flwr.server.strategy.strategy.Strategy.aggregate_fit:13 of -msgid "Exceptions that occurred while the server was waiting for client updates." +msgid "" +"Exceptions that occurred while the server was waiting for client updates." msgstr "" #: flwr.server.strategy.strategy.Strategy.aggregate_evaluate:16 of @@ -14168,23 +14863,22 @@ msgstr "" #: flwr.server.strategy.strategy.Strategy.aggregate_fit:5 of msgid "" -"Successful updates from the previously selected and configured clients. " -"Each pair of `(ClientProxy, FitRes)` constitutes a successful update from" -" one of the previously selected clients. Not that not all previously " -"selected clients are necessarily included in this list: a client might " -"drop out and not submit a result. For each client that did not submit an " -"update, there should be an `Exception` in `failures`." +"Successful updates from the previously selected and configured clients. Each " +"pair of `(ClientProxy, FitRes)` constitutes a successful update from one of " +"the previously selected clients. Not that not all previously selected " +"clients are necessarily included in this list: a client might drop out and " +"not submit a result. For each client that did not submit an update, there " +"should be an `Exception` in `failures`." msgstr "" #: flwr.server.strategy.strategy.Strategy.aggregate_fit:17 of msgid "" "**parameters** -- If parameters are returned, then the server will treat " -"these as the new global model parameters (i.e., it will replace the " -"previous parameters with the ones returned from this method). If `None` " -"is returned (e.g., because there were only failures and no viable " -"results) then the server will no update the previous model parameters, " -"the updates received in this round are discarded, and the global model " -"parameters remain the same." +"these as the new global model parameters (i.e., it will replace the previous " +"parameters with the ones returned from this method). If `None` is returned " +"(e.g., because there were only failures and no viable results) then the " +"server will no update the previous model parameters, the updates received in " +"this round are discarded, and the global model parameters remain the same." msgstr "" #: flwr.server.strategy.strategy.Strategy.evaluate:3 of @@ -14195,9 +14889,8 @@ msgstr "" #: flwr.server.strategy.strategy.Strategy.evaluate:11 of msgid "" -"**evaluation_result** -- The evaluation result, usually a Tuple " -"containing loss and a dictionary containing task-specific metrics (e.g., " -"accuracy)." +"**evaluation_result** -- The evaluation result, usually a Tuple containing " +"loss and a dictionary containing task-specific metrics (e.g., accuracy)." msgstr "" #: flwr.server.strategy.strategy.Strategy.initialize_parameters:6 of @@ -14255,17 +14948,17 @@ msgstr "" #: flwr.server.workflow.secure_aggregation.secaggplus_workflow.SecAggPlusWorkflow:3 #: of msgid "" -"The SecAgg+ protocol ensures the secure summation of integer vectors " -"owned by multiple parties, without accessing any individual integer " -"vector. This workflow allows the server to compute the weighted average " -"of model parameters across all clients, ensuring individual contributions" -" remain private. This is achieved by clients sending both, a weighting " -"factor and a weighted version of the locally updated parameters, both of " -"which are masked for privacy. Specifically, each client uploads \"[w, w *" -" params]\" with masks, where weighting factor 'w' is the number of " -"examples ('num_examples') and 'params' represents the model parameters " -"('parameters') from the client's `FitRes`. The server then aggregates " -"these contributions to compute the weighted average of model parameters." +"The SecAgg+ protocol ensures the secure summation of integer vectors owned " +"by multiple parties, without accessing any individual integer vector. This " +"workflow allows the server to compute the weighted average of model " +"parameters across all clients, ensuring individual contributions remain " +"private. This is achieved by clients sending both, a weighting factor and a " +"weighted version of the locally updated parameters, both of which are masked " +"for privacy. Specifically, each client uploads \"[w, w * params]\" with " +"masks, where weighting factor 'w' is the number of examples ('num_examples') " +"and 'params' represents the model parameters ('parameters') from the " +"client's `FitRes`. The server then aggregates these contributions to compute " +"the weighted average of model parameters." msgstr "" #: flwr.server.workflow.secure_aggregation.secaggplus_workflow.SecAggPlusWorkflow:14 @@ -14302,39 +14995,39 @@ msgstr "" #: flwr.server.workflow.secure_aggregation.secaggplus_workflow.SecAggPlusWorkflow:22 #: of msgid "" -"Only the aggregated model parameters are exposed and passed to " -"`Strategy.aggregate_fit`, ensuring individual data privacy." +"Only the aggregated model parameters are exposed and passed to `Strategy." +"aggregate_fit`, ensuring individual data privacy." msgstr "" #: flwr.server.workflow.secure_aggregation.secaggplus_workflow.SecAggPlusWorkflow:25 #: of msgid "" -"The number of shares into which each client's private key is split under " -"the SecAgg+ protocol. If specified as a float, it represents the " -"proportion of all selected clients, and the number of shares will be set " -"dynamically in the run time. A private key can be reconstructed from " -"these shares, allowing for the secure aggregation of model updates. Each " -"client sends one share to each of its neighbors while retaining one." +"The number of shares into which each client's private key is split under the " +"SecAgg+ protocol. If specified as a float, it represents the proportion of " +"all selected clients, and the number of shares will be set dynamically in " +"the run time. A private key can be reconstructed from these shares, allowing " +"for the secure aggregation of model updates. Each client sends one share to " +"each of its neighbors while retaining one." msgstr "" #: flwr.server.workflow.secure_aggregation.secagg_workflow.SecAggWorkflow:25 #: flwr.server.workflow.secure_aggregation.secaggplus_workflow.SecAggPlusWorkflow:32 #: of msgid "" -"The minimum number of shares required to reconstruct a client's private " -"key, or, if specified as a float, it represents the proportion of the " -"total number of shares needed for reconstruction. This threshold ensures " -"privacy by allowing for the recovery of contributions from dropped " -"clients during aggregation, without compromising individual client data." +"The minimum number of shares required to reconstruct a client's private key, " +"or, if specified as a float, it represents the proportion of the total " +"number of shares needed for reconstruction. This threshold ensures privacy " +"by allowing for the recovery of contributions from dropped clients during " +"aggregation, without compromising individual client data." msgstr "" #: flwr.server.workflow.secure_aggregation.secagg_workflow.SecAggWorkflow:31 #: flwr.server.workflow.secure_aggregation.secaggplus_workflow.SecAggPlusWorkflow:38 #: of msgid "" -"The maximum value of the weight that can be assigned to any single " -"client's update during the weighted average calculation on the server " -"side, e.g., in the FedAvg algorithm." +"The maximum value of the weight that can be assigned to any single client's " +"update during the weighted average calculation on the server side, e.g., in " +"the FedAvg algorithm." msgstr "" #: flwr.server.workflow.secure_aggregation.secagg_workflow.SecAggWorkflow:35 @@ -14342,8 +15035,8 @@ msgstr "" #: of msgid "" "The range within which model parameters are clipped before quantization. " -"This parameter ensures each model parameter is bounded within " -"[-clipping_range, clipping_range], facilitating quantization." +"This parameter ensures each model parameter is bounded within [-" +"clipping_range, clipping_range], facilitating quantization." msgstr "" #: flwr.server.workflow.secure_aggregation.secagg_workflow.SecAggWorkflow:39 @@ -14361,31 +15054,32 @@ msgstr "" #: of msgid "" "The range of values from which random mask entries are uniformly sampled " -"([0, modulus_range-1]). `modulus_range` must be less than 4294967296. " -"Please use 2**n values for `modulus_range` to prevent overflow issues." +"([0, modulus_range-1]). `modulus_range` must be less than 4294967296. Please " +"use 2**n values for `modulus_range` to prevent overflow issues." msgstr "" #: flwr.server.workflow.secure_aggregation.secagg_workflow.SecAggWorkflow:47 #: flwr.server.workflow.secure_aggregation.secaggplus_workflow.SecAggPlusWorkflow:54 #: of msgid "" -"The timeout duration in seconds. If specified, the workflow will wait for" -" replies for this duration each time. If `None`, there is no time limit " -"and the workflow will wait until replies for all messages are received." +"The timeout duration in seconds. If specified, the workflow will wait for " +"replies for this duration each time. If `None`, there is no time limit and " +"the workflow will wait until replies for all messages are received." msgstr "" #: flwr.server.workflow.secure_aggregation.secaggplus_workflow.SecAggPlusWorkflow:61 #: of msgid "" "Generally, higher `num_shares` means more robust to dropouts while " -"increasing the computational costs; higher `reconstruction_threshold` " -"means better privacy guarantees but less tolerance to dropouts." +"increasing the computational costs; higher `reconstruction_threshold` means " +"better privacy guarantees but less tolerance to dropouts." msgstr "" #: flwr.server.workflow.secure_aggregation.secagg_workflow.SecAggWorkflow:58 #: flwr.server.workflow.secure_aggregation.secaggplus_workflow.SecAggPlusWorkflow:64 #: of -msgid "Too large `max_weight` may compromise the precision of the quantization." +msgid "" +"Too large `max_weight` may compromise the precision of the quantization." msgstr "" #: flwr.server.workflow.secure_aggregation.secagg_workflow.SecAggWorkflow:59 @@ -14398,35 +15092,34 @@ msgstr "" #: of msgid "" "When `num_shares` is a float, it is interpreted as the proportion of all " -"selected clients, and hence the number of shares will be determined in " -"the runtime. This allows for dynamic adjustment based on the total number" -" of participating clients." +"selected clients, and hence the number of shares will be determined in the " +"runtime. This allows for dynamic adjustment based on the total number of " +"participating clients." msgstr "" #: flwr.server.workflow.secure_aggregation.secaggplus_workflow.SecAggPlusWorkflow:69 #: of msgid "" -"Similarly, when `reconstruction_threshold` is a float, it is interpreted " -"as the proportion of the number of shares needed for the reconstruction " -"of a private key. This feature enables flexibility in setting the " -"security threshold relative to the number of distributed shares." +"Similarly, when `reconstruction_threshold` is a float, it is interpreted as " +"the proportion of the number of shares needed for the reconstruction of a " +"private key. This feature enables flexibility in setting the security " +"threshold relative to the number of distributed shares." msgstr "" #: flwr.server.workflow.secure_aggregation.secaggplus_workflow.SecAggPlusWorkflow:73 #: of msgid "" -"`num_shares`, `reconstruction_threshold`, and the quantization parameters" -" (`clipping_range`, `quantization_range`, `modulus_range`) play critical " -"roles in balancing privacy, robustness, and efficiency within the SecAgg+" -" protocol." +"`num_shares`, `reconstruction_threshold`, and the quantization parameters " +"(`clipping_range`, `quantization_range`, `modulus_range`) play critical " +"roles in balancing privacy, robustness, and efficiency within the SecAgg+ " +"protocol." msgstr "" #: flwr.server.workflow.secure_aggregation.secaggplus_workflow.SecAggPlusWorkflow.collect_masked_vectors_stage:1::1 #: of msgid "" -":py:obj:`collect_masked_vectors_stage " -"`\\" -" \\(driver\\, ...\\)" +":py:obj:`collect_masked_vectors_stage `\\ \\(driver\\, ...\\)" msgstr "" #: flwr.server.workflow.secure_aggregation.secaggplus_workflow.SecAggPlusWorkflow.collect_masked_vectors_stage:1 @@ -14438,9 +15131,8 @@ msgstr "" #: flwr.server.workflow.secure_aggregation.secaggplus_workflow.SecAggPlusWorkflow.collect_masked_vectors_stage:1::1 #: of msgid "" -":py:obj:`setup_stage " -"`\\ \\(driver\\, " -"context\\, state\\)" +":py:obj:`setup_stage `\\ \\(driver\\, context\\, state\\)" msgstr "" #: flwr.server.workflow.secure_aggregation.secaggplus_workflow.SecAggPlusWorkflow.collect_masked_vectors_stage:1::1 @@ -14452,9 +15144,8 @@ msgstr "" #: flwr.server.workflow.secure_aggregation.secaggplus_workflow.SecAggPlusWorkflow.collect_masked_vectors_stage:1::1 #: of msgid "" -":py:obj:`share_keys_stage " -"`\\ " -"\\(driver\\, context\\, state\\)" +":py:obj:`share_keys_stage `\\ \\(driver\\, context\\, state\\)" msgstr "" #: flwr.server.workflow.secure_aggregation.secaggplus_workflow.SecAggPlusWorkflow.collect_masked_vectors_stage:1::1 @@ -14466,9 +15157,8 @@ msgstr "" #: flwr.server.workflow.secure_aggregation.secaggplus_workflow.SecAggPlusWorkflow.collect_masked_vectors_stage:1::1 #: of msgid "" -":py:obj:`unmask_stage " -"`\\ \\(driver\\, " -"context\\, state\\)" +":py:obj:`unmask_stage `\\ \\(driver\\, context\\, state\\)" msgstr "" #: flwr.server.workflow.secure_aggregation.secaggplus_workflow.SecAggPlusWorkflow.collect_masked_vectors_stage:1::1 @@ -14483,51 +15173,50 @@ msgstr "" #: flwr.server.workflow.secure_aggregation.secagg_workflow.SecAggWorkflow:1 of msgid "" -"Bases: " -":py:class:`~flwr.server.workflow.secure_aggregation.secaggplus_workflow.SecAggPlusWorkflow`" +"Bases: :py:class:`~flwr.server.workflow.secure_aggregation." +"secaggplus_workflow.SecAggPlusWorkflow`" msgstr "" #: flwr.server.workflow.secure_aggregation.secagg_workflow.SecAggWorkflow:3 of msgid "" -"The SecAgg protocol ensures the secure summation of integer vectors owned" -" by multiple parties, without accessing any individual integer vector. " -"This workflow allows the server to compute the weighted average of model " +"The SecAgg protocol ensures the secure summation of integer vectors owned by " +"multiple parties, without accessing any individual integer vector. This " +"workflow allows the server to compute the weighted average of model " "parameters across all clients, ensuring individual contributions remain " -"private. This is achieved by clients sending both, a weighting factor and" -" a weighted version of the locally updated parameters, both of which are " -"masked for privacy. Specifically, each client uploads \"[w, w * params]\"" -" with masks, where weighting factor 'w' is the number of examples " -"('num_examples') and 'params' represents the model parameters " -"('parameters') from the client's `FitRes`. The server then aggregates " -"these contributions to compute the weighted average of model parameters." +"private. This is achieved by clients sending both, a weighting factor and a " +"weighted version of the locally updated parameters, both of which are masked " +"for privacy. Specifically, each client uploads \"[w, w * params]\" with " +"masks, where weighting factor 'w' is the number of examples ('num_examples') " +"and 'params' represents the model parameters ('parameters') from the " +"client's `FitRes`. The server then aggregates these contributions to compute " +"the weighted average of model parameters." msgstr "" #: flwr.server.workflow.secure_aggregation.secagg_workflow.SecAggWorkflow:14 of msgid "" -"The protocol involves four main stages: - 'setup': Send SecAgg " -"configuration to clients and collect their public keys. - 'share keys': " -"Broadcast public keys among clients and collect encrypted secret" +"The protocol involves four main stages: - 'setup': Send SecAgg configuration " +"to clients and collect their public keys. - 'share keys': Broadcast public " +"keys among clients and collect encrypted secret" msgstr "" #: flwr.server.workflow.secure_aggregation.secagg_workflow.SecAggWorkflow:54 of msgid "" -"Each client's private key is split into N shares under the SecAgg " -"protocol, where N is the number of selected clients." +"Each client's private key is split into N shares under the SecAgg protocol, " +"where N is the number of selected clients." msgstr "" #: flwr.server.workflow.secure_aggregation.secagg_workflow.SecAggWorkflow:56 of msgid "" -"Generally, higher `reconstruction_threshold` means better privacy " -"guarantees but less tolerance to dropouts." +"Generally, higher `reconstruction_threshold` means better privacy guarantees " +"but less tolerance to dropouts." msgstr "" #: flwr.server.workflow.secure_aggregation.secagg_workflow.SecAggWorkflow:60 of msgid "" "When `reconstruction_threshold` is a float, it is interpreted as the " "proportion of the number of all selected clients needed for the " -"reconstruction of a private key. This feature enables flexibility in " -"setting the security threshold relative to the number of selected " -"clients." +"reconstruction of a private key. This feature enables flexibility in setting " +"the security threshold relative to the number of selected clients." msgstr "" #: flwr.server.workflow.secure_aggregation.secagg_workflow.SecAggWorkflow:64 of @@ -14541,32 +15230,29 @@ msgstr "" #: flwr.server.workflow.secure_aggregation.secaggplus_workflow.SecAggPlusWorkflow.collect_masked_vectors_stage:1::1 #: of msgid "" -":py:obj:`collect_masked_vectors_stage " -"`\\ " -"\\(driver\\, ...\\)" +":py:obj:`collect_masked_vectors_stage `\\ \\(driver\\, ...\\)" msgstr "" #: flwr.server.workflow.secure_aggregation.secaggplus_workflow.SecAggPlusWorkflow.collect_masked_vectors_stage:1::1 #: of msgid "" -":py:obj:`setup_stage `\\" -" \\(driver\\, context\\, state\\)" +":py:obj:`setup_stage `\\ " +"\\(driver\\, context\\, state\\)" msgstr "" #: flwr.server.workflow.secure_aggregation.secaggplus_workflow.SecAggPlusWorkflow.collect_masked_vectors_stage:1::1 #: of msgid "" -":py:obj:`share_keys_stage " -"`\\ \\(driver\\, " -"context\\, state\\)" +":py:obj:`share_keys_stage `\\ \\(driver\\, context\\, state\\)" msgstr "" #: flwr.server.workflow.secure_aggregation.secaggplus_workflow.SecAggPlusWorkflow.collect_masked_vectors_stage:1::1 #: of msgid "" -":py:obj:`unmask_stage " -"`\\ \\(driver\\, " -"context\\, state\\)" +":py:obj:`unmask_stage `\\ " +"\\(driver\\, context\\, state\\)" msgstr "" #: ../../source/ref-api/flwr.simulation.rst:2 @@ -14575,8 +15261,8 @@ msgstr "" #: ../../source/ref-api/flwr.simulation.rst:18::1 msgid "" -":py:obj:`start_simulation `\\ \\(\\*\\," -" client\\_fn\\[\\, ...\\]\\)" +":py:obj:`start_simulation `\\ \\(\\*\\, " +"client\\_fn\\[\\, ...\\]\\)" msgstr "" #: ../../source/ref-api/flwr.simulation.rst:18::1 @@ -14607,15 +15293,14 @@ msgstr "" #: flwr.simulation.run_simulation.run_simulation:6 of msgid "" -"The `ClientApp` to be executed by each of the SuperNodes. It will receive" -" messages sent by the `ServerApp`." +"The `ClientApp` to be executed by each of the SuperNodes. It will receive " +"messages sent by the `ServerApp`." msgstr "" #: flwr.simulation.run_simulation.run_simulation:9 of msgid "" -"Number of nodes that run a ClientApp. They can be sampled by a Driver in " -"the ServerApp and receive a Message describing what the ClientApp should " -"perform." +"Number of nodes that run a ClientApp. They can be sampled by a Driver in the " +"ServerApp and receive a Message describing what the ClientApp should perform." msgstr "" #: flwr.simulation.run_simulation.run_simulation:13 of @@ -14624,26 +15309,26 @@ msgstr "" #: flwr.simulation.run_simulation.run_simulation:15 of msgid "" -"'A dictionary, e.g {\"\": , \"\": } to " -"configure a backend. Values supported in are those included by " -"`flwr.common.typing.ConfigsRecordValues`." +"'A dictionary, e.g {\"\": , \"\": } to configure a " +"backend. Values supported in are those included by `flwr.common." +"typing.ConfigsRecordValues`." msgstr "" #: flwr.simulation.run_simulation.run_simulation:19 of msgid "" -"A boolean to indicate whether to enable GPU growth on the main thread. " -"This is desirable if you make use of a TensorFlow model on your " -"`ServerApp` while having your `ClientApp` running on the same GPU. " -"Without enabling this, you might encounter an out-of-memory error because" -" TensorFlow, by default, allocates all GPU memory. Read more about how " -"`tf.config.experimental.set_memory_growth()` works in the TensorFlow " -"documentation: https://www.tensorflow.org/api/stable." +"A boolean to indicate whether to enable GPU growth on the main thread. This " +"is desirable if you make use of a TensorFlow model on your `ServerApp` while " +"having your `ClientApp` running on the same GPU. Without enabling this, you " +"might encounter an out-of-memory error because TensorFlow, by default, " +"allocates all GPU memory. Read more about how `tf.config.experimental." +"set_memory_growth()` works in the TensorFlow documentation: https://www." +"tensorflow.org/api/stable." msgstr "" #: flwr.simulation.run_simulation.run_simulation:26 of msgid "" -"When diabled, only INFO, WARNING and ERROR log messages will be shown. If" -" enabled, DEBUG-level logs will be displayed." +"When diabled, only INFO, WARNING and ERROR log messages will be shown. If " +"enabled, DEBUG-level logs will be displayed." msgstr "" #: ../../source/ref-api/flwr.simulation.start_simulation.rst:2 @@ -14652,15 +15337,15 @@ msgstr "" #: flwr.simulation.app.start_simulation:3 of msgid "" -"A function creating client instances. The function must take a single " -"`str` argument called `cid`. It should return a single client instance of" -" type Client. Note that the created client instances are ephemeral and " -"will often be destroyed after a single method invocation. Since client " -"instances are not long-lived, they should not attempt to carry state over" -" method invocations. Any state required by the instance (model, dataset, " +"A function creating client instances. The function must take a single `str` " +"argument called `cid`. It should return a single client instance of type " +"Client. Note that the created client instances are ephemeral and will often " +"be destroyed after a single method invocation. Since client instances are " +"not long-lived, they should not attempt to carry state over method " +"invocations. Any state required by the instance (model, dataset, " "hyperparameters, ...) should be (re-)created in either the call to " -"`client_fn` or the call to any of the client methods (e.g., load " -"evaluation data in the `evaluate` method itself)." +"`client_fn` or the call to any of the client methods (e.g., load evaluation " +"data in the `evaluate` method itself)." msgstr "" #: flwr.simulation.app.start_simulation:13 of @@ -14671,16 +15356,16 @@ msgstr "" #: flwr.simulation.app.start_simulation:16 of msgid "" -"List `client_id`s for each client. This is only required if `num_clients`" -" is not set. Setting both `num_clients` and `clients_ids` with " +"List `client_id`s for each client. This is only required if `num_clients` is " +"not set. Setting both `num_clients` and `clients_ids` with " "`len(clients_ids)` not equal to `num_clients` generates an error." msgstr "" #: flwr.simulation.app.start_simulation:20 of msgid "" -"CPU and GPU resources for a single client. Supported keys are `num_cpus` " -"and `num_gpus`. To understand the GPU utilization caused by `num_gpus`, " -"as well as using custom resources, please consult the Ray documentation." +"CPU and GPU resources for a single client. Supported keys are `num_cpus` and " +"`num_gpus`. To understand the GPU utilization caused by `num_gpus`, as well " +"as using custom resources, please consult the Ray documentation." msgstr "" #: flwr.simulation.app.start_simulation:25 of @@ -14691,16 +15376,16 @@ msgstr "" #: flwr.simulation.app.start_simulation:31 of msgid "" -"An implementation of the abstract base class `flwr.server.Strategy`. If " -"no strategy is provided, then `start_server` will use " -"`flwr.server.strategy.FedAvg`." +"An implementation of the abstract base class `flwr.server.Strategy`. If no " +"strategy is provided, then `start_server` will use `flwr.server.strategy." +"FedAvg`." msgstr "" #: flwr.simulation.app.start_simulation:35 of msgid "" -"An implementation of the abstract base class `flwr.server.ClientManager`." -" If no implementation is provided, then `start_simulation` will use " -"`flwr.server.client_manager.SimpleClientManager`." +"An implementation of the abstract base class `flwr.server.ClientManager`. If " +"no implementation is provided, then `start_simulation` will use `flwr.server." +"client_manager.SimpleClientManager`." msgstr "" #: flwr.simulation.app.start_simulation:39 of @@ -14709,8 +15394,7 @@ msgid "" "ray_init_args is None (the default), Ray will be initialized with the " "following default args: { \"ignore_reinit_error\": True, " "\"include_dashboard\": False } An empty dictionary can be used " -"(ray_init_args={}) to prevent any arguments from being passed to " -"ray.init." +"(ray_init_args={}) to prevent any arguments from being passed to ray.init." msgstr "" #: flwr.simulation.app.start_simulation:39 of @@ -14726,14 +15410,13 @@ msgstr "" #: flwr.simulation.app.start_simulation:45 of msgid "" -"An empty dictionary can be used (ray_init_args={}) to prevent any " -"arguments from being passed to ray.init." +"An empty dictionary can be used (ray_init_args={}) to prevent any arguments " +"from being passed to ray.init." msgstr "" #: flwr.simulation.app.start_simulation:48 of msgid "" -"Set to True to prevent `ray.shutdown()` in case " -"`ray.is_initialized()=True`." +"Set to True to prevent `ray.shutdown()` in case `ray.is_initialized()=True`." msgstr "" #: flwr.simulation.app.start_simulation:50 of @@ -14745,19 +15428,19 @@ msgstr "" #: flwr.simulation.app.start_simulation:54 of msgid "" -"If you want to create your own Actor classes, you might need to pass some" -" input argument. You can use this dictionary for such purpose." +"If you want to create your own Actor classes, you might need to pass some " +"input argument. You can use this dictionary for such purpose." msgstr "" #: flwr.simulation.app.start_simulation:57 of msgid "" -"(default: \"DEFAULT\") Optional string (\"DEFAULT\" or \"SPREAD\") for " -"the VCE to choose in which node the actor is placed. If you are an " -"advanced user needed more control you can use lower-level scheduling " -"strategies to pin actors to specific compute nodes (e.g. via " -"NodeAffinitySchedulingStrategy). Please note this is an advanced feature." -" For all details, please refer to the Ray documentation: " -"https://docs.ray.io/en/latest/ray-core/scheduling/index.html" +"(default: \"DEFAULT\") Optional string (\"DEFAULT\" or \"SPREAD\") for the " +"VCE to choose in which node the actor is placed. If you are an advanced user " +"needed more control you can use lower-level scheduling strategies to pin " +"actors to specific compute nodes (e.g. via NodeAffinitySchedulingStrategy). " +"Please note this is an advanced feature. For all details, please refer to " +"the Ray documentation: https://docs.ray.io/en/latest/ray-core/scheduling/" +"index.html" msgstr "" #: flwr.simulation.app.start_simulation:66 of @@ -14785,16 +15468,16 @@ msgstr "" #: ../../source/ref-changelog.md:364 ../../source/ref-changelog.md:448 #: ../../source/ref-changelog.md:512 ../../source/ref-changelog.md:570 msgid "" -"We would like to give our special thanks to all the contributors who made" -" the new version of Flower possible (in `git shortlog` order):" +"We would like to give our special thanks to all the contributors who made " +"the new version of Flower possible (in `git shortlog` order):" msgstr "" #: ../../source/ref-changelog.md:9 msgid "" -"`Adam Narozniak`, `Charles Beauville`, `Chong Shen Ng`, `Daniel J. " -"Beutel`, `Daniel Nata Nugraha`, `Heng Pan`, `Javier`, `Mahdi Beitollahi`," -" `Robert Steiner`, `Taner Topal`, `Yan Gao`, `bapic`, `mohammadnaseri` " +"`Adam Narozniak`, `Charles Beauville`, `Chong Shen Ng`, `Daniel J. Beutel`, " +"`Daniel Nata Nugraha`, `Heng Pan`, `Javier`, `Mahdi Beitollahi`, `Robert " +"Steiner`, `Taner Topal`, `Yan Gao`, `bapic`, `mohammadnaseri` " msgstr "" #: ../../source/ref-changelog.md:11 ../../source/ref-changelog.md:111 @@ -14811,33 +15494,28 @@ msgstr "" #: ../../source/ref-changelog.md:13 msgid "" -"**Introduce built-in authentication (preview)** " -"([#2946](https://github.com/adap/flower/pull/2946), " -"[#3388](https://github.com/adap/flower/pull/3388), " -"[#2948](https://github.com/adap/flower/pull/2948), " -"[#2917](https://github.com/adap/flower/pull/2917), " -"[#3386](https://github.com/adap/flower/pull/3386), " -"[#3308](https://github.com/adap/flower/pull/3308), " -"[#3001](https://github.com/adap/flower/pull/3001), " -"[#3409](https://github.com/adap/flower/pull/3409), " -"[#2999](https://github.com/adap/flower/pull/2999), " -"[#2979](https://github.com/adap/flower/pull/2979), " -"[#3389](https://github.com/adap/flower/pull/3389), " -"[#3503](https://github.com/adap/flower/pull/3503), " -"[#3366](https://github.com/adap/flower/pull/3366), " -"[#3357](https://github.com/adap/flower/pull/3357))" +"**Introduce built-in authentication (preview)** ([#2946](https://github.com/" +"adap/flower/pull/2946), [#3388](https://github.com/adap/flower/pull/3388), " +"[#2948](https://github.com/adap/flower/pull/2948), [#2917](https://github." +"com/adap/flower/pull/2917), [#3386](https://github.com/adap/flower/" +"pull/3386), [#3308](https://github.com/adap/flower/pull/3308), [#3001]" +"(https://github.com/adap/flower/pull/3001), [#3409](https://github.com/adap/" +"flower/pull/3409), [#2999](https://github.com/adap/flower/pull/2999), [#2979]" +"(https://github.com/adap/flower/pull/2979), [#3389](https://github.com/adap/" +"flower/pull/3389), [#3503](https://github.com/adap/flower/pull/3503), [#3366]" +"(https://github.com/adap/flower/pull/3366), [#3357](https://github.com/adap/" +"flower/pull/3357))" msgstr "" #: ../../source/ref-changelog.md:15 msgid "" "Flower 1.9 introduces the first build-in version of client node " -"authentication. In previous releases, users often wrote glue code to " -"connect Flower to external authentication systems. With this release, the" -" SuperLink can authenticate SuperNodes using a built-in authentication " -"system. A new [how-to guide](https://flower.ai/docs/framework/how-to-" -"authenticate-supernodes.html) and a new [code " -"example](https://github.com/adap/flower/tree/main/examples/flower-" -"authentication) help you to get started." +"authentication. In previous releases, users often wrote glue code to connect " +"Flower to external authentication systems. With this release, the SuperLink " +"can authenticate SuperNodes using a built-in authentication system. A new " +"[how-to guide](https://flower.ai/docs/framework/how-to-authenticate-" +"supernodes.html) and a new [code example](https://github.com/adap/flower/" +"tree/main/examples/flower-authentication) help you to get started." msgstr "" #: ../../source/ref-changelog.md:17 @@ -14849,118 +15527,104 @@ msgstr "" #: ../../source/ref-changelog.md:19 msgid "" -"**Introduce end-to-end Docker support** " -"([#3483](https://github.com/adap/flower/pull/3483), " -"[#3266](https://github.com/adap/flower/pull/3266), " -"[#3390](https://github.com/adap/flower/pull/3390), " -"[#3283](https://github.com/adap/flower/pull/3283), " -"[#3285](https://github.com/adap/flower/pull/3285), " -"[#3391](https://github.com/adap/flower/pull/3391), " -"[#3403](https://github.com/adap/flower/pull/3403), " -"[#3458](https://github.com/adap/flower/pull/3458), " -"[#3533](https://github.com/adap/flower/pull/3533), " -"[#3453](https://github.com/adap/flower/pull/3453), " -"[#3486](https://github.com/adap/flower/pull/3486), " -"[#3290](https://github.com/adap/flower/pull/3290))" +"**Introduce end-to-end Docker support** ([#3483](https://github.com/adap/" +"flower/pull/3483), [#3266](https://github.com/adap/flower/pull/3266), [#3390]" +"(https://github.com/adap/flower/pull/3390), [#3283](https://github.com/adap/" +"flower/pull/3283), [#3285](https://github.com/adap/flower/pull/3285), [#3391]" +"(https://github.com/adap/flower/pull/3391), [#3403](https://github.com/adap/" +"flower/pull/3403), [#3458](https://github.com/adap/flower/pull/3458), [#3533]" +"(https://github.com/adap/flower/pull/3533), [#3453](https://github.com/adap/" +"flower/pull/3453), [#3486](https://github.com/adap/flower/pull/3486), [#3290]" +"(https://github.com/adap/flower/pull/3290))" msgstr "" #: ../../source/ref-changelog.md:21 msgid "" "Full Flower Next Docker support is here! With the release of Flower 1.9, " -"Flower provides stable Docker images for the Flower SuperLink, the Flower" -" SuperNode, and the Flower `ServerApp`. This set of images enables you to" -" run all Flower components in Docker. Check out the new [how-to " -"guide](https://flower.ai/docs/framework/how-to-run-flower-using-" -"docker.html) to get stated." +"Flower provides stable Docker images for the Flower SuperLink, the Flower " +"SuperNode, and the Flower `ServerApp`. This set of images enables you to run " +"all Flower components in Docker. Check out the new [how-to guide](https://" +"flower.ai/docs/framework/how-to-run-flower-using-docker.html) to get stated." msgstr "" #: ../../source/ref-changelog.md:23 msgid "" -"**Re-architect Flower Next simulation engine** " -"([#3307](https://github.com/adap/flower/pull/3307), " -"[#3355](https://github.com/adap/flower/pull/3355), " -"[#3272](https://github.com/adap/flower/pull/3272), " -"[#3273](https://github.com/adap/flower/pull/3273), " -"[#3417](https://github.com/adap/flower/pull/3417), " -"[#3281](https://github.com/adap/flower/pull/3281), " -"[#3343](https://github.com/adap/flower/pull/3343), " -"[#3326](https://github.com/adap/flower/pull/3326))" +"**Re-architect Flower Next simulation engine** ([#3307](https://github.com/" +"adap/flower/pull/3307), [#3355](https://github.com/adap/flower/pull/3355), " +"[#3272](https://github.com/adap/flower/pull/3272), [#3273](https://github." +"com/adap/flower/pull/3273), [#3417](https://github.com/adap/flower/" +"pull/3417), [#3281](https://github.com/adap/flower/pull/3281), [#3343]" +"(https://github.com/adap/flower/pull/3343), [#3326](https://github.com/adap/" +"flower/pull/3326))" msgstr "" #: ../../source/ref-changelog.md:25 msgid "" -"Flower Next simulations now use a new in-memory `Driver` that improves " -"the reliability of simulations, especially in notebook environments. This" -" is a significant step towards a complete overhaul of the Flower Next " -"simulation architecture." +"Flower Next simulations now use a new in-memory `Driver` that improves the " +"reliability of simulations, especially in notebook environments. This is a " +"significant step towards a complete overhaul of the Flower Next simulation " +"architecture." msgstr "" #: ../../source/ref-changelog.md:27 msgid "" -"**Upgrade simulation engine** " -"([#3354](https://github.com/adap/flower/pull/3354), " -"[#3378](https://github.com/adap/flower/pull/3378), " -"[#3262](https://github.com/adap/flower/pull/3262), " -"[#3435](https://github.com/adap/flower/pull/3435), " -"[#3501](https://github.com/adap/flower/pull/3501), " -"[#3482](https://github.com/adap/flower/pull/3482), " -"[#3494](https://github.com/adap/flower/pull/3494))" +"**Upgrade simulation engine** ([#3354](https://github.com/adap/flower/" +"pull/3354), [#3378](https://github.com/adap/flower/pull/3378), [#3262]" +"(https://github.com/adap/flower/pull/3262), [#3435](https://github.com/adap/" +"flower/pull/3435), [#3501](https://github.com/adap/flower/pull/3501), [#3482]" +"(https://github.com/adap/flower/pull/3482), [#3494](https://github.com/adap/" +"flower/pull/3494))" msgstr "" #: ../../source/ref-changelog.md:29 msgid "" "The Flower Next simulation engine comes with improved and configurable " -"logging. The Ray-based simulation backend in Flower 1.9 was updated to " -"use Ray 2.10." +"logging. The Ray-based simulation backend in Flower 1.9 was updated to use " +"Ray 2.10." msgstr "" #: ../../source/ref-changelog.md:31 msgid "" -"**Introduce FedPFT baseline** " -"([#3268](https://github.com/adap/flower/pull/3268))" +"**Introduce FedPFT baseline** ([#3268](https://github.com/adap/flower/" +"pull/3268))" msgstr "" #: ../../source/ref-changelog.md:33 msgid "" "FedPFT allows you to perform one-shot Federated Learning by leveraging " -"widely available foundational models, dramatically reducing communication" -" costs while delivering high performing models. This is work led by Mahdi" -" Beitollahi from Huawei Noah's Ark Lab (Montreal, Canada). Read all the " -"details in their paper: \"Parametric Feature Transfer: One-shot Federated" -" Learning with Foundation Models\" " -"([arxiv](https://arxiv.org/abs/2402.01862))" +"widely available foundational models, dramatically reducing communication " +"costs while delivering high performing models. This is work led by Mahdi " +"Beitollahi from Huawei Noah's Ark Lab (Montreal, Canada). Read all the " +"details in their paper: \"Parametric Feature Transfer: One-shot Federated " +"Learning with Foundation Models\" ([arxiv](https://arxiv.org/abs/2402.01862))" msgstr "" #: ../../source/ref-changelog.md:35 msgid "" "**Launch additional** `flwr new` **templates for Apple MLX, Hugging Face " -"Transformers, scikit-learn and TensorFlow** " -"([#3291](https://github.com/adap/flower/pull/3291), " -"[#3139](https://github.com/adap/flower/pull/3139), " -"[#3284](https://github.com/adap/flower/pull/3284), " -"[#3251](https://github.com/adap/flower/pull/3251), " -"[#3376](https://github.com/adap/flower/pull/3376), " -"[#3287](https://github.com/adap/flower/pull/3287))" +"Transformers, scikit-learn and TensorFlow** ([#3291](https://github.com/adap/" +"flower/pull/3291), [#3139](https://github.com/adap/flower/pull/3139), [#3284]" +"(https://github.com/adap/flower/pull/3284), [#3251](https://github.com/adap/" +"flower/pull/3251), [#3376](https://github.com/adap/flower/pull/3376), [#3287]" +"(https://github.com/adap/flower/pull/3287))" msgstr "" #: ../../source/ref-changelog.md:37 msgid "" -"The `flwr` CLI's `flwr new` command is starting to become everone's " -"favorite way of creating new Flower projects. This release introduces " -"additional `flwr new` templates for Apple MLX, Hugging Face Transformers," -" scikit-learn and TensorFlow. In addition to that, existing templates " -"also received updates." +"The `flwr` CLI's `flwr new` command is starting to become everone's favorite " +"way of creating new Flower projects. This release introduces additional " +"`flwr new` templates for Apple MLX, Hugging Face Transformers, scikit-learn " +"and TensorFlow. In addition to that, existing templates also received " +"updates." msgstr "" #: ../../source/ref-changelog.md:39 msgid "" -"**Refine** `RecordSet` **API** " -"([#3209](https://github.com/adap/flower/pull/3209), " -"[#3331](https://github.com/adap/flower/pull/3331), " -"[#3334](https://github.com/adap/flower/pull/3334), " -"[#3335](https://github.com/adap/flower/pull/3335), " -"[#3375](https://github.com/adap/flower/pull/3375), " -"[#3368](https://github.com/adap/flower/pull/3368))" +"**Refine** `RecordSet` **API** ([#3209](https://github.com/adap/flower/" +"pull/3209), [#3331](https://github.com/adap/flower/pull/3331), [#3334]" +"(https://github.com/adap/flower/pull/3334), [#3335](https://github.com/adap/" +"flower/pull/3335), [#3375](https://github.com/adap/flower/pull/3375), [#3368]" +"(https://github.com/adap/flower/pull/3368))" msgstr "" #: ../../source/ref-changelog.md:41 @@ -14973,29 +15637,25 @@ msgstr "" #: ../../source/ref-changelog.md:43 msgid "" "**Beautify logging** ([#3379](https://github.com/adap/flower/pull/3379), " -"[#3430](https://github.com/adap/flower/pull/3430), " -"[#3461](https://github.com/adap/flower/pull/3461), " -"[#3360](https://github.com/adap/flower/pull/3360), " -"[#3433](https://github.com/adap/flower/pull/3433))" +"[#3430](https://github.com/adap/flower/pull/3430), [#3461](https://github." +"com/adap/flower/pull/3461), [#3360](https://github.com/adap/flower/" +"pull/3360), [#3433](https://github.com/adap/flower/pull/3433))" msgstr "" #: ../../source/ref-changelog.md:45 msgid "" -"Logs received a substantial update. Not only are logs now much nicer to " -"look at, but they are also more configurable." +"Logs received a substantial update. Not only are logs now much nicer to look " +"at, but they are also more configurable." msgstr "" #: ../../source/ref-changelog.md:47 msgid "" -"**Improve reliability** " -"([#3564](https://github.com/adap/flower/pull/3564), " -"[#3561](https://github.com/adap/flower/pull/3561), " -"[#3566](https://github.com/adap/flower/pull/3566), " -"[#3462](https://github.com/adap/flower/pull/3462), " -"[#3225](https://github.com/adap/flower/pull/3225), " -"[#3514](https://github.com/adap/flower/pull/3514), " -"[#3535](https://github.com/adap/flower/pull/3535), " -"[#3372](https://github.com/adap/flower/pull/3372))" +"**Improve reliability** ([#3564](https://github.com/adap/flower/pull/3564), " +"[#3561](https://github.com/adap/flower/pull/3561), [#3566](https://github." +"com/adap/flower/pull/3566), [#3462](https://github.com/adap/flower/" +"pull/3462), [#3225](https://github.com/adap/flower/pull/3225), [#3514]" +"(https://github.com/adap/flower/pull/3514), [#3535](https://github.com/adap/" +"flower/pull/3535), [#3372](https://github.com/adap/flower/pull/3372))" msgstr "" #: ../../source/ref-changelog.md:49 @@ -15006,50 +15666,40 @@ msgstr "" #: ../../source/ref-changelog.md:51 msgid "" -"**Update Swift and C++ SDKs** " -"([#3321](https://github.com/adap/flower/pull/3321), " -"[#2763](https://github.com/adap/flower/pull/2763))" +"**Update Swift and C++ SDKs** ([#3321](https://github.com/adap/flower/" +"pull/3321), [#2763](https://github.com/adap/flower/pull/2763))" msgstr "" #: ../../source/ref-changelog.md:53 msgid "" -"In the C++ SDK, communication-related code is now separate from main " -"client logic. A new abstract class `Communicator` has been introduced " -"alongside a gRPC implementation of it." +"In the C++ SDK, communication-related code is now separate from main client " +"logic. A new abstract class `Communicator` has been introduced alongside a " +"gRPC implementation of it." msgstr "" #: ../../source/ref-changelog.md:55 msgid "" -"**Improve testing, tooling and CI/CD infrastructure** " -"([#3294](https://github.com/adap/flower/pull/3294), " -"[#3282](https://github.com/adap/flower/pull/3282), " -"[#3311](https://github.com/adap/flower/pull/3311), " -"[#2878](https://github.com/adap/flower/pull/2878), " -"[#3333](https://github.com/adap/flower/pull/3333), " -"[#3255](https://github.com/adap/flower/pull/3255), " -"[#3349](https://github.com/adap/flower/pull/3349), " -"[#3400](https://github.com/adap/flower/pull/3400), " -"[#3401](https://github.com/adap/flower/pull/3401), " -"[#3399](https://github.com/adap/flower/pull/3399), " -"[#3346](https://github.com/adap/flower/pull/3346), " -"[#3398](https://github.com/adap/flower/pull/3398), " -"[#3397](https://github.com/adap/flower/pull/3397), " -"[#3347](https://github.com/adap/flower/pull/3347), " -"[#3502](https://github.com/adap/flower/pull/3502), " -"[#3387](https://github.com/adap/flower/pull/3387), " -"[#3542](https://github.com/adap/flower/pull/3542), " -"[#3396](https://github.com/adap/flower/pull/3396), " -"[#3496](https://github.com/adap/flower/pull/3496), " -"[#3465](https://github.com/adap/flower/pull/3465), " -"[#3473](https://github.com/adap/flower/pull/3473), " -"[#3484](https://github.com/adap/flower/pull/3484), " -"[#3521](https://github.com/adap/flower/pull/3521), " -"[#3363](https://github.com/adap/flower/pull/3363), " -"[#3497](https://github.com/adap/flower/pull/3497), " -"[#3464](https://github.com/adap/flower/pull/3464), " -"[#3495](https://github.com/adap/flower/pull/3495), " -"[#3478](https://github.com/adap/flower/pull/3478), " -"[#3271](https://github.com/adap/flower/pull/3271))" +"**Improve testing, tooling and CI/CD infrastructure** ([#3294](https://" +"github.com/adap/flower/pull/3294), [#3282](https://github.com/adap/flower/" +"pull/3282), [#3311](https://github.com/adap/flower/pull/3311), [#2878]" +"(https://github.com/adap/flower/pull/2878), [#3333](https://github.com/adap/" +"flower/pull/3333), [#3255](https://github.com/adap/flower/pull/3255), [#3349]" +"(https://github.com/adap/flower/pull/3349), [#3400](https://github.com/adap/" +"flower/pull/3400), [#3401](https://github.com/adap/flower/pull/3401), [#3399]" +"(https://github.com/adap/flower/pull/3399), [#3346](https://github.com/adap/" +"flower/pull/3346), [#3398](https://github.com/adap/flower/pull/3398), [#3397]" +"(https://github.com/adap/flower/pull/3397), [#3347](https://github.com/adap/" +"flower/pull/3347), [#3502](https://github.com/adap/flower/pull/3502), [#3387]" +"(https://github.com/adap/flower/pull/3387), [#3542](https://github.com/adap/" +"flower/pull/3542), [#3396](https://github.com/adap/flower/pull/3396), [#3496]" +"(https://github.com/adap/flower/pull/3496), [#3465](https://github.com/adap/" +"flower/pull/3465), [#3473](https://github.com/adap/flower/pull/3473), [#3484]" +"(https://github.com/adap/flower/pull/3484), [#3521](https://github.com/adap/" +"flower/pull/3521), [#3363](https://github.com/adap/flower/pull/3363), [#3497]" +"(https://github.com/adap/flower/pull/3497), [#3464](https://github.com/adap/" +"flower/pull/3464), [#3495](https://github.com/adap/flower/pull/3495), [#3478]" +"(https://github.com/adap/flower/pull/3478), [#3271](https://github.com/adap/" +"flower/pull/3271))" msgstr "" #: ../../source/ref-changelog.md:57 @@ -15060,75 +15710,61 @@ msgstr "" #: ../../source/ref-changelog.md:59 msgid "" -"**Improve documentation** " -"([#3530](https://github.com/adap/flower/pull/3530), " -"[#3539](https://github.com/adap/flower/pull/3539), " -"[#3425](https://github.com/adap/flower/pull/3425), " -"[#3520](https://github.com/adap/flower/pull/3520), " -"[#3286](https://github.com/adap/flower/pull/3286), " -"[#3516](https://github.com/adap/flower/pull/3516), " -"[#3523](https://github.com/adap/flower/pull/3523), " -"[#3545](https://github.com/adap/flower/pull/3545), " -"[#3498](https://github.com/adap/flower/pull/3498), " -"[#3439](https://github.com/adap/flower/pull/3439), " -"[#3440](https://github.com/adap/flower/pull/3440), " -"[#3382](https://github.com/adap/flower/pull/3382), " -"[#3559](https://github.com/adap/flower/pull/3559), " -"[#3432](https://github.com/adap/flower/pull/3432), " -"[#3278](https://github.com/adap/flower/pull/3278), " -"[#3371](https://github.com/adap/flower/pull/3371), " -"[#3519](https://github.com/adap/flower/pull/3519), " -"[#3267](https://github.com/adap/flower/pull/3267), " -"[#3204](https://github.com/adap/flower/pull/3204), " -"[#3274](https://github.com/adap/flower/pull/3274))" +"**Improve documentation** ([#3530](https://github.com/adap/flower/" +"pull/3530), [#3539](https://github.com/adap/flower/pull/3539), [#3425]" +"(https://github.com/adap/flower/pull/3425), [#3520](https://github.com/adap/" +"flower/pull/3520), [#3286](https://github.com/adap/flower/pull/3286), [#3516]" +"(https://github.com/adap/flower/pull/3516), [#3523](https://github.com/adap/" +"flower/pull/3523), [#3545](https://github.com/adap/flower/pull/3545), [#3498]" +"(https://github.com/adap/flower/pull/3498), [#3439](https://github.com/adap/" +"flower/pull/3439), [#3440](https://github.com/adap/flower/pull/3440), [#3382]" +"(https://github.com/adap/flower/pull/3382), [#3559](https://github.com/adap/" +"flower/pull/3559), [#3432](https://github.com/adap/flower/pull/3432), [#3278]" +"(https://github.com/adap/flower/pull/3278), [#3371](https://github.com/adap/" +"flower/pull/3371), [#3519](https://github.com/adap/flower/pull/3519), [#3267]" +"(https://github.com/adap/flower/pull/3267), [#3204](https://github.com/adap/" +"flower/pull/3204), [#3274](https://github.com/adap/flower/pull/3274))" msgstr "" #: ../../source/ref-changelog.md:61 msgid "" -"As always, the Flower documentation has received many updates. Notable " -"new pages include:" +"As always, the Flower documentation has received many updates. Notable new " +"pages include:" msgstr "" #: ../../source/ref-changelog.md:63 msgid "" -"[How-to upgrate to Flower Next (Flower Next migration " -"guide)](https://flower.ai/docs/framework/how-to-upgrade-to-flower-" -"next.html)" +"[How-to upgrate to Flower Next (Flower Next migration guide)](https://flower." +"ai/docs/framework/how-to-upgrade-to-flower-next.html)" msgstr "" #: ../../source/ref-changelog.md:65 msgid "" -"[How-to run Flower using Docker](https://flower.ai/docs/framework/how-to-" -"run-flower-using-docker.html)" +"[How-to run Flower using Docker](https://flower.ai/docs/framework/how-to-run-" +"flower-using-docker.html)" msgstr "" #: ../../source/ref-changelog.md:67 msgid "" -"[Flower Mods reference](https://flower.ai/docs/framework/ref-" -"api/flwr.client.mod.html#module-flwr.client.mod)" +"[Flower Mods reference](https://flower.ai/docs/framework/ref-api/flwr.client." +"mod.html#module-flwr.client.mod)" msgstr "" #: ../../source/ref-changelog.md:69 msgid "" -"**General updates to Flower Examples** " -"([#3205](https://github.com/adap/flower/pull/3205), " -"[#3226](https://github.com/adap/flower/pull/3226), " -"[#3211](https://github.com/adap/flower/pull/3211), " -"[#3252](https://github.com/adap/flower/pull/3252), " -"[#3427](https://github.com/adap/flower/pull/3427), " -"[#3410](https://github.com/adap/flower/pull/3410), " -"[#3426](https://github.com/adap/flower/pull/3426), " -"[#3228](https://github.com/adap/flower/pull/3228), " -"[#3342](https://github.com/adap/flower/pull/3342), " -"[#3200](https://github.com/adap/flower/pull/3200), " -"[#3202](https://github.com/adap/flower/pull/3202), " -"[#3394](https://github.com/adap/flower/pull/3394), " -"[#3488](https://github.com/adap/flower/pull/3488), " -"[#3329](https://github.com/adap/flower/pull/3329), " -"[#3526](https://github.com/adap/flower/pull/3526), " -"[#3392](https://github.com/adap/flower/pull/3392), " -"[#3474](https://github.com/adap/flower/pull/3474), " -"[#3269](https://github.com/adap/flower/pull/3269))" +"**General updates to Flower Examples** ([#3205](https://github.com/adap/" +"flower/pull/3205), [#3226](https://github.com/adap/flower/pull/3226), [#3211]" +"(https://github.com/adap/flower/pull/3211), [#3252](https://github.com/adap/" +"flower/pull/3252), [#3427](https://github.com/adap/flower/pull/3427), [#3410]" +"(https://github.com/adap/flower/pull/3410), [#3426](https://github.com/adap/" +"flower/pull/3426), [#3228](https://github.com/adap/flower/pull/3228), [#3342]" +"(https://github.com/adap/flower/pull/3342), [#3200](https://github.com/adap/" +"flower/pull/3200), [#3202](https://github.com/adap/flower/pull/3202), [#3394]" +"(https://github.com/adap/flower/pull/3394), [#3488](https://github.com/adap/" +"flower/pull/3488), [#3329](https://github.com/adap/flower/pull/3329), [#3526]" +"(https://github.com/adap/flower/pull/3526), [#3392](https://github.com/adap/" +"flower/pull/3392), [#3474](https://github.com/adap/flower/pull/3474), [#3269]" +"(https://github.com/adap/flower/pull/3269))" msgstr "" #: ../../source/ref-changelog.md:71 @@ -15137,41 +15773,30 @@ msgstr "" #: ../../source/ref-changelog.md:73 msgid "" -"**General improvements** " -"([#3532](https://github.com/adap/flower/pull/3532), " -"[#3318](https://github.com/adap/flower/pull/3318), " -"[#3565](https://github.com/adap/flower/pull/3565), " -"[#3296](https://github.com/adap/flower/pull/3296), " -"[#3305](https://github.com/adap/flower/pull/3305), " -"[#3246](https://github.com/adap/flower/pull/3246), " -"[#3224](https://github.com/adap/flower/pull/3224), " -"[#3475](https://github.com/adap/flower/pull/3475), " -"[#3297](https://github.com/adap/flower/pull/3297), " -"[#3317](https://github.com/adap/flower/pull/3317), " -"[#3429](https://github.com/adap/flower/pull/3429), " -"[#3196](https://github.com/adap/flower/pull/3196), " -"[#3534](https://github.com/adap/flower/pull/3534), " -"[#3240](https://github.com/adap/flower/pull/3240), " -"[#3365](https://github.com/adap/flower/pull/3365), " -"[#3407](https://github.com/adap/flower/pull/3407), " -"[#3563](https://github.com/adap/flower/pull/3563), " -"[#3344](https://github.com/adap/flower/pull/3344), " -"[#3330](https://github.com/adap/flower/pull/3330), " -"[#3436](https://github.com/adap/flower/pull/3436), " -"[#3300](https://github.com/adap/flower/pull/3300), " -"[#3327](https://github.com/adap/flower/pull/3327), " -"[#3254](https://github.com/adap/flower/pull/3254), " -"[#3253](https://github.com/adap/flower/pull/3253), " -"[#3419](https://github.com/adap/flower/pull/3419), " -"[#3289](https://github.com/adap/flower/pull/3289), " -"[#3208](https://github.com/adap/flower/pull/3208), " -"[#3245](https://github.com/adap/flower/pull/3245), " -"[#3319](https://github.com/adap/flower/pull/3319), " -"[#3203](https://github.com/adap/flower/pull/3203), " -"[#3423](https://github.com/adap/flower/pull/3423), " -"[#3352](https://github.com/adap/flower/pull/3352), " -"[#3292](https://github.com/adap/flower/pull/3292), " -"[#3261](https://github.com/adap/flower/pull/3261))" +"**General improvements** ([#3532](https://github.com/adap/flower/pull/3532), " +"[#3318](https://github.com/adap/flower/pull/3318), [#3565](https://github." +"com/adap/flower/pull/3565), [#3296](https://github.com/adap/flower/" +"pull/3296), [#3305](https://github.com/adap/flower/pull/3305), [#3246]" +"(https://github.com/adap/flower/pull/3246), [#3224](https://github.com/adap/" +"flower/pull/3224), [#3475](https://github.com/adap/flower/pull/3475), [#3297]" +"(https://github.com/adap/flower/pull/3297), [#3317](https://github.com/adap/" +"flower/pull/3317), [#3429](https://github.com/adap/flower/pull/3429), [#3196]" +"(https://github.com/adap/flower/pull/3196), [#3534](https://github.com/adap/" +"flower/pull/3534), [#3240](https://github.com/adap/flower/pull/3240), [#3365]" +"(https://github.com/adap/flower/pull/3365), [#3407](https://github.com/adap/" +"flower/pull/3407), [#3563](https://github.com/adap/flower/pull/3563), [#3344]" +"(https://github.com/adap/flower/pull/3344), [#3330](https://github.com/adap/" +"flower/pull/3330), [#3436](https://github.com/adap/flower/pull/3436), [#3300]" +"(https://github.com/adap/flower/pull/3300), [#3327](https://github.com/adap/" +"flower/pull/3327), [#3254](https://github.com/adap/flower/pull/3254), [#3253]" +"(https://github.com/adap/flower/pull/3253), [#3419](https://github.com/adap/" +"flower/pull/3419), [#3289](https://github.com/adap/flower/pull/3289), [#3208]" +"(https://github.com/adap/flower/pull/3208), [#3245](https://github.com/adap/" +"flower/pull/3245), [#3319](https://github.com/adap/flower/pull/3319), [#3203]" +"(https://github.com/adap/flower/pull/3203), [#3423](https://github.com/adap/" +"flower/pull/3423), [#3352](https://github.com/adap/flower/pull/3352), [#3292]" +"(https://github.com/adap/flower/pull/3292), [#3261](https://github.com/adap/" +"flower/pull/3261))" msgstr "" #: ../../source/ref-changelog.md:75 ../../source/ref-changelog.md:1058 @@ -15184,36 +15809,36 @@ msgstr "" #: ../../source/ref-changelog.md:79 msgid "" -"Python 3.8 will stop receiving security fixes in [October " -"2024](https://devguide.python.org/versions/). Support for Python 3.8 is " -"now deprecated and will be removed in an upcoming release." +"Python 3.8 will stop receiving security fixes in [October 2024](https://" +"devguide.python.org/versions/). Support for Python 3.8 is now deprecated and " +"will be removed in an upcoming release." msgstr "" #: ../../source/ref-changelog.md:81 msgid "" -"**Deprecate (experimental)** `flower-driver-api` **and** `flower-fleet-" -"api` ([#3416](https://github.com/adap/flower/pull/3416), " -"[#3420](https://github.com/adap/flower/pull/3420))" +"**Deprecate (experimental)** `flower-driver-api` **and** `flower-fleet-api` " +"([#3416](https://github.com/adap/flower/pull/3416), [#3420](https://github." +"com/adap/flower/pull/3420))" msgstr "" #: ../../source/ref-changelog.md:83 msgid "" -"Flower 1.9 deprecates the two (experimental) commands `flower-driver-api`" -" and `flower-fleet-api`. Both commands will be removed in an upcoming " +"Flower 1.9 deprecates the two (experimental) commands `flower-driver-api` " +"and `flower-fleet-api`. Both commands will be removed in an upcoming " "release. Use `flower-superlink` instead." msgstr "" #: ../../source/ref-changelog.md:85 msgid "" -"**Deprecate** `--server` **in favor of** `--superlink` " -"([#3518](https://github.com/adap/flower/pull/3518))" +"**Deprecate** `--server` **in favor of** `--superlink` ([#3518](https://" +"github.com/adap/flower/pull/3518))" msgstr "" #: ../../source/ref-changelog.md:87 msgid "" -"The commands `flower-server-app` and `flower-client-app` should use " -"`--superlink` instead of the now deprecated `--server`. Support for " -"`--server` will be removed in a future release." +"The commands `flower-server-app` and `flower-client-app` should use `--" +"superlink` instead of the now deprecated `--server`. Support for `--server` " +"will be removed in a future release." msgstr "" #: ../../source/ref-changelog.md:89 ../../source/ref-changelog.md:163 @@ -15228,48 +15853,46 @@ msgstr "" #: ../../source/ref-changelog.md:91 msgid "" -"**Replace** `flower-superlink` **CLI option** `--certificates` **with** " -"`--ssl-ca-certfile` **,** `--ssl-certfile` **and** `--ssl-keyfile` " -"([#3512](https://github.com/adap/flower/pull/3512), " -"[#3408](https://github.com/adap/flower/pull/3408))" +"**Replace** `flower-superlink` **CLI option** `--certificates` **with** `--" +"ssl-ca-certfile` **,** `--ssl-certfile` **and** `--ssl-keyfile` ([#3512]" +"(https://github.com/adap/flower/pull/3512), [#3408](https://github.com/adap/" +"flower/pull/3408))" msgstr "" #: ../../source/ref-changelog.md:93 msgid "" "SSL-related `flower-superlink` CLI arguments were restructured in an " "incompatible way. Instead of passing a single `--certificates` flag with " -"three values, you now need to pass three flags (`--ssl-ca-certfile`, " -"`--ssl-certfile` and `--ssl-keyfile`) with one value each. Check out the " -"[SSL connections](https://flower.ai/docs/framework/how-to-enable-ssl-" -"connections.html) documentation page for details." +"three values, you now need to pass three flags (`--ssl-ca-certfile`, `--ssl-" +"certfile` and `--ssl-keyfile`) with one value each. Check out the [SSL " +"connections](https://flower.ai/docs/framework/how-to-enable-ssl-connections." +"html) documentation page for details." msgstr "" #: ../../source/ref-changelog.md:95 msgid "" -"**Remove SuperLink** `--vce` **option** " -"([#3513](https://github.com/adap/flower/pull/3513))" +"**Remove SuperLink** `--vce` **option** ([#3513](https://github.com/adap/" +"flower/pull/3513))" msgstr "" #: ../../source/ref-changelog.md:97 msgid "" -"Instead of separately starting a SuperLink and a `ServerApp` for " -"simulation, simulations must now be started using the single `flower-" -"simulation` command." +"Instead of separately starting a SuperLink and a `ServerApp` for simulation, " +"simulations must now be started using the single `flower-simulation` command." msgstr "" #: ../../source/ref-changelog.md:99 msgid "" -"**Merge** `--grpc-rere` **and** `--rest` **SuperLink options** " -"([#3527](https://github.com/adap/flower/pull/3527))" +"**Merge** `--grpc-rere` **and** `--rest` **SuperLink options** ([#3527]" +"(https://github.com/adap/flower/pull/3527))" msgstr "" #: ../../source/ref-changelog.md:101 msgid "" -"To simplify the usage of `flower-superlink`, previously separate sets of " -"CLI options for gRPC and REST were merged into one unified set of " -"options. Consult the [Flower CLI reference " -"documentation](https://flower.ai/docs/framework/ref-api-cli.html) for " -"details." +"To simplify the usage of `flower-superlink`, previously separate sets of CLI " +"options for gRPC and REST were merged into one unified set of options. " +"Consult the [Flower CLI reference documentation](https://flower.ai/docs/" +"framework/ref-api-cli.html) for details." msgstr "" #: ../../source/ref-changelog.md:103 @@ -15279,237 +15902,212 @@ msgstr "" #: ../../source/ref-changelog.md:109 msgid "" "`Adam Narozniak`, `Charles Beauville`, `Daniel J. Beutel`, `Daniel Nata " -"Nugraha`, `Danny`, `Gustavo Bertoli`, `Heng Pan`, `Ikko Eltociear " -"Ashimine`, `Jack Cook`, `Javier`, `Raj Parekh`, `Robert Steiner`, " -"`Sebastian van der Voort`, `Taner Topal`, `Yan Gao`, `mohammadnaseri`, " -"`tabdar-khan` " +"Nugraha`, `Danny`, `Gustavo Bertoli`, `Heng Pan`, `Ikko Eltociear Ashimine`, " +"`Jack Cook`, `Javier`, `Raj Parekh`, `Robert Steiner`, `Sebastian van der " +"Voort`, `Taner Topal`, `Yan Gao`, `mohammadnaseri`, `tabdar-khan` " msgstr "" #: ../../source/ref-changelog.md:113 msgid "" -"**Introduce Flower Next high-level API (stable)** " -"([#3002](https://github.com/adap/flower/pull/3002), " -"[#2934](https://github.com/adap/flower/pull/2934), " -"[#2958](https://github.com/adap/flower/pull/2958), " -"[#3173](https://github.com/adap/flower/pull/3173), " -"[#3174](https://github.com/adap/flower/pull/3174), " -"[#2923](https://github.com/adap/flower/pull/2923), " -"[#2691](https://github.com/adap/flower/pull/2691), " -"[#3079](https://github.com/adap/flower/pull/3079), " -"[#2961](https://github.com/adap/flower/pull/2961), " -"[#2924](https://github.com/adap/flower/pull/2924), " -"[#3166](https://github.com/adap/flower/pull/3166), " -"[#3031](https://github.com/adap/flower/pull/3031), " -"[#3057](https://github.com/adap/flower/pull/3057), " -"[#3000](https://github.com/adap/flower/pull/3000), " -"[#3113](https://github.com/adap/flower/pull/3113), " -"[#2957](https://github.com/adap/flower/pull/2957), " -"[#3183](https://github.com/adap/flower/pull/3183), " -"[#3180](https://github.com/adap/flower/pull/3180), " -"[#3035](https://github.com/adap/flower/pull/3035), " -"[#3189](https://github.com/adap/flower/pull/3189), " -"[#3185](https://github.com/adap/flower/pull/3185), " -"[#3190](https://github.com/adap/flower/pull/3190), " -"[#3191](https://github.com/adap/flower/pull/3191), " -"[#3195](https://github.com/adap/flower/pull/3195), " -"[#3197](https://github.com/adap/flower/pull/3197))" +"**Introduce Flower Next high-level API (stable)** ([#3002](https://github." +"com/adap/flower/pull/3002), [#2934](https://github.com/adap/flower/" +"pull/2934), [#2958](https://github.com/adap/flower/pull/2958), [#3173]" +"(https://github.com/adap/flower/pull/3173), [#3174](https://github.com/adap/" +"flower/pull/3174), [#2923](https://github.com/adap/flower/pull/2923), [#2691]" +"(https://github.com/adap/flower/pull/2691), [#3079](https://github.com/adap/" +"flower/pull/3079), [#2961](https://github.com/adap/flower/pull/2961), [#2924]" +"(https://github.com/adap/flower/pull/2924), [#3166](https://github.com/adap/" +"flower/pull/3166), [#3031](https://github.com/adap/flower/pull/3031), [#3057]" +"(https://github.com/adap/flower/pull/3057), [#3000](https://github.com/adap/" +"flower/pull/3000), [#3113](https://github.com/adap/flower/pull/3113), [#2957]" +"(https://github.com/adap/flower/pull/2957), [#3183](https://github.com/adap/" +"flower/pull/3183), [#3180](https://github.com/adap/flower/pull/3180), [#3035]" +"(https://github.com/adap/flower/pull/3035), [#3189](https://github.com/adap/" +"flower/pull/3189), [#3185](https://github.com/adap/flower/pull/3185), [#3190]" +"(https://github.com/adap/flower/pull/3190), [#3191](https://github.com/adap/" +"flower/pull/3191), [#3195](https://github.com/adap/flower/pull/3195), [#3197]" +"(https://github.com/adap/flower/pull/3197))" msgstr "" #: ../../source/ref-changelog.md:115 msgid "" "The Flower Next high-level API is stable! Flower Next is the future of " -"Flower - all new features (like Flower Mods) will be built on top of it. " -"You can start to migrate your existing projects to Flower Next by using " -"`ServerApp` and `ClientApp` (check out `quickstart-pytorch` or " -"`quickstart-tensorflow`, a detailed migration guide will follow shortly)." -" Flower Next allows you to run multiple projects concurrently (we call " -"this multi-run) and execute the same project in either simulation " -"environments or deployment environments without having to change a single" -" line of code. The best part? It's fully compatible with existing Flower " -"projects that use `Strategy`, `NumPyClient` & co." +"Flower - all new features (like Flower Mods) will be built on top of it. You " +"can start to migrate your existing projects to Flower Next by using " +"`ServerApp` and `ClientApp` (check out `quickstart-pytorch` or `quickstart-" +"tensorflow`, a detailed migration guide will follow shortly). Flower Next " +"allows you to run multiple projects concurrently (we call this multi-run) " +"and execute the same project in either simulation environments or deployment " +"environments without having to change a single line of code. The best part? " +"It's fully compatible with existing Flower projects that use `Strategy`, " +"`NumPyClient` & co." msgstr "" #: ../../source/ref-changelog.md:117 msgid "" -"**Introduce Flower Next low-level API (preview)** " -"([#3062](https://github.com/adap/flower/pull/3062), " -"[#3034](https://github.com/adap/flower/pull/3034), " -"[#3069](https://github.com/adap/flower/pull/3069))" +"**Introduce Flower Next low-level API (preview)** ([#3062](https://github." +"com/adap/flower/pull/3062), [#3034](https://github.com/adap/flower/" +"pull/3034), [#3069](https://github.com/adap/flower/pull/3069))" msgstr "" #: ../../source/ref-changelog.md:119 msgid "" "In addition to the Flower Next *high-level* API that uses `Strategy`, " -"`NumPyClient` & co, Flower 1.8 also comes with a preview version of the " -"new Flower Next *low-level* API. The low-level API allows for granular " -"control of every aspect of the learning process by sending/receiving " -"individual messages to/from client nodes. The new `ServerApp` supports " -"registering a custom `main` function that allows writing custom training " -"loops for methods like async FL, cyclic training, or federated analytics." -" The new `ClientApp` supports registering `train`, `evaluate` and `query`" -" functions that can access the raw message received from the `ServerApp`." -" New abstractions like `RecordSet`, `Message` and `Context` further " -"enable sending multiple models, multiple sets of config values and " -"metrics, stateful computations on the client node and implementations of " -"custom SMPC protocols, to name just a few." +"`NumPyClient` & co, Flower 1.8 also comes with a preview version of the new " +"Flower Next *low-level* API. The low-level API allows for granular control " +"of every aspect of the learning process by sending/receiving individual " +"messages to/from client nodes. The new `ServerApp` supports registering a " +"custom `main` function that allows writing custom training loops for methods " +"like async FL, cyclic training, or federated analytics. The new `ClientApp` " +"supports registering `train`, `evaluate` and `query` functions that can " +"access the raw message received from the `ServerApp`. New abstractions like " +"`RecordSet`, `Message` and `Context` further enable sending multiple models, " +"multiple sets of config values and metrics, stateful computations on the " +"client node and implementations of custom SMPC protocols, to name just a few." msgstr "" #: ../../source/ref-changelog.md:121 msgid "" -"**Introduce Flower Mods (preview)** " -"([#3054](https://github.com/adap/flower/pull/3054), " -"[#2911](https://github.com/adap/flower/pull/2911), " -"[#3083](https://github.com/adap/flower/pull/3083))" +"**Introduce Flower Mods (preview)** ([#3054](https://github.com/adap/flower/" +"pull/3054), [#2911](https://github.com/adap/flower/pull/2911), [#3083]" +"(https://github.com/adap/flower/pull/3083))" msgstr "" #: ../../source/ref-changelog.md:123 msgid "" "Flower Modifiers (we call them Mods) can intercept messages and analyze, " -"edit or handle them directly. Mods can be used to develop pluggable " -"modules that work across different projects. Flower 1.8 already includes " -"mods to log the size of a message, the number of parameters sent over the" -" network, differential privacy with fixed clipping and adaptive clipping," -" local differential privacy and secure aggregation protocols SecAgg and " -"SecAgg+. The Flower Mods API is released as a preview, but researchers " -"can already use it to experiment with arbirtrary SMPC protocols." +"edit or handle them directly. Mods can be used to develop pluggable modules " +"that work across different projects. Flower 1.8 already includes mods to log " +"the size of a message, the number of parameters sent over the network, " +"differential privacy with fixed clipping and adaptive clipping, local " +"differential privacy and secure aggregation protocols SecAgg and SecAgg+. " +"The Flower Mods API is released as a preview, but researchers can already " +"use it to experiment with arbirtrary SMPC protocols." msgstr "" #: ../../source/ref-changelog.md:125 msgid "" -"**Fine-tune LLMs with LLM FlowerTune** " -"([#3029](https://github.com/adap/flower/pull/3029), " -"[#3089](https://github.com/adap/flower/pull/3089), " -"[#3092](https://github.com/adap/flower/pull/3092), " -"[#3100](https://github.com/adap/flower/pull/3100), " -"[#3114](https://github.com/adap/flower/pull/3114), " -"[#3162](https://github.com/adap/flower/pull/3162), " -"[#3172](https://github.com/adap/flower/pull/3172))" +"**Fine-tune LLMs with LLM FlowerTune** ([#3029](https://github.com/adap/" +"flower/pull/3029), [#3089](https://github.com/adap/flower/pull/3089), [#3092]" +"(https://github.com/adap/flower/pull/3092), [#3100](https://github.com/adap/" +"flower/pull/3100), [#3114](https://github.com/adap/flower/pull/3114), [#3162]" +"(https://github.com/adap/flower/pull/3162), [#3172](https://github.com/adap/" +"flower/pull/3172))" msgstr "" #: ../../source/ref-changelog.md:127 msgid "" -"We are introducing LLM FlowerTune, an introductory example that " -"demonstrates federated LLM fine-tuning of pre-trained Llama2 models on " -"the Alpaca-GPT4 dataset. The example is built to be easily adapted to use" -" different models and/or datasets. Read our blog post [LLM FlowerTune: " -"Federated LLM Fine-tuning with Flower](https://flower.ai/blog/2024-03-14" -"-llm-flowertune-federated-llm-finetuning-with-flower/) for more details." +"We are introducing LLM FlowerTune, an introductory example that demonstrates " +"federated LLM fine-tuning of pre-trained Llama2 models on the Alpaca-GPT4 " +"dataset. The example is built to be easily adapted to use different models " +"and/or datasets. Read our blog post [LLM FlowerTune: Federated LLM Fine-" +"tuning with Flower](https://flower.ai/blog/2024-03-14-llm-flowertune-" +"federated-llm-finetuning-with-flower/) for more details." msgstr "" #: ../../source/ref-changelog.md:129 msgid "" -"**Introduce built-in Differential Privacy (preview)** " -"([#2798](https://github.com/adap/flower/pull/2798), " -"[#2959](https://github.com/adap/flower/pull/2959), " -"[#3038](https://github.com/adap/flower/pull/3038), " -"[#3147](https://github.com/adap/flower/pull/3147), " -"[#2909](https://github.com/adap/flower/pull/2909), " -"[#2893](https://github.com/adap/flower/pull/2893), " -"[#2892](https://github.com/adap/flower/pull/2892), " -"[#3039](https://github.com/adap/flower/pull/3039), " -"[#3074](https://github.com/adap/flower/pull/3074))" +"**Introduce built-in Differential Privacy (preview)** ([#2798](https://" +"github.com/adap/flower/pull/2798), [#2959](https://github.com/adap/flower/" +"pull/2959), [#3038](https://github.com/adap/flower/pull/3038), [#3147]" +"(https://github.com/adap/flower/pull/3147), [#2909](https://github.com/adap/" +"flower/pull/2909), [#2893](https://github.com/adap/flower/pull/2893), [#2892]" +"(https://github.com/adap/flower/pull/2892), [#3039](https://github.com/adap/" +"flower/pull/3039), [#3074](https://github.com/adap/flower/pull/3074))" msgstr "" #: ../../source/ref-changelog.md:131 msgid "" "Built-in Differential Privacy is here! Flower supports both central and " -"local differential privacy (DP). Central DP can be configured with either" -" fixed or adaptive clipping. The clipping can happen either on the " -"server-side or the client-side. Local DP does both clipping and noising " -"on the client-side. A new documentation page [explains Differential " -"Privacy approaches](https://flower.ai/docs/framework/explanation-" -"differential-privacy.html) and a new how-to guide describes [how to use " -"the new Differential Privacy components](https://flower.ai/docs/framework" -"/how-to-use-differential-privacy.html) in Flower." +"local differential privacy (DP). Central DP can be configured with either " +"fixed or adaptive clipping. The clipping can happen either on the server-" +"side or the client-side. Local DP does both clipping and noising on the " +"client-side. A new documentation page [explains Differential Privacy " +"approaches](https://flower.ai/docs/framework/explanation-differential-" +"privacy.html) and a new how-to guide describes [how to use the new " +"Differential Privacy components](https://flower.ai/docs/framework/how-to-use-" +"differential-privacy.html) in Flower." msgstr "" #: ../../source/ref-changelog.md:133 msgid "" -"**Introduce built-in Secure Aggregation (preview)** " -"([#3120](https://github.com/adap/flower/pull/3120), " -"[#3110](https://github.com/adap/flower/pull/3110), " -"[#3108](https://github.com/adap/flower/pull/3108))" +"**Introduce built-in Secure Aggregation (preview)** ([#3120](https://github." +"com/adap/flower/pull/3120), [#3110](https://github.com/adap/flower/" +"pull/3110), [#3108](https://github.com/adap/flower/pull/3108))" msgstr "" #: ../../source/ref-changelog.md:135 msgid "" -"Built-in Secure Aggregation is here! Flower now supports different secure" -" aggregation protocols out-of-the-box. The best part? You can add secure " -"aggregation to your Flower projects with only a few lines of code. In " -"this initial release, we inlcude support for SecAgg and SecAgg+, but more" -" protocols will be implemented shortly. We'll also add detailed docs that" -" explain secure aggregation and how to use it in Flower. You can already " +"Built-in Secure Aggregation is here! Flower now supports different secure " +"aggregation protocols out-of-the-box. The best part? You can add secure " +"aggregation to your Flower projects with only a few lines of code. In this " +"initial release, we inlcude support for SecAgg and SecAgg+, but more " +"protocols will be implemented shortly. We'll also add detailed docs that " +"explain secure aggregation and how to use it in Flower. You can already " "check out the new code example that shows how to use Flower to easily " -"combine Federated Learning, Differential Privacy and Secure Aggregation " -"in the same project." +"combine Federated Learning, Differential Privacy and Secure Aggregation in " +"the same project." msgstr "" #: ../../source/ref-changelog.md:137 msgid "" -"**Introduce** `flwr` **CLI (preview)** " -"([#2942](https://github.com/adap/flower/pull/2942), " -"[#3055](https://github.com/adap/flower/pull/3055), " -"[#3111](https://github.com/adap/flower/pull/3111), " -"[#3130](https://github.com/adap/flower/pull/3130), " -"[#3136](https://github.com/adap/flower/pull/3136), " -"[#3094](https://github.com/adap/flower/pull/3094), " -"[#3059](https://github.com/adap/flower/pull/3059), " -"[#3049](https://github.com/adap/flower/pull/3049), " -"[#3142](https://github.com/adap/flower/pull/3142))" +"**Introduce** `flwr` **CLI (preview)** ([#2942](https://github.com/adap/" +"flower/pull/2942), [#3055](https://github.com/adap/flower/pull/3055), [#3111]" +"(https://github.com/adap/flower/pull/3111), [#3130](https://github.com/adap/" +"flower/pull/3130), [#3136](https://github.com/adap/flower/pull/3136), [#3094]" +"(https://github.com/adap/flower/pull/3094), [#3059](https://github.com/adap/" +"flower/pull/3059), [#3049](https://github.com/adap/flower/pull/3049), [#3142]" +"(https://github.com/adap/flower/pull/3142))" msgstr "" #: ../../source/ref-changelog.md:139 msgid "" -"A new `flwr` CLI command allows creating new Flower projects (`flwr new`)" -" and then running them using the Simulation Engine (`flwr run`)." +"A new `flwr` CLI command allows creating new Flower projects (`flwr new`) " +"and then running them using the Simulation Engine (`flwr run`)." msgstr "" #: ../../source/ref-changelog.md:141 msgid "" -"**Introduce Flower Next Simulation Engine** " -"([#3024](https://github.com/adap/flower/pull/3024), " -"[#3061](https://github.com/adap/flower/pull/3061), " -"[#2997](https://github.com/adap/flower/pull/2997), " -"[#2783](https://github.com/adap/flower/pull/2783), " -"[#3184](https://github.com/adap/flower/pull/3184), " -"[#3075](https://github.com/adap/flower/pull/3075), " -"[#3047](https://github.com/adap/flower/pull/3047), " -"[#2998](https://github.com/adap/flower/pull/2998), " -"[#3009](https://github.com/adap/flower/pull/3009), " -"[#3008](https://github.com/adap/flower/pull/3008))" +"**Introduce Flower Next Simulation Engine** ([#3024](https://github.com/adap/" +"flower/pull/3024), [#3061](https://github.com/adap/flower/pull/3061), [#2997]" +"(https://github.com/adap/flower/pull/2997), [#2783](https://github.com/adap/" +"flower/pull/2783), [#3184](https://github.com/adap/flower/pull/3184), [#3075]" +"(https://github.com/adap/flower/pull/3075), [#3047](https://github.com/adap/" +"flower/pull/3047), [#2998](https://github.com/adap/flower/pull/2998), [#3009]" +"(https://github.com/adap/flower/pull/3009), [#3008](https://github.com/adap/" +"flower/pull/3008))" msgstr "" #: ../../source/ref-changelog.md:143 msgid "" -"The Flower Simulation Engine can now run Flower Next projects. For " -"notebook environments, there's also a new `run_simulation` function that " -"can run `ServerApp` and `ClientApp`." +"The Flower Simulation Engine can now run Flower Next projects. For notebook " +"environments, there's also a new `run_simulation` function that can run " +"`ServerApp` and `ClientApp`." msgstr "" #: ../../source/ref-changelog.md:145 msgid "" -"**Handle SuperNode connection errors** " -"([#2969](https://github.com/adap/flower/pull/2969))" +"**Handle SuperNode connection errors** ([#2969](https://github.com/adap/" +"flower/pull/2969))" msgstr "" #: ../../source/ref-changelog.md:147 msgid "" -"A SuperNode will now try to reconnect indefinitely to the SuperLink in " -"case of connection errors. The arguments `--max-retries` and `--max-wait-" -"time` can now be passed to the `flower-client-app` command. `--max-" -"retries` will define the number of tentatives the client should make " -"before it gives up trying to reconnect to the SuperLink, and, `--max-" -"wait-time` defines the time before the SuperNode gives up trying to " -"reconnect to the SuperLink." +"A SuperNode will now try to reconnect indefinitely to the SuperLink in case " +"of connection errors. The arguments `--max-retries` and `--max-wait-time` " +"can now be passed to the `flower-client-app` command. `--max-retries` will " +"define the number of tentatives the client should make before it gives up " +"trying to reconnect to the SuperLink, and, `--max-wait-time` defines the " +"time before the SuperNode gives up trying to reconnect to the SuperLink." msgstr "" #: ../../source/ref-changelog.md:149 msgid "" -"**General updates to Flower Baselines** " -"([#2904](https://github.com/adap/flower/pull/2904), " -"[#2482](https://github.com/adap/flower/pull/2482), " -"[#2985](https://github.com/adap/flower/pull/2985), " -"[#2968](https://github.com/adap/flower/pull/2968))" +"**General updates to Flower Baselines** ([#2904](https://github.com/adap/" +"flower/pull/2904), [#2482](https://github.com/adap/flower/pull/2482), [#2985]" +"(https://github.com/adap/flower/pull/2985), [#2968](https://github.com/adap/" +"flower/pull/2968))" msgstr "" #: ../../source/ref-changelog.md:151 @@ -15520,133 +16118,100 @@ msgstr "" #: ../../source/ref-changelog.md:153 msgid "" -"**Improve documentation and translations** " -"([#3050](https://github.com/adap/flower/pull/3050), " -"[#3044](https://github.com/adap/flower/pull/3044), " -"[#3043](https://github.com/adap/flower/pull/3043), " -"[#2986](https://github.com/adap/flower/pull/2986), " -"[#3041](https://github.com/adap/flower/pull/3041), " -"[#3046](https://github.com/adap/flower/pull/3046), " -"[#3042](https://github.com/adap/flower/pull/3042), " -"[#2978](https://github.com/adap/flower/pull/2978), " -"[#2952](https://github.com/adap/flower/pull/2952), " -"[#3167](https://github.com/adap/flower/pull/3167), " -"[#2953](https://github.com/adap/flower/pull/2953), " -"[#3045](https://github.com/adap/flower/pull/3045), " -"[#2654](https://github.com/adap/flower/pull/2654), " -"[#3082](https://github.com/adap/flower/pull/3082), " -"[#2990](https://github.com/adap/flower/pull/2990), " -"[#2989](https://github.com/adap/flower/pull/2989))" +"**Improve documentation and translations** ([#3050](https://github.com/adap/" +"flower/pull/3050), [#3044](https://github.com/adap/flower/pull/3044), [#3043]" +"(https://github.com/adap/flower/pull/3043), [#2986](https://github.com/adap/" +"flower/pull/2986), [#3041](https://github.com/adap/flower/pull/3041), [#3046]" +"(https://github.com/adap/flower/pull/3046), [#3042](https://github.com/adap/" +"flower/pull/3042), [#2978](https://github.com/adap/flower/pull/2978), [#2952]" +"(https://github.com/adap/flower/pull/2952), [#3167](https://github.com/adap/" +"flower/pull/3167), [#2953](https://github.com/adap/flower/pull/2953), [#3045]" +"(https://github.com/adap/flower/pull/3045), [#2654](https://github.com/adap/" +"flower/pull/2654), [#3082](https://github.com/adap/flower/pull/3082), [#2990]" +"(https://github.com/adap/flower/pull/2990), [#2989](https://github.com/adap/" +"flower/pull/2989))" msgstr "" #: ../../source/ref-changelog.md:155 msgid "" "As usual, we merged many smaller and larger improvements to the " -"documentation. A special thank you goes to [Sebastian van der " -"Voort](https://github.com/svdvoort) for landing a big documentation PR!" +"documentation. A special thank you goes to [Sebastian van der Voort](https://" +"github.com/svdvoort) for landing a big documentation PR!" msgstr "" #: ../../source/ref-changelog.md:157 msgid "" -"**General updates to Flower Examples** " -"([3134](https://github.com/adap/flower/pull/3134), " -"[2996](https://github.com/adap/flower/pull/2996), " -"[2930](https://github.com/adap/flower/pull/2930), " -"[2967](https://github.com/adap/flower/pull/2967), " -"[2467](https://github.com/adap/flower/pull/2467), " -"[2910](https://github.com/adap/flower/pull/2910), " -"[#2918](https://github.com/adap/flower/pull/2918), " -"[#2773](https://github.com/adap/flower/pull/2773), " -"[#3063](https://github.com/adap/flower/pull/3063), " -"[#3116](https://github.com/adap/flower/pull/3116), " -"[#3117](https://github.com/adap/flower/pull/3117))" +"**General updates to Flower Examples** ([3134](https://github.com/adap/" +"flower/pull/3134), [2996](https://github.com/adap/flower/pull/2996), [2930]" +"(https://github.com/adap/flower/pull/2930), [2967](https://github.com/adap/" +"flower/pull/2967), [2467](https://github.com/adap/flower/pull/2467), [2910]" +"(https://github.com/adap/flower/pull/2910), [#2918](https://github.com/adap/" +"flower/pull/2918), [#2773](https://github.com/adap/flower/pull/2773), [#3063]" +"(https://github.com/adap/flower/pull/3063), [#3116](https://github.com/adap/" +"flower/pull/3116), [#3117](https://github.com/adap/flower/pull/3117))" msgstr "" #: ../../source/ref-changelog.md:159 msgid "" -"Two new examples show federated training of a Vision Transformer (ViT) " -"and federated learning in a medical context using the popular MONAI " -"library. `quickstart-pytorch` and `quickstart-tensorflow` demonstrate the" -" new Flower Next `ServerApp` and `ClientApp`. Many other examples " -"received considerable updates as well." +"Two new examples show federated training of a Vision Transformer (ViT) and " +"federated learning in a medical context using the popular MONAI library. " +"`quickstart-pytorch` and `quickstart-tensorflow` demonstrate the new Flower " +"Next `ServerApp` and `ClientApp`. Many other examples received considerable " +"updates as well." msgstr "" #: ../../source/ref-changelog.md:161 msgid "" -"**General improvements** " -"([#3171](https://github.com/adap/flower/pull/3171), " -"[3099](https://github.com/adap/flower/pull/3099), " -"[3003](https://github.com/adap/flower/pull/3003), " -"[3145](https://github.com/adap/flower/pull/3145), " -"[3017](https://github.com/adap/flower/pull/3017), " -"[3085](https://github.com/adap/flower/pull/3085), " -"[3012](https://github.com/adap/flower/pull/3012), " -"[3119](https://github.com/adap/flower/pull/3119), " -"[2991](https://github.com/adap/flower/pull/2991), " -"[2970](https://github.com/adap/flower/pull/2970), " -"[2980](https://github.com/adap/flower/pull/2980), " -"[3086](https://github.com/adap/flower/pull/3086), " -"[2932](https://github.com/adap/flower/pull/2932), " -"[2928](https://github.com/adap/flower/pull/2928), " -"[2941](https://github.com/adap/flower/pull/2941), " -"[2933](https://github.com/adap/flower/pull/2933), " -"[3181](https://github.com/adap/flower/pull/3181), " -"[2973](https://github.com/adap/flower/pull/2973), " -"[2992](https://github.com/adap/flower/pull/2992), " -"[2915](https://github.com/adap/flower/pull/2915), " -"[3040](https://github.com/adap/flower/pull/3040), " -"[3022](https://github.com/adap/flower/pull/3022), " -"[3032](https://github.com/adap/flower/pull/3032), " -"[2902](https://github.com/adap/flower/pull/2902), " -"[2931](https://github.com/adap/flower/pull/2931), " -"[3005](https://github.com/adap/flower/pull/3005), " -"[3132](https://github.com/adap/flower/pull/3132), " -"[3115](https://github.com/adap/flower/pull/3115), " -"[2944](https://github.com/adap/flower/pull/2944), " -"[3064](https://github.com/adap/flower/pull/3064), " -"[3106](https://github.com/adap/flower/pull/3106), " -"[2974](https://github.com/adap/flower/pull/2974), " -"[3178](https://github.com/adap/flower/pull/3178), " -"[2993](https://github.com/adap/flower/pull/2993), " -"[3186](https://github.com/adap/flower/pull/3186), " -"[3091](https://github.com/adap/flower/pull/3091), " -"[3125](https://github.com/adap/flower/pull/3125), " -"[3093](https://github.com/adap/flower/pull/3093), " -"[3013](https://github.com/adap/flower/pull/3013), " -"[3033](https://github.com/adap/flower/pull/3033), " -"[3133](https://github.com/adap/flower/pull/3133), " -"[3068](https://github.com/adap/flower/pull/3068), " -"[2916](https://github.com/adap/flower/pull/2916), " -"[2975](https://github.com/adap/flower/pull/2975), " -"[2984](https://github.com/adap/flower/pull/2984), " -"[2846](https://github.com/adap/flower/pull/2846), " -"[3077](https://github.com/adap/flower/pull/3077), " -"[3143](https://github.com/adap/flower/pull/3143), " -"[2921](https://github.com/adap/flower/pull/2921), " -"[3101](https://github.com/adap/flower/pull/3101), " -"[2927](https://github.com/adap/flower/pull/2927), " -"[2995](https://github.com/adap/flower/pull/2995), " -"[2972](https://github.com/adap/flower/pull/2972), " -"[2912](https://github.com/adap/flower/pull/2912), " -"[3065](https://github.com/adap/flower/pull/3065), " -"[3028](https://github.com/adap/flower/pull/3028), " -"[2922](https://github.com/adap/flower/pull/2922), " -"[2982](https://github.com/adap/flower/pull/2982), " -"[2914](https://github.com/adap/flower/pull/2914), " -"[3179](https://github.com/adap/flower/pull/3179), " -"[3080](https://github.com/adap/flower/pull/3080), " -"[2994](https://github.com/adap/flower/pull/2994), " -"[3187](https://github.com/adap/flower/pull/3187), " -"[2926](https://github.com/adap/flower/pull/2926), " -"[3018](https://github.com/adap/flower/pull/3018), " -"[3144](https://github.com/adap/flower/pull/3144), " -"[3011](https://github.com/adap/flower/pull/3011), " -"[#3152](https://github.com/adap/flower/pull/3152), " -"[#2836](https://github.com/adap/flower/pull/2836), " -"[#2929](https://github.com/adap/flower/pull/2929), " -"[#2943](https://github.com/adap/flower/pull/2943), " -"[#2955](https://github.com/adap/flower/pull/2955), " -"[#2954](https://github.com/adap/flower/pull/2954))" +"**General improvements** ([#3171](https://github.com/adap/flower/pull/3171), " +"[3099](https://github.com/adap/flower/pull/3099), [3003](https://github.com/" +"adap/flower/pull/3003), [3145](https://github.com/adap/flower/pull/3145), " +"[3017](https://github.com/adap/flower/pull/3017), [3085](https://github.com/" +"adap/flower/pull/3085), [3012](https://github.com/adap/flower/pull/3012), " +"[3119](https://github.com/adap/flower/pull/3119), [2991](https://github.com/" +"adap/flower/pull/2991), [2970](https://github.com/adap/flower/pull/2970), " +"[2980](https://github.com/adap/flower/pull/2980), [3086](https://github.com/" +"adap/flower/pull/3086), [2932](https://github.com/adap/flower/pull/2932), " +"[2928](https://github.com/adap/flower/pull/2928), [2941](https://github.com/" +"adap/flower/pull/2941), [2933](https://github.com/adap/flower/pull/2933), " +"[3181](https://github.com/adap/flower/pull/3181), [2973](https://github.com/" +"adap/flower/pull/2973), [2992](https://github.com/adap/flower/pull/2992), " +"[2915](https://github.com/adap/flower/pull/2915), [3040](https://github.com/" +"adap/flower/pull/3040), [3022](https://github.com/adap/flower/pull/3022), " +"[3032](https://github.com/adap/flower/pull/3032), [2902](https://github.com/" +"adap/flower/pull/2902), [2931](https://github.com/adap/flower/pull/2931), " +"[3005](https://github.com/adap/flower/pull/3005), [3132](https://github.com/" +"adap/flower/pull/3132), [3115](https://github.com/adap/flower/pull/3115), " +"[2944](https://github.com/adap/flower/pull/2944), [3064](https://github.com/" +"adap/flower/pull/3064), [3106](https://github.com/adap/flower/pull/3106), " +"[2974](https://github.com/adap/flower/pull/2974), [3178](https://github.com/" +"adap/flower/pull/3178), [2993](https://github.com/adap/flower/pull/2993), " +"[3186](https://github.com/adap/flower/pull/3186), [3091](https://github.com/" +"adap/flower/pull/3091), [3125](https://github.com/adap/flower/pull/3125), " +"[3093](https://github.com/adap/flower/pull/3093), [3013](https://github.com/" +"adap/flower/pull/3013), [3033](https://github.com/adap/flower/pull/3033), " +"[3133](https://github.com/adap/flower/pull/3133), [3068](https://github.com/" +"adap/flower/pull/3068), [2916](https://github.com/adap/flower/pull/2916), " +"[2975](https://github.com/adap/flower/pull/2975), [2984](https://github.com/" +"adap/flower/pull/2984), [2846](https://github.com/adap/flower/pull/2846), " +"[3077](https://github.com/adap/flower/pull/3077), [3143](https://github.com/" +"adap/flower/pull/3143), [2921](https://github.com/adap/flower/pull/2921), " +"[3101](https://github.com/adap/flower/pull/3101), [2927](https://github.com/" +"adap/flower/pull/2927), [2995](https://github.com/adap/flower/pull/2995), " +"[2972](https://github.com/adap/flower/pull/2972), [2912](https://github.com/" +"adap/flower/pull/2912), [3065](https://github.com/adap/flower/pull/3065), " +"[3028](https://github.com/adap/flower/pull/3028), [2922](https://github.com/" +"adap/flower/pull/2922), [2982](https://github.com/adap/flower/pull/2982), " +"[2914](https://github.com/adap/flower/pull/2914), [3179](https://github.com/" +"adap/flower/pull/3179), [3080](https://github.com/adap/flower/pull/3080), " +"[2994](https://github.com/adap/flower/pull/2994), [3187](https://github.com/" +"adap/flower/pull/3187), [2926](https://github.com/adap/flower/pull/2926), " +"[3018](https://github.com/adap/flower/pull/3018), [3144](https://github.com/" +"adap/flower/pull/3144), [3011](https://github.com/adap/flower/pull/3011), " +"[#3152](https://github.com/adap/flower/pull/3152), [#2836](https://github." +"com/adap/flower/pull/2836), [#2929](https://github.com/adap/flower/" +"pull/2929), [#2943](https://github.com/adap/flower/pull/2943), [#2955]" +"(https://github.com/adap/flower/pull/2955), [#2954](https://github.com/adap/" +"flower/pull/2954))" msgstr "" #: ../../source/ref-changelog.md:165 ../../source/ref-changelog.md:442 @@ -15661,97 +16226,91 @@ msgstr "" #: ../../source/ref-changelog.md:173 msgid "" -"`Aasheesh Singh`, `Adam Narozniak`, `Aml Hassan Esmil`, `Charles " -"Beauville`, `Daniel J. Beutel`, `Daniel Nata Nugraha`, `Edoardo " -"Gabrielli`, `Gustavo Bertoli`, `HelinLin`, `Heng Pan`, `Javier`, `M S " -"Chaitanya Kumar`, `Mohammad Naseri`, `Nikos Vlachakis`, `Pritam Neog`, " -"`Robert Kuska`, `Robert Steiner`, `Taner Topal`, `Yahia Salaheldin " -"Shaaban`, `Yan Gao`, `Yasar Abbas` " +"`Aasheesh Singh`, `Adam Narozniak`, `Aml Hassan Esmil`, `Charles Beauville`, " +"`Daniel J. Beutel`, `Daniel Nata Nugraha`, `Edoardo Gabrielli`, `Gustavo " +"Bertoli`, `HelinLin`, `Heng Pan`, `Javier`, `M S Chaitanya Kumar`, `Mohammad " +"Naseri`, `Nikos Vlachakis`, `Pritam Neog`, `Robert Kuska`, `Robert Steiner`, " +"`Taner Topal`, `Yahia Salaheldin Shaaban`, `Yan Gao`, `Yasar Abbas` " msgstr "" #: ../../source/ref-changelog.md:177 msgid "" -"**Introduce stateful clients (experimental)** " -"([#2770](https://github.com/adap/flower/pull/2770), " -"[#2686](https://github.com/adap/flower/pull/2686), " -"[#2696](https://github.com/adap/flower/pull/2696), " -"[#2643](https://github.com/adap/flower/pull/2643), " -"[#2769](https://github.com/adap/flower/pull/2769))" +"**Introduce stateful clients (experimental)** ([#2770](https://github.com/" +"adap/flower/pull/2770), [#2686](https://github.com/adap/flower/pull/2686), " +"[#2696](https://github.com/adap/flower/pull/2696), [#2643](https://github." +"com/adap/flower/pull/2643), [#2769](https://github.com/adap/flower/" +"pull/2769))" msgstr "" #: ../../source/ref-changelog.md:179 msgid "" "Subclasses of `Client` and `NumPyClient` can now store local state that " "remains on the client. Let's start with the highlight first: this new " -"feature is compatible with both simulated clients (via " -"`start_simulation`) and networked clients (via `start_client`). It's also" -" the first preview of new abstractions like `Context` and `RecordSet`. " -"Clients can access state of type `RecordSet` via `state: RecordSet = " -"self.context.state`. Changes to this `RecordSet` are preserved across " -"different rounds of execution to enable stateful computations in a " -"unified way across simulation and deployment." +"feature is compatible with both simulated clients (via `start_simulation`) " +"and networked clients (via `start_client`). It's also the first preview of " +"new abstractions like `Context` and `RecordSet`. Clients can access state of " +"type `RecordSet` via `state: RecordSet = self.context.state`. Changes to " +"this `RecordSet` are preserved across different rounds of execution to " +"enable stateful computations in a unified way across simulation and " +"deployment." msgstr "" #: ../../source/ref-changelog.md:181 msgid "" -"**Improve performance** " -"([#2293](https://github.com/adap/flower/pull/2293))" +"**Improve performance** ([#2293](https://github.com/adap/flower/pull/2293))" msgstr "" #: ../../source/ref-changelog.md:183 msgid "" -"Flower is faster than ever. All `FedAvg`-derived strategies now use in-" -"place aggregation to reduce memory consumption. The Flower client " -"serialization/deserialization has been rewritten from the ground up, " -"which results in significant speedups, especially when the client-side " -"training time is short." +"Flower is faster than ever. All `FedAvg`-derived strategies now use in-place " +"aggregation to reduce memory consumption. The Flower client serialization/" +"deserialization has been rewritten from the ground up, which results in " +"significant speedups, especially when the client-side training time is short." msgstr "" #: ../../source/ref-changelog.md:185 msgid "" -"**Support Federated Learning with Apple MLX and Flower** " -"([#2693](https://github.com/adap/flower/pull/2693))" +"**Support Federated Learning with Apple MLX and Flower** ([#2693](https://" +"github.com/adap/flower/pull/2693))" msgstr "" #: ../../source/ref-changelog.md:187 msgid "" -"Flower has official support for federated learning using [Apple " -"MLX](https://ml-explore.github.io/mlx) via the new `quickstart-mlx` code " -"example." +"Flower has official support for federated learning using [Apple MLX](https://" +"ml-explore.github.io/mlx) via the new `quickstart-mlx` code example." msgstr "" #: ../../source/ref-changelog.md:189 msgid "" -"**Introduce new XGBoost cyclic strategy** " -"([#2666](https://github.com/adap/flower/pull/2666), " -"[#2668](https://github.com/adap/flower/pull/2668))" +"**Introduce new XGBoost cyclic strategy** ([#2666](https://github.com/adap/" +"flower/pull/2666), [#2668](https://github.com/adap/flower/pull/2668))" msgstr "" #: ../../source/ref-changelog.md:191 msgid "" -"A new strategy called `FedXgbCyclic` supports a client-by-client style of" -" training (often called cyclic). The `xgboost-comprehensive` code example" -" shows how to use it in a full project. In addition to that, `xgboost-" -"comprehensive` now also supports simulation mode. With this, Flower " -"offers best-in-class XGBoost support." +"A new strategy called `FedXgbCyclic` supports a client-by-client style of " +"training (often called cyclic). The `xgboost-comprehensive` code example " +"shows how to use it in a full project. In addition to that, `xgboost-" +"comprehensive` now also supports simulation mode. With this, Flower offers " +"best-in-class XGBoost support." msgstr "" #: ../../source/ref-changelog.md:193 msgid "" -"**Support Python 3.11** " -"([#2394](https://github.com/adap/flower/pull/2394))" +"**Support Python 3.11** ([#2394](https://github.com/adap/flower/pull/2394))" msgstr "" #: ../../source/ref-changelog.md:195 msgid "" -"Framework tests now run on Python 3.8, 3.9, 3.10, and 3.11. This will " -"ensure better support for users using more recent Python versions." +"Framework tests now run on Python 3.8, 3.9, 3.10, and 3.11. This will ensure " +"better support for users using more recent Python versions." msgstr "" #: ../../source/ref-changelog.md:197 msgid "" -"**Update gRPC and ProtoBuf dependencies** " -"([#2814](https://github.com/adap/flower/pull/2814))" +"**Update gRPC and ProtoBuf dependencies** ([#2814](https://github.com/adap/" +"flower/pull/2814))" msgstr "" #: ../../source/ref-changelog.md:199 @@ -15762,72 +16321,65 @@ msgstr "" #: ../../source/ref-changelog.md:201 msgid "" -"**Introduce Docker image for Flower server** " -"([#2700](https://github.com/adap/flower/pull/2700), " -"[#2688](https://github.com/adap/flower/pull/2688), " -"[#2705](https://github.com/adap/flower/pull/2705), " -"[#2695](https://github.com/adap/flower/pull/2695), " -"[#2747](https://github.com/adap/flower/pull/2747), " -"[#2746](https://github.com/adap/flower/pull/2746), " -"[#2680](https://github.com/adap/flower/pull/2680), " -"[#2682](https://github.com/adap/flower/pull/2682), " -"[#2701](https://github.com/adap/flower/pull/2701))" +"**Introduce Docker image for Flower server** ([#2700](https://github.com/" +"adap/flower/pull/2700), [#2688](https://github.com/adap/flower/pull/2688), " +"[#2705](https://github.com/adap/flower/pull/2705), [#2695](https://github." +"com/adap/flower/pull/2695), [#2747](https://github.com/adap/flower/" +"pull/2747), [#2746](https://github.com/adap/flower/pull/2746), [#2680]" +"(https://github.com/adap/flower/pull/2680), [#2682](https://github.com/adap/" +"flower/pull/2682), [#2701](https://github.com/adap/flower/pull/2701))" msgstr "" #: ../../source/ref-changelog.md:203 msgid "" -"The Flower server can now be run using an official Docker image. A new " -"how-to guide explains [how to run Flower using " -"Docker](https://flower.ai/docs/framework/how-to-run-flower-using-" -"docker.html). An official Flower client Docker image will follow." +"The Flower server can now be run using an official Docker image. A new how-" +"to guide explains [how to run Flower using Docker](https://flower.ai/docs/" +"framework/how-to-run-flower-using-docker.html). An official Flower client " +"Docker image will follow." msgstr "" #: ../../source/ref-changelog.md:205 msgid "" -"**Introduce** `flower-via-docker-compose` **example** " -"([#2626](https://github.com/adap/flower/pull/2626))" +"**Introduce** `flower-via-docker-compose` **example** ([#2626](https://" +"github.com/adap/flower/pull/2626))" msgstr "" #: ../../source/ref-changelog.md:207 msgid "" -"**Introduce** `quickstart-sklearn-tabular` **example** " -"([#2719](https://github.com/adap/flower/pull/2719))" +"**Introduce** `quickstart-sklearn-tabular` **example** ([#2719](https://" +"github.com/adap/flower/pull/2719))" msgstr "" #: ../../source/ref-changelog.md:209 msgid "" -"**Introduce** `custom-metrics` **example** " -"([#1958](https://github.com/adap/flower/pull/1958))" +"**Introduce** `custom-metrics` **example** ([#1958](https://github.com/adap/" +"flower/pull/1958))" msgstr "" #: ../../source/ref-changelog.md:211 msgid "" -"**Update code examples to use Flower Datasets** " -"([#2450](https://github.com/adap/flower/pull/2450), " -"[#2456](https://github.com/adap/flower/pull/2456), " -"[#2318](https://github.com/adap/flower/pull/2318), " -"[#2712](https://github.com/adap/flower/pull/2712))" +"**Update code examples to use Flower Datasets** ([#2450](https://github.com/" +"adap/flower/pull/2450), [#2456](https://github.com/adap/flower/pull/2456), " +"[#2318](https://github.com/adap/flower/pull/2318), [#2712](https://github." +"com/adap/flower/pull/2712))" msgstr "" #: ../../source/ref-changelog.md:213 msgid "" -"Several code examples were updated to use [Flower " -"Datasets](https://flower.ai/docs/datasets/)." +"Several code examples were updated to use [Flower Datasets](https://flower." +"ai/docs/datasets/)." msgstr "" #: ../../source/ref-changelog.md:215 msgid "" -"**General updates to Flower Examples** " -"([#2381](https://github.com/adap/flower/pull/2381), " -"[#2805](https://github.com/adap/flower/pull/2805), " -"[#2782](https://github.com/adap/flower/pull/2782), " -"[#2806](https://github.com/adap/flower/pull/2806), " -"[#2829](https://github.com/adap/flower/pull/2829), " -"[#2825](https://github.com/adap/flower/pull/2825), " -"[#2816](https://github.com/adap/flower/pull/2816), " -"[#2726](https://github.com/adap/flower/pull/2726), " -"[#2659](https://github.com/adap/flower/pull/2659), " -"[#2655](https://github.com/adap/flower/pull/2655))" +"**General updates to Flower Examples** ([#2381](https://github.com/adap/" +"flower/pull/2381), [#2805](https://github.com/adap/flower/pull/2805), [#2782]" +"(https://github.com/adap/flower/pull/2782), [#2806](https://github.com/adap/" +"flower/pull/2806), [#2829](https://github.com/adap/flower/pull/2829), [#2825]" +"(https://github.com/adap/flower/pull/2825), [#2816](https://github.com/adap/" +"flower/pull/2816), [#2726](https://github.com/adap/flower/pull/2726), [#2659]" +"(https://github.com/adap/flower/pull/2659), [#2655](https://github.com/adap/" +"flower/pull/2655))" msgstr "" #: ../../source/ref-changelog.md:217 @@ -15840,8 +16392,8 @@ msgstr "" #: ../../source/ref-changelog.md:221 msgid "" -"HFedXGBoost ([#2226](https://github.com/adap/flower/pull/2226), " -"[#2771](https://github.com/adap/flower/pull/2771))" +"HFedXGBoost ([#2226](https://github.com/adap/flower/pull/2226), [#2771]" +"(https://github.com/adap/flower/pull/2771))" msgstr "" #: ../../source/ref-changelog.md:222 @@ -15866,149 +16418,119 @@ msgstr "" #: ../../source/ref-changelog.md:228 msgid "" -"**Improve documentation** " -"([#2674](https://github.com/adap/flower/pull/2674), " -"[#2480](https://github.com/adap/flower/pull/2480), " -"[#2826](https://github.com/adap/flower/pull/2826), " -"[#2727](https://github.com/adap/flower/pull/2727), " -"[#2761](https://github.com/adap/flower/pull/2761), " -"[#2900](https://github.com/adap/flower/pull/2900))" +"**Improve documentation** ([#2674](https://github.com/adap/flower/" +"pull/2674), [#2480](https://github.com/adap/flower/pull/2480), [#2826]" +"(https://github.com/adap/flower/pull/2826), [#2727](https://github.com/adap/" +"flower/pull/2727), [#2761](https://github.com/adap/flower/pull/2761), [#2900]" +"(https://github.com/adap/flower/pull/2900))" msgstr "" #: ../../source/ref-changelog.md:230 msgid "" -"**Improved testing and development infrastructure** " -"([#2797](https://github.com/adap/flower/pull/2797), " -"[#2676](https://github.com/adap/flower/pull/2676), " -"[#2644](https://github.com/adap/flower/pull/2644), " -"[#2656](https://github.com/adap/flower/pull/2656), " -"[#2848](https://github.com/adap/flower/pull/2848), " -"[#2675](https://github.com/adap/flower/pull/2675), " -"[#2735](https://github.com/adap/flower/pull/2735), " -"[#2767](https://github.com/adap/flower/pull/2767), " -"[#2732](https://github.com/adap/flower/pull/2732), " -"[#2744](https://github.com/adap/flower/pull/2744), " -"[#2681](https://github.com/adap/flower/pull/2681), " -"[#2699](https://github.com/adap/flower/pull/2699), " -"[#2745](https://github.com/adap/flower/pull/2745), " -"[#2734](https://github.com/adap/flower/pull/2734), " -"[#2731](https://github.com/adap/flower/pull/2731), " -"[#2652](https://github.com/adap/flower/pull/2652), " -"[#2720](https://github.com/adap/flower/pull/2720), " -"[#2721](https://github.com/adap/flower/pull/2721), " -"[#2717](https://github.com/adap/flower/pull/2717), " -"[#2864](https://github.com/adap/flower/pull/2864), " -"[#2694](https://github.com/adap/flower/pull/2694), " -"[#2709](https://github.com/adap/flower/pull/2709), " -"[#2658](https://github.com/adap/flower/pull/2658), " -"[#2796](https://github.com/adap/flower/pull/2796), " -"[#2692](https://github.com/adap/flower/pull/2692), " -"[#2657](https://github.com/adap/flower/pull/2657), " -"[#2813](https://github.com/adap/flower/pull/2813), " -"[#2661](https://github.com/adap/flower/pull/2661), " -"[#2398](https://github.com/adap/flower/pull/2398))" +"**Improved testing and development infrastructure** ([#2797](https://github." +"com/adap/flower/pull/2797), [#2676](https://github.com/adap/flower/" +"pull/2676), [#2644](https://github.com/adap/flower/pull/2644), [#2656]" +"(https://github.com/adap/flower/pull/2656), [#2848](https://github.com/adap/" +"flower/pull/2848), [#2675](https://github.com/adap/flower/pull/2675), [#2735]" +"(https://github.com/adap/flower/pull/2735), [#2767](https://github.com/adap/" +"flower/pull/2767), [#2732](https://github.com/adap/flower/pull/2732), [#2744]" +"(https://github.com/adap/flower/pull/2744), [#2681](https://github.com/adap/" +"flower/pull/2681), [#2699](https://github.com/adap/flower/pull/2699), [#2745]" +"(https://github.com/adap/flower/pull/2745), [#2734](https://github.com/adap/" +"flower/pull/2734), [#2731](https://github.com/adap/flower/pull/2731), [#2652]" +"(https://github.com/adap/flower/pull/2652), [#2720](https://github.com/adap/" +"flower/pull/2720), [#2721](https://github.com/adap/flower/pull/2721), [#2717]" +"(https://github.com/adap/flower/pull/2717), [#2864](https://github.com/adap/" +"flower/pull/2864), [#2694](https://github.com/adap/flower/pull/2694), [#2709]" +"(https://github.com/adap/flower/pull/2709), [#2658](https://github.com/adap/" +"flower/pull/2658), [#2796](https://github.com/adap/flower/pull/2796), [#2692]" +"(https://github.com/adap/flower/pull/2692), [#2657](https://github.com/adap/" +"flower/pull/2657), [#2813](https://github.com/adap/flower/pull/2813), [#2661]" +"(https://github.com/adap/flower/pull/2661), [#2398](https://github.com/adap/" +"flower/pull/2398))" msgstr "" #: ../../source/ref-changelog.md:232 msgid "" -"The Flower testing and development infrastructure has received " -"substantial updates. This makes Flower 1.7 the most tested release ever." +"The Flower testing and development infrastructure has received substantial " +"updates. This makes Flower 1.7 the most tested release ever." msgstr "" #: ../../source/ref-changelog.md:234 msgid "" -"**Update dependencies** " -"([#2753](https://github.com/adap/flower/pull/2753), " -"[#2651](https://github.com/adap/flower/pull/2651), " -"[#2739](https://github.com/adap/flower/pull/2739), " -"[#2837](https://github.com/adap/flower/pull/2837), " -"[#2788](https://github.com/adap/flower/pull/2788), " -"[#2811](https://github.com/adap/flower/pull/2811), " -"[#2774](https://github.com/adap/flower/pull/2774), " -"[#2790](https://github.com/adap/flower/pull/2790), " -"[#2751](https://github.com/adap/flower/pull/2751), " -"[#2850](https://github.com/adap/flower/pull/2850), " -"[#2812](https://github.com/adap/flower/pull/2812), " -"[#2872](https://github.com/adap/flower/pull/2872), " -"[#2736](https://github.com/adap/flower/pull/2736), " -"[#2756](https://github.com/adap/flower/pull/2756), " -"[#2857](https://github.com/adap/flower/pull/2857), " -"[#2757](https://github.com/adap/flower/pull/2757), " -"[#2810](https://github.com/adap/flower/pull/2810), " -"[#2740](https://github.com/adap/flower/pull/2740), " -"[#2789](https://github.com/adap/flower/pull/2789))" +"**Update dependencies** ([#2753](https://github.com/adap/flower/pull/2753), " +"[#2651](https://github.com/adap/flower/pull/2651), [#2739](https://github." +"com/adap/flower/pull/2739), [#2837](https://github.com/adap/flower/" +"pull/2837), [#2788](https://github.com/adap/flower/pull/2788), [#2811]" +"(https://github.com/adap/flower/pull/2811), [#2774](https://github.com/adap/" +"flower/pull/2774), [#2790](https://github.com/adap/flower/pull/2790), [#2751]" +"(https://github.com/adap/flower/pull/2751), [#2850](https://github.com/adap/" +"flower/pull/2850), [#2812](https://github.com/adap/flower/pull/2812), [#2872]" +"(https://github.com/adap/flower/pull/2872), [#2736](https://github.com/adap/" +"flower/pull/2736), [#2756](https://github.com/adap/flower/pull/2756), [#2857]" +"(https://github.com/adap/flower/pull/2857), [#2757](https://github.com/adap/" +"flower/pull/2757), [#2810](https://github.com/adap/flower/pull/2810), [#2740]" +"(https://github.com/adap/flower/pull/2740), [#2789](https://github.com/adap/" +"flower/pull/2789))" msgstr "" #: ../../source/ref-changelog.md:236 msgid "" -"**General improvements** " -"([#2803](https://github.com/adap/flower/pull/2803), " -"[#2847](https://github.com/adap/flower/pull/2847), " -"[#2877](https://github.com/adap/flower/pull/2877), " -"[#2690](https://github.com/adap/flower/pull/2690), " -"[#2889](https://github.com/adap/flower/pull/2889), " -"[#2874](https://github.com/adap/flower/pull/2874), " -"[#2819](https://github.com/adap/flower/pull/2819), " -"[#2689](https://github.com/adap/flower/pull/2689), " -"[#2457](https://github.com/adap/flower/pull/2457), " -"[#2870](https://github.com/adap/flower/pull/2870), " -"[#2669](https://github.com/adap/flower/pull/2669), " -"[#2876](https://github.com/adap/flower/pull/2876), " -"[#2885](https://github.com/adap/flower/pull/2885), " -"[#2858](https://github.com/adap/flower/pull/2858), " -"[#2867](https://github.com/adap/flower/pull/2867), " -"[#2351](https://github.com/adap/flower/pull/2351), " -"[#2886](https://github.com/adap/flower/pull/2886), " -"[#2860](https://github.com/adap/flower/pull/2860), " -"[#2828](https://github.com/adap/flower/pull/2828), " -"[#2869](https://github.com/adap/flower/pull/2869), " -"[#2875](https://github.com/adap/flower/pull/2875), " -"[#2733](https://github.com/adap/flower/pull/2733), " -"[#2488](https://github.com/adap/flower/pull/2488), " -"[#2646](https://github.com/adap/flower/pull/2646), " -"[#2879](https://github.com/adap/flower/pull/2879), " -"[#2821](https://github.com/adap/flower/pull/2821), " -"[#2855](https://github.com/adap/flower/pull/2855), " -"[#2800](https://github.com/adap/flower/pull/2800), " -"[#2807](https://github.com/adap/flower/pull/2807), " -"[#2801](https://github.com/adap/flower/pull/2801), " -"[#2804](https://github.com/adap/flower/pull/2804), " -"[#2851](https://github.com/adap/flower/pull/2851), " -"[#2787](https://github.com/adap/flower/pull/2787), " -"[#2852](https://github.com/adap/flower/pull/2852), " -"[#2672](https://github.com/adap/flower/pull/2672), " -"[#2759](https://github.com/adap/flower/pull/2759))" +"**General improvements** ([#2803](https://github.com/adap/flower/pull/2803), " +"[#2847](https://github.com/adap/flower/pull/2847), [#2877](https://github." +"com/adap/flower/pull/2877), [#2690](https://github.com/adap/flower/" +"pull/2690), [#2889](https://github.com/adap/flower/pull/2889), [#2874]" +"(https://github.com/adap/flower/pull/2874), [#2819](https://github.com/adap/" +"flower/pull/2819), [#2689](https://github.com/adap/flower/pull/2689), [#2457]" +"(https://github.com/adap/flower/pull/2457), [#2870](https://github.com/adap/" +"flower/pull/2870), [#2669](https://github.com/adap/flower/pull/2669), [#2876]" +"(https://github.com/adap/flower/pull/2876), [#2885](https://github.com/adap/" +"flower/pull/2885), [#2858](https://github.com/adap/flower/pull/2858), [#2867]" +"(https://github.com/adap/flower/pull/2867), [#2351](https://github.com/adap/" +"flower/pull/2351), [#2886](https://github.com/adap/flower/pull/2886), [#2860]" +"(https://github.com/adap/flower/pull/2860), [#2828](https://github.com/adap/" +"flower/pull/2828), [#2869](https://github.com/adap/flower/pull/2869), [#2875]" +"(https://github.com/adap/flower/pull/2875), [#2733](https://github.com/adap/" +"flower/pull/2733), [#2488](https://github.com/adap/flower/pull/2488), [#2646]" +"(https://github.com/adap/flower/pull/2646), [#2879](https://github.com/adap/" +"flower/pull/2879), [#2821](https://github.com/adap/flower/pull/2821), [#2855]" +"(https://github.com/adap/flower/pull/2855), [#2800](https://github.com/adap/" +"flower/pull/2800), [#2807](https://github.com/adap/flower/pull/2807), [#2801]" +"(https://github.com/adap/flower/pull/2801), [#2804](https://github.com/adap/" +"flower/pull/2804), [#2851](https://github.com/adap/flower/pull/2851), [#2787]" +"(https://github.com/adap/flower/pull/2787), [#2852](https://github.com/adap/" +"flower/pull/2852), [#2672](https://github.com/adap/flower/pull/2672), [#2759]" +"(https://github.com/adap/flower/pull/2759))" msgstr "" #: ../../source/ref-changelog.md:240 msgid "" -"**Deprecate** `start_numpy_client` " -"([#2563](https://github.com/adap/flower/pull/2563), " -"[#2718](https://github.com/adap/flower/pull/2718))" +"**Deprecate** `start_numpy_client` ([#2563](https://github.com/adap/flower/" +"pull/2563), [#2718](https://github.com/adap/flower/pull/2718))" msgstr "" #: ../../source/ref-changelog.md:242 msgid "" "Until now, clients of type `NumPyClient` needed to be started via " -"`start_numpy_client`. In our efforts to consolidate framework APIs, we " -"have introduced changes, and now all client types should start via " -"`start_client`. To continue using `NumPyClient` clients, you simply need " -"to first call the `.to_client()` method and then pass returned `Client` " -"object to `start_client`. The examples and the documentation have been " -"updated accordingly." +"`start_numpy_client`. In our efforts to consolidate framework APIs, we have " +"introduced changes, and now all client types should start via " +"`start_client`. To continue using `NumPyClient` clients, you simply need to " +"first call the `.to_client()` method and then pass returned `Client` object " +"to `start_client`. The examples and the documentation have been updated " +"accordingly." msgstr "" #: ../../source/ref-changelog.md:244 msgid "" -"**Deprecate legacy DP wrappers** " -"([#2749](https://github.com/adap/flower/pull/2749))" +"**Deprecate legacy DP wrappers** ([#2749](https://github.com/adap/flower/" +"pull/2749))" msgstr "" #: ../../source/ref-changelog.md:246 msgid "" -"Legacy DP wrapper classes are deprecated, but still functional. This is " -"in preparation for an all-new pluggable version of differential privacy " -"support in Flower." +"Legacy DP wrapper classes are deprecated, but still functional. This is in " +"preparation for an all-new pluggable version of differential privacy support " +"in Flower." msgstr "" #: ../../source/ref-changelog.md:248 @@ -16019,28 +16541,26 @@ msgstr "" #: ../../source/ref-changelog.md:250 msgid "" -"**Rename** `certificates` **to** `root_certificates` **in** `Driver` " -"([#2890](https://github.com/adap/flower/pull/2890))" +"**Rename** `certificates` **to** `root_certificates` **in** `Driver` ([#2890]" +"(https://github.com/adap/flower/pull/2890))" msgstr "" #: ../../source/ref-changelog.md:252 msgid "" -"**Drop experimental** `Task` **fields** " -"([#2866](https://github.com/adap/flower/pull/2866), " -"[#2865](https://github.com/adap/flower/pull/2865))" +"**Drop experimental** `Task` **fields** ([#2866](https://github.com/adap/" +"flower/pull/2866), [#2865](https://github.com/adap/flower/pull/2865))" msgstr "" #: ../../source/ref-changelog.md:254 msgid "" "Experimental fields `sa`, `legacy_server_message` and " -"`legacy_client_message` were removed from `Task` message. The removed " -"fields are superseded by the new `RecordSet` abstraction." +"`legacy_client_message` were removed from `Task` message. The removed fields " +"are superseded by the new `RecordSet` abstraction." msgstr "" #: ../../source/ref-changelog.md:256 msgid "" -"**Retire MXNet examples** " -"([#2724](https://github.com/adap/flower/pull/2724))" +"**Retire MXNet examples** ([#2724](https://github.com/adap/flower/pull/2724))" msgstr "" #: ../../source/ref-changelog.md:258 @@ -16058,65 +16578,62 @@ msgstr "" msgid "" "`Aashish Kolluri`, `Adam Narozniak`, `Alessio Mora`, `Barathwaja S`, " "`Charles Beauville`, `Daniel J. Beutel`, `Daniel Nata Nugraha`, `Gabriel " -"Mota`, `Heng Pan`, `Ivan Agarský`, `JS.KIM`, `Javier`, `Marius Schlegel`," -" `Navin Chandra`, `Nic Lane`, `Peterpan828`, `Qinbin Li`, `Shaz-hash`, " -"`Steve Laskaridis`, `Taner Topal`, `William Lindskog`, `Yan Gao`, " -"`cnxdeveloper`, `k3nfalt` " +"Mota`, `Heng Pan`, `Ivan Agarský`, `JS.KIM`, `Javier`, `Marius Schlegel`, " +"`Navin Chandra`, `Nic Lane`, `Peterpan828`, `Qinbin Li`, `Shaz-hash`, `Steve " +"Laskaridis`, `Taner Topal`, `William Lindskog`, `Yan Gao`, `cnxdeveloper`, " +"`k3nfalt` " msgstr "" #: ../../source/ref-changelog.md:270 msgid "" -"**Add experimental support for Python 3.12** " -"([#2565](https://github.com/adap/flower/pull/2565))" +"**Add experimental support for Python 3.12** ([#2565](https://github.com/" +"adap/flower/pull/2565))" msgstr "" #: ../../source/ref-changelog.md:272 msgid "" -"**Add new XGBoost examples** " -"([#2612](https://github.com/adap/flower/pull/2612), " -"[#2554](https://github.com/adap/flower/pull/2554), " -"[#2617](https://github.com/adap/flower/pull/2617), " -"[#2618](https://github.com/adap/flower/pull/2618), " -"[#2619](https://github.com/adap/flower/pull/2619), " -"[#2567](https://github.com/adap/flower/pull/2567))" +"**Add new XGBoost examples** ([#2612](https://github.com/adap/flower/" +"pull/2612), [#2554](https://github.com/adap/flower/pull/2554), [#2617]" +"(https://github.com/adap/flower/pull/2617), [#2618](https://github.com/adap/" +"flower/pull/2618), [#2619](https://github.com/adap/flower/pull/2619), [#2567]" +"(https://github.com/adap/flower/pull/2567))" msgstr "" #: ../../source/ref-changelog.md:274 msgid "" -"We have added a new `xgboost-quickstart` example alongside a new " -"`xgboost-comprehensive` example that goes more in-depth." +"We have added a new `xgboost-quickstart` example alongside a new `xgboost-" +"comprehensive` example that goes more in-depth." msgstr "" #: ../../source/ref-changelog.md:276 msgid "" -"**Add Vertical FL example** " -"([#2598](https://github.com/adap/flower/pull/2598))" +"**Add Vertical FL example** ([#2598](https://github.com/adap/flower/" +"pull/2598))" msgstr "" #: ../../source/ref-changelog.md:278 msgid "" -"We had many questions about Vertical Federated Learning using Flower, so " -"we decided to add an simple example for it on the [Titanic " -"dataset](https://www.kaggle.com/competitions/titanic/data) alongside a " -"tutorial (in the README)." +"We had many questions about Vertical Federated Learning using Flower, so we " +"decided to add an simple example for it on the [Titanic dataset](https://www." +"kaggle.com/competitions/titanic/data) alongside a tutorial (in the README)." msgstr "" #: ../../source/ref-changelog.md:280 msgid "" -"**Support custom** `ClientManager` **in** `start_driver()` " -"([#2292](https://github.com/adap/flower/pull/2292))" +"**Support custom** `ClientManager` **in** `start_driver()` ([#2292](https://" +"github.com/adap/flower/pull/2292))" msgstr "" #: ../../source/ref-changelog.md:282 msgid "" -"**Update REST API to support create and delete nodes** " -"([#2283](https://github.com/adap/flower/pull/2283))" +"**Update REST API to support create and delete nodes** ([#2283](https://" +"github.com/adap/flower/pull/2283))" msgstr "" #: ../../source/ref-changelog.md:284 msgid "" -"**Update the Android SDK** " -"([#2187](https://github.com/adap/flower/pull/2187))" +"**Update the Android SDK** ([#2187](https://github.com/adap/flower/" +"pull/2187))" msgstr "" #: ../../source/ref-changelog.md:286 @@ -16125,11 +16642,10 @@ msgstr "" #: ../../source/ref-changelog.md:288 msgid "" -"**Update the C++ SDK** " -"([#2537](https://github.com/adap/flower/pull/2537), " -"[#2528](https://github.com/adap/flower/pull/2528), " -"[#2523](https://github.com/adap/flower/pull/2523), " -"[#2522](https://github.com/adap/flower/pull/2522))" +"**Update the C++ SDK** ([#2537](https://github.com/adap/flower/pull/2537), " +"[#2528](https://github.com/adap/flower/pull/2528), [#2523](https://github." +"com/adap/flower/pull/2523), [#2522](https://github.com/adap/flower/" +"pull/2522))" msgstr "" #: ../../source/ref-changelog.md:290 @@ -16138,93 +16654,90 @@ msgstr "" #: ../../source/ref-changelog.md:292 msgid "" -"**Make HTTPS the new default** " -"([#2591](https://github.com/adap/flower/pull/2591), " -"[#2636](https://github.com/adap/flower/pull/2636))" +"**Make HTTPS the new default** ([#2591](https://github.com/adap/flower/" +"pull/2591), [#2636](https://github.com/adap/flower/pull/2636))" msgstr "" #: ../../source/ref-changelog.md:294 msgid "" "Flower is moving to HTTPS by default. The new `flower-server` requires " -"passing `--certificates`, but users can enable `--insecure` to use HTTP " -"for prototyping. The same applies to `flower-client`, which can either " -"use user-provided credentials or gRPC-bundled certificates to connect to " -"an HTTPS-enabled server or requires opt-out via passing `--insecure` to " -"enable insecure HTTP connections." +"passing `--certificates`, but users can enable `--insecure` to use HTTP for " +"prototyping. The same applies to `flower-client`, which can either use user-" +"provided credentials or gRPC-bundled certificates to connect to an HTTPS-" +"enabled server or requires opt-out via passing `--insecure` to enable " +"insecure HTTP connections." msgstr "" #: ../../source/ref-changelog.md:296 msgid "" -"For backward compatibility, `start_client()` and `start_numpy_client()` " -"will still start in insecure mode by default. In a future release, " -"insecure connections will require user opt-in by passing `insecure=True`." +"For backward compatibility, `start_client()` and `start_numpy_client()` will " +"still start in insecure mode by default. In a future release, insecure " +"connections will require user opt-in by passing `insecure=True`." msgstr "" #: ../../source/ref-changelog.md:298 msgid "" "**Unify client API** ([#2303](https://github.com/adap/flower/pull/2303), " -"[#2390](https://github.com/adap/flower/pull/2390), " -"[#2493](https://github.com/adap/flower/pull/2493))" +"[#2390](https://github.com/adap/flower/pull/2390), [#2493](https://github." +"com/adap/flower/pull/2493))" msgstr "" #: ../../source/ref-changelog.md:300 msgid "" -"Using the `client_fn`, Flower clients can interchangeably run as " -"standalone processes (i.e. via `start_client`) or in simulation (i.e. via" -" `start_simulation`) without requiring changes to how the client class is" -" defined and instantiated. The `to_client()` function is introduced to " +"Using the `client_fn`, Flower clients can interchangeably run as standalone " +"processes (i.e. via `start_client`) or in simulation (i.e. via " +"`start_simulation`) without requiring changes to how the client class is " +"defined and instantiated. The `to_client()` function is introduced to " "convert a `NumPyClient` to a `Client`." msgstr "" #: ../../source/ref-changelog.md:302 msgid "" -"**Add new** `Bulyan` **strategy** " -"([#1817](https://github.com/adap/flower/pull/1817), " -"[#1891](https://github.com/adap/flower/pull/1891))" +"**Add new** `Bulyan` **strategy** ([#1817](https://github.com/adap/flower/" +"pull/1817), [#1891](https://github.com/adap/flower/pull/1891))" msgstr "" #: ../../source/ref-changelog.md:304 msgid "" -"The new `Bulyan` strategy implements Bulyan by [El Mhamdi et al., " -"2018](https://arxiv.org/abs/1802.07927)" +"The new `Bulyan` strategy implements Bulyan by [El Mhamdi et al., 2018]" +"(https://arxiv.org/abs/1802.07927)" msgstr "" #: ../../source/ref-changelog.md:306 msgid "" -"**Add new** `XGB Bagging` **strategy** " -"([#2611](https://github.com/adap/flower/pull/2611))" +"**Add new** `XGB Bagging` **strategy** ([#2611](https://github.com/adap/" +"flower/pull/2611))" msgstr "" #: ../../source/ref-changelog.md:308 ../../source/ref-changelog.md:310 msgid "" -"**Introduce `WorkloadState`** " -"([#2564](https://github.com/adap/flower/pull/2564), " -"[#2632](https://github.com/adap/flower/pull/2632))" +"**Introduce `WorkloadState`** ([#2564](https://github.com/adap/flower/" +"pull/2564), [#2632](https://github.com/adap/flower/pull/2632))" msgstr "" #: ../../source/ref-changelog.md:314 msgid "" -"FedProx ([#2210](https://github.com/adap/flower/pull/2210), " -"[#2286](https://github.com/adap/flower/pull/2286), " -"[#2509](https://github.com/adap/flower/pull/2509))" +"FedProx ([#2210](https://github.com/adap/flower/pull/2210), [#2286](https://" +"github.com/adap/flower/pull/2286), [#2509](https://github.com/adap/flower/" +"pull/2509))" msgstr "" #: ../../source/ref-changelog.md:316 msgid "" -"Baselines Docs ([#2290](https://github.com/adap/flower/pull/2290), " -"[#2400](https://github.com/adap/flower/pull/2400))" +"Baselines Docs ([#2290](https://github.com/adap/flower/pull/2290), [#2400]" +"(https://github.com/adap/flower/pull/2400))" msgstr "" #: ../../source/ref-changelog.md:318 msgid "" -"FedMLB ([#2340](https://github.com/adap/flower/pull/2340), " -"[#2507](https://github.com/adap/flower/pull/2507))" +"FedMLB ([#2340](https://github.com/adap/flower/pull/2340), [#2507](https://" +"github.com/adap/flower/pull/2507))" msgstr "" #: ../../source/ref-changelog.md:320 msgid "" -"TAMUNA ([#2254](https://github.com/adap/flower/pull/2254), " -"[#2508](https://github.com/adap/flower/pull/2508))" +"TAMUNA ([#2254](https://github.com/adap/flower/pull/2254), [#2508](https://" +"github.com/adap/flower/pull/2508))" msgstr "" #: ../../source/ref-changelog.md:322 @@ -16257,125 +16770,106 @@ msgstr "" #: ../../source/ref-changelog.md:336 msgid "" -"FedBN ([#2608](https://github.com/adap/flower/pull/2608), " -"[#2615](https://github.com/adap/flower/pull/2615))" +"FedBN ([#2608](https://github.com/adap/flower/pull/2608), [#2615](https://" +"github.com/adap/flower/pull/2615))" msgstr "" #: ../../source/ref-changelog.md:338 msgid "" -"**General updates to Flower Examples** " -"([#2384](https://github.com/adap/flower/pull/2384), " -"[#2425](https://github.com/adap/flower/pull/2425), " -"[#2526](https://github.com/adap/flower/pull/2526), " -"[#2302](https://github.com/adap/flower/pull/2302), " -"[#2545](https://github.com/adap/flower/pull/2545))" +"**General updates to Flower Examples** ([#2384](https://github.com/adap/" +"flower/pull/2384), [#2425](https://github.com/adap/flower/pull/2425), [#2526]" +"(https://github.com/adap/flower/pull/2526), [#2302](https://github.com/adap/" +"flower/pull/2302), [#2545](https://github.com/adap/flower/pull/2545))" msgstr "" #: ../../source/ref-changelog.md:340 msgid "" -"**General updates to Flower Baselines** " -"([#2301](https://github.com/adap/flower/pull/2301), " -"[#2305](https://github.com/adap/flower/pull/2305), " -"[#2307](https://github.com/adap/flower/pull/2307), " -"[#2327](https://github.com/adap/flower/pull/2327), " -"[#2435](https://github.com/adap/flower/pull/2435), " -"[#2462](https://github.com/adap/flower/pull/2462), " -"[#2463](https://github.com/adap/flower/pull/2463), " -"[#2461](https://github.com/adap/flower/pull/2461), " -"[#2469](https://github.com/adap/flower/pull/2469), " -"[#2466](https://github.com/adap/flower/pull/2466), " -"[#2471](https://github.com/adap/flower/pull/2471), " -"[#2472](https://github.com/adap/flower/pull/2472), " -"[#2470](https://github.com/adap/flower/pull/2470))" +"**General updates to Flower Baselines** ([#2301](https://github.com/adap/" +"flower/pull/2301), [#2305](https://github.com/adap/flower/pull/2305), [#2307]" +"(https://github.com/adap/flower/pull/2307), [#2327](https://github.com/adap/" +"flower/pull/2327), [#2435](https://github.com/adap/flower/pull/2435), [#2462]" +"(https://github.com/adap/flower/pull/2462), [#2463](https://github.com/adap/" +"flower/pull/2463), [#2461](https://github.com/adap/flower/pull/2461), [#2469]" +"(https://github.com/adap/flower/pull/2469), [#2466](https://github.com/adap/" +"flower/pull/2466), [#2471](https://github.com/adap/flower/pull/2471), [#2472]" +"(https://github.com/adap/flower/pull/2472), [#2470](https://github.com/adap/" +"flower/pull/2470))" msgstr "" #: ../../source/ref-changelog.md:342 msgid "" -"**General updates to the simulation engine** " -"([#2331](https://github.com/adap/flower/pull/2331), " -"[#2447](https://github.com/adap/flower/pull/2447), " -"[#2448](https://github.com/adap/flower/pull/2448), " -"[#2294](https://github.com/adap/flower/pull/2294))" +"**General updates to the simulation engine** ([#2331](https://github.com/" +"adap/flower/pull/2331), [#2447](https://github.com/adap/flower/pull/2447), " +"[#2448](https://github.com/adap/flower/pull/2448), [#2294](https://github." +"com/adap/flower/pull/2294))" msgstr "" #: ../../source/ref-changelog.md:344 msgid "" -"**General updates to Flower SDKs** " -"([#2288](https://github.com/adap/flower/pull/2288), " -"[#2429](https://github.com/adap/flower/pull/2429), " -"[#2555](https://github.com/adap/flower/pull/2555), " -"[#2543](https://github.com/adap/flower/pull/2543), " -"[#2544](https://github.com/adap/flower/pull/2544), " -"[#2597](https://github.com/adap/flower/pull/2597), " -"[#2623](https://github.com/adap/flower/pull/2623))" +"**General updates to Flower SDKs** ([#2288](https://github.com/adap/flower/" +"pull/2288), [#2429](https://github.com/adap/flower/pull/2429), [#2555]" +"(https://github.com/adap/flower/pull/2555), [#2543](https://github.com/adap/" +"flower/pull/2543), [#2544](https://github.com/adap/flower/pull/2544), [#2597]" +"(https://github.com/adap/flower/pull/2597), [#2623](https://github.com/adap/" +"flower/pull/2623))" msgstr "" #: ../../source/ref-changelog.md:346 msgid "" -"**General improvements** " -"([#2309](https://github.com/adap/flower/pull/2309), " -"[#2310](https://github.com/adap/flower/pull/2310), " -"[#2313](https://github.com/adap/flower/pull/2313), " -"[#2316](https://github.com/adap/flower/pull/2316), " -"[#2317](https://github.com/adap/flower/pull/2317), " -"[#2349](https://github.com/adap/flower/pull/2349), " -"[#2360](https://github.com/adap/flower/pull/2360), " -"[#2402](https://github.com/adap/flower/pull/2402), " -"[#2446](https://github.com/adap/flower/pull/2446), " -"[#2561](https://github.com/adap/flower/pull/2561), " -"[#2273](https://github.com/adap/flower/pull/2273), " -"[#2267](https://github.com/adap/flower/pull/2267), " -"[#2274](https://github.com/adap/flower/pull/2274), " -"[#2275](https://github.com/adap/flower/pull/2275), " -"[#2432](https://github.com/adap/flower/pull/2432), " -"[#2251](https://github.com/adap/flower/pull/2251), " -"[#2321](https://github.com/adap/flower/pull/2321), " -"[#1936](https://github.com/adap/flower/pull/1936), " -"[#2408](https://github.com/adap/flower/pull/2408), " -"[#2413](https://github.com/adap/flower/pull/2413), " -"[#2401](https://github.com/adap/flower/pull/2401), " -"[#2531](https://github.com/adap/flower/pull/2531), " -"[#2534](https://github.com/adap/flower/pull/2534), " -"[#2535](https://github.com/adap/flower/pull/2535), " -"[#2521](https://github.com/adap/flower/pull/2521), " -"[#2553](https://github.com/adap/flower/pull/2553), " -"[#2596](https://github.com/adap/flower/pull/2596))" +"**General improvements** ([#2309](https://github.com/adap/flower/pull/2309), " +"[#2310](https://github.com/adap/flower/pull/2310), [#2313](https://github." +"com/adap/flower/pull/2313), [#2316](https://github.com/adap/flower/" +"pull/2316), [#2317](https://github.com/adap/flower/pull/2317), [#2349]" +"(https://github.com/adap/flower/pull/2349), [#2360](https://github.com/adap/" +"flower/pull/2360), [#2402](https://github.com/adap/flower/pull/2402), [#2446]" +"(https://github.com/adap/flower/pull/2446), [#2561](https://github.com/adap/" +"flower/pull/2561), [#2273](https://github.com/adap/flower/pull/2273), [#2267]" +"(https://github.com/adap/flower/pull/2267), [#2274](https://github.com/adap/" +"flower/pull/2274), [#2275](https://github.com/adap/flower/pull/2275), [#2432]" +"(https://github.com/adap/flower/pull/2432), [#2251](https://github.com/adap/" +"flower/pull/2251), [#2321](https://github.com/adap/flower/pull/2321), [#1936]" +"(https://github.com/adap/flower/pull/1936), [#2408](https://github.com/adap/" +"flower/pull/2408), [#2413](https://github.com/adap/flower/pull/2413), [#2401]" +"(https://github.com/adap/flower/pull/2401), [#2531](https://github.com/adap/" +"flower/pull/2531), [#2534](https://github.com/adap/flower/pull/2534), [#2535]" +"(https://github.com/adap/flower/pull/2535), [#2521](https://github.com/adap/" +"flower/pull/2521), [#2553](https://github.com/adap/flower/pull/2553), [#2596]" +"(https://github.com/adap/flower/pull/2596))" msgstr "" #: ../../source/ref-changelog.md:348 ../../source/ref-changelog.md:438 #: ../../source/ref-changelog.md:502 ../../source/ref-changelog.md:556 #: ../../source/ref-changelog.md:623 -msgid "Flower received many improvements under the hood, too many to list here." +msgid "" +"Flower received many improvements under the hood, too many to list here." msgstr "" #: ../../source/ref-changelog.md:352 msgid "" -"**Remove support for Python 3.7** " -"([#2280](https://github.com/adap/flower/pull/2280), " -"[#2299](https://github.com/adap/flower/pull/2299), " -"[#2304](https://github.com/adap/flower/pull/2304), " -"[#2306](https://github.com/adap/flower/pull/2306), " -"[#2355](https://github.com/adap/flower/pull/2355), " -"[#2356](https://github.com/adap/flower/pull/2356))" +"**Remove support for Python 3.7** ([#2280](https://github.com/adap/flower/" +"pull/2280), [#2299](https://github.com/adap/flower/pull/2299), [#2304]" +"(https://github.com/adap/flower/pull/2304), [#2306](https://github.com/adap/" +"flower/pull/2306), [#2355](https://github.com/adap/flower/pull/2355), [#2356]" +"(https://github.com/adap/flower/pull/2356))" msgstr "" #: ../../source/ref-changelog.md:354 msgid "" -"Python 3.7 support was deprecated in Flower 1.5, and this release removes" -" support. Flower now requires Python 3.8." +"Python 3.7 support was deprecated in Flower 1.5, and this release removes " +"support. Flower now requires Python 3.8." msgstr "" #: ../../source/ref-changelog.md:356 msgid "" -"**Remove experimental argument** `rest` **from** `start_client` " -"([#2324](https://github.com/adap/flower/pull/2324))" +"**Remove experimental argument** `rest` **from** `start_client` ([#2324]" +"(https://github.com/adap/flower/pull/2324))" msgstr "" #: ../../source/ref-changelog.md:358 msgid "" -"The (still experimental) argument `rest` was removed from `start_client` " -"and `start_numpy_client`. Use `transport=\"rest\"` to opt into the " -"experimental REST API instead." +"The (still experimental) argument `rest` was removed from `start_client` and " +"`start_numpy_client`. Use `transport=\"rest\"` to opt into the experimental " +"REST API instead." msgstr "" #: ../../source/ref-changelog.md:360 @@ -16393,125 +16887,108 @@ msgstr "" #: ../../source/ref-changelog.md:370 msgid "" -"**Introduce new simulation engine** " -"([#1969](https://github.com/adap/flower/pull/1969), " -"[#2221](https://github.com/adap/flower/pull/2221), " -"[#2248](https://github.com/adap/flower/pull/2248))" +"**Introduce new simulation engine** ([#1969](https://github.com/adap/flower/" +"pull/1969), [#2221](https://github.com/adap/flower/pull/2221), [#2248]" +"(https://github.com/adap/flower/pull/2248))" msgstr "" #: ../../source/ref-changelog.md:372 msgid "" "The new simulation engine has been rewritten from the ground up, yet it " -"remains fully backwards compatible. It offers much improved stability and" -" memory handling, especially when working with GPUs. Simulations " -"transparently adapt to different settings to scale simulation in CPU-" -"only, CPU+GPU, multi-GPU, or multi-node multi-GPU environments." +"remains fully backwards compatible. It offers much improved stability and " +"memory handling, especially when working with GPUs. Simulations " +"transparently adapt to different settings to scale simulation in CPU-only, " +"CPU+GPU, multi-GPU, or multi-node multi-GPU environments." msgstr "" #: ../../source/ref-changelog.md:374 msgid "" -"Comprehensive documentation includes a new [how-to run " -"simulations](https://flower.ai/docs/framework/how-to-run-" -"simulations.html) guide, new [simulation-" +"Comprehensive documentation includes a new [how-to run simulations](https://" +"flower.ai/docs/framework/how-to-run-simulations.html) guide, new [simulation-" "pytorch](https://flower.ai/docs/examples/simulation-pytorch.html) and " "[simulation-tensorflow](https://flower.ai/docs/examples/simulation-" -"tensorflow.html) notebooks, and a new [YouTube tutorial " -"series](https://www.youtube.com/watch?v=cRebUIGB5RU&list=PLNG4feLHqCWlnj8a_E1A_n5zr2-8pafTB)." +"tensorflow.html) notebooks, and a new [YouTube tutorial series](https://www." +"youtube.com/watch?v=cRebUIGB5RU&list=PLNG4feLHqCWlnj8a_E1A_n5zr2-8pafTB)." msgstr "" #: ../../source/ref-changelog.md:376 msgid "" -"**Restructure Flower Docs** " -"([#1824](https://github.com/adap/flower/pull/1824), " -"[#1865](https://github.com/adap/flower/pull/1865), " -"[#1884](https://github.com/adap/flower/pull/1884), " -"[#1887](https://github.com/adap/flower/pull/1887), " -"[#1919](https://github.com/adap/flower/pull/1919), " -"[#1922](https://github.com/adap/flower/pull/1922), " -"[#1920](https://github.com/adap/flower/pull/1920), " -"[#1923](https://github.com/adap/flower/pull/1923), " -"[#1924](https://github.com/adap/flower/pull/1924), " -"[#1962](https://github.com/adap/flower/pull/1962), " -"[#2006](https://github.com/adap/flower/pull/2006), " -"[#2133](https://github.com/adap/flower/pull/2133), " -"[#2203](https://github.com/adap/flower/pull/2203), " -"[#2215](https://github.com/adap/flower/pull/2215), " -"[#2122](https://github.com/adap/flower/pull/2122), " -"[#2223](https://github.com/adap/flower/pull/2223), " -"[#2219](https://github.com/adap/flower/pull/2219), " -"[#2232](https://github.com/adap/flower/pull/2232), " -"[#2233](https://github.com/adap/flower/pull/2233), " -"[#2234](https://github.com/adap/flower/pull/2234), " -"[#2235](https://github.com/adap/flower/pull/2235), " -"[#2237](https://github.com/adap/flower/pull/2237), " -"[#2238](https://github.com/adap/flower/pull/2238), " -"[#2242](https://github.com/adap/flower/pull/2242), " -"[#2231](https://github.com/adap/flower/pull/2231), " -"[#2243](https://github.com/adap/flower/pull/2243), " -"[#2227](https://github.com/adap/flower/pull/2227))" +"**Restructure Flower Docs** ([#1824](https://github.com/adap/flower/" +"pull/1824), [#1865](https://github.com/adap/flower/pull/1865), [#1884]" +"(https://github.com/adap/flower/pull/1884), [#1887](https://github.com/adap/" +"flower/pull/1887), [#1919](https://github.com/adap/flower/pull/1919), [#1922]" +"(https://github.com/adap/flower/pull/1922), [#1920](https://github.com/adap/" +"flower/pull/1920), [#1923](https://github.com/adap/flower/pull/1923), [#1924]" +"(https://github.com/adap/flower/pull/1924), [#1962](https://github.com/adap/" +"flower/pull/1962), [#2006](https://github.com/adap/flower/pull/2006), [#2133]" +"(https://github.com/adap/flower/pull/2133), [#2203](https://github.com/adap/" +"flower/pull/2203), [#2215](https://github.com/adap/flower/pull/2215), [#2122]" +"(https://github.com/adap/flower/pull/2122), [#2223](https://github.com/adap/" +"flower/pull/2223), [#2219](https://github.com/adap/flower/pull/2219), [#2232]" +"(https://github.com/adap/flower/pull/2232), [#2233](https://github.com/adap/" +"flower/pull/2233), [#2234](https://github.com/adap/flower/pull/2234), [#2235]" +"(https://github.com/adap/flower/pull/2235), [#2237](https://github.com/adap/" +"flower/pull/2237), [#2238](https://github.com/adap/flower/pull/2238), [#2242]" +"(https://github.com/adap/flower/pull/2242), [#2231](https://github.com/adap/" +"flower/pull/2231), [#2243](https://github.com/adap/flower/pull/2243), [#2227]" +"(https://github.com/adap/flower/pull/2227))" msgstr "" #: ../../source/ref-changelog.md:378 msgid "" -"Much effort went into a completely restructured Flower docs experience. " -"The documentation on [flower.ai/docs](https://flower.ai/docs) is now " -"divided into Flower Framework, Flower Baselines, Flower Android SDK, " -"Flower iOS SDK, and code example projects." +"Much effort went into a completely restructured Flower docs experience. The " +"documentation on [flower.ai/docs](https://flower.ai/docs) is now divided " +"into Flower Framework, Flower Baselines, Flower Android SDK, Flower iOS SDK, " +"and code example projects." msgstr "" #: ../../source/ref-changelog.md:380 msgid "" -"**Introduce Flower Swift SDK** " -"([#1858](https://github.com/adap/flower/pull/1858), " -"[#1897](https://github.com/adap/flower/pull/1897))" +"**Introduce Flower Swift SDK** ([#1858](https://github.com/adap/flower/" +"pull/1858), [#1897](https://github.com/adap/flower/pull/1897))" msgstr "" #: ../../source/ref-changelog.md:382 msgid "" -"This is the first preview release of the Flower Swift SDK. Flower support" -" on iOS is improving, and alongside the Swift SDK and code example, there" -" is now also an iOS quickstart tutorial." +"This is the first preview release of the Flower Swift SDK. Flower support on " +"iOS is improving, and alongside the Swift SDK and code example, there is now " +"also an iOS quickstart tutorial." msgstr "" #: ../../source/ref-changelog.md:384 msgid "" -"**Introduce Flower Android SDK** " -"([#2131](https://github.com/adap/flower/pull/2131))" +"**Introduce Flower Android SDK** ([#2131](https://github.com/adap/flower/" +"pull/2131))" msgstr "" #: ../../source/ref-changelog.md:386 msgid "" -"This is the first preview release of the Flower Kotlin SDK. Flower " -"support on Android is improving, and alongside the Kotlin SDK and code " -"example, there is now also an Android quickstart tutorial." +"This is the first preview release of the Flower Kotlin SDK. Flower support " +"on Android is improving, and alongside the Kotlin SDK and code example, " +"there is now also an Android quickstart tutorial." msgstr "" #: ../../source/ref-changelog.md:388 msgid "" -"**Introduce new end-to-end testing infrastructure** " -"([#1842](https://github.com/adap/flower/pull/1842), " -"[#2071](https://github.com/adap/flower/pull/2071), " -"[#2072](https://github.com/adap/flower/pull/2072), " -"[#2068](https://github.com/adap/flower/pull/2068), " -"[#2067](https://github.com/adap/flower/pull/2067), " -"[#2069](https://github.com/adap/flower/pull/2069), " -"[#2073](https://github.com/adap/flower/pull/2073), " -"[#2070](https://github.com/adap/flower/pull/2070), " -"[#2074](https://github.com/adap/flower/pull/2074), " -"[#2082](https://github.com/adap/flower/pull/2082), " -"[#2084](https://github.com/adap/flower/pull/2084), " -"[#2093](https://github.com/adap/flower/pull/2093), " -"[#2109](https://github.com/adap/flower/pull/2109), " -"[#2095](https://github.com/adap/flower/pull/2095), " -"[#2140](https://github.com/adap/flower/pull/2140), " -"[#2137](https://github.com/adap/flower/pull/2137), " -"[#2165](https://github.com/adap/flower/pull/2165))" +"**Introduce new end-to-end testing infrastructure** ([#1842](https://github." +"com/adap/flower/pull/1842), [#2071](https://github.com/adap/flower/" +"pull/2071), [#2072](https://github.com/adap/flower/pull/2072), [#2068]" +"(https://github.com/adap/flower/pull/2068), [#2067](https://github.com/adap/" +"flower/pull/2067), [#2069](https://github.com/adap/flower/pull/2069), [#2073]" +"(https://github.com/adap/flower/pull/2073), [#2070](https://github.com/adap/" +"flower/pull/2070), [#2074](https://github.com/adap/flower/pull/2074), [#2082]" +"(https://github.com/adap/flower/pull/2082), [#2084](https://github.com/adap/" +"flower/pull/2084), [#2093](https://github.com/adap/flower/pull/2093), [#2109]" +"(https://github.com/adap/flower/pull/2109), [#2095](https://github.com/adap/" +"flower/pull/2095), [#2140](https://github.com/adap/flower/pull/2140), [#2137]" +"(https://github.com/adap/flower/pull/2137), [#2165](https://github.com/adap/" +"flower/pull/2165))" msgstr "" #: ../../source/ref-changelog.md:390 msgid "" -"A new testing infrastructure ensures that new changes stay compatible " -"with existing framework integrations or strategies." +"A new testing infrastructure ensures that new changes stay compatible with " +"existing framework integrations or strategies." msgstr "" #: ../../source/ref-changelog.md:392 @@ -16520,124 +16997,121 @@ msgstr "" #: ../../source/ref-changelog.md:394 msgid "" -"Since Python 3.7 reached its end of life (EOL) on 2023-06-27, support for" -" Python 3.7 is now deprecated and will be removed in an upcoming release." +"Since Python 3.7 reached its end of life (EOL) on 2023-06-27, support for " +"Python 3.7 is now deprecated and will be removed in an upcoming release." msgstr "" #: ../../source/ref-changelog.md:396 msgid "" -"**Add new** `FedTrimmedAvg` **strategy** " -"([#1769](https://github.com/adap/flower/pull/1769), " -"[#1853](https://github.com/adap/flower/pull/1853))" +"**Add new** `FedTrimmedAvg` **strategy** ([#1769](https://github.com/adap/" +"flower/pull/1769), [#1853](https://github.com/adap/flower/pull/1853))" msgstr "" #: ../../source/ref-changelog.md:398 msgid "" -"The new `FedTrimmedAvg` strategy implements Trimmed Mean by [Dong Yin, " -"2018](https://arxiv.org/abs/1803.01498)." +"The new `FedTrimmedAvg` strategy implements Trimmed Mean by [Dong Yin, 2018]" +"(https://arxiv.org/abs/1803.01498)." msgstr "" #: ../../source/ref-changelog.md:400 msgid "" -"**Introduce start_driver** " -"([#1697](https://github.com/adap/flower/pull/1697))" +"**Introduce start_driver** ([#1697](https://github.com/adap/flower/" +"pull/1697))" msgstr "" #: ../../source/ref-changelog.md:402 msgid "" -"In addition to `start_server` and using the raw Driver API, there is a " -"new `start_driver` function that allows for running `start_server` " -"scripts as a Flower driver with only a single-line code change. Check out" -" the `mt-pytorch` code example to see a working example using " -"`start_driver`." +"In addition to `start_server` and using the raw Driver API, there is a new " +"`start_driver` function that allows for running `start_server` scripts as a " +"Flower driver with only a single-line code change. Check out the `mt-" +"pytorch` code example to see a working example using `start_driver`." msgstr "" #: ../../source/ref-changelog.md:404 msgid "" -"**Add parameter aggregation to** `mt-pytorch` **code example** " -"([#1785](https://github.com/adap/flower/pull/1785))" +"**Add parameter aggregation to** `mt-pytorch` **code example** ([#1785]" +"(https://github.com/adap/flower/pull/1785))" msgstr "" #: ../../source/ref-changelog.md:406 msgid "" -"The `mt-pytorch` example shows how to aggregate parameters when writing a" -" driver script. The included `driver.py` and `server.py` have been " -"aligned to demonstrate both the low-level way and the high-level way of " -"building server-side logic." +"The `mt-pytorch` example shows how to aggregate parameters when writing a " +"driver script. The included `driver.py` and `server.py` have been aligned to " +"demonstrate both the low-level way and the high-level way of building server-" +"side logic." msgstr "" #: ../../source/ref-changelog.md:408 msgid "" -"**Migrate experimental REST API to Starlette** " -"([2171](https://github.com/adap/flower/pull/2171))" +"**Migrate experimental REST API to Starlette** ([2171](https://github.com/" +"adap/flower/pull/2171))" msgstr "" #: ../../source/ref-changelog.md:410 msgid "" -"The (experimental) REST API used to be implemented in " -"[FastAPI](https://fastapi.tiangolo.com/), but it has now been migrated to" -" use [Starlette](https://www.starlette.io/) directly." +"The (experimental) REST API used to be implemented in [FastAPI](https://" +"fastapi.tiangolo.com/), but it has now been migrated to use [Starlette]" +"(https://www.starlette.io/) directly." msgstr "" #: ../../source/ref-changelog.md:412 msgid "" -"Please note: The REST request-response API is still experimental and will" -" likely change significantly over time." +"Please note: The REST request-response API is still experimental and will " +"likely change significantly over time." msgstr "" #: ../../source/ref-changelog.md:414 msgid "" -"**Introduce experimental gRPC request-response API** " -"([#1867](https://github.com/adap/flower/pull/1867), " -"[#1901](https://github.com/adap/flower/pull/1901))" +"**Introduce experimental gRPC request-response API** ([#1867](https://github." +"com/adap/flower/pull/1867), [#1901](https://github.com/adap/flower/" +"pull/1901))" msgstr "" #: ../../source/ref-changelog.md:416 msgid "" -"In addition to the existing gRPC API (based on bidirectional streaming) " -"and the experimental REST API, there is now a new gRPC API that uses a " -"request-response model to communicate with client nodes." +"In addition to the existing gRPC API (based on bidirectional streaming) and " +"the experimental REST API, there is now a new gRPC API that uses a request-" +"response model to communicate with client nodes." msgstr "" #: ../../source/ref-changelog.md:418 msgid "" -"Please note: The gRPC request-response API is still experimental and will" -" likely change significantly over time." +"Please note: The gRPC request-response API is still experimental and will " +"likely change significantly over time." msgstr "" #: ../../source/ref-changelog.md:420 msgid "" "**Replace the experimental** `start_client(rest=True)` **with the new** " -"`start_client(transport=\"rest\")` " -"([#1880](https://github.com/adap/flower/pull/1880))" +"`start_client(transport=\"rest\")` ([#1880](https://github.com/adap/flower/" +"pull/1880))" msgstr "" #: ../../source/ref-changelog.md:422 msgid "" -"The (experimental) `start_client` argument `rest` was deprecated in " -"favour of a new argument `transport`. `start_client(transport=\"rest\")` " -"will yield the same behaviour as `start_client(rest=True)` did before. " -"All code should migrate to the new argument `transport`. The deprecated " -"argument `rest` will be removed in a future release." +"The (experimental) `start_client` argument `rest` was deprecated in favour " +"of a new argument `transport`. `start_client(transport=\"rest\")` will yield " +"the same behaviour as `start_client(rest=True)` did before. All code should " +"migrate to the new argument `transport`. The deprecated argument `rest` will " +"be removed in a future release." msgstr "" #: ../../source/ref-changelog.md:424 msgid "" -"**Add a new gRPC option** " -"([#2197](https://github.com/adap/flower/pull/2197))" +"**Add a new gRPC option** ([#2197](https://github.com/adap/flower/pull/2197))" msgstr "" #: ../../source/ref-changelog.md:426 msgid "" -"We now start a gRPC server with the `grpc.keepalive_permit_without_calls`" -" option set to 0 by default. This prevents the clients from sending " -"keepalive pings when there is no outstanding stream." +"We now start a gRPC server with the `grpc.keepalive_permit_without_calls` " +"option set to 0 by default. This prevents the clients from sending keepalive " +"pings when there is no outstanding stream." msgstr "" #: ../../source/ref-changelog.md:428 msgid "" -"**Improve example notebooks** " -"([#2005](https://github.com/adap/flower/pull/2005))" +"**Improve example notebooks** ([#2005](https://github.com/adap/flower/" +"pull/2005))" msgstr "" #: ../../source/ref-changelog.md:430 @@ -16647,36 +17121,31 @@ msgstr "" #: ../../source/ref-changelog.md:432 msgid "" "**Example updates** ([#1772](https://github.com/adap/flower/pull/1772), " -"[#1873](https://github.com/adap/flower/pull/1873), " -"[#1981](https://github.com/adap/flower/pull/1981), " -"[#1988](https://github.com/adap/flower/pull/1988), " -"[#1984](https://github.com/adap/flower/pull/1984), " -"[#1982](https://github.com/adap/flower/pull/1982), " -"[#2112](https://github.com/adap/flower/pull/2112), " -"[#2144](https://github.com/adap/flower/pull/2144), " -"[#2174](https://github.com/adap/flower/pull/2174), " -"[#2225](https://github.com/adap/flower/pull/2225), " -"[#2183](https://github.com/adap/flower/pull/2183))" +"[#1873](https://github.com/adap/flower/pull/1873), [#1981](https://github." +"com/adap/flower/pull/1981), [#1988](https://github.com/adap/flower/" +"pull/1988), [#1984](https://github.com/adap/flower/pull/1984), [#1982]" +"(https://github.com/adap/flower/pull/1982), [#2112](https://github.com/adap/" +"flower/pull/2112), [#2144](https://github.com/adap/flower/pull/2144), [#2174]" +"(https://github.com/adap/flower/pull/2174), [#2225](https://github.com/adap/" +"flower/pull/2225), [#2183](https://github.com/adap/flower/pull/2183))" msgstr "" #: ../../source/ref-changelog.md:434 msgid "" "Many examples have received significant updates, including simplified " "advanced-tensorflow and advanced-pytorch examples, improved macOS " -"compatibility of TensorFlow examples, and code examples for simulation. A" -" major upgrade is that all code examples now have a `requirements.txt` " -"(in addition to `pyproject.toml`)." +"compatibility of TensorFlow examples, and code examples for simulation. A " +"major upgrade is that all code examples now have a `requirements.txt` (in " +"addition to `pyproject.toml`)." msgstr "" #: ../../source/ref-changelog.md:436 msgid "" -"**General improvements** " -"([#1872](https://github.com/adap/flower/pull/1872), " -"[#1866](https://github.com/adap/flower/pull/1866), " -"[#1884](https://github.com/adap/flower/pull/1884), " -"[#1837](https://github.com/adap/flower/pull/1837), " -"[#1477](https://github.com/adap/flower/pull/1477), " -"[#2171](https://github.com/adap/flower/pull/2171))" +"**General improvements** ([#1872](https://github.com/adap/flower/pull/1872), " +"[#1866](https://github.com/adap/flower/pull/1866), [#1884](https://github." +"com/adap/flower/pull/1884), [#1837](https://github.com/adap/flower/" +"pull/1837), [#1477](https://github.com/adap/flower/pull/1477), [#2171]" +"(https://github.com/adap/flower/pull/2171))" msgstr "" #: ../../source/ref-changelog.md:444 @@ -16686,110 +17155,103 @@ msgstr "" #: ../../source/ref-changelog.md:450 msgid "" "`Adam Narozniak`, `Alexander Viala Bellander`, `Charles Beauville`, " -"`Chenyang Ma (Danny)`, `Daniel J. Beutel`, `Edoardo`, `Gautam Jajoo`, " -"`Iacob-Alexandru-Andrei`, `JDRanpariya`, `Jean Charle Yaacoub`, `Kunal " -"Sarkhel`, `L. Jiang`, `Lennart Behme`, `Max Kapsecker`, `Michał`, `Nic " -"Lane`, `Nikolaos Episkopos`, `Ragy`, `Saurav Maheshkar`, `Semo Yang`, " -"`Steve Laskaridis`, `Steven Hé (Sīchàng)`, `Taner Topal`" +"`Chenyang Ma (Danny)`, `Daniel J. Beutel`, `Edoardo`, `Gautam Jajoo`, `Iacob-" +"Alexandru-Andrei`, `JDRanpariya`, `Jean Charle Yaacoub`, `Kunal Sarkhel`, " +"`L. Jiang`, `Lennart Behme`, `Max Kapsecker`, `Michał`, `Nic Lane`, " +"`Nikolaos Episkopos`, `Ragy`, `Saurav Maheshkar`, `Semo Yang`, `Steve " +"Laskaridis`, `Steven Hé (Sīchàng)`, `Taner Topal`" msgstr "" #: ../../source/ref-changelog.md:454 msgid "" -"**Introduce support for XGBoost (**`FedXgbNnAvg` **strategy and " -"example)** ([#1694](https://github.com/adap/flower/pull/1694), " -"[#1709](https://github.com/adap/flower/pull/1709), " -"[#1715](https://github.com/adap/flower/pull/1715), " -"[#1717](https://github.com/adap/flower/pull/1717), " -"[#1763](https://github.com/adap/flower/pull/1763), " -"[#1795](https://github.com/adap/flower/pull/1795))" +"**Introduce support for XGBoost (**`FedXgbNnAvg` **strategy and example)** " +"([#1694](https://github.com/adap/flower/pull/1694), [#1709](https://github." +"com/adap/flower/pull/1709), [#1715](https://github.com/adap/flower/" +"pull/1715), [#1717](https://github.com/adap/flower/pull/1717), [#1763]" +"(https://github.com/adap/flower/pull/1763), [#1795](https://github.com/adap/" +"flower/pull/1795))" msgstr "" #: ../../source/ref-changelog.md:456 msgid "" "XGBoost is a tree-based ensemble machine learning algorithm that uses " -"gradient boosting to improve model accuracy. We added a new `FedXgbNnAvg`" -" " -"[strategy](https://github.com/adap/flower/tree/main/src/py/flwr/server/strategy/fedxgb_nn_avg.py)," -" and a [code example](https://github.com/adap/flower/tree/main/examples" -"/xgboost-quickstart) that demonstrates the usage of this new strategy in " -"an XGBoost project." +"gradient boosting to improve model accuracy. We added a new `FedXgbNnAvg` " +"[strategy](https://github.com/adap/flower/tree/main/src/py/flwr/server/" +"strategy/fedxgb_nn_avg.py), and a [code example](https://github.com/adap/" +"flower/tree/main/examples/xgboost-quickstart) that demonstrates the usage of " +"this new strategy in an XGBoost project." msgstr "" #: ../../source/ref-changelog.md:458 msgid "" -"**Introduce iOS SDK (preview)** " -"([#1621](https://github.com/adap/flower/pull/1621), " -"[#1764](https://github.com/adap/flower/pull/1764))" +"**Introduce iOS SDK (preview)** ([#1621](https://github.com/adap/flower/" +"pull/1621), [#1764](https://github.com/adap/flower/pull/1764))" msgstr "" #: ../../source/ref-changelog.md:460 msgid "" -"This is a major update for anyone wanting to implement Federated Learning" -" on iOS mobile devices. We now have a swift iOS SDK present under " -"[src/swift/flwr](https://github.com/adap/flower/tree/main/src/swift/flwr)" -" that will facilitate greatly the app creating process. To showcase its " -"use, the [iOS " +"This is a major update for anyone wanting to implement Federated Learning on " +"iOS mobile devices. We now have a swift iOS SDK present under [src/swift/" +"flwr](https://github.com/adap/flower/tree/main/src/swift/flwr) that will " +"facilitate greatly the app creating process. To showcase its use, the [iOS " "example](https://github.com/adap/flower/tree/main/examples/ios) has also " "been updated!" msgstr "" #: ../../source/ref-changelog.md:462 msgid "" -"**Introduce new \"What is Federated Learning?\" tutorial** " -"([#1657](https://github.com/adap/flower/pull/1657), " -"[#1721](https://github.com/adap/flower/pull/1721))" +"**Introduce new \"What is Federated Learning?\" tutorial** ([#1657](https://" +"github.com/adap/flower/pull/1657), [#1721](https://github.com/adap/flower/" +"pull/1721))" msgstr "" #: ../../source/ref-changelog.md:464 msgid "" -"A new [entry-level tutorial](https://flower.ai/docs/framework/tutorial-" -"what-is-federated-learning.html) in our documentation explains the basics" -" of Fedetated Learning. It enables anyone who's unfamiliar with Federated" -" Learning to start their journey with Flower. Forward it to anyone who's " +"A new [entry-level tutorial](https://flower.ai/docs/framework/tutorial-what-" +"is-federated-learning.html) in our documentation explains the basics of " +"Fedetated Learning. It enables anyone who's unfamiliar with Federated " +"Learning to start their journey with Flower. Forward it to anyone who's " "interested in Federated Learning!" msgstr "" #: ../../source/ref-changelog.md:466 msgid "" -"**Introduce new Flower Baseline: FedProx MNIST** " -"([#1513](https://github.com/adap/flower/pull/1513), " -"[#1680](https://github.com/adap/flower/pull/1680), " -"[#1681](https://github.com/adap/flower/pull/1681), " -"[#1679](https://github.com/adap/flower/pull/1679))" +"**Introduce new Flower Baseline: FedProx MNIST** ([#1513](https://github.com/" +"adap/flower/pull/1513), [#1680](https://github.com/adap/flower/pull/1680), " +"[#1681](https://github.com/adap/flower/pull/1681), [#1679](https://github." +"com/adap/flower/pull/1679))" msgstr "" #: ../../source/ref-changelog.md:468 msgid "" -"This new baseline replicates the MNIST+CNN task from the paper [Federated" -" Optimization in Heterogeneous Networks (Li et al., " -"2018)](https://arxiv.org/abs/1812.06127). It uses the `FedProx` strategy," -" which aims at making convergence more robust in heterogeneous settings." +"This new baseline replicates the MNIST+CNN task from the paper [Federated " +"Optimization in Heterogeneous Networks (Li et al., 2018)](https://arxiv.org/" +"abs/1812.06127). It uses the `FedProx` strategy, which aims at making " +"convergence more robust in heterogeneous settings." msgstr "" #: ../../source/ref-changelog.md:470 msgid "" -"**Introduce new Flower Baseline: FedAvg FEMNIST** " -"([#1655](https://github.com/adap/flower/pull/1655))" +"**Introduce new Flower Baseline: FedAvg FEMNIST** ([#1655](https://github." +"com/adap/flower/pull/1655))" msgstr "" #: ../../source/ref-changelog.md:472 msgid "" -"This new baseline replicates an experiment evaluating the performance of " -"the FedAvg algorithm on the FEMNIST dataset from the paper [LEAF: A " -"Benchmark for Federated Settings (Caldas et al., " -"2018)](https://arxiv.org/abs/1812.01097)." +"This new baseline replicates an experiment evaluating the performance of the " +"FedAvg algorithm on the FEMNIST dataset from the paper [LEAF: A Benchmark " +"for Federated Settings (Caldas et al., 2018)](https://arxiv.org/" +"abs/1812.01097)." msgstr "" #: ../../source/ref-changelog.md:474 msgid "" -"**Introduce (experimental) REST API** " -"([#1594](https://github.com/adap/flower/pull/1594), " -"[#1690](https://github.com/adap/flower/pull/1690), " -"[#1695](https://github.com/adap/flower/pull/1695), " -"[#1712](https://github.com/adap/flower/pull/1712), " -"[#1802](https://github.com/adap/flower/pull/1802), " -"[#1770](https://github.com/adap/flower/pull/1770), " -"[#1733](https://github.com/adap/flower/pull/1733))" +"**Introduce (experimental) REST API** ([#1594](https://github.com/adap/" +"flower/pull/1594), [#1690](https://github.com/adap/flower/pull/1690), [#1695]" +"(https://github.com/adap/flower/pull/1695), [#1712](https://github.com/adap/" +"flower/pull/1712), [#1802](https://github.com/adap/flower/pull/1802), [#1770]" +"(https://github.com/adap/flower/pull/1770), [#1733](https://github.com/adap/" +"flower/pull/1733))" msgstr "" #: ../../source/ref-changelog.md:476 @@ -16807,132 +17269,112 @@ msgstr "" #: ../../source/ref-changelog.md:480 msgid "" -"**Improve the (experimental) Driver API** " -"([#1663](https://github.com/adap/flower/pull/1663), " -"[#1666](https://github.com/adap/flower/pull/1666), " -"[#1667](https://github.com/adap/flower/pull/1667), " -"[#1664](https://github.com/adap/flower/pull/1664), " -"[#1675](https://github.com/adap/flower/pull/1675), " -"[#1676](https://github.com/adap/flower/pull/1676), " -"[#1693](https://github.com/adap/flower/pull/1693), " -"[#1662](https://github.com/adap/flower/pull/1662), " -"[#1794](https://github.com/adap/flower/pull/1794))" +"**Improve the (experimental) Driver API** ([#1663](https://github.com/adap/" +"flower/pull/1663), [#1666](https://github.com/adap/flower/pull/1666), [#1667]" +"(https://github.com/adap/flower/pull/1667), [#1664](https://github.com/adap/" +"flower/pull/1664), [#1675](https://github.com/adap/flower/pull/1675), [#1676]" +"(https://github.com/adap/flower/pull/1676), [#1693](https://github.com/adap/" +"flower/pull/1693), [#1662](https://github.com/adap/flower/pull/1662), [#1794]" +"(https://github.com/adap/flower/pull/1794))" msgstr "" #: ../../source/ref-changelog.md:482 msgid "" -"The Driver API is still an experimental feature, but this release " -"introduces some major upgrades. One of the main improvements is the " -"introduction of an SQLite database to store server state on disk (instead" -" of in-memory). Another improvement is that tasks (instructions or " -"results) that have been delivered will now be deleted. This greatly " -"improves the memory efficiency of a long-running Flower server." +"The Driver API is still an experimental feature, but this release introduces " +"some major upgrades. One of the main improvements is the introduction of an " +"SQLite database to store server state on disk (instead of in-memory). " +"Another improvement is that tasks (instructions or results) that have been " +"delivered will now be deleted. This greatly improves the memory efficiency " +"of a long-running Flower server." msgstr "" #: ../../source/ref-changelog.md:484 msgid "" -"**Fix spilling issues related to Ray during simulations** " -"([#1698](https://github.com/adap/flower/pull/1698))" +"**Fix spilling issues related to Ray during simulations** ([#1698](https://" +"github.com/adap/flower/pull/1698))" msgstr "" #: ../../source/ref-changelog.md:486 msgid "" -"While running long simulations, `ray` was sometimes spilling huge amounts" -" of data that would make the training unable to continue. This is now " -"fixed! 🎉" +"While running long simulations, `ray` was sometimes spilling huge amounts of " +"data that would make the training unable to continue. This is now fixed! 🎉" msgstr "" #: ../../source/ref-changelog.md:488 msgid "" -"**Add new example using** `TabNet` **and Flower** " -"([#1725](https://github.com/adap/flower/pull/1725))" +"**Add new example using** `TabNet` **and Flower** ([#1725](https://github." +"com/adap/flower/pull/1725))" msgstr "" #: ../../source/ref-changelog.md:490 msgid "" -"TabNet is a powerful and flexible framework for training machine learning" -" models on tabular data. We now have a federated example using Flower: " -"[quickstart-tabnet](https://github.com/adap/flower/tree/main/examples" -"/quickstart-tabnet)." +"TabNet is a powerful and flexible framework for training machine learning " +"models on tabular data. We now have a federated example using Flower: " +"[quickstart-tabnet](https://github.com/adap/flower/tree/main/examples/" +"quickstart-tabnet)." msgstr "" #: ../../source/ref-changelog.md:492 msgid "" -"**Add new how-to guide for monitoring simulations** " -"([#1649](https://github.com/adap/flower/pull/1649))" +"**Add new how-to guide for monitoring simulations** ([#1649](https://github." +"com/adap/flower/pull/1649))" msgstr "" #: ../../source/ref-changelog.md:494 msgid "" -"We now have a documentation guide to help users monitor their performance" -" during simulations." +"We now have a documentation guide to help users monitor their performance " +"during simulations." msgstr "" #: ../../source/ref-changelog.md:496 msgid "" -"**Add training metrics to** `History` **object during simulations** " -"([#1696](https://github.com/adap/flower/pull/1696))" +"**Add training metrics to** `History` **object during simulations** ([#1696]" +"(https://github.com/adap/flower/pull/1696))" msgstr "" #: ../../source/ref-changelog.md:498 msgid "" -"The `fit_metrics_aggregation_fn` can be used to aggregate training " -"metrics, but previous releases did not save the results in the `History` " -"object. This is now the case!" +"The `fit_metrics_aggregation_fn` can be used to aggregate training metrics, " +"but previous releases did not save the results in the `History` object. This " +"is now the case!" msgstr "" #: ../../source/ref-changelog.md:500 msgid "" -"**General improvements** " -"([#1659](https://github.com/adap/flower/pull/1659), " -"[#1646](https://github.com/adap/flower/pull/1646), " -"[#1647](https://github.com/adap/flower/pull/1647), " -"[#1471](https://github.com/adap/flower/pull/1471), " -"[#1648](https://github.com/adap/flower/pull/1648), " -"[#1651](https://github.com/adap/flower/pull/1651), " -"[#1652](https://github.com/adap/flower/pull/1652), " -"[#1653](https://github.com/adap/flower/pull/1653), " -"[#1659](https://github.com/adap/flower/pull/1659), " -"[#1665](https://github.com/adap/flower/pull/1665), " -"[#1670](https://github.com/adap/flower/pull/1670), " -"[#1672](https://github.com/adap/flower/pull/1672), " -"[#1677](https://github.com/adap/flower/pull/1677), " -"[#1684](https://github.com/adap/flower/pull/1684), " -"[#1683](https://github.com/adap/flower/pull/1683), " -"[#1686](https://github.com/adap/flower/pull/1686), " -"[#1682](https://github.com/adap/flower/pull/1682), " -"[#1685](https://github.com/adap/flower/pull/1685), " -"[#1692](https://github.com/adap/flower/pull/1692), " -"[#1705](https://github.com/adap/flower/pull/1705), " -"[#1708](https://github.com/adap/flower/pull/1708), " -"[#1711](https://github.com/adap/flower/pull/1711), " -"[#1713](https://github.com/adap/flower/pull/1713), " -"[#1714](https://github.com/adap/flower/pull/1714), " -"[#1718](https://github.com/adap/flower/pull/1718), " -"[#1716](https://github.com/adap/flower/pull/1716), " -"[#1723](https://github.com/adap/flower/pull/1723), " -"[#1735](https://github.com/adap/flower/pull/1735), " -"[#1678](https://github.com/adap/flower/pull/1678), " -"[#1750](https://github.com/adap/flower/pull/1750), " -"[#1753](https://github.com/adap/flower/pull/1753), " -"[#1736](https://github.com/adap/flower/pull/1736), " -"[#1766](https://github.com/adap/flower/pull/1766), " -"[#1760](https://github.com/adap/flower/pull/1760), " -"[#1775](https://github.com/adap/flower/pull/1775), " -"[#1776](https://github.com/adap/flower/pull/1776), " -"[#1777](https://github.com/adap/flower/pull/1777), " -"[#1779](https://github.com/adap/flower/pull/1779), " -"[#1784](https://github.com/adap/flower/pull/1784), " -"[#1773](https://github.com/adap/flower/pull/1773), " -"[#1755](https://github.com/adap/flower/pull/1755), " -"[#1789](https://github.com/adap/flower/pull/1789), " -"[#1788](https://github.com/adap/flower/pull/1788), " -"[#1798](https://github.com/adap/flower/pull/1798), " -"[#1799](https://github.com/adap/flower/pull/1799), " -"[#1739](https://github.com/adap/flower/pull/1739), " -"[#1800](https://github.com/adap/flower/pull/1800), " -"[#1804](https://github.com/adap/flower/pull/1804), " -"[#1805](https://github.com/adap/flower/pull/1805))" +"**General improvements** ([#1659](https://github.com/adap/flower/pull/1659), " +"[#1646](https://github.com/adap/flower/pull/1646), [#1647](https://github." +"com/adap/flower/pull/1647), [#1471](https://github.com/adap/flower/" +"pull/1471), [#1648](https://github.com/adap/flower/pull/1648), [#1651]" +"(https://github.com/adap/flower/pull/1651), [#1652](https://github.com/adap/" +"flower/pull/1652), [#1653](https://github.com/adap/flower/pull/1653), [#1659]" +"(https://github.com/adap/flower/pull/1659), [#1665](https://github.com/adap/" +"flower/pull/1665), [#1670](https://github.com/adap/flower/pull/1670), [#1672]" +"(https://github.com/adap/flower/pull/1672), [#1677](https://github.com/adap/" +"flower/pull/1677), [#1684](https://github.com/adap/flower/pull/1684), [#1683]" +"(https://github.com/adap/flower/pull/1683), [#1686](https://github.com/adap/" +"flower/pull/1686), [#1682](https://github.com/adap/flower/pull/1682), [#1685]" +"(https://github.com/adap/flower/pull/1685), [#1692](https://github.com/adap/" +"flower/pull/1692), [#1705](https://github.com/adap/flower/pull/1705), [#1708]" +"(https://github.com/adap/flower/pull/1708), [#1711](https://github.com/adap/" +"flower/pull/1711), [#1713](https://github.com/adap/flower/pull/1713), [#1714]" +"(https://github.com/adap/flower/pull/1714), [#1718](https://github.com/adap/" +"flower/pull/1718), [#1716](https://github.com/adap/flower/pull/1716), [#1723]" +"(https://github.com/adap/flower/pull/1723), [#1735](https://github.com/adap/" +"flower/pull/1735), [#1678](https://github.com/adap/flower/pull/1678), [#1750]" +"(https://github.com/adap/flower/pull/1750), [#1753](https://github.com/adap/" +"flower/pull/1753), [#1736](https://github.com/adap/flower/pull/1736), [#1766]" +"(https://github.com/adap/flower/pull/1766), [#1760](https://github.com/adap/" +"flower/pull/1760), [#1775](https://github.com/adap/flower/pull/1775), [#1776]" +"(https://github.com/adap/flower/pull/1776), [#1777](https://github.com/adap/" +"flower/pull/1777), [#1779](https://github.com/adap/flower/pull/1779), [#1784]" +"(https://github.com/adap/flower/pull/1784), [#1773](https://github.com/adap/" +"flower/pull/1773), [#1755](https://github.com/adap/flower/pull/1755), [#1789]" +"(https://github.com/adap/flower/pull/1789), [#1788](https://github.com/adap/" +"flower/pull/1788), [#1798](https://github.com/adap/flower/pull/1798), [#1799]" +"(https://github.com/adap/flower/pull/1799), [#1739](https://github.com/adap/" +"flower/pull/1739), [#1800](https://github.com/adap/flower/pull/1800), [#1804]" +"(https://github.com/adap/flower/pull/1804), [#1805](https://github.com/adap/" +"flower/pull/1805))" msgstr "" #: ../../source/ref-changelog.md:508 @@ -16941,8 +17383,8 @@ msgstr "" #: ../../source/ref-changelog.md:514 msgid "" -"`Adam Narozniak`, `Alexander Viala Bellander`, `Charles Beauville`, " -"`Daniel J. Beutel`, `JDRanpariya`, `Lennart Behme`, `Taner Topal`" +"`Adam Narozniak`, `Alexander Viala Bellander`, `Charles Beauville`, `Daniel " +"J. Beutel`, `JDRanpariya`, `Lennart Behme`, `Taner Topal`" msgstr "" #: ../../source/ref-changelog.md:518 @@ -16953,24 +17395,24 @@ msgstr "" #: ../../source/ref-changelog.md:520 msgid "" -"The (experimental) Driver API now supports a `workload_id` that can be " -"used to identify which workload a task belongs to. It also supports a new" -" `group_id` that can be used, for example, to indicate the current " -"training round. Both the `workload_id` and `group_id` enable client nodes" -" to decide whether they want to handle a task or not." +"The (experimental) Driver API now supports a `workload_id` that can be used " +"to identify which workload a task belongs to. It also supports a new " +"`group_id` that can be used, for example, to indicate the current training " +"round. Both the `workload_id` and `group_id` enable client nodes to decide " +"whether they want to handle a task or not." msgstr "" #: ../../source/ref-changelog.md:522 msgid "" -"**Make Driver API and Fleet API address configurable** " -"([#1637](https://github.com/adap/flower/pull/1637))" +"**Make Driver API and Fleet API address configurable** ([#1637](https://" +"github.com/adap/flower/pull/1637))" msgstr "" #: ../../source/ref-changelog.md:524 msgid "" -"The (experimental) long-running Flower server (Driver API and Fleet API) " -"can now configure the server address of both Driver API (via `--driver-" -"api-address`) and Fleet API (via `--fleet-api-address`) when starting:" +"The (experimental) long-running Flower server (Driver API and Fleet API) can " +"now configure the server address of both Driver API (via `--driver-api-" +"address`) and Fleet API (via `--fleet-api-address`) when starting:" msgstr "" #: ../../source/ref-changelog.md:526 @@ -16985,55 +17427,51 @@ msgstr "" #: ../../source/ref-changelog.md:530 msgid "" -"**Add new example of Federated Learning using fastai and Flower** " -"([#1598](https://github.com/adap/flower/pull/1598))" +"**Add new example of Federated Learning using fastai and Flower** ([#1598]" +"(https://github.com/adap/flower/pull/1598))" msgstr "" #: ../../source/ref-changelog.md:532 msgid "" "A new code example (`quickstart-fastai`) demonstrates federated learning " "with [fastai](https://www.fast.ai/) and Flower. You can find it here: " -"[quickstart-fastai](https://github.com/adap/flower/tree/main/examples" -"/quickstart-fastai)." +"[quickstart-fastai](https://github.com/adap/flower/tree/main/examples/" +"quickstart-fastai)." msgstr "" #: ../../source/ref-changelog.md:534 msgid "" -"**Make Android example compatible with** `flwr >= 1.0.0` **and the latest" -" versions of Android** " -"([#1603](https://github.com/adap/flower/pull/1603))" +"**Make Android example compatible with** `flwr >= 1.0.0` **and the latest " +"versions of Android** ([#1603](https://github.com/adap/flower/pull/1603))" msgstr "" #: ../../source/ref-changelog.md:536 msgid "" -"The Android code example has received a substantial update: the project " -"is compatible with Flower 1.0 (and later), the UI received a full " -"refresh, and the project is updated to be compatible with newer Android " -"tooling." +"The Android code example has received a substantial update: the project is " +"compatible with Flower 1.0 (and later), the UI received a full refresh, and " +"the project is updated to be compatible with newer Android tooling." msgstr "" #: ../../source/ref-changelog.md:538 msgid "" -"**Add new `FedProx` strategy** " -"([#1619](https://github.com/adap/flower/pull/1619))" +"**Add new `FedProx` strategy** ([#1619](https://github.com/adap/flower/" +"pull/1619))" msgstr "" #: ../../source/ref-changelog.md:540 msgid "" -"This " -"[strategy](https://github.com/adap/flower/blob/main/src/py/flwr/server/strategy/fedprox.py)" -" is almost identical to " -"[`FedAvg`](https://github.com/adap/flower/blob/main/src/py/flwr/server/strategy/fedavg.py)," -" but helps users replicate what is described in this " -"[paper](https://arxiv.org/abs/1812.06127). It essentially adds a " -"parameter called `proximal_mu` to regularize the local models with " -"respect to the global models." +"This [strategy](https://github.com/adap/flower/blob/main/src/py/flwr/server/" +"strategy/fedprox.py) is almost identical to [`FedAvg`](https://github.com/" +"adap/flower/blob/main/src/py/flwr/server/strategy/fedavg.py), but helps " +"users replicate what is described in this [paper](https://arxiv.org/" +"abs/1812.06127). It essentially adds a parameter called `proximal_mu` to " +"regularize the local models with respect to the global models." msgstr "" #: ../../source/ref-changelog.md:542 msgid "" -"**Add new metrics to telemetry events** " -"([#1640](https://github.com/adap/flower/pull/1640))" +"**Add new metrics to telemetry events** ([#1640](https://github.com/adap/" +"flower/pull/1640))" msgstr "" #: ../../source/ref-changelog.md:544 @@ -17044,87 +17482,73 @@ msgstr "" #: ../../source/ref-changelog.md:546 msgid "" -"**Add new custom strategy tutorial section** " -"[#1623](https://github.com/adap/flower/pull/1623)" +"**Add new custom strategy tutorial section** [#1623](https://github.com/adap/" +"flower/pull/1623)" msgstr "" #: ../../source/ref-changelog.md:548 msgid "" -"The Flower tutorial now has a new section that covers implementing a " -"custom strategy from scratch: [Open in " -"Colab](https://colab.research.google.com/github/adap/flower/blob/main/doc/source" -"/tutorial-build-a-strategy-from-scratch-pytorch.ipynb)" +"The Flower tutorial now has a new section that covers implementing a custom " +"strategy from scratch: [Open in Colab](https://colab.research.google.com/" +"github/adap/flower/blob/main/doc/source/tutorial-build-a-strategy-from-" +"scratch-pytorch.ipynb)" msgstr "" #: ../../source/ref-changelog.md:550 msgid "" -"**Add new custom serialization tutorial section** " -"([#1622](https://github.com/adap/flower/pull/1622))" +"**Add new custom serialization tutorial section** ([#1622](https://github." +"com/adap/flower/pull/1622))" msgstr "" #: ../../source/ref-changelog.md:552 msgid "" -"The Flower tutorial now has a new section that covers custom " -"serialization: [Open in " -"Colab](https://colab.research.google.com/github/adap/flower/blob/main/doc/source" -"/tutorial-customize-the-client-pytorch.ipynb)" +"The Flower tutorial now has a new section that covers custom serialization: " +"[Open in Colab](https://colab.research.google.com/github/adap/flower/blob/" +"main/doc/source/tutorial-customize-the-client-pytorch.ipynb)" msgstr "" #: ../../source/ref-changelog.md:554 msgid "" -"**General improvements** " -"([#1638](https://github.com/adap/flower/pull/1638), " -"[#1634](https://github.com/adap/flower/pull/1634), " -"[#1636](https://github.com/adap/flower/pull/1636), " -"[#1635](https://github.com/adap/flower/pull/1635), " -"[#1633](https://github.com/adap/flower/pull/1633), " -"[#1632](https://github.com/adap/flower/pull/1632), " -"[#1631](https://github.com/adap/flower/pull/1631), " -"[#1630](https://github.com/adap/flower/pull/1630), " -"[#1627](https://github.com/adap/flower/pull/1627), " -"[#1593](https://github.com/adap/flower/pull/1593), " -"[#1616](https://github.com/adap/flower/pull/1616), " -"[#1615](https://github.com/adap/flower/pull/1615), " -"[#1607](https://github.com/adap/flower/pull/1607), " -"[#1609](https://github.com/adap/flower/pull/1609), " -"[#1608](https://github.com/adap/flower/pull/1608), " -"[#1603](https://github.com/adap/flower/pull/1603), " -"[#1590](https://github.com/adap/flower/pull/1590), " -"[#1580](https://github.com/adap/flower/pull/1580), " -"[#1599](https://github.com/adap/flower/pull/1599), " -"[#1600](https://github.com/adap/flower/pull/1600), " -"[#1601](https://github.com/adap/flower/pull/1601), " -"[#1597](https://github.com/adap/flower/pull/1597), " -"[#1595](https://github.com/adap/flower/pull/1595), " -"[#1591](https://github.com/adap/flower/pull/1591), " -"[#1588](https://github.com/adap/flower/pull/1588), " -"[#1589](https://github.com/adap/flower/pull/1589), " -"[#1587](https://github.com/adap/flower/pull/1587), " -"[#1573](https://github.com/adap/flower/pull/1573), " -"[#1581](https://github.com/adap/flower/pull/1581), " -"[#1578](https://github.com/adap/flower/pull/1578), " -"[#1574](https://github.com/adap/flower/pull/1574), " -"[#1572](https://github.com/adap/flower/pull/1572), " -"[#1586](https://github.com/adap/flower/pull/1586))" +"**General improvements** ([#1638](https://github.com/adap/flower/pull/1638), " +"[#1634](https://github.com/adap/flower/pull/1634), [#1636](https://github." +"com/adap/flower/pull/1636), [#1635](https://github.com/adap/flower/" +"pull/1635), [#1633](https://github.com/adap/flower/pull/1633), [#1632]" +"(https://github.com/adap/flower/pull/1632), [#1631](https://github.com/adap/" +"flower/pull/1631), [#1630](https://github.com/adap/flower/pull/1630), [#1627]" +"(https://github.com/adap/flower/pull/1627), [#1593](https://github.com/adap/" +"flower/pull/1593), [#1616](https://github.com/adap/flower/pull/1616), [#1615]" +"(https://github.com/adap/flower/pull/1615), [#1607](https://github.com/adap/" +"flower/pull/1607), [#1609](https://github.com/adap/flower/pull/1609), [#1608]" +"(https://github.com/adap/flower/pull/1608), [#1603](https://github.com/adap/" +"flower/pull/1603), [#1590](https://github.com/adap/flower/pull/1590), [#1580]" +"(https://github.com/adap/flower/pull/1580), [#1599](https://github.com/adap/" +"flower/pull/1599), [#1600](https://github.com/adap/flower/pull/1600), [#1601]" +"(https://github.com/adap/flower/pull/1601), [#1597](https://github.com/adap/" +"flower/pull/1597), [#1595](https://github.com/adap/flower/pull/1595), [#1591]" +"(https://github.com/adap/flower/pull/1591), [#1588](https://github.com/adap/" +"flower/pull/1588), [#1589](https://github.com/adap/flower/pull/1589), [#1587]" +"(https://github.com/adap/flower/pull/1587), [#1573](https://github.com/adap/" +"flower/pull/1573), [#1581](https://github.com/adap/flower/pull/1581), [#1578]" +"(https://github.com/adap/flower/pull/1578), [#1574](https://github.com/adap/" +"flower/pull/1574), [#1572](https://github.com/adap/flower/pull/1572), [#1586]" +"(https://github.com/adap/flower/pull/1586))" msgstr "" #: ../../source/ref-changelog.md:558 msgid "" -"**Updated documentation** " -"([#1629](https://github.com/adap/flower/pull/1629), " -"[#1628](https://github.com/adap/flower/pull/1628), " -"[#1620](https://github.com/adap/flower/pull/1620), " -"[#1618](https://github.com/adap/flower/pull/1618), " -"[#1617](https://github.com/adap/flower/pull/1617), " -"[#1613](https://github.com/adap/flower/pull/1613), " -"[#1614](https://github.com/adap/flower/pull/1614))" +"**Updated documentation** ([#1629](https://github.com/adap/flower/" +"pull/1629), [#1628](https://github.com/adap/flower/pull/1628), [#1620]" +"(https://github.com/adap/flower/pull/1620), [#1618](https://github.com/adap/" +"flower/pull/1618), [#1617](https://github.com/adap/flower/pull/1617), [#1613]" +"(https://github.com/adap/flower/pull/1613), [#1614](https://github.com/adap/" +"flower/pull/1614))" msgstr "" #: ../../source/ref-changelog.md:560 ../../source/ref-changelog.md:627 msgid "" -"As usual, the documentation has improved quite a bit. It is another step " -"in our effort to make the Flower documentation the best documentation of " -"any project. Stay tuned and as always, feel free to provide feedback!" +"As usual, the documentation has improved quite a bit. It is another step in " +"our effort to make the Flower documentation the best documentation of any " +"project. Stay tuned and as always, feel free to provide feedback!" msgstr "" #: ../../source/ref-changelog.md:566 @@ -17133,15 +17557,14 @@ msgstr "" #: ../../source/ref-changelog.md:572 msgid "" -"`Adam Narozniak`, `Charles Beauville`, `Daniel J. Beutel`, `Edoardo`, `L." -" Jiang`, `Ragy`, `Taner Topal`, `dannymcy`" +"`Adam Narozniak`, `Charles Beauville`, `Daniel J. Beutel`, `Edoardo`, `L. " +"Jiang`, `Ragy`, `Taner Topal`, `dannymcy`" msgstr "" #: ../../source/ref-changelog.md:576 msgid "" -"**Introduce new Flower Baseline: FedAvg MNIST** " -"([#1497](https://github.com/adap/flower/pull/1497), " -"[#1552](https://github.com/adap/flower/pull/1552))" +"**Introduce new Flower Baseline: FedAvg MNIST** ([#1497](https://github.com/" +"adap/flower/pull/1497), [#1552](https://github.com/adap/flower/pull/1552))" msgstr "" #: ../../source/ref-changelog.md:578 @@ -17150,207 +17573,195 @@ msgid "" "implementations useful especially to FL newcomers. They will typically " "revisit well known papers from the literature, and be suitable for " "integration in your own application or for experimentation, in order to " -"deepen your knowledge of FL in general. Today's release is the first in " -"this series. [Read more.](https://flower.ai/blog/2023-01-12-fl-starter-" -"pack-fedavg-mnist-cnn/)" +"deepen your knowledge of FL in general. Today's release is the first in this " +"series. [Read more.](https://flower.ai/blog/2023-01-12-fl-starter-pack-" +"fedavg-mnist-cnn/)" msgstr "" #: ../../source/ref-changelog.md:580 msgid "" -"**Improve GPU support in simulations** " -"([#1555](https://github.com/adap/flower/pull/1555))" +"**Improve GPU support in simulations** ([#1555](https://github.com/adap/" +"flower/pull/1555))" msgstr "" #: ../../source/ref-changelog.md:582 msgid "" -"The Ray-based Virtual Client Engine (`start_simulation`) has been updated" -" to improve GPU support. The update includes some of the hard-earned " -"lessons from scaling simulations in GPU cluster environments. New " -"defaults make running GPU-based simulations substantially more robust." +"The Ray-based Virtual Client Engine (`start_simulation`) has been updated to " +"improve GPU support. The update includes some of the hard-earned lessons " +"from scaling simulations in GPU cluster environments. New defaults make " +"running GPU-based simulations substantially more robust." msgstr "" #: ../../source/ref-changelog.md:584 msgid "" -"**Improve GPU support in Jupyter Notebook tutorials** " -"([#1527](https://github.com/adap/flower/pull/1527), " -"[#1558](https://github.com/adap/flower/pull/1558))" +"**Improve GPU support in Jupyter Notebook tutorials** ([#1527](https://" +"github.com/adap/flower/pull/1527), [#1558](https://github.com/adap/flower/" +"pull/1558))" msgstr "" #: ../../source/ref-changelog.md:586 msgid "" -"Some users reported that Jupyter Notebooks have not always been easy to " -"use on GPU instances. We listened and made improvements to all of our " -"Jupyter notebooks! Check out the updated notebooks here:" +"Some users reported that Jupyter Notebooks have not always been easy to use " +"on GPU instances. We listened and made improvements to all of our Jupyter " +"notebooks! Check out the updated notebooks here:" msgstr "" #: ../../source/ref-changelog.md:588 msgid "" -"[An Introduction to Federated Learning](https://flower.ai/docs/framework" -"/tutorial-get-started-with-flower-pytorch.html)" +"[An Introduction to Federated Learning](https://flower.ai/docs/framework/" +"tutorial-get-started-with-flower-pytorch.html)" msgstr "" #: ../../source/ref-changelog.md:589 msgid "" -"[Strategies in Federated Learning](https://flower.ai/docs/framework" -"/tutorial-use-a-federated-learning-strategy-pytorch.html)" +"[Strategies in Federated Learning](https://flower.ai/docs/framework/tutorial-" +"use-a-federated-learning-strategy-pytorch.html)" msgstr "" #: ../../source/ref-changelog.md:590 msgid "" -"[Building a Strategy](https://flower.ai/docs/framework/tutorial-build-a" -"-strategy-from-scratch-pytorch.html)" +"[Building a Strategy](https://flower.ai/docs/framework/tutorial-build-a-" +"strategy-from-scratch-pytorch.html)" msgstr "" #: ../../source/ref-changelog.md:591 msgid "" -"[Client and NumPyClient](https://flower.ai/docs/framework/tutorial-" -"customize-the-client-pytorch.html)" +"[Client and NumPyClient](https://flower.ai/docs/framework/tutorial-customize-" +"the-client-pytorch.html)" msgstr "" #: ../../source/ref-changelog.md:593 msgid "" -"**Introduce optional telemetry** " -"([#1533](https://github.com/adap/flower/pull/1533), " -"[#1544](https://github.com/adap/flower/pull/1544), " -"[#1584](https://github.com/adap/flower/pull/1584))" +"**Introduce optional telemetry** ([#1533](https://github.com/adap/flower/" +"pull/1533), [#1544](https://github.com/adap/flower/pull/1544), [#1584]" +"(https://github.com/adap/flower/pull/1584))" msgstr "" #: ../../source/ref-changelog.md:595 msgid "" -"After a [request for " -"feedback](https://github.com/adap/flower/issues/1534) from the community," -" the Flower open-source project introduces optional collection of " -"*anonymous* usage metrics to make well-informed decisions to improve " -"Flower. Doing this enables the Flower team to understand how Flower is " -"used and what challenges users might face." +"After a [request for feedback](https://github.com/adap/flower/issues/1534) " +"from the community, the Flower open-source project introduces optional " +"collection of *anonymous* usage metrics to make well-informed decisions to " +"improve Flower. Doing this enables the Flower team to understand how Flower " +"is used and what challenges users might face." msgstr "" #: ../../source/ref-changelog.md:597 msgid "" -"**Flower is a friendly framework for collaborative AI and data science.**" -" Staying true to this statement, Flower makes it easy to disable " -"telemetry for users who do not want to share anonymous usage metrics. " -"[Read more.](https://flower.ai/docs/telemetry.html)." +"**Flower is a friendly framework for collaborative AI and data science.** " +"Staying true to this statement, Flower makes it easy to disable telemetry " +"for users who do not want to share anonymous usage metrics. [Read more.]" +"(https://flower.ai/docs/telemetry.html)." msgstr "" #: ../../source/ref-changelog.md:599 msgid "" -"**Introduce (experimental) Driver API** " -"([#1520](https://github.com/adap/flower/pull/1520), " -"[#1525](https://github.com/adap/flower/pull/1525), " -"[#1545](https://github.com/adap/flower/pull/1545), " -"[#1546](https://github.com/adap/flower/pull/1546), " -"[#1550](https://github.com/adap/flower/pull/1550), " -"[#1551](https://github.com/adap/flower/pull/1551), " -"[#1567](https://github.com/adap/flower/pull/1567))" +"**Introduce (experimental) Driver API** ([#1520](https://github.com/adap/" +"flower/pull/1520), [#1525](https://github.com/adap/flower/pull/1525), [#1545]" +"(https://github.com/adap/flower/pull/1545), [#1546](https://github.com/adap/" +"flower/pull/1546), [#1550](https://github.com/adap/flower/pull/1550), [#1551]" +"(https://github.com/adap/flower/pull/1551), [#1567](https://github.com/adap/" +"flower/pull/1567))" msgstr "" #: ../../source/ref-changelog.md:601 msgid "" "Flower now has a new (experimental) Driver API which will enable fully " "programmable, async, and multi-tenant Federated Learning and Federated " -"Analytics applications. Phew, that's a lot! Going forward, the Driver API" -" will be the abstraction that many upcoming features will be built on - " -"and you can start building those things now, too." +"Analytics applications. Phew, that's a lot! Going forward, the Driver API " +"will be the abstraction that many upcoming features will be built on - and " +"you can start building those things now, too." msgstr "" #: ../../source/ref-changelog.md:603 msgid "" -"The Driver API also enables a new execution mode in which the server runs" -" indefinitely. Multiple individual workloads can run concurrently and " -"start and stop their execution independent of the server. This is " -"especially useful for users who want to deploy Flower in production." +"The Driver API also enables a new execution mode in which the server runs " +"indefinitely. Multiple individual workloads can run concurrently and start " +"and stop their execution independent of the server. This is especially " +"useful for users who want to deploy Flower in production." msgstr "" #: ../../source/ref-changelog.md:605 msgid "" -"To learn more, check out the `mt-pytorch` code example. We look forward " -"to you feedback!" +"To learn more, check out the `mt-pytorch` code example. We look forward to " +"you feedback!" msgstr "" #: ../../source/ref-changelog.md:607 msgid "" -"Please note: *The Driver API is still experimental and will likely change" -" significantly over time.*" +"Please note: *The Driver API is still experimental and will likely change " +"significantly over time.*" msgstr "" #: ../../source/ref-changelog.md:609 msgid "" -"**Add new Federated Analytics with Pandas example** " -"([#1469](https://github.com/adap/flower/pull/1469), " -"[#1535](https://github.com/adap/flower/pull/1535))" +"**Add new Federated Analytics with Pandas example** ([#1469](https://github." +"com/adap/flower/pull/1469), [#1535](https://github.com/adap/flower/" +"pull/1535))" msgstr "" #: ../../source/ref-changelog.md:611 msgid "" -"A new code example (`quickstart-pandas`) demonstrates federated analytics" -" with Pandas and Flower. You can find it here: [quickstart-" -"pandas](https://github.com/adap/flower/tree/main/examples/quickstart-" -"pandas)." +"A new code example (`quickstart-pandas`) demonstrates federated analytics " +"with Pandas and Flower. You can find it here: [quickstart-pandas](https://" +"github.com/adap/flower/tree/main/examples/quickstart-pandas)." msgstr "" #: ../../source/ref-changelog.md:613 msgid "" -"**Add new strategies: Krum and MultiKrum** " -"([#1481](https://github.com/adap/flower/pull/1481))" +"**Add new strategies: Krum and MultiKrum** ([#1481](https://github.com/adap/" +"flower/pull/1481))" msgstr "" #: ../../source/ref-changelog.md:615 msgid "" "Edoardo, a computer science student at the Sapienza University of Rome, " -"contributed a new `Krum` strategy that enables users to easily use Krum " -"and MultiKrum in their workloads." +"contributed a new `Krum` strategy that enables users to easily use Krum and " +"MultiKrum in their workloads." msgstr "" #: ../../source/ref-changelog.md:617 msgid "" -"**Update C++ example to be compatible with Flower v1.2.0** " -"([#1495](https://github.com/adap/flower/pull/1495))" +"**Update C++ example to be compatible with Flower v1.2.0** ([#1495](https://" +"github.com/adap/flower/pull/1495))" msgstr "" #: ../../source/ref-changelog.md:619 msgid "" -"The C++ code example has received a substantial update to make it " -"compatible with the latest version of Flower." +"The C++ code example has received a substantial update to make it compatible " +"with the latest version of Flower." msgstr "" #: ../../source/ref-changelog.md:621 msgid "" -"**General improvements** " -"([#1491](https://github.com/adap/flower/pull/1491), " -"[#1504](https://github.com/adap/flower/pull/1504), " -"[#1506](https://github.com/adap/flower/pull/1506), " -"[#1514](https://github.com/adap/flower/pull/1514), " -"[#1522](https://github.com/adap/flower/pull/1522), " -"[#1523](https://github.com/adap/flower/pull/1523), " -"[#1526](https://github.com/adap/flower/pull/1526), " -"[#1528](https://github.com/adap/flower/pull/1528), " -"[#1547](https://github.com/adap/flower/pull/1547), " -"[#1549](https://github.com/adap/flower/pull/1549), " -"[#1560](https://github.com/adap/flower/pull/1560), " -"[#1564](https://github.com/adap/flower/pull/1564), " -"[#1566](https://github.com/adap/flower/pull/1566))" +"**General improvements** ([#1491](https://github.com/adap/flower/pull/1491), " +"[#1504](https://github.com/adap/flower/pull/1504), [#1506](https://github." +"com/adap/flower/pull/1506), [#1514](https://github.com/adap/flower/" +"pull/1514), [#1522](https://github.com/adap/flower/pull/1522), [#1523]" +"(https://github.com/adap/flower/pull/1523), [#1526](https://github.com/adap/" +"flower/pull/1526), [#1528](https://github.com/adap/flower/pull/1528), [#1547]" +"(https://github.com/adap/flower/pull/1547), [#1549](https://github.com/adap/" +"flower/pull/1549), [#1560](https://github.com/adap/flower/pull/1560), [#1564]" +"(https://github.com/adap/flower/pull/1564), [#1566](https://github.com/adap/" +"flower/pull/1566))" msgstr "" #: ../../source/ref-changelog.md:625 msgid "" -"**Updated documentation** " -"([#1494](https://github.com/adap/flower/pull/1494), " -"[#1496](https://github.com/adap/flower/pull/1496), " -"[#1500](https://github.com/adap/flower/pull/1500), " -"[#1503](https://github.com/adap/flower/pull/1503), " -"[#1505](https://github.com/adap/flower/pull/1505), " -"[#1524](https://github.com/adap/flower/pull/1524), " -"[#1518](https://github.com/adap/flower/pull/1518), " -"[#1519](https://github.com/adap/flower/pull/1519), " -"[#1515](https://github.com/adap/flower/pull/1515))" +"**Updated documentation** ([#1494](https://github.com/adap/flower/" +"pull/1494), [#1496](https://github.com/adap/flower/pull/1496), [#1500]" +"(https://github.com/adap/flower/pull/1500), [#1503](https://github.com/adap/" +"flower/pull/1503), [#1505](https://github.com/adap/flower/pull/1505), [#1524]" +"(https://github.com/adap/flower/pull/1524), [#1518](https://github.com/adap/" +"flower/pull/1518), [#1519](https://github.com/adap/flower/pull/1519), [#1515]" +"(https://github.com/adap/flower/pull/1515))" msgstr "" #: ../../source/ref-changelog.md:629 msgid "" -"One highlight is the new [first time contributor " -"guide](https://flower.ai/docs/first-time-contributors.html): if you've " -"never contributed on GitHub before, this is the perfect place to start!" +"One highlight is the new [first time contributor guide](https://flower.ai/" +"docs/first-time-contributors.html): if you've never contributed on GitHub " +"before, this is the perfect place to start!" msgstr "" #: ../../source/ref-changelog.md:635 @@ -17367,110 +17778,106 @@ msgstr "" msgid "" "`Akis Linardos`, `Christopher S`, `Daniel J. Beutel`, `George`, `Jan " "Schlicht`, `Mohammad Fares`, `Pedro Porto Buarque de Gusmão`, `Philipp " -"Wiesner`, `Rob Luke`, `Taner Topal`, `VasundharaAgarwal`, " -"`danielnugraha`, `edogab33`" +"Wiesner`, `Rob Luke`, `Taner Topal`, `VasundharaAgarwal`, `danielnugraha`, " +"`edogab33`" msgstr "" #: ../../source/ref-changelog.md:645 msgid "" -"**Introduce Differential Privacy wrappers (preview)** " -"([#1357](https://github.com/adap/flower/pull/1357), " -"[#1460](https://github.com/adap/flower/pull/1460))" +"**Introduce Differential Privacy wrappers (preview)** ([#1357](https://" +"github.com/adap/flower/pull/1357), [#1460](https://github.com/adap/flower/" +"pull/1460))" msgstr "" #: ../../source/ref-changelog.md:647 msgid "" -"The first (experimental) preview of pluggable Differential Privacy " -"wrappers enables easy configuration and usage of differential privacy " -"(DP). The pluggable DP wrappers enable framework-agnostic **and** " -"strategy-agnostic usage of both client-side DP and server-side DP. Head " -"over to the Flower docs, a new explainer goes into more detail." +"The first (experimental) preview of pluggable Differential Privacy wrappers " +"enables easy configuration and usage of differential privacy (DP). The " +"pluggable DP wrappers enable framework-agnostic **and** strategy-agnostic " +"usage of both client-side DP and server-side DP. Head over to the Flower " +"docs, a new explainer goes into more detail." msgstr "" #: ../../source/ref-changelog.md:649 msgid "" -"**New iOS CoreML code example** " -"([#1289](https://github.com/adap/flower/pull/1289))" +"**New iOS CoreML code example** ([#1289](https://github.com/adap/flower/" +"pull/1289))" msgstr "" #: ../../source/ref-changelog.md:651 msgid "" -"Flower goes iOS! A massive new code example shows how Flower clients can " -"be built for iOS. The code example contains both Flower iOS SDK " -"components that can be used for many tasks, and one task example running " -"on CoreML." +"Flower goes iOS! A massive new code example shows how Flower clients can be " +"built for iOS. The code example contains both Flower iOS SDK components that " +"can be used for many tasks, and one task example running on CoreML." msgstr "" #: ../../source/ref-changelog.md:653 msgid "" -"**New FedMedian strategy** " -"([#1461](https://github.com/adap/flower/pull/1461))" +"**New FedMedian strategy** ([#1461](https://github.com/adap/flower/" +"pull/1461))" msgstr "" #: ../../source/ref-changelog.md:655 msgid "" -"The new `FedMedian` strategy implements Federated Median (FedMedian) by " -"[Yin et al., 2018](https://arxiv.org/pdf/1803.01498v1.pdf)." +"The new `FedMedian` strategy implements Federated Median (FedMedian) by [Yin " +"et al., 2018](https://arxiv.org/pdf/1803.01498v1.pdf)." msgstr "" #: ../../source/ref-changelog.md:657 msgid "" -"**Log** `Client` **exceptions in Virtual Client Engine** " -"([#1493](https://github.com/adap/flower/pull/1493))" +"**Log** `Client` **exceptions in Virtual Client Engine** ([#1493](https://" +"github.com/adap/flower/pull/1493))" msgstr "" #: ../../source/ref-changelog.md:659 msgid "" -"All `Client` exceptions happening in the VCE are now logged by default " -"and not just exposed to the configured `Strategy` (via the `failures` " -"argument)." +"All `Client` exceptions happening in the VCE are now logged by default and " +"not just exposed to the configured `Strategy` (via the `failures` argument)." msgstr "" #: ../../source/ref-changelog.md:661 msgid "" -"**Improve Virtual Client Engine internals** " -"([#1401](https://github.com/adap/flower/pull/1401), " -"[#1453](https://github.com/adap/flower/pull/1453))" +"**Improve Virtual Client Engine internals** ([#1401](https://github.com/adap/" +"flower/pull/1401), [#1453](https://github.com/adap/flower/pull/1453))" msgstr "" #: ../../source/ref-changelog.md:663 msgid "" -"Some internals of the Virtual Client Engine have been revamped. The VCE " -"now uses Ray 2.0 under the hood, the value type of the `client_resources`" -" dictionary changed to `float` to allow fractions of resources to be " +"Some internals of the Virtual Client Engine have been revamped. The VCE now " +"uses Ray 2.0 under the hood, the value type of the `client_resources` " +"dictionary changed to `float` to allow fractions of resources to be " "allocated." msgstr "" #: ../../source/ref-changelog.md:665 msgid "" -"**Support optional** `Client`**/**`NumPyClient` **methods in Virtual " -"Client Engine**" +"**Support optional** `Client`**/**`NumPyClient` **methods in Virtual Client " +"Engine**" msgstr "" #: ../../source/ref-changelog.md:667 msgid "" -"The Virtual Client Engine now has full support for optional `Client` (and" -" `NumPyClient`) methods." +"The Virtual Client Engine now has full support for optional `Client` (and " +"`NumPyClient`) methods." msgstr "" #: ../../source/ref-changelog.md:669 msgid "" -"**Provide type information to packages using** `flwr` " -"([#1377](https://github.com/adap/flower/pull/1377))" +"**Provide type information to packages using** `flwr` ([#1377](https://" +"github.com/adap/flower/pull/1377))" msgstr "" #: ../../source/ref-changelog.md:671 msgid "" -"The package `flwr` is now bundled with a `py.typed` file indicating that " -"the package is typed. This enables typing support for projects or " -"packages that use `flwr` by enabling them to improve their code using " -"static type checkers like `mypy`." +"The package `flwr` is now bundled with a `py.typed` file indicating that the " +"package is typed. This enables typing support for projects or packages that " +"use `flwr` by enabling them to improve their code using static type checkers " +"like `mypy`." msgstr "" #: ../../source/ref-changelog.md:673 msgid "" -"**Updated code example** " -"([#1344](https://github.com/adap/flower/pull/1344), " +"**Updated code example** ([#1344](https://github.com/adap/flower/pull/1344), " "[#1347](https://github.com/adap/flower/pull/1347))" msgstr "" @@ -17482,24 +17889,18 @@ msgstr "" #: ../../source/ref-changelog.md:677 msgid "" -"**Updated documentation** " -"([#1355](https://github.com/adap/flower/pull/1355), " -"[#1558](https://github.com/adap/flower/pull/1558), " -"[#1379](https://github.com/adap/flower/pull/1379), " -"[#1380](https://github.com/adap/flower/pull/1380), " -"[#1381](https://github.com/adap/flower/pull/1381), " -"[#1332](https://github.com/adap/flower/pull/1332), " -"[#1391](https://github.com/adap/flower/pull/1391), " -"[#1403](https://github.com/adap/flower/pull/1403), " -"[#1364](https://github.com/adap/flower/pull/1364), " -"[#1409](https://github.com/adap/flower/pull/1409), " -"[#1419](https://github.com/adap/flower/pull/1419), " -"[#1444](https://github.com/adap/flower/pull/1444), " -"[#1448](https://github.com/adap/flower/pull/1448), " -"[#1417](https://github.com/adap/flower/pull/1417), " -"[#1449](https://github.com/adap/flower/pull/1449), " -"[#1465](https://github.com/adap/flower/pull/1465), " -"[#1467](https://github.com/adap/flower/pull/1467))" +"**Updated documentation** ([#1355](https://github.com/adap/flower/" +"pull/1355), [#1558](https://github.com/adap/flower/pull/1558), [#1379]" +"(https://github.com/adap/flower/pull/1379), [#1380](https://github.com/adap/" +"flower/pull/1380), [#1381](https://github.com/adap/flower/pull/1381), [#1332]" +"(https://github.com/adap/flower/pull/1332), [#1391](https://github.com/adap/" +"flower/pull/1391), [#1403](https://github.com/adap/flower/pull/1403), [#1364]" +"(https://github.com/adap/flower/pull/1364), [#1409](https://github.com/adap/" +"flower/pull/1409), [#1419](https://github.com/adap/flower/pull/1419), [#1444]" +"(https://github.com/adap/flower/pull/1444), [#1448](https://github.com/adap/" +"flower/pull/1448), [#1417](https://github.com/adap/flower/pull/1417), [#1449]" +"(https://github.com/adap/flower/pull/1449), [#1465](https://github.com/adap/" +"flower/pull/1465), [#1467](https://github.com/adap/flower/pull/1467))" msgstr "" #: ../../source/ref-changelog.md:679 @@ -17510,47 +17911,45 @@ msgstr "" #: ../../source/ref-changelog.md:681 msgid "" -"**Restructured documentation** " -"([#1387](https://github.com/adap/flower/pull/1387))" +"**Restructured documentation** ([#1387](https://github.com/adap/flower/" +"pull/1387))" msgstr "" #: ../../source/ref-changelog.md:683 msgid "" -"The documentation has been restructured to make it easier to navigate. " -"This is just the first step in a larger effort to make the Flower " -"documentation the best documentation of any project ever. Stay tuned!" +"The documentation has been restructured to make it easier to navigate. This " +"is just the first step in a larger effort to make the Flower documentation " +"the best documentation of any project ever. Stay tuned!" msgstr "" #: ../../source/ref-changelog.md:685 msgid "" -"**Open in Colab button** " -"([#1389](https://github.com/adap/flower/pull/1389))" +"**Open in Colab button** ([#1389](https://github.com/adap/flower/pull/1389))" msgstr "" #: ../../source/ref-changelog.md:687 msgid "" -"The four parts of the Flower Federated Learning Tutorial now come with a " -"new `Open in Colab` button. No need to install anything on your local " -"machine, you can now use and learn about Flower in your browser, it's " -"only a single click away." +"The four parts of the Flower Federated Learning Tutorial now come with a new " +"`Open in Colab` button. No need to install anything on your local machine, " +"you can now use and learn about Flower in your browser, it's only a single " +"click away." msgstr "" #: ../../source/ref-changelog.md:689 msgid "" -"**Improved tutorial** ([#1468](https://github.com/adap/flower/pull/1468)," -" [#1470](https://github.com/adap/flower/pull/1470), " -"[#1472](https://github.com/adap/flower/pull/1472), " -"[#1473](https://github.com/adap/flower/pull/1473), " -"[#1474](https://github.com/adap/flower/pull/1474), " -"[#1475](https://github.com/adap/flower/pull/1475))" +"**Improved tutorial** ([#1468](https://github.com/adap/flower/pull/1468), " +"[#1470](https://github.com/adap/flower/pull/1470), [#1472](https://github." +"com/adap/flower/pull/1472), [#1473](https://github.com/adap/flower/" +"pull/1473), [#1474](https://github.com/adap/flower/pull/1474), [#1475]" +"(https://github.com/adap/flower/pull/1475))" msgstr "" #: ../../source/ref-changelog.md:691 msgid "" "The Flower Federated Learning Tutorial has two brand-new parts covering " "custom strategies (still WIP) and the distinction between `Client` and " -"`NumPyClient`. The existing parts one and two have also been improved " -"(many small changes and fixes)." +"`NumPyClient`. The existing parts one and two have also been improved (many " +"small changes and fixes)." msgstr "" #: ../../source/ref-changelog.md:697 @@ -17575,93 +17974,79 @@ msgstr "" #: ../../source/ref-changelog.md:704 msgid "" -"Tons of small API cleanups resulting in a more coherent developer " -"experience" +"Tons of small API cleanups resulting in a more coherent developer experience" msgstr "" #: ../../source/ref-changelog.md:708 msgid "" "We would like to give our **special thanks** to all the contributors who " -"made Flower 1.0 possible (in reverse [GitHub " -"Contributors](https://github.com/adap/flower/graphs/contributors) order):" +"made Flower 1.0 possible (in reverse [GitHub Contributors](https://github." +"com/adap/flower/graphs/contributors) order):" msgstr "" #: ../../source/ref-changelog.md:710 msgid "" -"[@rtaiello](https://github.com/rtaiello), " -"[@g-pichler](https://github.com/g-pichler), [@rob-" -"luke](https://github.com/rob-luke), [@andreea-zaharia](https://github.com" -"/andreea-zaharia), [@kinshukdua](https://github.com/kinshukdua), " -"[@nfnt](https://github.com/nfnt), " -"[@tatiana-s](https://github.com/tatiana-s), " -"[@TParcollet](https://github.com/TParcollet), " -"[@vballoli](https://github.com/vballoli), " -"[@negedng](https://github.com/negedng), " -"[@RISHIKESHAVAN](https://github.com/RISHIKESHAVAN), " -"[@hei411](https://github.com/hei411), " -"[@SebastianSpeitel](https://github.com/SebastianSpeitel), " -"[@AmitChaulwar](https://github.com/AmitChaulwar), " -"[@Rubiel1](https://github.com/Rubiel1), [@FANTOME-PAN](https://github.com" -"/FANTOME-PAN), [@Rono-BC](https://github.com/Rono-BC), " -"[@lbhm](https://github.com/lbhm), " -"[@sishtiaq](https://github.com/sishtiaq), " -"[@remde](https://github.com/remde), [@Jueun-Park](https://github.com" -"/Jueun-Park), [@architjen](https://github.com/architjen), " -"[@PratikGarai](https://github.com/PratikGarai), " -"[@mrinaald](https://github.com/mrinaald), " -"[@zliel](https://github.com/zliel), " -"[@MeiruiJiang](https://github.com/MeiruiJiang), " -"[@sancarlim](https://github.com/sancarlim), " -"[@gubertoli](https://github.com/gubertoli), " -"[@Vingt100](https://github.com/Vingt100), " -"[@MakGulati](https://github.com/MakGulati), " -"[@cozek](https://github.com/cozek), " -"[@jafermarq](https://github.com/jafermarq), " -"[@sisco0](https://github.com/sisco0), " -"[@akhilmathurs](https://github.com/akhilmathurs), " -"[@CanTuerk](https://github.com/CanTuerk), " -"[@mariaboerner1987](https://github.com/mariaboerner1987), " -"[@pedropgusmao](https://github.com/pedropgusmao), " -"[@tanertopal](https://github.com/tanertopal), " -"[@danieljanes](https://github.com/danieljanes)." +"[@rtaiello](https://github.com/rtaiello), [@g-pichler](https://github.com/g-" +"pichler), [@rob-luke](https://github.com/rob-luke), [@andreea-zaharia]" +"(https://github.com/andreea-zaharia), [@kinshukdua](https://github.com/" +"kinshukdua), [@nfnt](https://github.com/nfnt), [@tatiana-s](https://github." +"com/tatiana-s), [@TParcollet](https://github.com/TParcollet), [@vballoli]" +"(https://github.com/vballoli), [@negedng](https://github.com/negedng), " +"[@RISHIKESHAVAN](https://github.com/RISHIKESHAVAN), [@hei411](https://github." +"com/hei411), [@SebastianSpeitel](https://github.com/SebastianSpeitel), " +"[@AmitChaulwar](https://github.com/AmitChaulwar), [@Rubiel1](https://github." +"com/Rubiel1), [@FANTOME-PAN](https://github.com/FANTOME-PAN), [@Rono-BC]" +"(https://github.com/Rono-BC), [@lbhm](https://github.com/lbhm), [@sishtiaq]" +"(https://github.com/sishtiaq), [@remde](https://github.com/remde), [@Jueun-" +"Park](https://github.com/Jueun-Park), [@architjen](https://github.com/" +"architjen), [@PratikGarai](https://github.com/PratikGarai), [@mrinaald]" +"(https://github.com/mrinaald), [@zliel](https://github.com/zliel), " +"[@MeiruiJiang](https://github.com/MeiruiJiang), [@sancarlim](https://github." +"com/sancarlim), [@gubertoli](https://github.com/gubertoli), [@Vingt100]" +"(https://github.com/Vingt100), [@MakGulati](https://github.com/MakGulati), " +"[@cozek](https://github.com/cozek), [@jafermarq](https://github.com/" +"jafermarq), [@sisco0](https://github.com/sisco0), [@akhilmathurs](https://" +"github.com/akhilmathurs), [@CanTuerk](https://github.com/CanTuerk), " +"[@mariaboerner1987](https://github.com/mariaboerner1987), [@pedropgusmao]" +"(https://github.com/pedropgusmao), [@tanertopal](https://github.com/" +"tanertopal), [@danieljanes](https://github.com/danieljanes)." msgstr "" #: ../../source/ref-changelog.md:714 msgid "" -"**All arguments must be passed as keyword arguments** " -"([#1338](https://github.com/adap/flower/pull/1338))" +"**All arguments must be passed as keyword arguments** ([#1338](https://" +"github.com/adap/flower/pull/1338))" msgstr "" #: ../../source/ref-changelog.md:716 msgid "" -"Pass all arguments as keyword arguments, positional arguments are not " -"longer supported. Code that uses positional arguments (e.g., " -"`start_client(\"127.0.0.1:8080\", FlowerClient())`) must add the keyword " -"for each positional argument (e.g., " -"`start_client(server_address=\"127.0.0.1:8080\", " -"client=FlowerClient())`)." +"Pass all arguments as keyword arguments, positional arguments are not longer " +"supported. Code that uses positional arguments (e.g., " +"`start_client(\"127.0.0.1:8080\", FlowerClient())`) must add the keyword for " +"each positional argument (e.g., " +"`start_client(server_address=\"127.0.0.1:8080\", client=FlowerClient())`)." msgstr "" #: ../../source/ref-changelog.md:718 msgid "" "**Introduce configuration object** `ServerConfig` **in** `start_server` " -"**and** `start_simulation` " -"([#1317](https://github.com/adap/flower/pull/1317))" +"**and** `start_simulation` ([#1317](https://github.com/adap/flower/" +"pull/1317))" msgstr "" #: ../../source/ref-changelog.md:720 msgid "" -"Instead of a config dictionary `{\"num_rounds\": 3, \"round_timeout\": " -"600.0}`, `start_server` and `start_simulation` now expect a configuration" -" object of type `flwr.server.ServerConfig`. `ServerConfig` takes the same" -" arguments that as the previous config dict, but it makes writing type-" -"safe code easier and the default parameters values more transparent." +"Instead of a config dictionary `{\"num_rounds\": 3, \"round_timeout\": 600.0}" +"`, `start_server` and `start_simulation` now expect a configuration object " +"of type `flwr.server.ServerConfig`. `ServerConfig` takes the same arguments " +"that as the previous config dict, but it makes writing type-safe code easier " +"and the default parameters values more transparent." msgstr "" #: ../../source/ref-changelog.md:722 msgid "" -"**Rename built-in strategy parameters for clarity** " -"([#1334](https://github.com/adap/flower/pull/1334))" +"**Rename built-in strategy parameters for clarity** ([#1334](https://github." +"com/adap/flower/pull/1334))" msgstr "" #: ../../source/ref-changelog.md:724 @@ -17684,17 +18069,17 @@ msgstr "" #: ../../source/ref-changelog.md:730 msgid "" -"**Update default arguments of built-in strategies** " -"([#1278](https://github.com/adap/flower/pull/1278))" +"**Update default arguments of built-in strategies** ([#1278](https://github." +"com/adap/flower/pull/1278))" msgstr "" #: ../../source/ref-changelog.md:732 msgid "" "All built-in strategies now use `fraction_fit=1.0` and " -"`fraction_evaluate=1.0`, which means they select *all* currently " -"available clients for training and evaluation. Projects that relied on " -"the previous default values can get the previous behaviour by " -"initializing the strategy in the following way:" +"`fraction_evaluate=1.0`, which means they select *all* currently available " +"clients for training and evaluation. Projects that relied on the previous " +"default values can get the previous behaviour by initializing the strategy " +"in the following way:" msgstr "" #: ../../source/ref-changelog.md:734 @@ -17703,14 +18088,14 @@ msgstr "" #: ../../source/ref-changelog.md:736 msgid "" -"**Add** `server_round` **to** `Strategy.evaluate` " -"([#1334](https://github.com/adap/flower/pull/1334))" +"**Add** `server_round` **to** `Strategy.evaluate` ([#1334](https://github." +"com/adap/flower/pull/1334))" msgstr "" #: ../../source/ref-changelog.md:738 msgid "" -"The `Strategy` method `evaluate` now receives the current round of " -"federated learning/evaluation as the first parameter." +"The `Strategy` method `evaluate` now receives the current round of federated " +"learning/evaluation as the first parameter." msgstr "" #: ../../source/ref-changelog.md:740 @@ -17723,39 +18108,40 @@ msgstr "" msgid "" "The `evaluate_fn` passed to built-in strategies like `FedAvg` now takes " "three parameters: (1) The current round of federated learning/evaluation " -"(`server_round`), (2) the model parameters to evaluate (`parameters`), " -"and (3) a config dictionary (`config`)." +"(`server_round`), (2) the model parameters to evaluate (`parameters`), and " +"(3) a config dictionary (`config`)." msgstr "" #: ../../source/ref-changelog.md:744 msgid "" -"**Rename** `rnd` **to** `server_round` " -"([#1321](https://github.com/adap/flower/pull/1321))" +"**Rename** `rnd` **to** `server_round` ([#1321](https://github.com/adap/" +"flower/pull/1321))" msgstr "" #: ../../source/ref-changelog.md:746 msgid "" "Several Flower methods and functions (`evaluate_fn`, `configure_fit`, " "`aggregate_fit`, `configure_evaluate`, `aggregate_evaluate`) receive the " -"current round of federated learning/evaluation as their first parameter. " -"To improve reaability and avoid confusion with *random*, this parameter " -"has been renamed from `rnd` to `server_round`." +"current round of federated learning/evaluation as their first parameter. To " +"improve reaability and avoid confusion with *random*, this parameter has " +"been renamed from `rnd` to `server_round`." msgstr "" #: ../../source/ref-changelog.md:748 msgid "" -"**Move** `flwr.dataset` **to** `flwr_baselines` " -"([#1273](https://github.com/adap/flower/pull/1273))" +"**Move** `flwr.dataset` **to** `flwr_baselines` ([#1273](https://github.com/" +"adap/flower/pull/1273))" msgstr "" #: ../../source/ref-changelog.md:750 -msgid "The experimental package `flwr.dataset` was migrated to Flower Baselines." +msgid "" +"The experimental package `flwr.dataset` was migrated to Flower Baselines." msgstr "" #: ../../source/ref-changelog.md:752 msgid "" -"**Remove experimental strategies** " -"([#1280](https://github.com/adap/flower/pull/1280))" +"**Remove experimental strategies** ([#1280](https://github.com/adap/flower/" +"pull/1280))" msgstr "" #: ../../source/ref-changelog.md:754 @@ -17766,9 +18152,8 @@ msgstr "" #: ../../source/ref-changelog.md:756 msgid "" -"**Rename** `Weights` **to** `NDArrays` " -"([#1258](https://github.com/adap/flower/pull/1258), " -"[#1259](https://github.com/adap/flower/pull/1259))" +"**Rename** `Weights` **to** `NDArrays` ([#1258](https://github.com/adap/" +"flower/pull/1258), [#1259](https://github.com/adap/flower/pull/1259))" msgstr "" #: ../../source/ref-changelog.md:758 @@ -17779,21 +18164,21 @@ msgstr "" #: ../../source/ref-changelog.md:760 msgid "" -"**Remove antiquated** `force_final_distributed_eval` **from** " -"`start_server` ([#1258](https://github.com/adap/flower/pull/1258), " -"[#1259](https://github.com/adap/flower/pull/1259))" +"**Remove antiquated** `force_final_distributed_eval` **from** `start_server` " +"([#1258](https://github.com/adap/flower/pull/1258), [#1259](https://github." +"com/adap/flower/pull/1259))" msgstr "" #: ../../source/ref-changelog.md:762 msgid "" -"The `start_server` parameter `force_final_distributed_eval` has long been" -" a historic artefact, in this release it is finally gone for good." +"The `start_server` parameter `force_final_distributed_eval` has long been a " +"historic artefact, in this release it is finally gone for good." msgstr "" #: ../../source/ref-changelog.md:764 msgid "" -"**Make** `get_parameters` **configurable** " -"([#1242](https://github.com/adap/flower/pull/1242))" +"**Make** `get_parameters` **configurable** ([#1242](https://github.com/adap/" +"flower/pull/1242))" msgstr "" #: ../../source/ref-changelog.md:766 @@ -17811,64 +18196,62 @@ msgstr "" #: ../../source/ref-changelog.md:770 msgid "" "The `start_simulation` function now accepts a configuration dictionary " -"`config` instead of the `num_rounds` integer. This improves the " -"consistency between `start_simulation` and `start_server` and makes " -"transitioning between the two easier." +"`config` instead of the `num_rounds` integer. This improves the consistency " +"between `start_simulation` and `start_server` and makes transitioning " +"between the two easier." msgstr "" #: ../../source/ref-changelog.md:774 msgid "" -"**Support Python 3.10** " -"([#1320](https://github.com/adap/flower/pull/1320))" +"**Support Python 3.10** ([#1320](https://github.com/adap/flower/pull/1320))" msgstr "" #: ../../source/ref-changelog.md:776 msgid "" -"The previous Flower release introduced experimental support for Python " -"3.10, this release declares Python 3.10 support as stable." +"The previous Flower release introduced experimental support for Python 3.10, " +"this release declares Python 3.10 support as stable." msgstr "" #: ../../source/ref-changelog.md:778 msgid "" -"**Make all** `Client` **and** `NumPyClient` **methods optional** " -"([#1260](https://github.com/adap/flower/pull/1260), " -"[#1277](https://github.com/adap/flower/pull/1277))" +"**Make all** `Client` **and** `NumPyClient` **methods optional** ([#1260]" +"(https://github.com/adap/flower/pull/1260), [#1277](https://github.com/adap/" +"flower/pull/1277))" msgstr "" #: ../../source/ref-changelog.md:780 msgid "" "The `Client`/`NumPyClient` methods `get_properties`, `get_parameters`, " -"`fit`, and `evaluate` are all optional. This enables writing clients that" -" implement, for example, only `fit`, but no other method. No need to " +"`fit`, and `evaluate` are all optional. This enables writing clients that " +"implement, for example, only `fit`, but no other method. No need to " "implement `evaluate` when using centralized evaluation!" msgstr "" #: ../../source/ref-changelog.md:782 msgid "" -"**Enable passing a** `Server` **instance to** `start_simulation` " -"([#1281](https://github.com/adap/flower/pull/1281))" +"**Enable passing a** `Server` **instance to** `start_simulation` ([#1281]" +"(https://github.com/adap/flower/pull/1281))" msgstr "" #: ../../source/ref-changelog.md:784 msgid "" -"Similar to `start_server`, `start_simulation` now accepts a full `Server`" -" instance. This enables users to heavily customize the execution of " -"eperiments and opens the door to running, for example, async FL using the" -" Virtual Client Engine." +"Similar to `start_server`, `start_simulation` now accepts a full `Server` " +"instance. This enables users to heavily customize the execution of " +"eperiments and opens the door to running, for example, async FL using the " +"Virtual Client Engine." msgstr "" #: ../../source/ref-changelog.md:786 msgid "" -"**Update code examples** " -"([#1291](https://github.com/adap/flower/pull/1291), " -"[#1286](https://github.com/adap/flower/pull/1286), " -"[#1282](https://github.com/adap/flower/pull/1282))" +"**Update code examples** ([#1291](https://github.com/adap/flower/pull/1291), " +"[#1286](https://github.com/adap/flower/pull/1286), [#1282](https://github." +"com/adap/flower/pull/1282))" msgstr "" #: ../../source/ref-changelog.md:788 msgid "" -"Many code examples received small or even large maintenance updates, " -"among them are" +"Many code examples received small or even large maintenance updates, among " +"them are" msgstr "" #: ../../source/ref-changelog.md:790 @@ -17897,8 +18280,8 @@ msgstr "" #: ../../source/ref-changelog.md:797 msgid "" -"**Remove the obsolete simulation example** " -"([#1328](https://github.com/adap/flower/pull/1328))" +"**Remove the obsolete simulation example** ([#1328](https://github.com/adap/" +"flower/pull/1328))" msgstr "" #: ../../source/ref-changelog.md:799 @@ -17910,27 +18293,24 @@ msgstr "" #: ../../source/ref-changelog.md:801 msgid "" -"**Update documentation** " -"([#1223](https://github.com/adap/flower/pull/1223), " -"[#1209](https://github.com/adap/flower/pull/1209), " -"[#1251](https://github.com/adap/flower/pull/1251), " -"[#1257](https://github.com/adap/flower/pull/1257), " -"[#1267](https://github.com/adap/flower/pull/1267), " -"[#1268](https://github.com/adap/flower/pull/1268), " -"[#1300](https://github.com/adap/flower/pull/1300), " -"[#1304](https://github.com/adap/flower/pull/1304), " -"[#1305](https://github.com/adap/flower/pull/1305), " -"[#1307](https://github.com/adap/flower/pull/1307))" +"**Update documentation** ([#1223](https://github.com/adap/flower/pull/1223), " +"[#1209](https://github.com/adap/flower/pull/1209), [#1251](https://github." +"com/adap/flower/pull/1251), [#1257](https://github.com/adap/flower/" +"pull/1257), [#1267](https://github.com/adap/flower/pull/1267), [#1268]" +"(https://github.com/adap/flower/pull/1268), [#1300](https://github.com/adap/" +"flower/pull/1300), [#1304](https://github.com/adap/flower/pull/1304), [#1305]" +"(https://github.com/adap/flower/pull/1305), [#1307](https://github.com/adap/" +"flower/pull/1307))" msgstr "" #: ../../source/ref-changelog.md:803 msgid "" "One substantial documentation update fixes multiple smaller rendering " "issues, makes titles more succinct to improve navigation, removes a " -"deprecated library, updates documentation dependencies, includes the " -"`flwr.common` module in the API reference, includes support for markdown-" -"based documentation, migrates the changelog from `.rst` to `.md`, and " -"fixes a number of smaller details!" +"deprecated library, updates documentation dependencies, includes the `flwr." +"common` module in the API reference, includes support for markdown-based " +"documentation, migrates the changelog from `.rst` to `.md`, and fixes a " +"number of smaller details!" msgstr "" #: ../../source/ref-changelog.md:805 ../../source/ref-changelog.md:860 @@ -17940,30 +18320,28 @@ msgstr "" #: ../../source/ref-changelog.md:807 msgid "" -"Add round number to fit and evaluate log messages " -"([#1266](https://github.com/adap/flower/pull/1266))" +"Add round number to fit and evaluate log messages ([#1266](https://github." +"com/adap/flower/pull/1266))" msgstr "" #: ../../source/ref-changelog.md:808 msgid "" -"Add secure gRPC connection to the `advanced_tensorflow` code example " -"([#847](https://github.com/adap/flower/pull/847))" +"Add secure gRPC connection to the `advanced_tensorflow` code example ([#847]" +"(https://github.com/adap/flower/pull/847))" msgstr "" #: ../../source/ref-changelog.md:809 msgid "" -"Update developer tooling " -"([#1231](https://github.com/adap/flower/pull/1231), " -"[#1276](https://github.com/adap/flower/pull/1276), " -"[#1301](https://github.com/adap/flower/pull/1301), " -"[#1310](https://github.com/adap/flower/pull/1310))" +"Update developer tooling ([#1231](https://github.com/adap/flower/pull/1231), " +"[#1276](https://github.com/adap/flower/pull/1276), [#1301](https://github." +"com/adap/flower/pull/1301), [#1310](https://github.com/adap/flower/" +"pull/1310))" msgstr "" #: ../../source/ref-changelog.md:810 msgid "" -"Rename ProtoBuf messages to improve consistency " -"([#1214](https://github.com/adap/flower/pull/1214), " -"[#1258](https://github.com/adap/flower/pull/1258), " +"Rename ProtoBuf messages to improve consistency ([#1214](https://github.com/" +"adap/flower/pull/1214), [#1258](https://github.com/adap/flower/pull/1258), " "[#1259](https://github.com/adap/flower/pull/1259))" msgstr "" @@ -17973,123 +18351,120 @@ msgstr "" #: ../../source/ref-changelog.md:816 msgid "" -"**Flower Baselines (preview): FedOpt, FedBN, FedAvgM** " -"([#919](https://github.com/adap/flower/pull/919), " -"[#1127](https://github.com/adap/flower/pull/1127), " -"[#914](https://github.com/adap/flower/pull/914))" +"**Flower Baselines (preview): FedOpt, FedBN, FedAvgM** ([#919](https://" +"github.com/adap/flower/pull/919), [#1127](https://github.com/adap/flower/" +"pull/1127), [#914](https://github.com/adap/flower/pull/914))" msgstr "" #: ../../source/ref-changelog.md:818 msgid "" "The first preview release of Flower Baselines has arrived! We're " "kickstarting Flower Baselines with implementations of FedOpt (FedYogi, " -"FedAdam, FedAdagrad), FedBN, and FedAvgM. Check the documentation on how " -"to use [Flower Baselines](https://flower.ai/docs/using-baselines.html). " -"With this first preview release we're also inviting the community to " -"[contribute their own baselines](https://flower.ai/docs/baselines/how-to-" -"contribute-baselines.html)." +"FedAdam, FedAdagrad), FedBN, and FedAvgM. Check the documentation on how to " +"use [Flower Baselines](https://flower.ai/docs/using-baselines.html). With " +"this first preview release we're also inviting the community to [contribute " +"their own baselines](https://flower.ai/docs/baselines/how-to-contribute-" +"baselines.html)." msgstr "" #: ../../source/ref-changelog.md:820 msgid "" -"**C++ client SDK (preview) and code example** " -"([#1111](https://github.com/adap/flower/pull/1111))" +"**C++ client SDK (preview) and code example** ([#1111](https://github.com/" +"adap/flower/pull/1111))" msgstr "" #: ../../source/ref-changelog.md:822 msgid "" -"Preview support for Flower clients written in C++. The C++ preview " -"includes a Flower client SDK and a quickstart code example that " -"demonstrates a simple C++ client using the SDK." +"Preview support for Flower clients written in C++. The C++ preview includes " +"a Flower client SDK and a quickstart code example that demonstrates a simple " +"C++ client using the SDK." msgstr "" #: ../../source/ref-changelog.md:824 msgid "" -"**Add experimental support for Python 3.10 and Python 3.11** " -"([#1135](https://github.com/adap/flower/pull/1135))" +"**Add experimental support for Python 3.10 and Python 3.11** ([#1135]" +"(https://github.com/adap/flower/pull/1135))" msgstr "" #: ../../source/ref-changelog.md:826 msgid "" -"Python 3.10 is the latest stable release of Python and Python 3.11 is due" -" to be released in October. This Flower release adds experimental support" -" for both Python versions." +"Python 3.10 is the latest stable release of Python and Python 3.11 is due to " +"be released in October. This Flower release adds experimental support for " +"both Python versions." msgstr "" #: ../../source/ref-changelog.md:828 msgid "" -"**Aggregate custom metrics through user-provided functions** " -"([#1144](https://github.com/adap/flower/pull/1144))" +"**Aggregate custom metrics through user-provided functions** ([#1144]" +"(https://github.com/adap/flower/pull/1144))" msgstr "" #: ../../source/ref-changelog.md:830 msgid "" -"Custom metrics (e.g., `accuracy`) can now be aggregated without having to" -" customize the strategy. Built-in strategies support two new arguments, " +"Custom metrics (e.g., `accuracy`) can now be aggregated without having to " +"customize the strategy. Built-in strategies support two new arguments, " "`fit_metrics_aggregation_fn` and `evaluate_metrics_aggregation_fn`, that " "allow passing custom metric aggregation functions." msgstr "" #: ../../source/ref-changelog.md:832 msgid "" -"**User-configurable round timeout** " -"([#1162](https://github.com/adap/flower/pull/1162))" +"**User-configurable round timeout** ([#1162](https://github.com/adap/flower/" +"pull/1162))" msgstr "" #: ../../source/ref-changelog.md:834 msgid "" "A new configuration value allows the round timeout to be set for " -"`start_server` and `start_simulation`. If the `config` dictionary " -"contains a `round_timeout` key (with a `float` value in seconds), the " -"server will wait *at least* `round_timeout` seconds before it closes the " -"connection." +"`start_server` and `start_simulation`. If the `config` dictionary contains a " +"`round_timeout` key (with a `float` value in seconds), the server will wait " +"*at least* `round_timeout` seconds before it closes the connection." msgstr "" #: ../../source/ref-changelog.md:836 msgid "" -"**Enable both federated evaluation and centralized evaluation to be used " -"at the same time in all built-in strategies** " -"([#1091](https://github.com/adap/flower/pull/1091))" +"**Enable both federated evaluation and centralized evaluation to be used at " +"the same time in all built-in strategies** ([#1091](https://github.com/adap/" +"flower/pull/1091))" msgstr "" #: ../../source/ref-changelog.md:838 msgid "" -"Built-in strategies can now perform both federated evaluation (i.e., " -"client-side) and centralized evaluation (i.e., server-side) in the same " -"round. Federated evaluation can be disabled by setting `fraction_eval` to" -" `0.0`." +"Built-in strategies can now perform both federated evaluation (i.e., client-" +"side) and centralized evaluation (i.e., server-side) in the same round. " +"Federated evaluation can be disabled by setting `fraction_eval` to `0.0`." msgstr "" #: ../../source/ref-changelog.md:840 msgid "" -"**Two new Jupyter Notebook tutorials** " -"([#1141](https://github.com/adap/flower/pull/1141))" +"**Two new Jupyter Notebook tutorials** ([#1141](https://github.com/adap/" +"flower/pull/1141))" msgstr "" #: ../../source/ref-changelog.md:842 msgid "" -"Two Jupyter Notebook tutorials (compatible with Google Colab) explain " -"basic and intermediate Flower features:" +"Two Jupyter Notebook tutorials (compatible with Google Colab) explain basic " +"and intermediate Flower features:" msgstr "" #: ../../source/ref-changelog.md:844 msgid "" -"*An Introduction to Federated Learning*: [Open in " -"Colab](https://colab.research.google.com/github/adap/flower/blob/main/tutorials/Flower-1" -"-Intro-to-FL-PyTorch.ipynb)" +"*An Introduction to Federated Learning*: [Open in Colab](https://colab." +"research.google.com/github/adap/flower/blob/main/tutorials/Flower-1-Intro-to-" +"FL-PyTorch.ipynb)" msgstr "" #: ../../source/ref-changelog.md:846 msgid "" -"*Using Strategies in Federated Learning*: [Open in " -"Colab](https://colab.research.google.com/github/adap/flower/blob/main/tutorials/Flower-2" -"-Strategies-in-FL-PyTorch.ipynb)" +"*Using Strategies in Federated Learning*: [Open in Colab](https://colab." +"research.google.com/github/adap/flower/blob/main/tutorials/Flower-2-" +"Strategies-in-FL-PyTorch.ipynb)" msgstr "" #: ../../source/ref-changelog.md:848 msgid "" -"**New FedAvgM strategy (Federated Averaging with Server Momentum)** " -"([#1076](https://github.com/adap/flower/pull/1076))" +"**New FedAvgM strategy (Federated Averaging with Server Momentum)** ([#1076]" +"(https://github.com/adap/flower/pull/1076))" msgstr "" #: ../../source/ref-changelog.md:850 @@ -18100,8 +18475,8 @@ msgstr "" #: ../../source/ref-changelog.md:852 msgid "" -"**New advanced PyTorch code example** " -"([#1007](https://github.com/adap/flower/pull/1007))" +"**New advanced PyTorch code example** ([#1007](https://github.com/adap/" +"flower/pull/1007))" msgstr "" #: ../../source/ref-changelog.md:854 @@ -18112,8 +18487,7 @@ msgstr "" #: ../../source/ref-changelog.md:856 msgid "" -"**New JAX code example** " -"([#906](https://github.com/adap/flower/pull/906), " +"**New JAX code example** ([#906](https://github.com/adap/flower/pull/906), " "[#1143](https://github.com/adap/flower/pull/1143))" msgstr "" @@ -18137,41 +18511,40 @@ msgstr "" #: ../../source/ref-changelog.md:864 msgid "" -"New documentation for [implementing " -"strategies](https://flower.ai/docs/framework/how-to-implement-" -"strategies.html) ([#1097](https://github.com/adap/flower/pull/1097), " -"[#1175](https://github.com/adap/flower/pull/1175))" +"New documentation for [implementing strategies](https://flower.ai/docs/" +"framework/how-to-implement-strategies.html) ([#1097](https://github.com/adap/" +"flower/pull/1097), [#1175](https://github.com/adap/flower/pull/1175))" msgstr "" #: ../../source/ref-changelog.md:865 msgid "" -"New mobile-friendly documentation theme " -"([#1174](https://github.com/adap/flower/pull/1174))" +"New mobile-friendly documentation theme ([#1174](https://github.com/adap/" +"flower/pull/1174))" msgstr "" #: ../../source/ref-changelog.md:866 msgid "" "Limit version range for (optional) `ray` dependency to include only " -"compatible releases (`>=1.9.2,<1.12.0`) " -"([#1205](https://github.com/adap/flower/pull/1205))" +"compatible releases (`>=1.9.2,<1.12.0`) ([#1205](https://github.com/adap/" +"flower/pull/1205))" msgstr "" #: ../../source/ref-changelog.md:870 msgid "" -"**Remove deprecated support for Python 3.6** " -"([#871](https://github.com/adap/flower/pull/871))" +"**Remove deprecated support for Python 3.6** ([#871](https://github.com/adap/" +"flower/pull/871))" msgstr "" #: ../../source/ref-changelog.md:871 msgid "" -"**Remove deprecated KerasClient** " -"([#857](https://github.com/adap/flower/pull/857))" +"**Remove deprecated KerasClient** ([#857](https://github.com/adap/flower/" +"pull/857))" msgstr "" #: ../../source/ref-changelog.md:872 msgid "" -"**Remove deprecated no-op extra installs** " -"([#973](https://github.com/adap/flower/pull/973))" +"**Remove deprecated no-op extra installs** ([#973](https://github.com/adap/" +"flower/pull/973))" msgstr "" #: ../../source/ref-changelog.md:873 @@ -18182,20 +18555,20 @@ msgstr "" #: ../../source/ref-changelog.md:874 msgid "" -"**Remove deprecated QffedAvg strategy (replaced by QFedAvg)** " -"([#1107](https://github.com/adap/flower/pull/1107))" +"**Remove deprecated QffedAvg strategy (replaced by QFedAvg)** ([#1107]" +"(https://github.com/adap/flower/pull/1107))" msgstr "" #: ../../source/ref-changelog.md:875 msgid "" -"**Remove deprecated DefaultStrategy strategy** " -"([#1142](https://github.com/adap/flower/pull/1142))" +"**Remove deprecated DefaultStrategy strategy** ([#1142](https://github.com/" +"adap/flower/pull/1142))" msgstr "" #: ../../source/ref-changelog.md:876 msgid "" -"**Remove deprecated support for eval_fn accuracy return value** " -"([#1142](https://github.com/adap/flower/pull/1142))" +"**Remove deprecated support for eval_fn accuracy return value** ([#1142]" +"(https://github.com/adap/flower/pull/1142))" msgstr "" #: ../../source/ref-changelog.md:877 @@ -18211,156 +18584,152 @@ msgstr "" #: ../../source/ref-changelog.md:883 msgid "" "**Improved Virtual Client Engine compatibility with Jupyter Notebook / " -"Google Colab** ([#866](https://github.com/adap/flower/pull/866), " -"[#872](https://github.com/adap/flower/pull/872), " -"[#833](https://github.com/adap/flower/pull/833), " -"[#1036](https://github.com/adap/flower/pull/1036))" +"Google Colab** ([#866](https://github.com/adap/flower/pull/866), [#872]" +"(https://github.com/adap/flower/pull/872), [#833](https://github.com/adap/" +"flower/pull/833), [#1036](https://github.com/adap/flower/pull/1036))" msgstr "" #: ../../source/ref-changelog.md:885 msgid "" -"Simulations (using the Virtual Client Engine through `start_simulation`) " -"now work more smoothly on Jupyter Notebooks (incl. Google Colab) after " +"Simulations (using the Virtual Client Engine through `start_simulation`) now " +"work more smoothly on Jupyter Notebooks (incl. Google Colab) after " "installing Flower with the `simulation` extra (`pip install " "flwr[simulation]`)." msgstr "" #: ../../source/ref-changelog.md:887 msgid "" -"**New Jupyter Notebook code example** " -"([#833](https://github.com/adap/flower/pull/833))" +"**New Jupyter Notebook code example** ([#833](https://github.com/adap/flower/" +"pull/833))" msgstr "" #: ../../source/ref-changelog.md:889 msgid "" -"A new code example (`quickstart_simulation`) demonstrates Flower " -"simulations using the Virtual Client Engine through Jupyter Notebook " -"(incl. Google Colab)." +"A new code example (`quickstart_simulation`) demonstrates Flower simulations " +"using the Virtual Client Engine through Jupyter Notebook (incl. Google " +"Colab)." msgstr "" #: ../../source/ref-changelog.md:891 msgid "" -"**Client properties (feature preview)** " -"([#795](https://github.com/adap/flower/pull/795))" +"**Client properties (feature preview)** ([#795](https://github.com/adap/" +"flower/pull/795))" msgstr "" #: ../../source/ref-changelog.md:893 msgid "" -"Clients can implement a new method `get_properties` to enable server-side" -" strategies to query client properties." +"Clients can implement a new method `get_properties` to enable server-side " +"strategies to query client properties." msgstr "" #: ../../source/ref-changelog.md:895 msgid "" -"**Experimental Android support with TFLite** " -"([#865](https://github.com/adap/flower/pull/865))" +"**Experimental Android support with TFLite** ([#865](https://github.com/adap/" +"flower/pull/865))" msgstr "" #: ../../source/ref-changelog.md:897 msgid "" "Android support has finally arrived in `main`! Flower is both client-" "agnostic and framework-agnostic by design. One can integrate arbitrary " -"client platforms and with this release, using Flower on Android has " -"become a lot easier." +"client platforms and with this release, using Flower on Android has become a " +"lot easier." msgstr "" #: ../../source/ref-changelog.md:899 msgid "" -"The example uses TFLite on the client side, along with a new " -"`FedAvgAndroid` strategy. The Android client and `FedAvgAndroid` are " -"still experimental, but they are a first step towards a fully-fledged " -"Android SDK and a unified `FedAvg` implementation that integrated the new" -" functionality from `FedAvgAndroid`." +"The example uses TFLite on the client side, along with a new `FedAvgAndroid` " +"strategy. The Android client and `FedAvgAndroid` are still experimental, but " +"they are a first step towards a fully-fledged Android SDK and a unified " +"`FedAvg` implementation that integrated the new functionality from " +"`FedAvgAndroid`." msgstr "" #: ../../source/ref-changelog.md:901 msgid "" -"**Make gRPC keepalive time user-configurable and decrease default " -"keepalive time** ([#1069](https://github.com/adap/flower/pull/1069))" +"**Make gRPC keepalive time user-configurable and decrease default keepalive " +"time** ([#1069](https://github.com/adap/flower/pull/1069))" msgstr "" #: ../../source/ref-changelog.md:903 msgid "" "The default gRPC keepalive time has been reduced to increase the " -"compatibility of Flower with more cloud environments (for example, " -"Microsoft Azure). Users can configure the keepalive time to customize the" -" gRPC stack based on specific requirements." +"compatibility of Flower with more cloud environments (for example, Microsoft " +"Azure). Users can configure the keepalive time to customize the gRPC stack " +"based on specific requirements." msgstr "" #: ../../source/ref-changelog.md:905 msgid "" -"**New differential privacy example using Opacus and PyTorch** " -"([#805](https://github.com/adap/flower/pull/805))" +"**New differential privacy example using Opacus and PyTorch** ([#805]" +"(https://github.com/adap/flower/pull/805))" msgstr "" #: ../../source/ref-changelog.md:907 msgid "" -"A new code example (`opacus`) demonstrates differentially-private " -"federated learning with Opacus, PyTorch, and Flower." +"A new code example (`opacus`) demonstrates differentially-private federated " +"learning with Opacus, PyTorch, and Flower." msgstr "" #: ../../source/ref-changelog.md:909 msgid "" -"**New Hugging Face Transformers code example** " -"([#863](https://github.com/adap/flower/pull/863))" +"**New Hugging Face Transformers code example** ([#863](https://github.com/" +"adap/flower/pull/863))" msgstr "" #: ../../source/ref-changelog.md:911 msgid "" -"A new code example (`quickstart_huggingface`) demonstrates usage of " -"Hugging Face Transformers with Flower." +"A new code example (`quickstart_huggingface`) demonstrates usage of Hugging " +"Face Transformers with Flower." msgstr "" #: ../../source/ref-changelog.md:913 msgid "" -"**New MLCube code example** " -"([#779](https://github.com/adap/flower/pull/779), " -"[#1034](https://github.com/adap/flower/pull/1034), " -"[#1065](https://github.com/adap/flower/pull/1065), " -"[#1090](https://github.com/adap/flower/pull/1090))" +"**New MLCube code example** ([#779](https://github.com/adap/flower/" +"pull/779), [#1034](https://github.com/adap/flower/pull/1034), [#1065]" +"(https://github.com/adap/flower/pull/1065), [#1090](https://github.com/adap/" +"flower/pull/1090))" msgstr "" #: ../../source/ref-changelog.md:915 msgid "" -"A new code example (`quickstart_mlcube`) demonstrates usage of MLCube " -"with Flower." +"A new code example (`quickstart_mlcube`) demonstrates usage of MLCube with " +"Flower." msgstr "" #: ../../source/ref-changelog.md:917 msgid "" -"**SSL-enabled server and client** " -"([#842](https://github.com/adap/flower/pull/842), " -"[#844](https://github.com/adap/flower/pull/844), " -"[#845](https://github.com/adap/flower/pull/845), " -"[#847](https://github.com/adap/flower/pull/847), " -"[#993](https://github.com/adap/flower/pull/993), " -"[#994](https://github.com/adap/flower/pull/994))" +"**SSL-enabled server and client** ([#842](https://github.com/adap/flower/" +"pull/842), [#844](https://github.com/adap/flower/pull/844), [#845](https://" +"github.com/adap/flower/pull/845), [#847](https://github.com/adap/flower/" +"pull/847), [#993](https://github.com/adap/flower/pull/993), [#994](https://" +"github.com/adap/flower/pull/994))" msgstr "" #: ../../source/ref-changelog.md:919 msgid "" -"SSL enables secure encrypted connections between clients and servers. " -"This release open-sources the Flower secure gRPC implementation to make " -"encrypted communication channels accessible to all Flower users." +"SSL enables secure encrypted connections between clients and servers. This " +"release open-sources the Flower secure gRPC implementation to make encrypted " +"communication channels accessible to all Flower users." msgstr "" #: ../../source/ref-changelog.md:921 msgid "" -"**Updated** `FedAdam` **and** `FedYogi` **strategies** " -"([#885](https://github.com/adap/flower/pull/885), " -"[#895](https://github.com/adap/flower/pull/895))" +"**Updated** `FedAdam` **and** `FedYogi` **strategies** ([#885](https://" +"github.com/adap/flower/pull/885), [#895](https://github.com/adap/flower/" +"pull/895))" msgstr "" #: ../../source/ref-changelog.md:923 msgid "" -"`FedAdam` and `FedAdam` match the latest version of the Adaptive " -"Federated Optimization paper." +"`FedAdam` and `FedAdam` match the latest version of the Adaptive Federated " +"Optimization paper." msgstr "" #: ../../source/ref-changelog.md:925 msgid "" -"**Initialize** `start_simulation` **with a list of client IDs** " -"([#860](https://github.com/adap/flower/pull/860))" +"**Initialize** `start_simulation` **with a list of client IDs** ([#860]" +"(https://github.com/adap/flower/pull/860))" msgstr "" #: ../../source/ref-changelog.md:927 @@ -18374,38 +18743,38 @@ msgstr "" #: ../../source/ref-changelog.md:931 msgid "" -"Update `num_examples` calculation in PyTorch code examples in " -"([#909](https://github.com/adap/flower/pull/909))" +"Update `num_examples` calculation in PyTorch code examples in ([#909]" +"(https://github.com/adap/flower/pull/909))" msgstr "" #: ../../source/ref-changelog.md:932 msgid "" -"Expose Flower version through `flwr.__version__` " -"([#952](https://github.com/adap/flower/pull/952))" +"Expose Flower version through `flwr.__version__` ([#952](https://github.com/" +"adap/flower/pull/952))" msgstr "" #: ../../source/ref-changelog.md:933 msgid "" -"`start_server` in `app.py` now returns a `History` object containing " -"metrics from training ([#974](https://github.com/adap/flower/pull/974))" +"`start_server` in `app.py` now returns a `History` object containing metrics " +"from training ([#974](https://github.com/adap/flower/pull/974))" msgstr "" #: ../../source/ref-changelog.md:934 msgid "" -"Make `max_workers` (used by `ThreadPoolExecutor`) configurable " -"([#978](https://github.com/adap/flower/pull/978))" +"Make `max_workers` (used by `ThreadPoolExecutor`) configurable ([#978]" +"(https://github.com/adap/flower/pull/978))" msgstr "" #: ../../source/ref-changelog.md:935 msgid "" -"Increase sleep time after server start to three seconds in all code " -"examples ([#1086](https://github.com/adap/flower/pull/1086))" +"Increase sleep time after server start to three seconds in all code examples " +"([#1086](https://github.com/adap/flower/pull/1086))" msgstr "" #: ../../source/ref-changelog.md:936 msgid "" -"Added a new FAQ section to the documentation " -"([#948](https://github.com/adap/flower/pull/948))" +"Added a new FAQ section to the documentation ([#948](https://github.com/adap/" +"flower/pull/948))" msgstr "" #: ../../source/ref-changelog.md:937 @@ -18425,8 +18794,8 @@ msgid "" "The packages `flwr_example` and `flwr_experimental` have been deprecated " "since Flower 0.12.0 and they are not longer included in Flower release " "builds. The associated extras (`baseline`, `examples-pytorch`, `examples-" -"tensorflow`, `http-logger`, `ops`) are now no-op and will be removed in " -"an upcoming release." +"tensorflow`, `http-logger`, `ops`) are now no-op and will be removed in an " +"upcoming release." msgstr "" #: ../../source/ref-changelog.md:945 @@ -18435,34 +18804,32 @@ msgstr "" #: ../../source/ref-changelog.md:949 msgid "" -"**Experimental virtual client engine** " -"([#781](https://github.com/adap/flower/pull/781) " -"[#790](https://github.com/adap/flower/pull/790) " -"[#791](https://github.com/adap/flower/pull/791))" +"**Experimental virtual client engine** ([#781](https://github.com/adap/" +"flower/pull/781) [#790](https://github.com/adap/flower/pull/790) [#791]" +"(https://github.com/adap/flower/pull/791))" msgstr "" #: ../../source/ref-changelog.md:951 msgid "" -"One of Flower's goals is to enable research at scale. This release " -"enables a first (experimental) peek at a major new feature, codenamed the" -" virtual client engine. Virtual clients enable simulations that scale to " -"a (very) large number of clients on a single machine or compute cluster. " -"The easiest way to test the new functionality is to look at the two new " -"code examples called `quickstart_simulation` and `simulation_pytorch`." +"One of Flower's goals is to enable research at scale. This release enables a " +"first (experimental) peek at a major new feature, codenamed the virtual " +"client engine. Virtual clients enable simulations that scale to a (very) " +"large number of clients on a single machine or compute cluster. The easiest " +"way to test the new functionality is to look at the two new code examples " +"called `quickstart_simulation` and `simulation_pytorch`." msgstr "" #: ../../source/ref-changelog.md:953 msgid "" -"The feature is still experimental, so there's no stability guarantee for " -"the API. It's also not quite ready for prime time and comes with a few " -"known caveats. However, those who are curious are encouraged to try it " -"out and share their thoughts." +"The feature is still experimental, so there's no stability guarantee for the " +"API. It's also not quite ready for prime time and comes with a few known " +"caveats. However, those who are curious are encouraged to try it out and " +"share their thoughts." msgstr "" #: ../../source/ref-changelog.md:955 msgid "" -"**New built-in strategies** " -"([#828](https://github.com/adap/flower/pull/828) " +"**New built-in strategies** ([#828](https://github.com/adap/flower/pull/828) " "[#822](https://github.com/adap/flower/pull/822))" msgstr "" @@ -18480,101 +18847,99 @@ msgstr "" #: ../../source/ref-changelog.md:960 msgid "" -"**New PyTorch Lightning code example** " -"([#617](https://github.com/adap/flower/pull/617))" +"**New PyTorch Lightning code example** ([#617](https://github.com/adap/" +"flower/pull/617))" msgstr "" #: ../../source/ref-changelog.md:962 msgid "" -"**New Variational Auto-Encoder code example** " -"([#752](https://github.com/adap/flower/pull/752))" +"**New Variational Auto-Encoder code example** ([#752](https://github.com/" +"adap/flower/pull/752))" msgstr "" #: ../../source/ref-changelog.md:964 msgid "" -"**New scikit-learn code example** " -"([#748](https://github.com/adap/flower/pull/748))" +"**New scikit-learn code example** ([#748](https://github.com/adap/flower/" +"pull/748))" msgstr "" #: ../../source/ref-changelog.md:966 msgid "" -"**New experimental TensorBoard strategy** " -"([#789](https://github.com/adap/flower/pull/789))" +"**New experimental TensorBoard strategy** ([#789](https://github.com/adap/" +"flower/pull/789))" msgstr "" #: ../../source/ref-changelog.md:970 msgid "" -"Improved advanced TensorFlow code example " -"([#769](https://github.com/adap/flower/pull/769))" +"Improved advanced TensorFlow code example ([#769](https://github.com/adap/" +"flower/pull/769))" msgstr "" #: ../../source/ref-changelog.md:971 msgid "" -"Warning when `min_available_clients` is misconfigured " -"([#830](https://github.com/adap/flower/pull/830))" +"Warning when `min_available_clients` is misconfigured ([#830](https://github." +"com/adap/flower/pull/830))" msgstr "" #: ../../source/ref-changelog.md:972 msgid "" -"Improved gRPC server docs " -"([#841](https://github.com/adap/flower/pull/841))" +"Improved gRPC server docs ([#841](https://github.com/adap/flower/pull/841))" msgstr "" #: ../../source/ref-changelog.md:973 msgid "" -"Improved error message in `NumPyClient` " -"([#851](https://github.com/adap/flower/pull/851))" +"Improved error message in `NumPyClient` ([#851](https://github.com/adap/" +"flower/pull/851))" msgstr "" #: ../../source/ref-changelog.md:974 msgid "" -"Improved PyTorch quickstart code example " -"([#852](https://github.com/adap/flower/pull/852))" +"Improved PyTorch quickstart code example ([#852](https://github.com/adap/" +"flower/pull/852))" msgstr "" #: ../../source/ref-changelog.md:978 msgid "" -"**Disabled final distributed evaluation** " -"([#800](https://github.com/adap/flower/pull/800))" +"**Disabled final distributed evaluation** ([#800](https://github.com/adap/" +"flower/pull/800))" msgstr "" #: ../../source/ref-changelog.md:980 msgid "" -"Prior behaviour was to perform a final round of distributed evaluation on" -" all connected clients, which is often not required (e.g., when using " -"server-side evaluation). The prior behaviour can be enabled by passing " +"Prior behaviour was to perform a final round of distributed evaluation on " +"all connected clients, which is often not required (e.g., when using server-" +"side evaluation). The prior behaviour can be enabled by passing " "`force_final_distributed_eval=True` to `start_server`." msgstr "" #: ../../source/ref-changelog.md:982 msgid "" -"**Renamed q-FedAvg strategy** " -"([#802](https://github.com/adap/flower/pull/802))" +"**Renamed q-FedAvg strategy** ([#802](https://github.com/adap/flower/" +"pull/802))" msgstr "" #: ../../source/ref-changelog.md:984 msgid "" -"The strategy named `QffedAvg` was renamed to `QFedAvg` to better reflect " -"the notation given in the original paper (q-FFL is the optimization " -"objective, q-FedAvg is the proposed solver). Note the original (now " -"deprecated) `QffedAvg` class is still available for compatibility reasons" -" (it will be removed in a future release)." +"The strategy named `QffedAvg` was renamed to `QFedAvg` to better reflect the " +"notation given in the original paper (q-FFL is the optimization objective, q-" +"FedAvg is the proposed solver). Note the original (now deprecated) " +"`QffedAvg` class is still available for compatibility reasons (it will be " +"removed in a future release)." msgstr "" #: ../../source/ref-changelog.md:986 msgid "" "**Deprecated and renamed code example** `simulation_pytorch` **to** " -"`simulation_pytorch_legacy` " -"([#791](https://github.com/adap/flower/pull/791))" +"`simulation_pytorch_legacy` ([#791](https://github.com/adap/flower/pull/791))" msgstr "" #: ../../source/ref-changelog.md:988 msgid "" -"This example has been replaced by a new example. The new example is based" -" on the experimental virtual client engine, which will become the new " -"default way of doing most types of large-scale simulations in Flower. The" -" existing example was kept for reference purposes, but it might be " -"removed in the future." +"This example has been replaced by a new example. The new example is based on " +"the experimental virtual client engine, which will become the new default " +"way of doing most types of large-scale simulations in Flower. The existing " +"example was kept for reference purposes, but it might be removed in the " +"future." msgstr "" #: ../../source/ref-changelog.md:990 @@ -18583,8 +18948,7 @@ msgstr "" #: ../../source/ref-changelog.md:994 msgid "" -"**New built-in strategies** " -"([#549](https://github.com/adap/flower/pull/549))" +"**New built-in strategies** ([#549](https://github.com/adap/flower/pull/549))" msgstr "" #: ../../source/ref-changelog.md:996 @@ -18593,8 +18957,8 @@ msgstr "" #: ../../source/ref-changelog.md:999 msgid "" -"**Custom metrics for server and strategies** " -"([#717](https://github.com/adap/flower/pull/717))" +"**Custom metrics for server and strategies** ([#717](https://github.com/adap/" +"flower/pull/717))" msgstr "" #: ../../source/ref-changelog.md:1001 @@ -18608,20 +18972,19 @@ msgstr "" #: ../../source/ref-changelog.md:1003 msgid "" -"Custom metric dictionaries are now used in two user-facing APIs: they are" -" returned from Strategy methods `aggregate_fit`/`aggregate_evaluate` and " -"they enable evaluation functions passed to built-in strategies (via " -"`eval_fn`) to return more than two evaluation metrics. Strategies can " -"even return *aggregated* metrics dictionaries for the server to keep " -"track of." +"Custom metric dictionaries are now used in two user-facing APIs: they are " +"returned from Strategy methods `aggregate_fit`/`aggregate_evaluate` and they " +"enable evaluation functions passed to built-in strategies (via `eval_fn`) to " +"return more than two evaluation metrics. Strategies can even return " +"*aggregated* metrics dictionaries for the server to keep track of." msgstr "" #: ../../source/ref-changelog.md:1005 msgid "" "Strategy implementations should migrate their `aggregate_fit` and " "`aggregate_evaluate` methods to the new return type (e.g., by simply " -"returning an empty `{}`), server-side evaluation functions should migrate" -" from `return loss, accuracy` to `return loss, {\"accuracy\": accuracy}`." +"returning an empty `{}`), server-side evaluation functions should migrate " +"from `return loss, accuracy` to `return loss, {\"accuracy\": accuracy}`." msgstr "" #: ../../source/ref-changelog.md:1007 @@ -18632,25 +18995,24 @@ msgstr "" #: ../../source/ref-changelog.md:1009 msgid "" -"**Migration warnings for deprecated functionality** " -"([#690](https://github.com/adap/flower/pull/690))" +"**Migration warnings for deprecated functionality** ([#690](https://github." +"com/adap/flower/pull/690))" msgstr "" #: ../../source/ref-changelog.md:1011 msgid "" "Earlier versions of Flower were often migrated to new APIs, while " -"maintaining compatibility with legacy APIs. This release introduces " -"detailed warning messages if usage of deprecated APIs is detected. The " -"new warning messages often provide details on how to migrate to more " -"recent APIs, thus easing the transition from one release to another." +"maintaining compatibility with legacy APIs. This release introduces detailed " +"warning messages if usage of deprecated APIs is detected. The new warning " +"messages often provide details on how to migrate to more recent APIs, thus " +"easing the transition from one release to another." msgstr "" #: ../../source/ref-changelog.md:1013 msgid "" -"Improved docs and docstrings " -"([#691](https://github.com/adap/flower/pull/691) " -"[#692](https://github.com/adap/flower/pull/692) " -"[#713](https://github.com/adap/flower/pull/713))" +"Improved docs and docstrings ([#691](https://github.com/adap/flower/" +"pull/691) [#692](https://github.com/adap/flower/pull/692) [#713](https://" +"github.com/adap/flower/pull/713))" msgstr "" #: ../../source/ref-changelog.md:1015 @@ -18660,43 +19022,39 @@ msgstr "" #: ../../source/ref-changelog.md:1017 msgid "" "FedBN implementation in example PyTorch: From Centralized To Federated " -"([#696](https://github.com/adap/flower/pull/696) " -"[#702](https://github.com/adap/flower/pull/702) " -"[#705](https://github.com/adap/flower/pull/705))" +"([#696](https://github.com/adap/flower/pull/696) [#702](https://github.com/" +"adap/flower/pull/702) [#705](https://github.com/adap/flower/pull/705))" msgstr "" #: ../../source/ref-changelog.md:1021 msgid "" -"**Serialization-agnostic server** " -"([#721](https://github.com/adap/flower/pull/721))" +"**Serialization-agnostic server** ([#721](https://github.com/adap/flower/" +"pull/721))" msgstr "" #: ../../source/ref-changelog.md:1023 msgid "" -"The Flower server is now fully serialization-agnostic. Prior usage of " -"class `Weights` (which represents parameters as deserialized NumPy " -"ndarrays) was replaced by class `Parameters` (e.g., in `Strategy`). " -"`Parameters` objects are fully serialization-agnostic and represents " -"parameters as byte arrays, the `tensor_type` attributes indicates how " -"these byte arrays should be interpreted (e.g., for " -"serialization/deserialization)." +"The Flower server is now fully serialization-agnostic. Prior usage of class " +"`Weights` (which represents parameters as deserialized NumPy ndarrays) was " +"replaced by class `Parameters` (e.g., in `Strategy`). `Parameters` objects " +"are fully serialization-agnostic and represents parameters as byte arrays, " +"the `tensor_type` attributes indicates how these byte arrays should be " +"interpreted (e.g., for serialization/deserialization)." msgstr "" #: ../../source/ref-changelog.md:1025 msgid "" -"Built-in strategies implement this approach by handling serialization and" -" deserialization to/from `Weights` internally. Custom/3rd-party Strategy " +"Built-in strategies implement this approach by handling serialization and " +"deserialization to/from `Weights` internally. Custom/3rd-party Strategy " "implementations should update to the slightly changed Strategy method " -"definitions. Strategy authors can consult PR " -"[#721](https://github.com/adap/flower/pull/721) to see how strategies can" -" easily migrate to the new format." +"definitions. Strategy authors can consult PR [#721](https://github.com/adap/" +"flower/pull/721) to see how strategies can easily migrate to the new format." msgstr "" #: ../../source/ref-changelog.md:1027 msgid "" -"Deprecated `flwr.server.Server.evaluate`, use " -"`flwr.server.Server.evaluate_round` instead " -"([#717](https://github.com/adap/flower/pull/717))" +"Deprecated `flwr.server.Server.evaluate`, use `flwr.server.Server." +"evaluate_round` instead ([#717](https://github.com/adap/flower/pull/717))" msgstr "" #: ../../source/ref-changelog.md:1029 @@ -18705,8 +19063,8 @@ msgstr "" #: ../../source/ref-changelog.md:1033 msgid "" -"**Server-side parameter initialization** " -"([#658](https://github.com/adap/flower/pull/658))" +"**Server-side parameter initialization** ([#658](https://github.com/adap/" +"flower/pull/658))" msgstr "" #: ../../source/ref-changelog.md:1035 @@ -18719,9 +19077,9 @@ msgstr "" #: ../../source/ref-changelog.md:1037 msgid "" "Built-in strategies support a new constructor argument called " -"`initial_parameters` to set the initial parameters. Built-in strategies " -"will provide these initial parameters to the server on startup and then " -"delete them to free the memory afterwards." +"`initial_parameters` to set the initial parameters. Built-in strategies will " +"provide these initial parameters to the server on startup and then delete " +"them to free the memory afterwards." msgstr "" #: ../../source/ref-changelog.md:1056 @@ -18734,8 +19092,8 @@ msgstr "" #: ../../source/ref-changelog.md:1060 msgid "" -"Deprecate `flwr.server.strategy.DefaultStrategy` (migrate to " -"`flwr.server.strategy.FedAvg`, which is equivalent)" +"Deprecate `flwr.server.strategy.DefaultStrategy` (migrate to `flwr.server." +"strategy.FedAvg`, which is equivalent)" msgstr "" #: ../../source/ref-changelog.md:1062 @@ -18745,35 +19103,33 @@ msgstr "" #: ../../source/ref-changelog.md:1066 msgid "" "**Generalized** `Client.fit` **and** `Client.evaluate` **return values** " -"([#610](https://github.com/adap/flower/pull/610) " -"[#572](https://github.com/adap/flower/pull/572) " -"[#633](https://github.com/adap/flower/pull/633))" +"([#610](https://github.com/adap/flower/pull/610) [#572](https://github.com/" +"adap/flower/pull/572) [#633](https://github.com/adap/flower/pull/633))" msgstr "" #: ../../source/ref-changelog.md:1068 msgid "" -"Clients can now return an additional dictionary mapping `str` keys to " -"values of the following types: `bool`, `bytes`, `float`, `int`, `str`. " -"This means one can return almost arbitrary values from `fit`/`evaluate` " -"and make use of them on the server side!" +"Clients can now return an additional dictionary mapping `str` keys to values " +"of the following types: `bool`, `bytes`, `float`, `int`, `str`. This means " +"one can return almost arbitrary values from `fit`/`evaluate` and make use of " +"them on the server side!" msgstr "" #: ../../source/ref-changelog.md:1070 msgid "" -"This improvement also allowed for more consistent return types between " -"`fit` and `evaluate`: `evaluate` should now return a tuple `(float, int, " -"dict)` representing the loss, number of examples, and a dictionary " -"holding arbitrary problem-specific values like accuracy." +"This improvement also allowed for more consistent return types between `fit` " +"and `evaluate`: `evaluate` should now return a tuple `(float, int, dict)` " +"representing the loss, number of examples, and a dictionary holding " +"arbitrary problem-specific values like accuracy." msgstr "" #: ../../source/ref-changelog.md:1072 msgid "" -"In case you wondered: this feature is compatible with existing projects, " -"the additional dictionary return value is optional. New code should " -"however migrate to the new return types to be compatible with upcoming " -"Flower releases (`fit`: `List[np.ndarray], int, Dict[str, Scalar]`, " -"`evaluate`: `float, int, Dict[str, Scalar]`). See the example below for " -"details." +"In case you wondered: this feature is compatible with existing projects, the " +"additional dictionary return value is optional. New code should however " +"migrate to the new return types to be compatible with upcoming Flower " +"releases (`fit`: `List[np.ndarray], int, Dict[str, Scalar]`, `evaluate`: " +"`float, int, Dict[str, Scalar]`). See the example below for details." msgstr "" #: ../../source/ref-changelog.md:1074 @@ -18784,23 +19140,23 @@ msgstr "" #: ../../source/ref-changelog.md:1089 msgid "" -"**Generalized** `config` **argument in** `Client.fit` **and** " -"`Client.evaluate` ([#595](https://github.com/adap/flower/pull/595))" +"**Generalized** `config` **argument in** `Client.fit` **and** `Client." +"evaluate` ([#595](https://github.com/adap/flower/pull/595))" msgstr "" #: ../../source/ref-changelog.md:1091 msgid "" -"The `config` argument used to be of type `Dict[str, str]`, which means " -"that dictionary values were expected to be strings. The new release " -"generalizes this to enable values of the following types: `bool`, " -"`bytes`, `float`, `int`, `str`." +"The `config` argument used to be of type `Dict[str, str]`, which means that " +"dictionary values were expected to be strings. The new release generalizes " +"this to enable values of the following types: `bool`, `bytes`, `float`, " +"`int`, `str`." msgstr "" #: ../../source/ref-changelog.md:1093 msgid "" "This means one can now pass almost arbitrary values to `fit`/`evaluate` " -"using the `config` dictionary. Yay, no more `str(epochs)` on the server-" -"side and `int(config[\"epochs\"])` on the client side!" +"using the `config` dictionary. Yay, no more `str(epochs)` on the server-side " +"and `int(config[\"epochs\"])` on the client side!" msgstr "" #: ../../source/ref-changelog.md:1095 @@ -18815,8 +19171,8 @@ msgstr "" #: ../../source/ref-changelog.md:1116 msgid "" -"New example: PyTorch From Centralized To Federated " -"([#549](https://github.com/adap/flower/pull/549))" +"New example: PyTorch From Centralized To Federated ([#549](https://github." +"com/adap/flower/pull/549))" msgstr "" #: ../../source/ref-changelog.md:1117 @@ -18824,7 +19180,8 @@ msgid "Improved documentation" msgstr "" #: ../../source/ref-changelog.md:1118 -msgid "New documentation theme ([#551](https://github.com/adap/flower/pull/551))" +msgid "" +"New documentation theme ([#551](https://github.com/adap/flower/pull/551))" msgstr "" #: ../../source/ref-changelog.md:1119 @@ -18833,14 +19190,14 @@ msgstr "" #: ../../source/ref-changelog.md:1120 msgid "" -"Updated examples documentation " -"([#549](https://github.com/adap/flower/pull/549))" +"Updated examples documentation ([#549](https://github.com/adap/flower/" +"pull/549))" msgstr "" #: ../../source/ref-changelog.md:1121 msgid "" -"Removed obsolete documentation " -"([#548](https://github.com/adap/flower/pull/548))" +"Removed obsolete documentation ([#548](https://github.com/adap/flower/" +"pull/548))" msgstr "" #: ../../source/ref-changelog.md:1123 @@ -18849,10 +19206,9 @@ msgstr "" #: ../../source/ref-changelog.md:1125 msgid "" -"`Server.fit` does not disconnect clients when finished, disconnecting the" -" clients is now handled in `flwr.server.start_server` " -"([#553](https://github.com/adap/flower/pull/553) " -"[#540](https://github.com/adap/flower/issues/540))." +"`Server.fit` does not disconnect clients when finished, disconnecting the " +"clients is now handled in `flwr.server.start_server` ([#553](https://github." +"com/adap/flower/pull/553) [#540](https://github.com/adap/flower/issues/540))." msgstr "" #: ../../source/ref-changelog.md:1127 @@ -18865,23 +19221,22 @@ msgstr "" #: ../../source/ref-changelog.md:1131 msgid "" -"Added an example for embedded devices " -"([#507](https://github.com/adap/flower/pull/507))" +"Added an example for embedded devices ([#507](https://github.com/adap/flower/" +"pull/507))" msgstr "" #: ../../source/ref-changelog.md:1132 msgid "" -"Added a new NumPyClient (in addition to the existing KerasClient) " -"([#504](https://github.com/adap/flower/pull/504) " -"[#508](https://github.com/adap/flower/pull/508))" +"Added a new NumPyClient (in addition to the existing KerasClient) ([#504]" +"(https://github.com/adap/flower/pull/504) [#508](https://github.com/adap/" +"flower/pull/508))" msgstr "" #: ../../source/ref-changelog.md:1133 msgid "" -"Deprecated `flwr_example` package and started to migrate examples into " -"the top-level `examples` directory " -"([#494](https://github.com/adap/flower/pull/494) " -"[#512](https://github.com/adap/flower/pull/512))" +"Deprecated `flwr_example` package and started to migrate examples into the " +"top-level `examples` directory ([#494](https://github.com/adap/flower/" +"pull/494) [#512](https://github.com/adap/flower/pull/512))" msgstr "" #: ../../source/ref-changelog.md:1135 @@ -18894,12 +19249,11 @@ msgstr "" #: ../../source/ref-changelog.md:1139 msgid "" -"Renamed strategy methods " -"([#486](https://github.com/adap/flower/pull/486)) to unify the naming of " -"Flower's public APIs. Other public methods/functions (e.g., every method " -"in `Client`, but also `Strategy.evaluate`) do not use the `on_` prefix, " -"which is why we're removing it from the four methods in Strategy. To " -"migrate rename the following `Strategy` methods accordingly:" +"Renamed strategy methods ([#486](https://github.com/adap/flower/pull/486)) " +"to unify the naming of Flower's public APIs. Other public methods/functions " +"(e.g., every method in `Client`, but also `Strategy.evaluate`) do not use " +"the `on_` prefix, which is why we're removing it from the four methods in " +"Strategy. To migrate rename the following `Strategy` methods accordingly:" msgstr "" #: ../../source/ref-changelog.md:1140 @@ -18920,33 +19274,32 @@ msgstr "" #: ../../source/ref-changelog.md:1147 msgid "" -"Deprecated `DefaultStrategy` " -"([#479](https://github.com/adap/flower/pull/479)). To migrate use " -"`FedAvg` instead." +"Deprecated `DefaultStrategy` ([#479](https://github.com/adap/flower/" +"pull/479)). To migrate use `FedAvg` instead." msgstr "" #: ../../source/ref-changelog.md:1148 msgid "" -"Simplified examples and baselines " -"([#484](https://github.com/adap/flower/pull/484))." +"Simplified examples and baselines ([#484](https://github.com/adap/flower/" +"pull/484))." msgstr "" #: ../../source/ref-changelog.md:1149 msgid "" -"Removed presently unused `on_conclude_round` from strategy interface " -"([#483](https://github.com/adap/flower/pull/483))." +"Removed presently unused `on_conclude_round` from strategy interface ([#483]" +"(https://github.com/adap/flower/pull/483))." msgstr "" #: ../../source/ref-changelog.md:1150 msgid "" -"Set minimal Python version to 3.6.1 instead of 3.6.9 " -"([#471](https://github.com/adap/flower/pull/471))." +"Set minimal Python version to 3.6.1 instead of 3.6.9 ([#471](https://github." +"com/adap/flower/pull/471))." msgstr "" #: ../../source/ref-changelog.md:1151 msgid "" -"Improved `Strategy` docstrings " -"([#470](https://github.com/adap/flower/pull/470))." +"Improved `Strategy` docstrings ([#470](https://github.com/adap/flower/" +"pull/470))." msgstr "" #: ../../source/ref-example-projects.rst:2 @@ -18955,11 +19308,11 @@ msgstr "" #: ../../source/ref-example-projects.rst:4 msgid "" -"Flower comes with a number of usage examples. The examples demonstrate " -"how Flower can be used to federate different kinds of existing machine " -"learning pipelines, usually leveraging popular machine learning " -"frameworks such as `PyTorch `_ or `TensorFlow " -"`_." +"Flower comes with a number of usage examples. The examples demonstrate how " +"Flower can be used to federate different kinds of existing machine learning " +"pipelines, usually leveraging popular machine learning frameworks such as " +"`PyTorch `_ or `TensorFlow `_." msgstr "" #: ../../source/ref-example-projects.rst:10 @@ -18970,25 +19323,25 @@ msgstr "" #: ../../source/ref-example-projects.rst:14 msgid "" -"The TensorFlow/Keras quickstart example shows CIFAR-10 image " -"classification with MobileNetV2:" +"The TensorFlow/Keras quickstart example shows CIFAR-10 image classification " +"with MobileNetV2:" msgstr "" #: ../../source/ref-example-projects.rst:17 msgid "" -"`Quickstart TensorFlow (Code) " -"`_" +"`Quickstart TensorFlow (Code) `_" msgstr "" #: ../../source/ref-example-projects.rst:18 -msgid ":doc:`Quickstart TensorFlow (Tutorial) `" +msgid "" +":doc:`Quickstart TensorFlow (Tutorial) `" msgstr "" #: ../../source/ref-example-projects.rst:19 msgid "" -"`Quickstart TensorFlow (Blog Post) `_" +"`Quickstart TensorFlow (Blog Post) `_" msgstr "" #: ../../source/ref-example-projects.rst:23 @@ -18998,14 +19351,14 @@ msgstr "" #: ../../source/ref-example-projects.rst:25 msgid "" -"The PyTorch quickstart example shows CIFAR-10 image classification with a" -" simple Convolutional Neural Network:" +"The PyTorch quickstart example shows CIFAR-10 image classification with a " +"simple Convolutional Neural Network:" msgstr "" #: ../../source/ref-example-projects.rst:28 msgid "" -"`Quickstart PyTorch (Code) " -"`_" +"`Quickstart PyTorch (Code) `_" msgstr "" #: ../../source/ref-example-projects.rst:29 @@ -19024,9 +19377,8 @@ msgstr "" #: ../../source/ref-example-projects.rst:37 msgid "" -"`PyTorch: From Centralized To Federated (Code) " -"`_" +"`PyTorch: From Centralized To Federated (Code) `_" msgstr "" #: ../../source/ref-example-projects.rst:38 @@ -19047,14 +19399,15 @@ msgstr "" #: ../../source/ref-example-projects.rst:46 msgid "" -"`Federated Learning on Raspberry Pi and Nvidia Jetson (Code) " -"`_" +"`Federated Learning on Raspberry Pi and Nvidia Jetson (Code) `_" msgstr "" #: ../../source/ref-example-projects.rst:47 msgid "" -"`Federated Learning on Raspberry Pi and Nvidia Jetson (Blog Post) " -"`_" +"`Federated Learning on Raspberry Pi and Nvidia Jetson (Blog Post) `_" msgstr "" #: ../../source/ref-faq.rst:4 @@ -19069,22 +19422,20 @@ msgstr "" #: ../../source/ref-faq.rst:8 msgid "" -"Yes, it can! Flower even comes with a few under-the-hood optimizations to" -" make it work even better on Colab. Here's a quickstart example:" +"Yes, it can! Flower even comes with a few under-the-hood optimizations to " +"make it work even better on Colab. Here's a quickstart example:" msgstr "" #: ../../source/ref-faq.rst:10 msgid "" -"`Flower simulation PyTorch " -"`_" +"`Flower simulation PyTorch `_" msgstr "" #: ../../source/ref-faq.rst:11 msgid "" -"`Flower simulation TensorFlow/Keras " -"`_" +"`Flower simulation TensorFlow/Keras `_" msgstr "" #: ../../source/ref-faq.rst @@ -19094,26 +19445,28 @@ msgstr "" #: ../../source/ref-faq.rst:15 msgid "" "Find the `blog post about federated learning on embedded device here " -"`_" -" and the corresponding `GitHub code example " -"`_." +"`_ " +"and the corresponding `GitHub code example `_." msgstr "" #: ../../source/ref-faq.rst -msgid ":fa:`eye,mr-1` Does Flower support federated learning on Android devices?" +msgid "" +":fa:`eye,mr-1` Does Flower support federated learning on Android devices?" msgstr "" #: ../../source/ref-faq.rst:19 msgid "" -"Yes, it does. Please take a look at our `blog post " -"`_ or check out the code examples:" +"Yes, it does. Please take a look at our `blog post `_ or " +"check out the code examples:" msgstr "" #: ../../source/ref-faq.rst:21 msgid "" -"`Android Kotlin example `_" +"`Android Kotlin example `_" msgstr "" #: ../../source/ref-faq.rst:22 @@ -19132,33 +19485,33 @@ msgstr "" #: ../../source/ref-faq.rst:28 msgid "" -"`Flower meets Nevermined GitHub Repository `_." +"`Flower meets Nevermined GitHub Repository `_." msgstr "" #: ../../source/ref-faq.rst:29 msgid "" -"`Flower meets Nevermined YouTube video " -"`_." +"`Flower meets Nevermined YouTube video `_." msgstr "" #: ../../source/ref-faq.rst:30 msgid "" -"`Flower meets KOSMoS `_." +"`Flower meets KOSMoS `_." msgstr "" #: ../../source/ref-faq.rst:31 msgid "" "`Flower meets Talan blog post `_ ." +"learning-same-mask-different-faces-imen-ayari/?" +"trackingId=971oIlxLQ9%2BA9RB0IQ73XQ%3D%3D>`_ ." msgstr "" #: ../../source/ref-faq.rst:32 msgid "" -"`Flower meets Talan GitHub Repository " -"`_ ." +"`Flower meets Talan GitHub Repository `_ ." msgstr "" #: ../../source/ref-telemetry.md:1 @@ -19167,17 +19520,16 @@ msgstr "" #: ../../source/ref-telemetry.md:3 msgid "" -"The Flower open-source project collects **anonymous** usage metrics to " -"make well-informed decisions to improve Flower. Doing this enables the " -"Flower team to understand how Flower is used and what challenges users " -"might face." +"The Flower open-source project collects **anonymous** usage metrics to make " +"well-informed decisions to improve Flower. Doing this enables the Flower " +"team to understand how Flower is used and what challenges users might face." msgstr "" #: ../../source/ref-telemetry.md:5 msgid "" -"**Flower is a friendly framework for collaborative AI and data science.**" -" Staying true to this statement, Flower makes it easy to disable " -"telemetry for users that do not want to share anonymous usage metrics." +"**Flower is a friendly framework for collaborative AI and data science.** " +"Staying true to this statement, Flower makes it easy to disable telemetry " +"for users that do not want to share anonymous usage metrics." msgstr "" #: ../../source/ref-telemetry.md:7 @@ -19185,35 +19537,34 @@ msgid "Principles" msgstr "" #: ../../source/ref-telemetry.md:9 -msgid "We follow strong principles guarding anonymous usage metrics collection:" +msgid "" +"We follow strong principles guarding anonymous usage metrics collection:" msgstr "" #: ../../source/ref-telemetry.md:11 msgid "" -"**Optional:** You will always be able to disable telemetry; read on to " -"learn “[How to opt-out](#how-to-opt-out)”." +"**Optional:** You will always be able to disable telemetry; read on to learn " +"“[How to opt-out](#how-to-opt-out)”." msgstr "" #: ../../source/ref-telemetry.md:12 msgid "" -"**Anonymous:** The reported usage metrics are anonymous and do not " -"contain any personally identifiable information (PII). See “[Collected " -"metrics](#collected-metrics)” to understand what metrics are being " -"reported." +"**Anonymous:** The reported usage metrics are anonymous and do not contain " +"any personally identifiable information (PII). See “[Collected metrics]" +"(#collected-metrics)” to understand what metrics are being reported." msgstr "" #: ../../source/ref-telemetry.md:13 msgid "" "**Transparent:** You can easily inspect what anonymous metrics are being " -"reported; see the section “[How to inspect what is being reported](#how-" -"to-inspect-what-is-being-reported)”" +"reported; see the section “[How to inspect what is being reported](#how-to-" +"inspect-what-is-being-reported)”" msgstr "" #: ../../source/ref-telemetry.md:14 msgid "" -"**Open for feedback:** You can always reach out to us if you have " -"feedback; see the section “[How to contact us](#how-to-contact-us)” for " -"details." +"**Open for feedback:** You can always reach out to us if you have feedback; " +"see the section “[How to contact us](#how-to-contact-us)” for details." msgstr "" #: ../../source/ref-telemetry.md:16 @@ -19230,9 +19581,9 @@ msgstr "" #: ../../source/ref-telemetry.md:24 msgid "" -"Alternatively, you can export `FLWR_TELEMETRY_ENABLED=0` in, for example," -" `.bashrc` (or whatever configuration file applies to your environment) " -"to disable Flower telemetry permanently." +"Alternatively, you can export `FLWR_TELEMETRY_ENABLED=0` in, for example, `." +"bashrc` (or whatever configuration file applies to your environment) to " +"disable Flower telemetry permanently." msgstr "" #: ../../source/ref-telemetry.md:26 @@ -19245,10 +19596,10 @@ msgstr "" #: ../../source/ref-telemetry.md:30 msgid "" -"**Flower version.** Understand which versions of Flower are currently " -"being used. This helps us to decide whether we should invest effort into " -"releasing a patch version for an older version of Flower or instead use " -"the bandwidth to build new features." +"**Flower version.** Understand which versions of Flower are currently being " +"used. This helps us to decide whether we should invest effort into releasing " +"a patch version for an older version of Flower or instead use the bandwidth " +"to build new features." msgstr "" #: ../../source/ref-telemetry.md:32 @@ -19267,15 +19618,15 @@ msgstr "" #: ../../source/ref-telemetry.md:36 msgid "" -"**Hardware properties.** Understanding the hardware environment that " -"Flower is being used in helps to decide whether we should, for example, " -"put more effort into supporting low-resource environments." +"**Hardware properties.** Understanding the hardware environment that Flower " +"is being used in helps to decide whether we should, for example, put more " +"effort into supporting low-resource environments." msgstr "" #: ../../source/ref-telemetry.md:38 msgid "" -"**Execution mode.** Knowing what execution mode Flower starts in enables " -"us to understand how heavily certain features are being used and better " +"**Execution mode.** Knowing what execution mode Flower starts in enables us " +"to understand how heavily certain features are being used and better " "prioritize based on that." msgstr "" @@ -19283,37 +19634,34 @@ msgstr "" msgid "" "**Cluster.** Flower telemetry assigns a random in-memory cluster ID each " "time a Flower workload starts. This allows us to understand which device " -"types not only start Flower workloads but also successfully complete " -"them." +"types not only start Flower workloads but also successfully complete them." msgstr "" #: ../../source/ref-telemetry.md:42 msgid "" -"**Source.** Flower telemetry tries to store a random source ID in " -"`~/.flwr/source` the first time a telemetry event is generated. The " -"source ID is important to identify whether an issue is recurring or " -"whether an issue is triggered by multiple clusters running concurrently " -"(which often happens in simulation). For example, if a device runs " -"multiple workloads at the same time, and this results in an issue, then, " -"in order to reproduce the issue, multiple workloads must be started at " -"the same time." +"**Source.** Flower telemetry tries to store a random source ID in `~/.flwr/" +"source` the first time a telemetry event is generated. The source ID is " +"important to identify whether an issue is recurring or whether an issue is " +"triggered by multiple clusters running concurrently (which often happens in " +"simulation). For example, if a device runs multiple workloads at the same " +"time, and this results in an issue, then, in order to reproduce the issue, " +"multiple workloads must be started at the same time." msgstr "" #: ../../source/ref-telemetry.md:44 msgid "" -"You may delete the source ID at any time. If you wish for all events " -"logged under a specific source ID to be deleted, you can send a deletion " -"request mentioning the source ID to `telemetry@flower.ai`. All events " -"related to that source ID will then be permanently deleted." +"You may delete the source ID at any time. If you wish for all events logged " +"under a specific source ID to be deleted, you can send a deletion request " +"mentioning the source ID to `telemetry@flower.ai`. All events related to " +"that source ID will then be permanently deleted." msgstr "" #: ../../source/ref-telemetry.md:46 msgid "" -"We will not collect any personally identifiable information. If you think" -" any of the metrics collected could be misused in any way, please [get in" -" touch with us](#how-to-contact-us). We will update this page to reflect " -"any changes to the metrics collected and publish changes in the " -"changelog." +"We will not collect any personally identifiable information. If you think " +"any of the metrics collected could be misused in any way, please [get in " +"touch with us](#how-to-contact-us). We will update this page to reflect any " +"changes to the metrics collected and publish changes in the changelog." msgstr "" #: ../../source/ref-telemetry.md:48 @@ -19330,17 +19678,17 @@ msgstr "" #: ../../source/ref-telemetry.md:52 msgid "" "We wanted to make it very easy for you to inspect what anonymous usage " -"metrics are reported. You can view all the reported telemetry information" -" by setting the environment variable `FLWR_TELEMETRY_LOGGING=1`. Logging " -"is disabled by default. You may use logging independently from " +"metrics are reported. You can view all the reported telemetry information by " +"setting the environment variable `FLWR_TELEMETRY_LOGGING=1`. Logging is " +"disabled by default. You may use logging independently from " "`FLWR_TELEMETRY_ENABLED` so that you can inspect the telemetry feature " "without sending any metrics." msgstr "" #: ../../source/ref-telemetry.md:58 msgid "" -"The inspect Flower telemetry without sending any anonymous usage metrics," -" use both environment variables:" +"The inspect Flower telemetry without sending any anonymous usage metrics, " +"use both environment variables:" msgstr "" #: ../../source/ref-telemetry.md:64 @@ -19357,8 +19705,8 @@ msgstr "" #: ../../source/tutorial-quickstart-android.rst:-1 msgid "" -"Read this Federated Learning quickstart tutorial for creating an Android " -"app using Flower." +"Read this Federated Learning quickstart tutorial for creating an Android app " +"using Flower." msgstr "" #: ../../source/tutorial-quickstart-android.rst:5 @@ -19367,21 +19715,19 @@ msgstr "" #: ../../source/tutorial-quickstart-android.rst:10 msgid "" -"Let's build a federated learning system using TFLite and Flower on " -"Android!" +"Let's build a federated learning system using TFLite and Flower on Android!" msgstr "" #: ../../source/tutorial-quickstart-android.rst:12 msgid "" -"Please refer to the `full code example " -"`_ to learn " -"more." +"Please refer to the `full code example `_ to learn more." msgstr "" #: ../../source/tutorial-quickstart-fastai.rst:-1 msgid "" -"Check out this Federated Learning quickstart tutorial for using Flower " -"with FastAI to train a vision model on CIFAR-10." +"Check out this Federated Learning quickstart tutorial for using Flower with " +"FastAI to train a vision model on CIFAR-10." msgstr "" #: ../../source/tutorial-quickstart-fastai.rst:5 @@ -19394,15 +19740,14 @@ msgstr "" #: ../../source/tutorial-quickstart-fastai.rst:12 msgid "" -"Please refer to the `full code example " -"`_ " -"to learn more." +"Please refer to the `full code example `_ to learn more." msgstr "" #: ../../source/tutorial-quickstart-huggingface.rst:-1 msgid "" -"Check out this Federating Learning quickstart tutorial for using Flower " -"with HuggingFace Transformers in order to fine-tune an LLM." +"Check out this Federating Learning quickstart tutorial for using Flower with " +"HuggingFace Transformers in order to fine-tune an LLM." msgstr "" #: ../../source/tutorial-quickstart-huggingface.rst:5 @@ -19411,17 +19756,17 @@ msgstr "" #: ../../source/tutorial-quickstart-huggingface.rst:10 msgid "" -"Let's build a federated learning system using Hugging Face Transformers " -"and Flower!" +"Let's build a federated learning system using Hugging Face Transformers and " +"Flower!" msgstr "" #: ../../source/tutorial-quickstart-huggingface.rst:12 msgid "" -"We will leverage Hugging Face to federate the training of language models" -" over multiple clients using Flower. More specifically, we will fine-tune" -" a pre-trained Transformer model (distilBERT) for sequence classification" -" over a dataset of IMDB ratings. The end goal is to detect if a movie " -"rating is positive or negative." +"We will leverage Hugging Face to federate the training of language models " +"over multiple clients using Flower. More specifically, we will fine-tune a " +"pre-trained Transformer model (distilBERT) for sequence classification over " +"a dataset of IMDB ratings. The end goal is to detect if a movie rating is " +"positive or negative." msgstr "" #: ../../source/tutorial-quickstart-huggingface.rst:18 @@ -19431,9 +19776,8 @@ msgstr "" #: ../../source/tutorial-quickstart-huggingface.rst:20 msgid "" "To follow along this tutorial you will need to install the following " -"packages: :code:`datasets`, :code:`evaluate`, :code:`flwr`, " -":code:`torch`, and :code:`transformers`. This can be done using " -":code:`pip`:" +"packages: :code:`datasets`, :code:`evaluate`, :code:`flwr`, :code:`torch`, " +"and :code:`transformers`. This can be done using :code:`pip`:" msgstr "" #: ../../source/tutorial-quickstart-huggingface.rst:30 @@ -19457,9 +19801,9 @@ msgstr "" #: ../../source/tutorial-quickstart-huggingface.rst:83 msgid "" -"Once we have a way of creating our trainloader and testloader, we can " -"take care of the training and testing. This is very similar to any " -":code:`PyTorch` training or testing loop:" +"Once we have a way of creating our trainloader and testloader, we can take " +"care of the training and testing. This is very similar to any :code:" +"`PyTorch` training or testing loop:" msgstr "" #: ../../source/tutorial-quickstart-huggingface.rst:121 @@ -19468,8 +19812,8 @@ msgstr "" #: ../../source/tutorial-quickstart-huggingface.rst:123 msgid "" -"To create the model itself, we will just load the pre-trained distillBERT" -" model using Hugging Face’s :code:`AutoModelForSequenceClassification` :" +"To create the model itself, we will just load the pre-trained distillBERT " +"model using Hugging Face’s :code:`AutoModelForSequenceClassification` :" msgstr "" #: ../../source/tutorial-quickstart-huggingface.rst:136 @@ -19483,18 +19827,17 @@ msgstr "" #: ../../source/tutorial-quickstart-huggingface.rst:141 msgid "" "To federate our example to multiple clients, we first need to write our " -"Flower client class (inheriting from :code:`flwr.client.NumPyClient`). " -"This is very easy, as our model is a standard :code:`PyTorch` model:" +"Flower client class (inheriting from :code:`flwr.client.NumPyClient`). This " +"is very easy, as our model is a standard :code:`PyTorch` model:" msgstr "" #: ../../source/tutorial-quickstart-huggingface.rst:169 msgid "" "The :code:`get_parameters` function lets the server get the client's " -"parameters. Inversely, the :code:`set_parameters` function allows the " -"server to send its parameters to the client. Finally, the :code:`fit` " -"function trains the model locally for the client, and the " -":code:`evaluate` function tests the model locally and returns the " -"relevant metrics." +"parameters. Inversely, the :code:`set_parameters` function allows the server " +"to send its parameters to the client. Finally, the :code:`fit` function " +"trains the model locally for the client, and the :code:`evaluate` function " +"tests the model locally and returns the relevant metrics." msgstr "" #: ../../source/tutorial-quickstart-huggingface.rst:175 @@ -19503,19 +19846,19 @@ msgstr "" #: ../../source/tutorial-quickstart-huggingface.rst:177 msgid "" -"Now that we have a way to instantiate clients, we need to create our " -"server in order to aggregate the results. Using Flower, this can be done " -"very easily by first choosing a strategy (here, we are using " -":code:`FedAvg`, which will define the global weights as the average of " -"all the clients' weights at each round) and then using the " -":code:`flwr.server.start_server` function:" +"Now that we have a way to instantiate clients, we need to create our server " +"in order to aggregate the results. Using Flower, this can be done very " +"easily by first choosing a strategy (here, we are using :code:`FedAvg`, " +"which will define the global weights as the average of all the clients' " +"weights at each round) and then using the :code:`flwr.server.start_server` " +"function:" msgstr "" #: ../../source/tutorial-quickstart-huggingface.rst:205 msgid "" -"The :code:`weighted_average` function is there to provide a way to " -"aggregate the metrics distributed amongst the clients (basically this " -"allows us to display a nice average accuracy and loss for every round)." +"The :code:`weighted_average` function is there to provide a way to aggregate " +"the metrics distributed amongst the clients (basically this allows us to " +"display a nice average accuracy and loss for every round)." msgstr "" #: ../../source/tutorial-quickstart-huggingface.rst:209 @@ -19534,22 +19877,22 @@ msgstr "" #: ../../source/tutorial-quickstart-huggingface.rst:223 msgid "" -"If you want to check out everything put together, you should check out " -"the `full code example `_ ." +"If you want to check out everything put together, you should check out the " +"`full code example `_ ." msgstr "" #: ../../source/tutorial-quickstart-huggingface.rst:226 msgid "" -"Of course, this is a very basic example, and a lot can be added or " -"modified, it was just to showcase how simply we could federate a Hugging " -"Face workflow using Flower." +"Of course, this is a very basic example, and a lot can be added or modified, " +"it was just to showcase how simply we could federate a Hugging Face workflow " +"using Flower." msgstr "" #: ../../source/tutorial-quickstart-huggingface.rst:229 msgid "" -"Note that in this example we used :code:`PyTorch`, but we could have very" -" well used :code:`TensorFlow`." +"Note that in this example we used :code:`PyTorch`, but we could have very " +"well used :code:`TensorFlow`." msgstr "" #: ../../source/tutorial-quickstart-ios.rst:-1 @@ -19564,38 +19907,38 @@ msgstr "" #: ../../source/tutorial-quickstart-ios.rst:10 msgid "" -"In this tutorial we will learn how to train a Neural Network on MNIST " -"using Flower and CoreML on iOS devices." +"In this tutorial we will learn how to train a Neural Network on MNIST using " +"Flower and CoreML on iOS devices." msgstr "" #: ../../source/tutorial-quickstart-ios.rst:12 msgid "" "First of all, for running the Flower Python server, it is recommended to " -"create a virtual environment and run everything within a :doc:`virtualenv" -" `. For the Flower client " +"create a virtual environment and run everything within a :doc:`virtualenv " +"`. For the Flower client " "implementation in iOS, it is recommended to use Xcode as our IDE." msgstr "" #: ../../source/tutorial-quickstart-ios.rst:15 msgid "" -"Our example consists of one Python *server* and two iPhone *clients* that" -" all have the same model." +"Our example consists of one Python *server* and two iPhone *clients* that " +"all have the same model." msgstr "" #: ../../source/tutorial-quickstart-ios.rst:17 msgid "" -"*Clients* are responsible for generating individual weight updates for " -"the model based on their local datasets. These updates are then sent to " -"the *server* which will aggregate them to produce a better model. " -"Finally, the *server* sends this improved version of the model back to " -"each *client*. A complete cycle of weight updates is called a *round*." +"*Clients* are responsible for generating individual weight updates for the " +"model based on their local datasets. These updates are then sent to the " +"*server* which will aggregate them to produce a better model. Finally, the " +"*server* sends this improved version of the model back to each *client*. A " +"complete cycle of weight updates is called a *round*." msgstr "" #: ../../source/tutorial-quickstart-ios.rst:21 msgid "" "Now that we have a rough idea of what is going on, let's get started to " -"setup our Flower server environment. We first need to install Flower. You" -" can do this by using pip:" +"setup our Flower server environment. We first need to install Flower. You " +"can do this by using pip:" msgstr "" #: ../../source/tutorial-quickstart-ios.rst:27 @@ -19613,21 +19956,20 @@ msgstr "" #: ../../source/tutorial-quickstart-ios.rst:36 msgid "" "Now that we have all our dependencies installed, let's run a simple " -"distributed training using CoreML as our local training pipeline and " -"MNIST as our dataset. For simplicity reasons we will use the complete " -"Flower client with CoreML, that has been implemented and stored inside " -"the Swift SDK. The client implementation can be seen below:" +"distributed training using CoreML as our local training pipeline and MNIST " +"as our dataset. For simplicity reasons we will use the complete Flower " +"client with CoreML, that has been implemented and stored inside the Swift " +"SDK. The client implementation can be seen below:" msgstr "" #: ../../source/tutorial-quickstart-ios.rst:72 msgid "" -"Let's create a new application project in Xcode and add :code:`flwr` as a" -" dependency in your project. For our application, we will store the logic" -" of our app in :code:`FLiOSModel.swift` and the UI elements in " -":code:`ContentView.swift`. We will focus more on :code:`FLiOSModel.swift`" -" in this quickstart. Please refer to the `full code example " -"`_ to learn more " -"about the app." +"Let's create a new application project in Xcode and add :code:`flwr` as a " +"dependency in your project. For our application, we will store the logic of " +"our app in :code:`FLiOSModel.swift` and the UI elements in :code:" +"`ContentView.swift`. We will focus more on :code:`FLiOSModel.swift` in this " +"quickstart. Please refer to the `full code example `_ to learn more about the app." msgstr "" #: ../../source/tutorial-quickstart-ios.rst:75 @@ -19637,22 +19979,21 @@ msgstr "" #: ../../source/tutorial-quickstart-ios.rst:83 msgid "" "Then add the mlmodel to the project simply by drag-and-drop, the mlmodel " -"will be bundled inside the application during deployment to your iOS " -"device. We need to pass the url to access mlmodel and run CoreML machine " -"learning processes, it can be retrieved by calling the function " -":code:`Bundle.main.url`. For the MNIST dataset, we need to preprocess it " -"into :code:`MLBatchProvider` object. The preprocessing is done inside " -":code:`DataLoader.swift`." +"will be bundled inside the application during deployment to your iOS device. " +"We need to pass the url to access mlmodel and run CoreML machine learning " +"processes, it can be retrieved by calling the function :code:`Bundle.main." +"url`. For the MNIST dataset, we need to preprocess it into :code:" +"`MLBatchProvider` object. The preprocessing is done inside :code:`DataLoader." +"swift`." msgstr "" #: ../../source/tutorial-quickstart-ios.rst:99 msgid "" -"Since CoreML does not allow the model parameters to be seen before " -"training, and accessing the model parameters during or after the training" -" can only be done by specifying the layer name, we need to know this " -"information beforehand, through looking at the model specification, which" -" are written as proto files. The implementation can be seen in " -":code:`MLModelInspect`." +"Since CoreML does not allow the model parameters to be seen before training, " +"and accessing the model parameters during or after the training can only be " +"done by specifying the layer name, we need to know this information " +"beforehand, through looking at the model specification, which are written as " +"proto files. The implementation can be seen in :code:`MLModelInspect`." msgstr "" #: ../../source/tutorial-quickstart-ios.rst:102 @@ -19663,18 +20004,18 @@ msgstr "" #: ../../source/tutorial-quickstart-ios.rst:117 msgid "" -"Then start the Flower gRPC client and start communicating to the server " -"by passing our Flower client to the function :code:`startFlwrGRPC`." +"Then start the Flower gRPC client and start communicating to the server by " +"passing our Flower client to the function :code:`startFlwrGRPC`." msgstr "" #: ../../source/tutorial-quickstart-ios.rst:124 msgid "" -"That's it for the client. We only have to implement :code:`Client` or " -"call the provided :code:`MLFlwrClient` and call :code:`startFlwrGRPC()`. " -"The attribute :code:`hostname` and :code:`port` tells the client which " -"server to connect to. This can be done by entering the hostname and port " -"in the application before clicking the start button to start the " -"federated learning process." +"That's it for the client. We only have to implement :code:`Client` or call " +"the provided :code:`MLFlwrClient` and call :code:`startFlwrGRPC()`. The " +"attribute :code:`hostname` and :code:`port` tells the client which server to " +"connect to. This can be done by entering the hostname and port in the " +"application before clicking the start button to start the federated learning " +"process." msgstr "" #: ../../source/tutorial-quickstart-ios.rst:129 @@ -19690,8 +20031,8 @@ msgstr "" #: ../../source/tutorial-quickstart-tensorflow.rst:100 msgid "" "For simple workloads we can start a Flower server and leave all the " -"configuration possibilities at their default values. In a file named " -":code:`server.py`, import Flower and start the server:" +"configuration possibilities at their default values. In a file named :code:" +"`server.py`, import Flower and start the server:" msgstr "" #: ../../source/tutorial-quickstart-ios.rst:142 @@ -19707,32 +20048,31 @@ msgstr "" #: ../../source/tutorial-quickstart-xgboost.rst:525 msgid "" "With both client and server ready, we can now run everything and see " -"federated learning in action. FL systems usually have a server and " -"multiple clients. We therefore have to start the server first:" +"federated learning in action. FL systems usually have a server and multiple " +"clients. We therefore have to start the server first:" msgstr "" #: ../../source/tutorial-quickstart-ios.rst:152 msgid "" -"Once the server is running we can start the clients in different " -"terminals. Build and run the client through your Xcode, one through Xcode" -" Simulator and the other by deploying it to your iPhone. To see more " -"about how to deploy your app to iPhone or Simulator visit `here " -"`_." +"Once the server is running we can start the clients in different terminals. " +"Build and run the client through your Xcode, one through Xcode Simulator and " +"the other by deploying it to your iPhone. To see more about how to deploy " +"your app to iPhone or Simulator visit `here `_." msgstr "" #: ../../source/tutorial-quickstart-ios.rst:156 msgid "" "Congratulations! You've successfully built and run your first federated " -"learning system in your ios device. The full `source code " -"`_ for this " -"example can be found in :code:`examples/ios`." +"learning system in your ios device. The full `source code `_ for this example can be found in :" +"code:`examples/ios`." msgstr "" #: ../../source/tutorial-quickstart-jax.rst:-1 msgid "" -"Check out this Federated Learning quickstart tutorial for using Flower " -"with Jax to train a linear regression model on a scikit-learn dataset." +"Check out this Federated Learning quickstart tutorial for using Flower with " +"Jax to train a linear regression model on a scikit-learn dataset." msgstr "" #: ../../source/tutorial-quickstart-jax.rst:5 @@ -19741,8 +20081,8 @@ msgstr "" #: ../../source/tutorial-quickstart-pandas.rst:-1 msgid "" -"Check out this Federated Learning quickstart tutorial for using Flower " -"with Pandas to perform Federated Analytics." +"Check out this Federated Learning quickstart tutorial for using Flower with " +"Pandas to perform Federated Analytics." msgstr "" #: ../../source/tutorial-quickstart-pandas.rst:5 @@ -19755,45 +20095,44 @@ msgstr "" #: ../../source/tutorial-quickstart-pandas.rst:12 msgid "" -"Please refer to the `full code example " -"`_ " -"to learn more." +"Please refer to the `full code example `_ to learn more." msgstr "" #: ../../source/tutorial-quickstart-pytorch.rst:-1 msgid "" -"Check out this Federated Learning quickstart tutorial for using Flower " -"with PyTorch to train a CNN model on MNIST." +"Check out this Federated Learning quickstart tutorial for using Flower with " +"PyTorch to train a CNN model on MNIST." msgstr "" #: ../../source/tutorial-quickstart-pytorch.rst:13 msgid "" -"In this tutorial we will learn how to train a Convolutional Neural " -"Network on CIFAR10 using Flower and PyTorch." +"In this tutorial we will learn how to train a Convolutional Neural Network " +"on CIFAR10 using Flower and PyTorch." msgstr "" #: ../../source/tutorial-quickstart-pytorch.rst:15 #: ../../source/tutorial-quickstart-xgboost.rst:39 msgid "" "First of all, it is recommended to create a virtual environment and run " -"everything within a :doc:`virtualenv `." +"everything within a :doc:`virtualenv `." msgstr "" #: ../../source/tutorial-quickstart-pytorch.rst:17 #: ../../source/tutorial-quickstart-scikitlearn.rst:14 msgid "" -"Our example consists of one *server* and two *clients* all having the " -"same model." +"Our example consists of one *server* and two *clients* all having the same " +"model." msgstr "" #: ../../source/tutorial-quickstart-pytorch.rst:19 msgid "" -"*Clients* are responsible for generating individual weight-updates for " -"the model based on their local datasets. These updates are then sent to " -"the *server* which will aggregate them to produce a better model. " -"Finally, the *server* sends this improved version of the model back to " -"each *client*. A complete cycle of weight updates is called a *round*." +"*Clients* are responsible for generating individual weight-updates for the " +"model based on their local datasets. These updates are then sent to the " +"*server* which will aggregate them to produce a better model. Finally, the " +"*server* sends this improved version of the model back to each *client*. A " +"complete cycle of weight updates is called a *round*." msgstr "" #: ../../source/tutorial-quickstart-pytorch.rst:23 @@ -19804,16 +20143,15 @@ msgstr "" #: ../../source/tutorial-quickstart-pytorch.rst:29 msgid "" -"Since we want to use PyTorch to solve a computer vision task, let's go " -"ahead and install PyTorch and the **torchvision** library:" +"Since we want to use PyTorch to solve a computer vision task, let's go ahead " +"and install PyTorch and the **torchvision** library:" msgstr "" #: ../../source/tutorial-quickstart-pytorch.rst:39 msgid "" "Now that we have all our dependencies installed, let's run a simple " -"distributed training with two clients and one server. Our training " -"procedure and network architecture are based on PyTorch's `Deep Learning " -"with PyTorch " +"distributed training with two clients and one server. Our training procedure " +"and network architecture are based on PyTorch's `Deep Learning with PyTorch " "`_." msgstr "" @@ -19830,33 +20168,33 @@ msgstr "" #: ../../source/tutorial-quickstart-pytorch.rst:62 msgid "" "We use PyTorch to load CIFAR10, a popular colored image classification " -"dataset for machine learning. The PyTorch :code:`DataLoader()` downloads " -"the training and test data that are then normalized." +"dataset for machine learning. The PyTorch :code:`DataLoader()` downloads the " +"training and test data that are then normalized." msgstr "" #: ../../source/tutorial-quickstart-pytorch.rst:78 msgid "" -"Define the loss and optimizer with PyTorch. The training of the dataset " -"is done by looping over the dataset, measure the corresponding loss and " +"Define the loss and optimizer with PyTorch. The training of the dataset is " +"done by looping over the dataset, measure the corresponding loss and " "optimize it." msgstr "" #: ../../source/tutorial-quickstart-pytorch.rst:94 msgid "" -"Define then the validation of the machine learning network. We loop over" -" the test set and measure the loss and accuracy of the test set." +"Define then the validation of the machine learning network. We loop over " +"the test set and measure the loss and accuracy of the test set." msgstr "" #: ../../source/tutorial-quickstart-pytorch.rst:113 msgid "" -"After defining the training and testing of a PyTorch machine learning " -"model, we use the functions for the Flower clients." +"After defining the training and testing of a PyTorch machine learning model, " +"we use the functions for the Flower clients." msgstr "" #: ../../source/tutorial-quickstart-pytorch.rst:115 msgid "" -"The Flower clients will use a simple CNN adapted from 'PyTorch: A 60 " -"Minute Blitz':" +"The Flower clients will use a simple CNN adapted from 'PyTorch: A 60 Minute " +"Blitz':" msgstr "" #: ../../source/tutorial-quickstart-pytorch.rst:142 @@ -19868,20 +20206,19 @@ msgstr "" #: ../../source/tutorial-quickstart-pytorch.rst:144 #: ../../source/tutorial-quickstart-tensorflow.rst:54 msgid "" -"The Flower server interacts with clients through an interface called " -":code:`Client`. When the server selects a particular client for training," -" it sends training instructions over the network. The client receives " -"those instructions and calls one of the :code:`Client` methods to run " -"your code (i.e., to train the neural network we defined earlier)." +"The Flower server interacts with clients through an interface called :code:" +"`Client`. When the server selects a particular client for training, it sends " +"training instructions over the network. The client receives those " +"instructions and calls one of the :code:`Client` methods to run your code (i." +"e., to train the neural network we defined earlier)." msgstr "" #: ../../source/tutorial-quickstart-pytorch.rst:150 msgid "" -"Flower provides a convenience class called :code:`NumPyClient` which " -"makes it easier to implement the :code:`Client` interface when your " -"workload uses PyTorch. Implementing :code:`NumPyClient` usually means " -"defining the following methods (:code:`set_parameters` is optional " -"though):" +"Flower provides a convenience class called :code:`NumPyClient` which makes " +"it easier to implement the :code:`Client` interface when your workload uses " +"PyTorch. Implementing :code:`NumPyClient` usually means defining the " +"following methods (:code:`set_parameters` is optional though):" msgstr "" #: ../../source/tutorial-quickstart-pytorch.rst:156 @@ -19897,8 +20234,7 @@ msgstr "" #: ../../source/tutorial-quickstart-pytorch.rst:158 #: ../../source/tutorial-quickstart-scikitlearn.rst:121 msgid "" -"update the local model weights with the parameters received from the " -"server" +"update the local model weights with the parameters received from the server" msgstr "" #: ../../source/tutorial-quickstart-pytorch.rst:160 @@ -19928,22 +20264,22 @@ msgstr "" #: ../../source/tutorial-quickstart-pytorch.rst:189 #: ../../source/tutorial-quickstart-tensorflow.rst:82 msgid "" -"We can now create an instance of our class :code:`CifarClient` and add " -"one line to actually run this client:" +"We can now create an instance of our class :code:`CifarClient` and add one " +"line to actually run this client:" msgstr "" #: ../../source/tutorial-quickstart-pytorch.rst:196 #: ../../source/tutorial-quickstart-tensorflow.rst:90 msgid "" -"That's it for the client. We only have to implement :code:`Client` or " -":code:`NumPyClient` and call :code:`fl.client.start_client()`. If you " -"implement a client of type :code:`NumPyClient` you'll need to first call " -"its :code:`to_client()` method. The string :code:`\"[::]:8080\"` tells " -"the client which server to connect to. In our case we can run the server " -"and the client on the same machine, therefore we use " -":code:`\"[::]:8080\"`. If we run a truly federated workload with the " -"server and clients running on different machines, all that needs to " -"change is the :code:`server_address` we point the client at." +"That's it for the client. We only have to implement :code:`Client` or :code:" +"`NumPyClient` and call :code:`fl.client.start_client()`. If you implement a " +"client of type :code:`NumPyClient` you'll need to first call its :code:" +"`to_client()` method. The string :code:`\"[::]:8080\"` tells the client " +"which server to connect to. In our case we can run the server and the client " +"on the same machine, therefore we use :code:`\"[::]:8080\"`. If we run a " +"truly federated workload with the server and clients running on different " +"machines, all that needs to change is the :code:`server_address` we point " +"the client at." msgstr "" #: ../../source/tutorial-quickstart-pytorch.rst:226 @@ -19951,8 +20287,8 @@ msgstr "" #: ../../source/tutorial-quickstart-tensorflow.rst:122 #: ../../source/tutorial-quickstart-xgboost.rst:533 msgid "" -"Once the server is running we can start the clients in different " -"terminals. Open a new terminal and start the first client:" +"Once the server is running we can start the clients in different terminals. " +"Open a new terminal and start the first client:" msgstr "" #: ../../source/tutorial-quickstart-pytorch.rst:233 @@ -19966,24 +20302,22 @@ msgstr "" #: ../../source/tutorial-quickstart-scikitlearn.rst:252 #: ../../source/tutorial-quickstart-xgboost.rst:546 msgid "" -"Each client will have its own dataset. You should now see how the " -"training does in the very first terminal (the one that started the " -"server):" +"Each client will have its own dataset. You should now see how the training " +"does in the very first terminal (the one that started the server):" msgstr "" #: ../../source/tutorial-quickstart-pytorch.rst:271 msgid "" "Congratulations! You've successfully built and run your first federated " -"learning system. The full `source code " -"`_ for this example can be found in :code:`examples" -"/quickstart-pytorch`." +"learning system. The full `source code `_ for this example can be found " +"in :code:`examples/quickstart-pytorch`." msgstr "" #: ../../source/tutorial-quickstart-pytorch-lightning.rst:-1 msgid "" -"Check out this Federated Learning quickstart tutorial for using Flower " -"with PyTorch Lightning to train an Auto Encoder model on MNIST." +"Check out this Federated Learning quickstart tutorial for using Flower with " +"PyTorch Lightning to train an Auto Encoder model on MNIST." msgstr "" #: ../../source/tutorial-quickstart-pytorch-lightning.rst:5 @@ -19992,21 +20326,20 @@ msgstr "" #: ../../source/tutorial-quickstart-pytorch-lightning.rst:10 msgid "" -"Let's build a horizontal federated learning system using PyTorch " -"Lightning and Flower!" +"Let's build a horizontal federated learning system using PyTorch Lightning " +"and Flower!" msgstr "" #: ../../source/tutorial-quickstart-pytorch-lightning.rst:12 msgid "" -"Please refer to the `full code example " -"`_ to learn more." +"Please refer to the `full code example `_ to learn more." msgstr "" #: ../../source/tutorial-quickstart-scikitlearn.rst:-1 msgid "" -"Check out this Federated Learning quickstart tutorial for using Flower " -"with scikit-learn to train a linear regression model." +"Check out this Federated Learning quickstart tutorial for using Flower with " +"scikit-learn to train a linear regression model." msgstr "" #: ../../source/tutorial-quickstart-scikitlearn.rst:5 @@ -20015,24 +20348,23 @@ msgstr "" #: ../../source/tutorial-quickstart-scikitlearn.rst:10 msgid "" -"In this tutorial, we will learn how to train a :code:`Logistic " -"Regression` model on MNIST using Flower and scikit-learn." +"In this tutorial, we will learn how to train a :code:`Logistic Regression` " +"model on MNIST using Flower and scikit-learn." msgstr "" #: ../../source/tutorial-quickstart-scikitlearn.rst:12 msgid "" -"It is recommended to create a virtual environment and run everything " -"within this :doc:`virtualenv `." +"It is recommended to create a virtual environment and run everything within " +"this :doc:`virtualenv `." msgstr "" #: ../../source/tutorial-quickstart-scikitlearn.rst:16 msgid "" -"*Clients* are responsible for generating individual model parameter " -"updates for the model based on their local datasets. These updates are " -"then sent to the *server* which will aggregate them to produce an updated" -" global model. Finally, the *server* sends this improved version of the " -"model back to each *client*. A complete cycle of parameters updates is " -"called a *round*." +"*Clients* are responsible for generating individual model parameter updates " +"for the model based on their local datasets. These updates are then sent to " +"the *server* which will aggregate them to produce an updated global model. " +"Finally, the *server* sends this improved version of the model back to each " +"*client*. A complete cycle of parameters updates is called a *round*." msgstr "" #: ../../source/tutorial-quickstart-scikitlearn.rst:20 @@ -20053,10 +20385,10 @@ msgstr "" msgid "" "Now that we have all our dependencies installed, let's run a simple " "distributed training with two clients and one server. However, before " -"setting up the client and server, we will define all functionalities that" -" we need for our federated learning setup within :code:`utils.py`. The " -":code:`utils.py` contains different functions defining all the machine " -"learning basics:" +"setting up the client and server, we will define all functionalities that we " +"need for our federated learning setup within :code:`utils.py`. The :code:" +"`utils.py` contains different functions defining all the machine learning " +"basics:" msgstr "" #: ../../source/tutorial-quickstart-scikitlearn.rst:45 @@ -20085,46 +20417,44 @@ msgstr "" #: ../../source/tutorial-quickstart-scikitlearn.rst:52 msgid "" -"Please check out :code:`utils.py` `here " -"`_ for more details. The pre-defined functions are used in" -" the :code:`client.py` and imported. The :code:`client.py` also requires " -"to import several packages such as Flower and scikit-learn:" +"Please check out :code:`utils.py` `here `_ for more details. The pre-" +"defined functions are used in the :code:`client.py` and imported. The :code:" +"`client.py` also requires to import several packages such as Flower and " +"scikit-learn:" msgstr "" #: ../../source/tutorial-quickstart-scikitlearn.rst:67 msgid "" -"Prior to local training, we need to load the MNIST dataset, a popular " -"image classification dataset of handwritten digits for machine learning, " -"and partition the dataset for FL. This can be conveniently achieved using" -" `Flower Datasets `_. The " -":code:`FederatedDataset.load_partition()` method loads the partitioned " -"training set for each partition ID defined in the :code:`--partition-id` " -"argument." +"Prior to local training, we need to load the MNIST dataset, a popular image " +"classification dataset of handwritten digits for machine learning, and " +"partition the dataset for FL. This can be conveniently achieved using " +"`Flower Datasets `_. The :code:" +"`FederatedDataset.load_partition()` method loads the partitioned training " +"set for each partition ID defined in the :code:`--partition-id` argument." msgstr "" #: ../../source/tutorial-quickstart-scikitlearn.rst:95 msgid "" -"Next, the logistic regression model is defined and initialized with " -":code:`utils.set_initial_params()`." +"Next, the logistic regression model is defined and initialized with :code:" +"`utils.set_initial_params()`." msgstr "" #: ../../source/tutorial-quickstart-scikitlearn.rst:107 msgid "" -"The Flower server interacts with clients through an interface called " -":code:`Client`. When the server selects a particular client for training," -" it sends training instructions over the network. The client receives " -"those instructions and calls one of the :code:`Client` methods to run " -"your code (i.e., to fit the logistic regression we defined earlier)." +"The Flower server interacts with clients through an interface called :code:" +"`Client`. When the server selects a particular client for training, it sends " +"training instructions over the network. The client receives those " +"instructions and calls one of the :code:`Client` methods to run your code (i." +"e., to fit the logistic regression we defined earlier)." msgstr "" #: ../../source/tutorial-quickstart-scikitlearn.rst:113 msgid "" -"Flower provides a convenience class called :code:`NumPyClient` which " -"makes it easier to implement the :code:`Client` interface when your " -"workload uses scikit-learn. Implementing :code:`NumPyClient` usually " -"means defining the following methods (:code:`set_parameters` is optional " -"though):" +"Flower provides a convenience class called :code:`NumPyClient` which makes " +"it easier to implement the :code:`Client` interface when your workload uses " +"scikit-learn. Implementing :code:`NumPyClient` usually means defining the " +"following methods (:code:`set_parameters` is optional though):" msgstr "" #: ../../source/tutorial-quickstart-scikitlearn.rst:122 @@ -20137,28 +20467,28 @@ msgstr "" #: ../../source/tutorial-quickstart-scikitlearn.rst:153 msgid "" -"We can now create an instance of our class :code:`MnistClient` and add " -"one line to actually run this client:" +"We can now create an instance of our class :code:`MnistClient` and add one " +"line to actually run this client:" msgstr "" #: ../../source/tutorial-quickstart-scikitlearn.rst:160 msgid "" -"That's it for the client. We only have to implement :code:`Client` or " -":code:`NumPyClient` and call :code:`fl.client.start_client()`. If you " -"implement a client of type :code:`NumPyClient` you'll need to first call " -"its :code:`to_client()` method. The string :code:`\"0.0.0.0:8080\"` tells" -" the client which server to connect to. In our case we can run the server" -" and the client on the same machine, therefore we use " -":code:`\"0.0.0.0:8080\"`. If we run a truly federated workload with the " -"server and clients running on different machines, all that needs to " -"change is the :code:`server_address` we pass to the client." +"That's it for the client. We only have to implement :code:`Client` or :code:" +"`NumPyClient` and call :code:`fl.client.start_client()`. If you implement a " +"client of type :code:`NumPyClient` you'll need to first call its :code:" +"`to_client()` method. The string :code:`\"0.0.0.0:8080\"` tells the client " +"which server to connect to. In our case we can run the server and the client " +"on the same machine, therefore we use :code:`\"0.0.0.0:8080\"`. If we run a " +"truly federated workload with the server and clients running on different " +"machines, all that needs to change is the :code:`server_address` we pass to " +"the client." msgstr "" #: ../../source/tutorial-quickstart-scikitlearn.rst:169 msgid "" "The following Flower server is a little bit more advanced and returns an " -"evaluation function for the server-side evaluation. First, we import " -"again all required libraries such as Flower and scikit-learn." +"evaluation function for the server-side evaluation. First, we import again " +"all required libraries such as Flower and scikit-learn." msgstr "" #: ../../source/tutorial-quickstart-scikitlearn.rst:172 @@ -20167,46 +20497,44 @@ msgstr "" #: ../../source/tutorial-quickstart-scikitlearn.rst:185 msgid "" -"The number of federated learning rounds is set in :code:`fit_round()` and" -" the evaluation is defined in :code:`get_evaluate_fn()`. The evaluation " +"The number of federated learning rounds is set in :code:`fit_round()` and " +"the evaluation is defined in :code:`get_evaluate_fn()`. The evaluation " "function is called after each federated learning round and gives you " -"information about loss and accuracy. Note that we also make use of Flower" -" Datasets here to load the test split of the MNIST dataset for server-" -"side evaluation." +"information about loss and accuracy. Note that we also make use of Flower " +"Datasets here to load the test split of the MNIST dataset for server-side " +"evaluation." msgstr "" #: ../../source/tutorial-quickstart-scikitlearn.rst:213 msgid "" -"The :code:`main` contains the server-side parameter initialization " -":code:`utils.set_initial_params()` as well as the aggregation strategy " -":code:`fl.server.strategy:FedAvg()`. The strategy is the default one, " -"federated averaging (or FedAvg), with two clients and evaluation after " -"each federated learning round. The server can be started with the command" -" :code:`fl.server.start_server(server_address=\"0.0.0.0:8080\", " -"strategy=strategy, config=fl.server.ServerConfig(num_rounds=3))`." +"The :code:`main` contains the server-side parameter initialization :code:" +"`utils.set_initial_params()` as well as the aggregation strategy :code:`fl." +"server.strategy:FedAvg()`. The strategy is the default one, federated " +"averaging (or FedAvg), with two clients and evaluation after each federated " +"learning round. The server can be started with the command :code:`fl.server." +"start_server(server_address=\"0.0.0.0:8080\", strategy=strategy, config=fl." +"server.ServerConfig(num_rounds=3))`." msgstr "" #: ../../source/tutorial-quickstart-scikitlearn.rst:232 msgid "" "With both client and server ready, we can now run everything and see " "federated learning in action. Federated learning systems usually have a " -"server and multiple clients. We, therefore, have to start the server " -"first:" +"server and multiple clients. We, therefore, have to start the server first:" msgstr "" #: ../../source/tutorial-quickstart-scikitlearn.rst:286 msgid "" "Congratulations! You've successfully built and run your first federated " -"learning system. The full `source code " -"`_ for this example can be found in :code:`examples/sklearn-logreg-" -"mnist`." +"learning system. The full `source code `_ for this example can be found in :code:" +"`examples/sklearn-logreg-mnist`." msgstr "" #: ../../source/tutorial-quickstart-tensorflow.rst:-1 msgid "" -"Check out this Federated Learning quickstart tutorial for using Flower " -"with TensorFlow to train a MobilNetV2 model on CIFAR-10." +"Check out this Federated Learning quickstart tutorial for using Flower with " +"TensorFlow to train a MobilNetV2 model on CIFAR-10." msgstr "" #: ../../source/tutorial-quickstart-tensorflow.rst:5 @@ -20223,8 +20551,8 @@ msgstr "" #: ../../source/tutorial-quickstart-tensorflow.rst:21 msgid "" -"Since we want to use the Keras API of TensorFlow (TF), we have to install" -" TF as well:" +"Since we want to use the Keras API of TensorFlow (TF), we have to install TF " +"as well:" msgstr "" #: ../../source/tutorial-quickstart-tensorflow.rst:31 @@ -20233,25 +20561,24 @@ msgstr "" #: ../../source/tutorial-quickstart-tensorflow.rst:38 msgid "" -"We use the Keras utilities of TF to load CIFAR10, a popular colored image" -" classification dataset for machine learning. The call to " -":code:`tf.keras.datasets.cifar10.load_data()` downloads CIFAR10, caches " -"it locally, and then returns the entire training and test set as NumPy " -"ndarrays." +"We use the Keras utilities of TF to load CIFAR10, a popular colored image " +"classification dataset for machine learning. The call to :code:`tf.keras." +"datasets.cifar10.load_data()` downloads CIFAR10, caches it locally, and then " +"returns the entire training and test set as NumPy ndarrays." msgstr "" #: ../../source/tutorial-quickstart-tensorflow.rst:47 msgid "" -"Next, we need a model. For the purpose of this tutorial, we use " -"MobilNetV2 with 10 output classes:" +"Next, we need a model. For the purpose of this tutorial, we use MobilNetV2 " +"with 10 output classes:" msgstr "" #: ../../source/tutorial-quickstart-tensorflow.rst:60 msgid "" -"Flower provides a convenience class called :code:`NumPyClient` which " -"makes it easier to implement the :code:`Client` interface when your " -"workload uses Keras. The :code:`NumPyClient` interface defines three " -"methods which can be implemented in the following way:" +"Flower provides a convenience class called :code:`NumPyClient` which makes " +"it easier to implement the :code:`Client` interface when your workload uses " +"Keras. The :code:`NumPyClient` interface defines three methods which can be " +"implemented in the following way:" msgstr "" #: ../../source/tutorial-quickstart-tensorflow.rst:135 @@ -20260,23 +20587,22 @@ msgstr "" #: ../../source/tutorial-quickstart-tensorflow.rst:137 msgid "" -"You should now see how the training does in the very first terminal (the " -"one that started the server):" +"You should now see how the training does in the very first terminal (the one " +"that started the server):" msgstr "" #: ../../source/tutorial-quickstart-tensorflow.rst:169 msgid "" "Congratulations! You've successfully built and run your first federated " -"learning system. The full `source code " -"`_ for this can be found in :code:`examples" -"/quickstart-tensorflow/client.py`." +"learning system. The full `source code `_ for this can be found in :" +"code:`examples/quickstart-tensorflow/client.py`." msgstr "" #: ../../source/tutorial-quickstart-xgboost.rst:-1 msgid "" -"Check out this Federated Learning quickstart tutorial for using Flower " -"with XGBoost to train classification models on trees." +"Check out this Federated Learning quickstart tutorial for using Flower with " +"XGBoost to train classification models on trees." msgstr "" #: ../../source/tutorial-quickstart-xgboost.rst:5 @@ -20290,18 +20616,17 @@ msgstr "" #: ../../source/tutorial-quickstart-xgboost.rst:16 msgid "" "EXtreme Gradient Boosting (**XGBoost**) is a robust and efficient " -"implementation of gradient-boosted decision tree (**GBDT**), that " -"maximises the computational boundaries for boosted tree methods. It's " -"primarily designed to enhance both the performance and computational " -"speed of machine learning models. In XGBoost, trees are constructed " -"concurrently, unlike the sequential approach taken by GBDT." +"implementation of gradient-boosted decision tree (**GBDT**), that maximises " +"the computational boundaries for boosted tree methods. It's primarily " +"designed to enhance both the performance and computational speed of machine " +"learning models. In XGBoost, trees are constructed concurrently, unlike the " +"sequential approach taken by GBDT." msgstr "" #: ../../source/tutorial-quickstart-xgboost.rst:20 msgid "" "Often, for tabular data on medium-sized datasets with fewer than 10k " -"training examples, XGBoost surpasses the results of deep learning " -"techniques." +"training examples, XGBoost surpasses the results of deep learning techniques." msgstr "" #: ../../source/tutorial-quickstart-xgboost.rst:23 @@ -20311,30 +20636,30 @@ msgstr "" #: ../../source/tutorial-quickstart-xgboost.rst:25 msgid "" "Indeed, as the demand for data privacy and decentralized learning grows, " -"there's an increasing requirement to implement federated XGBoost systems " -"for specialised applications, like survival analysis and financial fraud " +"there's an increasing requirement to implement federated XGBoost systems for " +"specialised applications, like survival analysis and financial fraud " "detection." msgstr "" #: ../../source/tutorial-quickstart-xgboost.rst:27 msgid "" -"Federated learning ensures that raw data remains on the local device, " -"making it an attractive approach for sensitive domains where data " -"security and privacy are paramount. Given the robustness and efficiency " -"of XGBoost, combining it with federated learning offers a promising " -"solution for these specific challenges." +"Federated learning ensures that raw data remains on the local device, making " +"it an attractive approach for sensitive domains where data security and " +"privacy are paramount. Given the robustness and efficiency of XGBoost, " +"combining it with federated learning offers a promising solution for these " +"specific challenges." msgstr "" #: ../../source/tutorial-quickstart-xgboost.rst:30 msgid "" "In this tutorial we will learn how to train a federated XGBoost model on " "HIGGS dataset using Flower and :code:`xgboost` package. We use a simple " -"example (`full code xgboost-quickstart " -"`_)" -" with two *clients* and one *server* to demonstrate how federated XGBoost" -" works, and then we dive into a more complex example (`full code xgboost-" -"comprehensive `_) to run various experiments." +"example (`full code xgboost-quickstart `_) with two *clients* and one *server* to " +"demonstrate how federated XGBoost works, and then we dive into a more " +"complex example (`full code xgboost-comprehensive `_) to run various " +"experiments." msgstr "" #: ../../source/tutorial-quickstart-xgboost.rst:37 @@ -20355,16 +20680,16 @@ msgstr "" #: ../../source/tutorial-quickstart-xgboost.rst:57 msgid "" -"*Clients* are responsible for generating individual weight-updates for " -"the model based on their local datasets. Now that we have all our " -"dependencies installed, let's run a simple distributed training with two " -"clients and one server." +"*Clients* are responsible for generating individual weight-updates for the " +"model based on their local datasets. Now that we have all our dependencies " +"installed, let's run a simple distributed training with two clients and one " +"server." msgstr "" #: ../../source/tutorial-quickstart-xgboost.rst:60 msgid "" -"In a file called :code:`client.py`, import xgboost, Flower, Flower " -"Datasets and other related functions:" +"In a file called :code:`client.py`, import xgboost, Flower, Flower Datasets " +"and other related functions:" msgstr "" #: ../../source/tutorial-quickstart-xgboost.rst:87 @@ -20373,15 +20698,15 @@ msgstr "" #: ../../source/tutorial-quickstart-xgboost.rst:89 msgid "" -"Prior to local training, we require loading the HIGGS dataset from Flower" -" Datasets and conduct data partitioning for FL:" +"Prior to local training, we require loading the HIGGS dataset from Flower " +"Datasets and conduct data partitioning for FL:" msgstr "" #: ../../source/tutorial-quickstart-xgboost.rst:102 msgid "" "In this example, we split the dataset into two partitions with uniform " -"distribution (:code:`IidPartitioner(num_partitions=2)`). Then, we load " -"the partition for the given client based on :code:`node_id`:" +"distribution (:code:`IidPartitioner(num_partitions=2)`). Then, we load the " +"partition for the given client based on :code:`node_id`:" msgstr "" #: ../../source/tutorial-quickstart-xgboost.rst:121 @@ -20392,8 +20717,8 @@ msgstr "" #: ../../source/tutorial-quickstart-xgboost.rst:134 msgid "" -"The functions of :code:`train_test_split` and " -":code:`transform_dataset_to_dmatrix` are defined as below:" +"The functions of :code:`train_test_split` and :code:" +"`transform_dataset_to_dmatrix` are defined as below:" msgstr "" #: ../../source/tutorial-quickstart-xgboost.rst:158 @@ -20402,10 +20727,10 @@ msgstr "" #: ../../source/tutorial-quickstart-xgboost.rst:174 msgid "" -"The :code:`num_local_round` represents the number of iterations for local" -" tree boost. We use CPU for the training in default. One can shift it to " -"GPU by setting :code:`tree_method` to :code:`gpu_hist`. We use AUC as " -"evaluation metric." +"The :code:`num_local_round` represents the number of iterations for local " +"tree boost. We use CPU for the training in default. One can shift it to GPU " +"by setting :code:`tree_method` to :code:`gpu_hist`. We use AUC as evaluation " +"metric." msgstr "" #: ../../source/tutorial-quickstart-xgboost.rst:181 @@ -20414,86 +20739,85 @@ msgstr "" #: ../../source/tutorial-quickstart-xgboost.rst:183 msgid "" -"After loading the dataset we define the Flower client. We follow the " -"general rule to define :code:`XgbClient` class inherited from " -":code:`fl.client.Client`." +"After loading the dataset we define the Flower client. We follow the general " +"rule to define :code:`XgbClient` class inherited from :code:`fl.client." +"Client`." msgstr "" #: ../../source/tutorial-quickstart-xgboost.rst:193 msgid "" "The :code:`self.bst` is used to keep the Booster objects that remain " "consistent across rounds, allowing them to store predictions from trees " -"integrated in earlier rounds and maintain other essential data structures" -" for training." +"integrated in earlier rounds and maintain other essential data structures " +"for training." msgstr "" #: ../../source/tutorial-quickstart-xgboost.rst:196 msgid "" -"Then, we override :code:`get_parameters`, :code:`fit` and " -":code:`evaluate` methods insides :code:`XgbClient` class as follows." +"Then, we override :code:`get_parameters`, :code:`fit` and :code:`evaluate` " +"methods insides :code:`XgbClient` class as follows." msgstr "" #: ../../source/tutorial-quickstart-xgboost.rst:210 msgid "" "Unlike neural network training, XGBoost trees are not started from a " -"specified random weights. In this case, we do not use " -":code:`get_parameters` and :code:`set_parameters` to initialise model " -"parameters for XGBoost. As a result, let's return an empty tensor in " -":code:`get_parameters` when it is called by the server at the first " -"round." +"specified random weights. In this case, we do not use :code:`get_parameters` " +"and :code:`set_parameters` to initialise model parameters for XGBoost. As a " +"result, let's return an empty tensor in :code:`get_parameters` when it is " +"called by the server at the first round." msgstr "" #: ../../source/tutorial-quickstart-xgboost.rst:251 msgid "" -"In :code:`fit`, at the first round, we call :code:`xgb.train()` to build " -"up the first set of trees. the returned Booster object and config are " -"stored in :code:`self.bst` and :code:`self.config`, respectively. From " -"the second round, we load the global model sent from server to " -":code:`self.bst`, and then update model weights on local training data " -"with function :code:`local_boost` as follows:" +"In :code:`fit`, at the first round, we call :code:`xgb.train()` to build up " +"the first set of trees. the returned Booster object and config are stored " +"in :code:`self.bst` and :code:`self.config`, respectively. From the second " +"round, we load the global model sent from server to :code:`self.bst`, and " +"then update model weights on local training data with function :code:" +"`local_boost` as follows:" msgstr "" #: ../../source/tutorial-quickstart-xgboost.rst:269 msgid "" -"Given :code:`num_local_round`, we update trees by calling " -":code:`self.bst.update` method. After training, the last " -":code:`N=num_local_round` trees will be extracted to send to the server." +"Given :code:`num_local_round`, we update trees by calling :code:`self.bst." +"update` method. After training, the last :code:`N=num_local_round` trees " +"will be extracted to send to the server." msgstr "" #: ../../source/tutorial-quickstart-xgboost.rst:291 msgid "" -"In :code:`evaluate`, we call :code:`self.bst.eval_set` function to " -"conduct evaluation on valid set. The AUC value will be returned." +"In :code:`evaluate`, we call :code:`self.bst.eval_set` function to conduct " +"evaluation on valid set. The AUC value will be returned." msgstr "" #: ../../source/tutorial-quickstart-xgboost.rst:294 msgid "" -"Now, we can create an instance of our class :code:`XgbClient` and add one" -" line to actually run this client:" +"Now, we can create an instance of our class :code:`XgbClient` and add one " +"line to actually run this client:" msgstr "" #: ../../source/tutorial-quickstart-xgboost.rst:300 msgid "" -"That's it for the client. We only have to implement :code:`Client`and " -"call :code:`fl.client.start_client()`. The string :code:`\"[::]:8080\"` " -"tells the client which server to connect to. In our case we can run the " -"server and the client on the same machine, therefore we use " -":code:`\"[::]:8080\"`. If we run a truly federated workload with the " -"server and clients running on different machines, all that needs to " -"change is the :code:`server_address` we point the client at." +"That's it for the client. We only have to implement :code:`Client`and call :" +"code:`fl.client.start_client()`. The string :code:`\"[::]:8080\"` tells the " +"client which server to connect to. In our case we can run the server and the " +"client on the same machine, therefore we use :code:`\"[::]:8080\"`. If we " +"run a truly federated workload with the server and clients running on " +"different machines, all that needs to change is the :code:`server_address` " +"we point the client at." msgstr "" #: ../../source/tutorial-quickstart-xgboost.rst:311 msgid "" "These updates are then sent to the *server* which will aggregate them to " -"produce a better model. Finally, the *server* sends this improved version" -" of the model back to each *client* to finish a complete FL round." +"produce a better model. Finally, the *server* sends this improved version of " +"the model back to each *client* to finish a complete FL round." msgstr "" #: ../../source/tutorial-quickstart-xgboost.rst:314 msgid "" -"In a file named :code:`server.py`, import Flower and FedXgbBagging from " -":code:`flwr.server.strategy`." +"In a file named :code:`server.py`, import Flower and FedXgbBagging from :" +"code:`flwr.server.strategy`." msgstr "" #: ../../source/tutorial-quickstart-xgboost.rst:316 @@ -20502,9 +20826,9 @@ msgstr "" #: ../../source/tutorial-quickstart-xgboost.rst:339 msgid "" -"We use two clients for this example. An " -":code:`evaluate_metrics_aggregation` function is defined to collect and " -"wighted average the AUC values from clients." +"We use two clients for this example. An :code:`evaluate_metrics_aggregation` " +"function is defined to collect and wighted average the AUC values from " +"clients." msgstr "" #: ../../source/tutorial-quickstart-xgboost.rst:342 @@ -20517,16 +20841,16 @@ msgstr "" #: ../../source/tutorial-quickstart-xgboost.rst:356 msgid "" -"You must be curious about how bagging aggregation works. Let's look into " -"the details." +"You must be curious about how bagging aggregation works. Let's look into the " +"details." msgstr "" #: ../../source/tutorial-quickstart-xgboost.rst:358 msgid "" -"In file :code:`flwr.server.strategy.fedxgb_bagging.py`, we define " -":code:`FedXgbBagging` inherited from :code:`flwr.server.strategy.FedAvg`." -" Then, we override the :code:`aggregate_fit`, :code:`aggregate_evaluate` " -"and :code:`evaluate` methods as follows:" +"In file :code:`flwr.server.strategy.fedxgb_bagging.py`, we define :code:" +"`FedXgbBagging` inherited from :code:`flwr.server.strategy.FedAvg`. Then, we " +"override the :code:`aggregate_fit`, :code:`aggregate_evaluate` and :code:" +"`evaluate` methods as follows:" msgstr "" #: ../../source/tutorial-quickstart-xgboost.rst:454 @@ -20538,10 +20862,10 @@ msgstr "" #: ../../source/tutorial-quickstart-xgboost.rst:513 msgid "" "In this function, we first fetch the number of trees and the number of " -"parallel trees for the current and previous model by calling " -":code:`_get_tree_nums`. Then, the fetched information will be aggregated." -" After that, the trees (containing model weights) are aggregated to " -"generate a new tree model." +"parallel trees for the current and previous model by calling :code:" +"`_get_tree_nums`. Then, the fetched information will be aggregated. After " +"that, the trees (containing model weights) are aggregated to generate a new " +"tree model." msgstr "" #: ../../source/tutorial-quickstart-xgboost.rst:518 @@ -20557,16 +20881,16 @@ msgstr "" #: ../../source/tutorial-quickstart-xgboost.rst:585 msgid "" "Congratulations! You've successfully built and run your first federated " -"XGBoost system. The AUC values can be checked in " -":code:`metrics_distributed`. One can see that the average AUC increases " -"over FL rounds." +"XGBoost system. The AUC values can be checked in :code:" +"`metrics_distributed`. One can see that the average AUC increases over FL " +"rounds." msgstr "" #: ../../source/tutorial-quickstart-xgboost.rst:590 msgid "" -"The full `source code `_ for this example can be found in :code:`examples" -"/xgboost-quickstart`." +"The full `source code `_ for this example can be found in :code:`examples/" +"xgboost-quickstart`." msgstr "" #: ../../source/tutorial-quickstart-xgboost.rst:594 @@ -20575,15 +20899,15 @@ msgstr "" #: ../../source/tutorial-quickstart-xgboost.rst:596 msgid "" -"Now that you have known how federated XGBoost work with Flower, it's time" -" to run some more comprehensive experiments by customising the " -"experimental settings. In the xgboost-comprehensive example (`full code " -"`_), we provide more options to define various experimental" -" setups, including aggregation strategies, data partitioning and " -"centralised/distributed evaluation. We also support :doc:`Flower " -"simulation ` making it easy to simulate large " -"client cohorts in a resource-aware manner. Let's take a look!" +"Now that you have known how federated XGBoost work with Flower, it's time to " +"run some more comprehensive experiments by customising the experimental " +"settings. In the xgboost-comprehensive example (`full code `_), we provide " +"more options to define various experimental setups, including aggregation " +"strategies, data partitioning and centralised/distributed evaluation. We " +"also support :doc:`Flower simulation ` making it " +"easy to simulate large client cohorts in a resource-aware manner. Let's take " +"a look!" msgstr "" #: ../../source/tutorial-quickstart-xgboost.rst:603 @@ -20592,41 +20916,40 @@ msgstr "" #: ../../source/tutorial-quickstart-xgboost.rst:605 msgid "" -"In addition to bagging aggregation, we offer a cyclic training scheme, " -"which performs FL in a client-by-client fashion. Instead of aggregating " -"multiple clients, there is only one single client participating in the " -"training per round in the cyclic training scenario. The trained local " -"XGBoost trees will be passed to the next client as an initialised model " -"for next round's boosting." +"In addition to bagging aggregation, we offer a cyclic training scheme, which " +"performs FL in a client-by-client fashion. Instead of aggregating multiple " +"clients, there is only one single client participating in the training per " +"round in the cyclic training scenario. The trained local XGBoost trees will " +"be passed to the next client as an initialised model for next round's " +"boosting." msgstr "" #: ../../source/tutorial-quickstart-xgboost.rst:609 msgid "" -"To do this, we first customise a :code:`ClientManager` in " -":code:`server_utils.py`:" +"To do this, we first customise a :code:`ClientManager` in :code:" +"`server_utils.py`:" msgstr "" #: ../../source/tutorial-quickstart-xgboost.rst:649 msgid "" -"The customised :code:`ClientManager` samples all available clients in " -"each FL round based on the order of connection to the server. Then, we " -"define a new strategy :code:`FedXgbCyclic` in " -":code:`flwr.server.strategy.fedxgb_cyclic.py`, in order to sequentially " -"select only one client in given round and pass the received model to next" -" client." +"The customised :code:`ClientManager` samples all available clients in each " +"FL round based on the order of connection to the server. Then, we define a " +"new strategy :code:`FedXgbCyclic` in :code:`flwr.server.strategy." +"fedxgb_cyclic.py`, in order to sequentially select only one client in given " +"round and pass the received model to next client." msgstr "" #: ../../source/tutorial-quickstart-xgboost.rst:690 msgid "" "Unlike the original :code:`FedAvg`, we don't perform aggregation here. " -"Instead, we just make a copy of the received client model as global model" -" by overriding :code:`aggregate_fit`." +"Instead, we just make a copy of the received client model as global model by " +"overriding :code:`aggregate_fit`." msgstr "" #: ../../source/tutorial-quickstart-xgboost.rst:693 msgid "" -"Also, the customised :code:`configure_fit` and :code:`configure_evaluate`" -" methods ensure the clients to be sequentially selected given FL round:" +"Also, the customised :code:`configure_fit` and :code:`configure_evaluate` " +"methods ensure the clients to be sequentially selected given FL round:" msgstr "" #: ../../source/tutorial-quickstart-xgboost.rst:757 @@ -20635,11 +20958,11 @@ msgstr "" #: ../../source/tutorial-quickstart-xgboost.rst:759 msgid "" -"In :code:`dataset.py`, we have a function :code:`instantiate_partitioner`" -" to instantiate the data partitioner based on the given " -":code:`num_partitions` and :code:`partitioner_type`. Currently, we " -"provide four supported partitioner type to simulate the uniformity/non-" -"uniformity in data quantity (uniform, linear, square, exponential)." +"In :code:`dataset.py`, we have a function :code:`instantiate_partitioner` to " +"instantiate the data partitioner based on the given :code:`num_partitions` " +"and :code:`partitioner_type`. Currently, we provide four supported " +"partitioner type to simulate the uniformity/non-uniformity in data quantity " +"(uniform, linear, square, exponential)." msgstr "" #: ../../source/tutorial-quickstart-xgboost.rst:790 @@ -20648,23 +20971,23 @@ msgstr "" #: ../../source/tutorial-quickstart-xgboost.rst:792 msgid "" -"To facilitate centralised evaluation, we define a function in " -":code:`server_utils.py`:" +"To facilitate centralised evaluation, we define a function in :code:" +"`server_utils.py`:" msgstr "" #: ../../source/tutorial-quickstart-xgboost.rst:824 msgid "" -"This function returns a evaluation function which instantiates a " -":code:`Booster` object and loads the global model weights to it. The " -"evaluation is conducted by calling :code:`eval_set()` method, and the " -"tested AUC value is reported." +"This function returns a evaluation function which instantiates a :code:" +"`Booster` object and loads the global model weights to it. The evaluation is " +"conducted by calling :code:`eval_set()` method, and the tested AUC value is " +"reported." msgstr "" #: ../../source/tutorial-quickstart-xgboost.rst:827 msgid "" -"As for distributed evaluation on the clients, it's same as the quick-" -"start example by overriding the :code:`evaluate()` method insides the " -":code:`XgbClient` class in :code:`client_utils.py`." +"As for distributed evaluation on the clients, it's same as the quick-start " +"example by overriding the :code:`evaluate()` method insides the :code:" +"`XgbClient` class in :code:`client_utils.py`." msgstr "" #: ../../source/tutorial-quickstart-xgboost.rst:831 @@ -20674,21 +20997,21 @@ msgstr "" #: ../../source/tutorial-quickstart-xgboost.rst:832 msgid "" "We also provide an example code (:code:`sim.py`) to use the simulation " -"capabilities of Flower to simulate federated XGBoost training on either a" -" single machine or a cluster of machines." +"capabilities of Flower to simulate federated XGBoost training on either a " +"single machine or a cluster of machines." msgstr "" #: ../../source/tutorial-quickstart-xgboost.rst:866 msgid "" -"After importing all required packages, we define a :code:`main()` " -"function to perform the simulation process:" +"After importing all required packages, we define a :code:`main()` function " +"to perform the simulation process:" msgstr "" #: ../../source/tutorial-quickstart-xgboost.rst:921 msgid "" "We first load the dataset and perform data partitioning, and the pre-" -"processed data is stored in a :code:`list`. After the simulation begins, " -"the clients won't need to pre-process their partitions again." +"processed data is stored in a :code:`list`. After the simulation begins, the " +"clients won't need to pre-process their partitions again." msgstr "" #: ../../source/tutorial-quickstart-xgboost.rst:924 @@ -20697,8 +21020,8 @@ msgstr "" #: ../../source/tutorial-quickstart-xgboost.rst:975 msgid "" -"After that, we start the simulation by calling " -":code:`fl.simulation.start_simulation`:" +"After that, we start the simulation by calling :code:`fl.simulation." +"start_simulation`:" msgstr "" #: ../../source/tutorial-quickstart-xgboost.rst:995 @@ -20713,18 +21036,18 @@ msgstr "" #: ../../source/tutorial-quickstart-xgboost.rst:1040 msgid "" -"In :code:`utils.py`, we define the arguments parsers for clients, server " -"and simulation, allowing users to specify different experimental " -"settings. Let's first see the sever side:" +"In :code:`utils.py`, we define the arguments parsers for clients, server and " +"simulation, allowing users to specify different experimental settings. Let's " +"first see the sever side:" msgstr "" #: ../../source/tutorial-quickstart-xgboost.rst:1086 msgid "" "This allows user to specify training strategies / the number of total " -"clients / FL rounds / participating clients / clients for evaluation, and" -" evaluation fashion. Note that with :code:`--centralised-eval`, the sever" -" will do centralised evaluation and all functionalities for client " -"evaluation will be disabled." +"clients / FL rounds / participating clients / clients for evaluation, and " +"evaluation fashion. Note that with :code:`--centralised-eval`, the sever " +"will do centralised evaluation and all functionalities for client evaluation " +"will be disabled." msgstr "" #: ../../source/tutorial-quickstart-xgboost.rst:1090 @@ -20733,11 +21056,10 @@ msgstr "" #: ../../source/tutorial-quickstart-xgboost.rst:1144 msgid "" -"This defines various options for client data partitioning. Besides, " -"clients also have an option to conduct evaluation on centralised test set" -" by setting :code:`--centralised-eval`, as well as an option to perform " -"scaled learning rate based on the number of clients by setting :code" -":`--scaled-lr`." +"This defines various options for client data partitioning. Besides, clients " +"also have an option to conduct evaluation on centralised test set by " +"setting :code:`--centralised-eval`, as well as an option to perform scaled " +"learning rate based on the number of clients by setting :code:`--scaled-lr`." msgstr "" #: ../../source/tutorial-quickstart-xgboost.rst:1148 @@ -20754,9 +21076,9 @@ msgstr "" #: ../../source/tutorial-quickstart-xgboost.rst:1231 msgid "" -"To run a centralised evaluated experiment with bagging strategy on 5 " -"clients with exponential distribution for 50 rounds, we first start the " -"server as below:" +"To run a centralised evaluated experiment with bagging strategy on 5 clients " +"with exponential distribution for 50 rounds, we first start the server as " +"below:" msgstr "" #: ../../source/tutorial-quickstart-xgboost.rst:1238 @@ -20769,9 +21091,9 @@ msgstr "" #: ../../source/tutorial-quickstart-xgboost.rst:1250 msgid "" -"The full `code `_ for this comprehensive example can be found in" -" :code:`examples/xgboost-comprehensive`." +"The full `code `_ for this comprehensive example can be found in :code:" +"`examples/xgboost-comprehensive`." msgstr "" #: ../../source/tutorial-series-build-a-strategy-from-scratch-pytorch.ipynb:9 @@ -20782,19 +21104,18 @@ msgstr "" msgid "" "Welcome to the third part of the Flower federated learning tutorial. In " "previous parts of this tutorial, we introduced federated learning with " -"PyTorch and Flower (`part 1 `__) and we learned how strategies " -"can be used to customize the execution on both the server and the clients" -" (`part 2 `__)." +"PyTorch and Flower (`part 1 `__) and we learned how strategies can be " +"used to customize the execution on both the server and the clients (`part 2 " +"`__)." msgstr "" #: ../../source/tutorial-series-build-a-strategy-from-scratch-pytorch.ipynb:13 msgid "" -"In this notebook, we'll continue to customize the federated learning " -"system we built previously by creating a custom version of FedAvg (again," -" using `Flower `__ and `PyTorch " -"`__)." +"In this notebook, we'll continue to customize the federated learning system " +"we built previously by creating a custom version of FedAvg (again, using " +"`Flower `__ and `PyTorch `__)." msgstr "" #: ../../source/tutorial-series-build-a-strategy-from-scratch-pytorch.ipynb:15 @@ -20802,11 +21123,11 @@ msgstr "" #: ../../source/tutorial-series-get-started-with-flower-pytorch.ipynb:15 #: ../../source/tutorial-series-use-a-federated-learning-strategy-pytorch.ipynb:15 msgid "" -"`Star Flower on GitHub `__ ⭐️ and join " -"the Flower community on Slack to connect, ask questions, and get help: " -"`Join Slack `__ 🌼 We'd love to hear from " -"you in the ``#introductions`` channel! And if anything is unclear, head " -"over to the ``#questions`` channel." +"`Star Flower on GitHub `__ ⭐️ and join the " +"Flower community on Slack to connect, ask questions, and get help: `Join " +"Slack `__ 🌼 We'd love to hear from you in the " +"``#introductions`` channel! And if anything is unclear, head over to the " +"``#questions`` channel." msgstr "" #: ../../source/tutorial-series-build-a-strategy-from-scratch-pytorch.ipynb:17 @@ -20852,14 +21173,14 @@ msgstr "" #: ../../source/tutorial-series-customize-the-client-pytorch.ipynb:102 #: ../../source/tutorial-series-use-a-federated-learning-strategy-pytorch.ipynb:101 msgid "" -"It is possible to switch to a runtime that has GPU acceleration enabled " -"(on Google Colab: ``Runtime > Change runtime type > Hardware acclerator: " -"GPU > Save``). Note, however, that Google Colab is not always able to " -"offer GPU acceleration. If you see an error related to GPU availability " -"in one of the following sections, consider switching back to CPU-based " -"execution by setting ``DEVICE = torch.device(\"cpu\")``. If the runtime " -"has GPU acceleration enabled, you should see the output ``Training on " -"cuda``, otherwise it'll say ``Training on cpu``." +"It is possible to switch to a runtime that has GPU acceleration enabled (on " +"Google Colab: ``Runtime > Change runtime type > Hardware acclerator: GPU > " +"Save``). Note, however, that Google Colab is not always able to offer GPU " +"acceleration. If you see an error related to GPU availability in one of the " +"following sections, consider switching back to CPU-based execution by " +"setting ``DEVICE = torch.device(\"cpu\")``. If the runtime has GPU " +"acceleration enabled, you should see the output ``Training on cuda``, " +"otherwise it'll say ``Training on cpu``." msgstr "" #: ../../source/tutorial-series-build-a-strategy-from-scratch-pytorch.ipynb:114 @@ -20871,11 +21192,11 @@ msgstr "" #: ../../source/tutorial-series-build-a-strategy-from-scratch-pytorch.ipynb:116 #: ../../source/tutorial-series-use-a-federated-learning-strategy-pytorch.ipynb:116 msgid "" -"Let's now load the CIFAR-10 training and test set, partition them into " -"ten smaller datasets (each split into training and validation set), and " -"wrap everything in their own ``DataLoader``. We introduce a new parameter" -" ``num_clients`` which allows us to call ``load_datasets`` with different" -" numbers of clients." +"Let's now load the CIFAR-10 training and test set, partition them into ten " +"smaller datasets (each split into training and validation set), and wrap " +"everything in their own ``DataLoader``. We introduce a new parameter " +"``num_clients`` which allows us to call ``load_datasets`` with different " +"numbers of clients." msgstr "" #: ../../source/tutorial-series-build-a-strategy-from-scratch-pytorch.ipynb:167 @@ -20888,8 +21209,8 @@ msgstr "" #: ../../source/tutorial-series-customize-the-client-pytorch.ipynb:170 #: ../../source/tutorial-series-use-a-federated-learning-strategy-pytorch.ipynb:169 msgid "" -"Let's continue with the usual model definition (including " -"``set_parameters`` and ``get_parameters``), training and test functions:" +"Let's continue with the usual model definition (including ``set_parameters`` " +"and ``get_parameters``), training and test functions:" msgstr "" #: ../../source/tutorial-series-build-a-strategy-from-scratch-pytorch.ipynb:258 @@ -20900,10 +21221,10 @@ msgstr "" #: ../../source/tutorial-series-build-a-strategy-from-scratch-pytorch.ipynb:260 #: ../../source/tutorial-series-use-a-federated-learning-strategy-pytorch.ipynb:260 msgid "" -"To implement the Flower client, we (again) create a subclass of " -"``flwr.client.NumPyClient`` and implement the three methods " -"``get_parameters``, ``fit``, and ``evaluate``. Here, we also pass the " -"``cid`` to the client and use it log additional details:" +"To implement the Flower client, we (again) create a subclass of ``flwr." +"client.NumPyClient`` and implement the three methods ``get_parameters``, " +"``fit``, and ``evaluate``. Here, we also pass the ``cid`` to the client and " +"use it log additional details:" msgstr "" #: ../../source/tutorial-series-build-a-strategy-from-scratch-pytorch.ipynb:308 @@ -20916,11 +21237,11 @@ msgstr "" #: ../../source/tutorial-series-build-a-strategy-from-scratch-pytorch.ipynb:341 msgid "" -"Let’s overwrite the ``configure_fit`` method such that it passes a higher" -" learning rate (potentially also other hyperparameters) to the optimizer " -"of a fraction of the clients. We will keep the sampling of the clients as" -" it is in ``FedAvg`` and then change the configuration dictionary (one of" -" the ``FitIns`` attributes)." +"Let’s overwrite the ``configure_fit`` method such that it passes a higher " +"learning rate (potentially also other hyperparameters) to the optimizer of a " +"fraction of the clients. We will keep the sampling of the clients as it is " +"in ``FedAvg`` and then change the configuration dictionary (one of the " +"``FitIns`` attributes)." msgstr "" #: ../../source/tutorial-series-build-a-strategy-from-scratch-pytorch.ipynb:507 @@ -20937,13 +21258,13 @@ msgstr "" #: ../../source/tutorial-series-build-a-strategy-from-scratch-pytorch.ipynb:536 msgid "" -"In this notebook, we’ve seen how to implement a custom strategy. A custom" -" strategy enables granular control over client node configuration, result" -" aggregation, and more. To define a custom strategy, you only have to " -"overwrite the abstract methods of the (abstract) base class ``Strategy``." -" To make custom strategies even more powerful, you can pass custom " -"functions to the constructor of your new class (``__init__``) and then " -"call these functions whenever needed." +"In this notebook, we’ve seen how to implement a custom strategy. A custom " +"strategy enables granular control over client node configuration, result " +"aggregation, and more. To define a custom strategy, you only have to " +"overwrite the abstract methods of the (abstract) base class ``Strategy``. To " +"make custom strategies even more powerful, you can pass custom functions to " +"the constructor of your new class (``__init__``) and then call these " +"functions whenever needed." msgstr "" #: ../../source/tutorial-series-build-a-strategy-from-scratch-pytorch.ipynb:550 @@ -20952,8 +21273,8 @@ msgstr "" #: ../../source/tutorial-series-use-a-federated-learning-strategy-pytorch.ipynb:715 #: ../../source/tutorial-series-what-is-federated-learning.ipynb:369 msgid "" -"Before you continue, make sure to join the Flower community on Slack: " -"`Join Slack `__" +"Before you continue, make sure to join the Flower community on Slack: `Join " +"Slack `__" msgstr "" #: ../../source/tutorial-series-build-a-strategy-from-scratch-pytorch.ipynb:552 @@ -20962,16 +21283,15 @@ msgstr "" #: ../../source/tutorial-series-use-a-federated-learning-strategy-pytorch.ipynb:717 #: ../../source/tutorial-series-what-is-federated-learning.ipynb:371 msgid "" -"There's a dedicated ``#questions`` channel if you need help, but we'd " -"also love to hear who you are in ``#introductions``!" +"There's a dedicated ``#questions`` channel if you need help, but we'd also " +"love to hear who you are in ``#introductions``!" msgstr "" #: ../../source/tutorial-series-build-a-strategy-from-scratch-pytorch.ipynb:554 msgid "" -"The `Flower Federated Learning Tutorial - Part 4 " -"`__ introduces ``Client``, the flexible API underlying " -"``NumPyClient``." +"The `Flower Federated Learning Tutorial - Part 4 `__ introduces " +"``Client``, the flexible API underlying ``NumPyClient``." msgstr "" #: ../../source/tutorial-series-customize-the-client-pytorch.ipynb:9 @@ -20980,26 +21300,26 @@ msgstr "" #: ../../source/tutorial-series-customize-the-client-pytorch.ipynb:11 msgid "" -"Welcome to the fourth part of the Flower federated learning tutorial. In " -"the previous parts of this tutorial, we introduced federated learning " -"with PyTorch and Flower (`part 1 `__), we learned how " -"strategies can be used to customize the execution on both the server and " -"the clients (`part 2 `__), and we built our own " -"custom strategy from scratch (`part 3 `__)." +"Welcome to the fourth part of the Flower federated learning tutorial. In the " +"previous parts of this tutorial, we introduced federated learning with " +"PyTorch and Flower (`part 1 `__), we learned how strategies can be used " +"to customize the execution on both the server and the clients (`part 2 " +"`__), and we built our own custom strategy from scratch (`part " +"3 `__)." msgstr "" #: ../../source/tutorial-series-customize-the-client-pytorch.ipynb:14 msgid "" -"In this notebook, we revisit ``NumPyClient`` and introduce a new " -"baseclass for building clients, simply named ``Client``. In previous " -"parts of this tutorial, we've based our client on ``NumPyClient``, a " -"convenience class which makes it easy to work with machine learning " -"libraries that have good NumPy interoperability. With ``Client``, we gain" -" a lot of flexibility that we didn't have before, but we'll also have to " -"do a few things the we didn't have to do before." +"In this notebook, we revisit ``NumPyClient`` and introduce a new baseclass " +"for building clients, simply named ``Client``. In previous parts of this " +"tutorial, we've based our client on ``NumPyClient``, a convenience class " +"which makes it easy to work with machine learning libraries that have good " +"NumPy interoperability. With ``Client``, we gain a lot of flexibility that " +"we didn't have before, but we'll also have to do a few things the we didn't " +"have to do before." msgstr "" #: ../../source/tutorial-series-customize-the-client-pytorch.ipynb:18 @@ -21015,9 +21335,9 @@ msgstr "" #: ../../source/tutorial-series-customize-the-client-pytorch.ipynb:117 msgid "" -"Let's now load the CIFAR-10 training and test set, partition them into " -"ten smaller datasets (each split into training and validation set), and " -"wrap everything in their own ``DataLoader``." +"Let's now load the CIFAR-10 training and test set, partition them into ten " +"smaller datasets (each split into training and validation set), and wrap " +"everything in their own ``DataLoader``." msgstr "" #: ../../source/tutorial-series-customize-the-client-pytorch.ipynb:259 @@ -21026,10 +21346,10 @@ msgstr "" #: ../../source/tutorial-series-customize-the-client-pytorch.ipynb:261 msgid "" -"So far, we've implemented our client by subclassing " -"``flwr.client.NumPyClient``. The three methods we implemented are " -"``get_parameters``, ``fit``, and ``evaluate``. Finally, we wrap the " -"creation of instances of this class in a function called ``client_fn``:" +"So far, we've implemented our client by subclassing ``flwr.client." +"NumPyClient``. The three methods we implemented are ``get_parameters``, " +"``fit``, and ``evaluate``. Finally, we wrap the creation of instances of " +"this class in a function called ``client_fn``:" msgstr "" #: ../../source/tutorial-series-customize-the-client-pytorch.ipynb:309 @@ -21051,25 +21371,24 @@ msgid "" "Let's dive a little bit deeper and discuss how Flower executes this " "simulation. Whenever a client is selected to do some work, " "``start_simulation`` calls the function ``numpyclient_fn`` to create an " -"instance of our ``FlowerNumPyClient`` (along with loading the model and " -"the data)." +"instance of our ``FlowerNumPyClient`` (along with loading the model and the " +"data)." msgstr "" #: ../../source/tutorial-series-customize-the-client-pytorch.ipynb:343 msgid "" "But here's the perhaps surprising part: Flower doesn't actually use the " -"``FlowerNumPyClient`` object directly. Instead, it wraps the object to " -"makes it look like a subclass of ``flwr.client.Client``, not " -"``flwr.client.NumPyClient``. In fact, the Flower core framework doesn't " -"know how to handle ``NumPyClient``'s, it only knows how to handle " -"``Client``'s. ``NumPyClient`` is just a convenience abstraction built on " -"top of ``Client``." +"``FlowerNumPyClient`` object directly. Instead, it wraps the object to makes " +"it look like a subclass of ``flwr.client.Client``, not ``flwr.client." +"NumPyClient``. In fact, the Flower core framework doesn't know how to handle " +"``NumPyClient``'s, it only knows how to handle ``Client``'s. ``NumPyClient`` " +"is just a convenience abstraction built on top of ``Client``." msgstr "" #: ../../source/tutorial-series-customize-the-client-pytorch.ipynb:345 msgid "" -"Instead of building on top of ``NumPyClient``, we can directly build on " -"top of ``Client``." +"Instead of building on top of ``NumPyClient``, we can directly build on top " +"of ``Client``." msgstr "" #: ../../source/tutorial-series-customize-the-client-pytorch.ipynb:357 @@ -21078,14 +21397,13 @@ msgstr "" #: ../../source/tutorial-series-customize-the-client-pytorch.ipynb:359 msgid "" -"Let's try to do the same thing using ``Client`` instead of " -"``NumPyClient``." +"Let's try to do the same thing using ``Client`` instead of ``NumPyClient``." msgstr "" #: ../../source/tutorial-series-customize-the-client-pytorch.ipynb:465 msgid "" -"Before we discuss the code in more detail, let's try to run it! Gotta " -"make sure our new ``Client``-based client works, right?" +"Before we discuss the code in more detail, let's try to run it! Gotta make " +"sure our new ``Client``-based client works, right?" msgstr "" #: ../../source/tutorial-series-customize-the-client-pytorch.ipynb:490 @@ -21096,40 +21414,40 @@ msgstr "" #: ../../source/tutorial-series-customize-the-client-pytorch.ipynb:492 msgid "" -"First of all, it's more code. But why? The difference comes from the fact" -" that ``Client`` expects us to take care of parameter serialization and " -"deserialization. For Flower to be able to send parameters over the " -"network, it eventually needs to turn these parameters into ``bytes``. " -"Turning parameters (e.g., NumPy ``ndarray``'s) into raw bytes is called " +"First of all, it's more code. But why? The difference comes from the fact " +"that ``Client`` expects us to take care of parameter serialization and " +"deserialization. For Flower to be able to send parameters over the network, " +"it eventually needs to turn these parameters into ``bytes``. Turning " +"parameters (e.g., NumPy ``ndarray``'s) into raw bytes is called " "serialization. Turning raw bytes into something more useful (like NumPy " -"``ndarray``'s) is called deserialization. Flower needs to do both: it " -"needs to serialize parameters on the server-side and send them to the " -"client, the client needs to deserialize them to use them for local " -"training, and then serialize the updated parameters again to send them " -"back to the server, which (finally!) deserializes them again in order to " -"aggregate them with the updates received from other clients." +"``ndarray``'s) is called deserialization. Flower needs to do both: it needs " +"to serialize parameters on the server-side and send them to the client, the " +"client needs to deserialize them to use them for local training, and then " +"serialize the updated parameters again to send them back to the server, " +"which (finally!) deserializes them again in order to aggregate them with the " +"updates received from other clients." msgstr "" #: ../../source/tutorial-series-customize-the-client-pytorch.ipynb:495 msgid "" "The only *real* difference between Client and NumPyClient is that " -"NumPyClient takes care of serialization and deserialization for you. It " -"can do so because it expects you to return parameters as NumPy ndarray's," -" and it knows how to handle these. This makes working with machine " -"learning libraries that have good NumPy support (most of them) a breeze." +"NumPyClient takes care of serialization and deserialization for you. It can " +"do so because it expects you to return parameters as NumPy ndarray's, and it " +"knows how to handle these. This makes working with machine learning " +"libraries that have good NumPy support (most of them) a breeze." msgstr "" #: ../../source/tutorial-series-customize-the-client-pytorch.ipynb:497 msgid "" -"In terms of API, there's one major difference: all methods in Client take" -" exactly one argument (e.g., ``FitIns`` in ``Client.fit``) and return " -"exactly one value (e.g., ``FitRes`` in ``Client.fit``). The methods in " +"In terms of API, there's one major difference: all methods in Client take " +"exactly one argument (e.g., ``FitIns`` in ``Client.fit``) and return exactly " +"one value (e.g., ``FitRes`` in ``Client.fit``). The methods in " "``NumPyClient`` on the other hand have multiple arguments (e.g., " -"``parameters`` and ``config`` in ``NumPyClient.fit``) and multiple return" -" values (e.g., ``parameters``, ``num_example``, and ``metrics`` in " -"``NumPyClient.fit``) if there are multiple things to handle. These " -"``*Ins`` and ``*Res`` objects in ``Client`` wrap all the individual " -"values you're used to from ``NumPyClient``." +"``parameters`` and ``config`` in ``NumPyClient.fit``) and multiple return " +"values (e.g., ``parameters``, ``num_example``, and ``metrics`` in " +"``NumPyClient.fit``) if there are multiple things to handle. These ``*Ins`` " +"and ``*Res`` objects in ``Client`` wrap all the individual values you're " +"used to from ``NumPyClient``." msgstr "" #: ../../source/tutorial-series-customize-the-client-pytorch.ipynb:510 @@ -21146,17 +21464,16 @@ msgstr "" msgid "" "But first what is serialization? Serialization is just the process of " "converting an object into raw bytes, and equally as important, " -"deserialization is the process of converting raw bytes back into an " -"object. This is very useful for network communication. Indeed, without " +"deserialization is the process of converting raw bytes back into an object. " +"This is very useful for network communication. Indeed, without " "serialization, you could not just a Python object through the internet." msgstr "" #: ../../source/tutorial-series-customize-the-client-pytorch.ipynb:516 msgid "" -"Federated Learning relies heavily on internet communication for training " -"by sending Python objects back and forth between the clients and the " -"server. This means that serialization is an essential part of Federated " -"Learning." +"Federated Learning relies heavily on internet communication for training by " +"sending Python objects back and forth between the clients and the server. " +"This means that serialization is an essential part of Federated Learning." msgstr "" #: ../../source/tutorial-series-customize-the-client-pytorch.ipynb:518 @@ -21176,15 +21493,15 @@ msgstr "" #: ../../source/tutorial-series-customize-the-client-pytorch.ipynb:523 msgid "" -"This is where the real serialization/deserialization will happen, " -"especially in ``ndarray_to_sparse_bytes`` for serialization and " +"This is where the real serialization/deserialization will happen, especially " +"in ``ndarray_to_sparse_bytes`` for serialization and " "``sparse_bytes_to_ndarray`` for deserialization." msgstr "" #: ../../source/tutorial-series-customize-the-client-pytorch.ipynb:525 msgid "" -"Note that we imported the ``scipy.sparse`` library in order to convert " -"our arrays." +"Note that we imported the ``scipy.sparse`` library in order to convert our " +"arrays." msgstr "" #: ../../source/tutorial-series-customize-the-client-pytorch.ipynb:613 @@ -21193,30 +21510,28 @@ msgstr "" #: ../../source/tutorial-series-customize-the-client-pytorch.ipynb:615 msgid "" -"To be able to serialize our ``ndarray``\\ s into sparse parameters, we " -"will just have to call our custom functions in our " -"``flwr.client.Client``." +"To be able to serialize our ``ndarray``\\ s into sparse parameters, we will " +"just have to call our custom functions in our ``flwr.client.Client``." msgstr "" #: ../../source/tutorial-series-customize-the-client-pytorch.ipynb:617 msgid "" "Indeed, in ``get_parameters`` we need to serialize the parameters we got " -"from our network using our custom ``ndarrays_to_sparse_parameters`` " -"defined above." +"from our network using our custom ``ndarrays_to_sparse_parameters`` defined " +"above." msgstr "" #: ../../source/tutorial-series-customize-the-client-pytorch.ipynb:619 msgid "" "In ``fit``, we first need to deserialize the parameters coming from the " -"server using our custom ``sparse_parameters_to_ndarrays`` and then we " -"need to serialize our local results with " -"``ndarrays_to_sparse_parameters``." +"server using our custom ``sparse_parameters_to_ndarrays`` and then we need " +"to serialize our local results with ``ndarrays_to_sparse_parameters``." msgstr "" #: ../../source/tutorial-series-customize-the-client-pytorch.ipynb:621 msgid "" -"In ``evaluate``, we will only need to deserialize the global parameters " -"with our custom function." +"In ``evaluate``, we will only need to deserialize the global parameters with " +"our custom function." msgstr "" #: ../../source/tutorial-series-customize-the-client-pytorch.ipynb:725 @@ -21225,11 +21540,10 @@ msgstr "" #: ../../source/tutorial-series-customize-the-client-pytorch.ipynb:727 msgid "" -"For this example, we will just use ``FedAvg`` as a strategy. To change " -"the serialization and deserialization here, we only need to reimplement " -"the ``evaluate`` and ``aggregate_fit`` functions of ``FedAvg``. The other" -" functions of the strategy will be inherited from the super class " -"``FedAvg``." +"For this example, we will just use ``FedAvg`` as a strategy. To change the " +"serialization and deserialization here, we only need to reimplement the " +"``evaluate`` and ``aggregate_fit`` functions of ``FedAvg``. The other " +"functions of the strategy will be inherited from the super class ``FedAvg``." msgstr "" #: ../../source/tutorial-series-customize-the-client-pytorch.ipynb:729 @@ -21254,19 +21568,19 @@ msgstr "" msgid "" "In this part of the tutorial, we've seen how we can build clients by " "subclassing either ``NumPyClient`` or ``Client``. ``NumPyClient`` is a " -"convenience abstraction that makes it easier to work with machine " -"learning libraries that have good NumPy interoperability. ``Client`` is a" -" more flexible abstraction that allows us to do things that are not " -"possible in ``NumPyClient``. In order to do so, it requires us to handle " -"parameter serialization and deserialization ourselves." +"convenience abstraction that makes it easier to work with machine learning " +"libraries that have good NumPy interoperability. ``Client`` is a more " +"flexible abstraction that allows us to do things that are not possible in " +"``NumPyClient``. In order to do so, it requires us to handle parameter " +"serialization and deserialization ourselves." msgstr "" #: ../../source/tutorial-series-customize-the-client-pytorch.ipynb:952 msgid "" -"This is the final part of the Flower tutorial (for now!), " -"congratulations! You're now well equipped to understand the rest of the " -"documentation. There are many topics we didn't cover in the tutorial, we " -"recommend the following resources:" +"This is the final part of the Flower tutorial (for now!), congratulations! " +"You're now well equipped to understand the rest of the documentation. There " +"are many topics we didn't cover in the tutorial, we recommend the following " +"resources:" msgstr "" #: ../../source/tutorial-series-customize-the-client-pytorch.ipynb:954 @@ -21275,20 +21589,20 @@ msgstr "" #: ../../source/tutorial-series-customize-the-client-pytorch.ipynb:955 msgid "" -"`Check out Flower Code Examples " -"`__" +"`Check out Flower Code Examples `__" msgstr "" #: ../../source/tutorial-series-customize-the-client-pytorch.ipynb:956 msgid "" -"`Use Flower Baselines for your research " -"`__" +"`Use Flower Baselines for your research `__" msgstr "" #: ../../source/tutorial-series-customize-the-client-pytorch.ipynb:957 msgid "" -"`Watch Flower Summit 2023 videos `__" +"`Watch Flower Summit 2023 videos `__" msgstr "" #: ../../source/tutorial-series-get-started-with-flower-pytorch.ipynb:9 @@ -21303,10 +21617,9 @@ msgstr "" #: ../../source/tutorial-series-get-started-with-flower-pytorch.ipynb:13 msgid "" "In this notebook, we'll build a federated learning system using Flower, " -"`Flower Datasets `__ and PyTorch. In " -"part 1, we use PyTorch for the model training pipeline and data loading. " -"In part 2, we continue to federate the PyTorch-based pipeline using " -"Flower." +"`Flower Datasets `__ and PyTorch. In part " +"1, we use PyTorch for the model training pipeline and data loading. In part " +"2, we continue to federate the PyTorch-based pipeline using Flower." msgstr "" #: ../../source/tutorial-series-get-started-with-flower-pytorch.ipynb:17 @@ -21323,20 +21636,19 @@ msgstr "" #: ../../source/tutorial-series-get-started-with-flower-pytorch.ipynb:45 msgid "" "Next, we install the necessary packages for PyTorch (``torch`` and " -"``torchvision``), Flower Datasets (``flwr-datasets``) and Flower " -"(``flwr``):" +"``torchvision``), Flower Datasets (``flwr-datasets``) and Flower (``flwr``):" msgstr "" #: ../../source/tutorial-series-get-started-with-flower-pytorch.ipynb:105 msgid "" -"It is possible to switch to a runtime that has GPU acceleration enabled " -"(on Google Colab: ``Runtime > Change runtime type > Hardware accelerator:" -" GPU > Save``). Note, however, that Google Colab is not always able to " -"offer GPU acceleration. If you see an error related to GPU availability " -"in one of the following sections, consider switching back to CPU-based " -"execution by setting ``DEVICE = torch.device(\"cpu\")``. If the runtime " -"has GPU acceleration enabled, you should see the output ``Training on " -"cuda``, otherwise it'll say ``Training on cpu``." +"It is possible to switch to a runtime that has GPU acceleration enabled (on " +"Google Colab: ``Runtime > Change runtime type > Hardware accelerator: GPU > " +"Save``). Note, however, that Google Colab is not always able to offer GPU " +"acceleration. If you see an error related to GPU availability in one of the " +"following sections, consider switching back to CPU-based execution by " +"setting ``DEVICE = torch.device(\"cpu\")``. If the runtime has GPU " +"acceleration enabled, you should see the output ``Training on cuda``, " +"otherwise it'll say ``Training on cpu``." msgstr "" #: ../../source/tutorial-series-get-started-with-flower-pytorch.ipynb:118 @@ -21345,51 +21657,50 @@ msgstr "" #: ../../source/tutorial-series-get-started-with-flower-pytorch.ipynb:120 msgid "" -"Federated learning can be applied to many different types of tasks across" -" different domains. In this tutorial, we introduce federated learning by " -"training a simple convolutional neural network (CNN) on the popular " -"CIFAR-10 dataset. CIFAR-10 can be used to train image classifiers that " -"distinguish between images from ten different classes: 'airplane', " -"'automobile', 'bird', 'cat', 'deer', 'dog', 'frog', 'horse', 'ship', and " -"'truck'." +"Federated learning can be applied to many different types of tasks across " +"different domains. In this tutorial, we introduce federated learning by " +"training a simple convolutional neural network (CNN) on the popular CIFAR-10 " +"dataset. CIFAR-10 can be used to train image classifiers that distinguish " +"between images from ten different classes: 'airplane', 'automobile', 'bird', " +"'cat', 'deer', 'dog', 'frog', 'horse', 'ship', and 'truck'." msgstr "" #: ../../source/tutorial-series-get-started-with-flower-pytorch.ipynb:131 msgid "" "We simulate having multiple datasets from multiple organizations (also " -"called the \"cross-silo\" setting in federated learning) by splitting the" -" original CIFAR-10 dataset into multiple partitions. Each partition will " -"represent the data from a single organization. We're doing this purely " -"for experimentation purposes, in the real world there's no need for data " -"splitting because each organization already has their own data (so the " -"data is naturally partitioned)." +"called the \"cross-silo\" setting in federated learning) by splitting the " +"original CIFAR-10 dataset into multiple partitions. Each partition will " +"represent the data from a single organization. We're doing this purely for " +"experimentation purposes, in the real world there's no need for data " +"splitting because each organization already has their own data (so the data " +"is naturally partitioned)." msgstr "" #: ../../source/tutorial-series-get-started-with-flower-pytorch.ipynb:133 msgid "" -"Each organization will act as a client in the federated learning system. " -"So having ten organizations participate in a federation means having ten " +"Each organization will act as a client in the federated learning system. So " +"having ten organizations participate in a federation means having ten " "clients connected to the federated learning server." msgstr "" #: ../../source/tutorial-series-get-started-with-flower-pytorch.ipynb:144 msgid "" "Let's now create the Federated Dataset abstraction that from ``flwr-" -"datasets`` that partitions the CIFAR-10. We will create small training " -"and test set for each edge device and wrap each of them into a PyTorch " +"datasets`` that partitions the CIFAR-10. We will create small training and " +"test set for each edge device and wrap each of them into a PyTorch " "``DataLoader``:" msgstr "" #: ../../source/tutorial-series-get-started-with-flower-pytorch.ipynb:198 msgid "" "We now have a list of ten training sets and ten validation sets " -"(``trainloaders`` and ``valloaders``) representing the data of ten " -"different organizations. Each ``trainloader``/``valloader`` pair contains" -" 4000 training examples and 1000 validation examples. There's also a " -"single ``testloader`` (we did not split the test set). Again, this is " -"only necessary for building research or educational systems, actual " -"federated learning systems have their data naturally distributed across " -"multiple partitions." +"(``trainloaders`` and ``valloaders``) representing the data of ten different " +"organizations. Each ``trainloader``/``valloader`` pair contains 4000 " +"training examples and 1000 validation examples. There's also a single " +"``testloader`` (we did not split the test set). Again, this is only " +"necessary for building research or educational systems, actual federated " +"learning systems have their data naturally distributed across multiple " +"partitions." msgstr "" #: ../../source/tutorial-series-get-started-with-flower-pytorch.ipynb:201 @@ -21403,8 +21714,8 @@ msgid "" "The output above shows a random batch of images from the first " "``trainloader`` in our list of ten ``trainloaders``. It also prints the " "labels associated with each image (i.e., one of the ten possible labels " -"we've seen above). If you run the cell again, you should see another " -"batch of images." +"we've seen above). If you run the cell again, you should see another batch " +"of images." msgstr "" #: ../../source/tutorial-series-get-started-with-flower-pytorch.ipynb:252 @@ -21417,8 +21728,8 @@ msgid "" "network. This introduction assumes basic familiarity with PyTorch, so it " "doesn't cover the PyTorch-related aspects in full detail. If you want to " "dive deeper into PyTorch, we recommend `DEEP LEARNING WITH PYTORCH: A 60 " -"MINUTE BLITZ " -"`__." +"MINUTE BLITZ `__." msgstr "" #: ../../source/tutorial-series-get-started-with-flower-pytorch.ipynb:275 @@ -21427,9 +21738,9 @@ msgstr "" #: ../../source/tutorial-series-get-started-with-flower-pytorch.ipynb:277 msgid "" -"We use the simple CNN described in the `PyTorch tutorial " -"`__:" +"We use the simple CNN described in the `PyTorch tutorial `__:" msgstr "" #: ../../source/tutorial-series-get-started-with-flower-pytorch.ipynb:314 @@ -21443,20 +21754,19 @@ msgstr "" #: ../../source/tutorial-series-get-started-with-flower-pytorch.ipynb:376 msgid "" "We now have all the basic building blocks we need: a dataset, a model, a " -"training function, and a test function. Let's put them together to train " -"the model on the dataset of one of our organizations " -"(``trainloaders[0]``). This simulates the reality of most machine " -"learning projects today: each organization has their own data and trains " -"models only on this internal data:" +"training function, and a test function. Let's put them together to train the " +"model on the dataset of one of our organizations (``trainloaders[0]``). This " +"simulates the reality of most machine learning projects today: each " +"organization has their own data and trains models only on this internal data:" msgstr "" #: ../../source/tutorial-series-get-started-with-flower-pytorch.ipynb:406 msgid "" -"Training the simple CNN on our CIFAR-10 split for 5 epochs should result " -"in a test set accuracy of about 41%, which is not good, but at the same " -"time, it doesn't really matter for the purposes of this tutorial. The " -"intent was just to show a simplistic centralized training pipeline that " -"sets the stage for what comes next - federated learning!" +"Training the simple CNN on our CIFAR-10 split for 5 epochs should result in " +"a test set accuracy of about 41%, which is not good, but at the same time, " +"it doesn't really matter for the purposes of this tutorial. The intent was " +"just to show a simplistic centralized training pipeline that sets the stage " +"for what comes next - federated learning!" msgstr "" #: ../../source/tutorial-series-get-started-with-flower-pytorch.ipynb:418 @@ -21465,11 +21775,11 @@ msgstr "" #: ../../source/tutorial-series-get-started-with-flower-pytorch.ipynb:420 msgid "" -"Step 1 demonstrated a simple centralized training pipeline. All data was " -"in one place (i.e., a single ``trainloader`` and a single ``valloader``)." -" Next, we'll simulate a situation where we have multiple datasets in " -"multiple organizations and where we train a model over these " -"organizations using federated learning." +"Step 1 demonstrated a simple centralized training pipeline. All data was in " +"one place (i.e., a single ``trainloader`` and a single ``valloader``). Next, " +"we'll simulate a situation where we have multiple datasets in multiple " +"organizations and where we train a model over these organizations using " +"federated learning." msgstr "" #: ../../source/tutorial-series-get-started-with-flower-pytorch.ipynb:432 @@ -21478,30 +21788,29 @@ msgstr "" #: ../../source/tutorial-series-get-started-with-flower-pytorch.ipynb:434 msgid "" -"In federated learning, the server sends the global model parameters to " -"the client, and the client updates the local model with the parameters " -"received from the server. It then trains the model on the local data " -"(which changes the model parameters locally) and sends the " -"updated/changed model parameters back to the server (or, alternatively, " -"it sends just the gradients back to the server, not the full model " -"parameters)." +"In federated learning, the server sends the global model parameters to the " +"client, and the client updates the local model with the parameters received " +"from the server. It then trains the model on the local data (which changes " +"the model parameters locally) and sends the updated/changed model parameters " +"back to the server (or, alternatively, it sends just the gradients back to " +"the server, not the full model parameters)." msgstr "" #: ../../source/tutorial-series-get-started-with-flower-pytorch.ipynb:436 msgid "" "We need two helper functions to update the local model with parameters " -"received from the server and to get the updated model parameters from the" -" local model: ``set_parameters`` and ``get_parameters``. The following " -"two functions do just that for the PyTorch model above." +"received from the server and to get the updated model parameters from the " +"local model: ``set_parameters`` and ``get_parameters``. The following two " +"functions do just that for the PyTorch model above." msgstr "" #: ../../source/tutorial-series-get-started-with-flower-pytorch.ipynb:438 msgid "" -"The details of how this works are not really important here (feel free to" -" consult the PyTorch documentation if you want to learn more). In " -"essence, we use ``state_dict`` to access PyTorch model parameter tensors." -" The parameter tensors are then converted to/from a list of NumPy " -"ndarray's (which Flower knows how to serialize/deserialize):" +"The details of how this works are not really important here (feel free to " +"consult the PyTorch documentation if you want to learn more). In essence, we " +"use ``state_dict`` to access PyTorch model parameter tensors. The parameter " +"tensors are then converted to/from a list of NumPy ndarray's (which Flower " +"knows how to serialize/deserialize):" msgstr "" #: ../../source/tutorial-series-get-started-with-flower-pytorch.ipynb:466 @@ -21510,19 +21819,18 @@ msgstr "" #: ../../source/tutorial-series-get-started-with-flower-pytorch.ipynb:468 msgid "" -"With that out of the way, let's move on to the interesting part. " -"Federated learning systems consist of a server and multiple clients. In " -"Flower, we create clients by implementing subclasses of " -"``flwr.client.Client`` or ``flwr.client.NumPyClient``. We use " -"``NumPyClient`` in this tutorial because it is easier to implement and " -"requires us to write less boilerplate." +"With that out of the way, let's move on to the interesting part. Federated " +"learning systems consist of a server and multiple clients. In Flower, we " +"create clients by implementing subclasses of ``flwr.client.Client`` or " +"``flwr.client.NumPyClient``. We use ``NumPyClient`` in this tutorial because " +"it is easier to implement and requires us to write less boilerplate." msgstr "" #: ../../source/tutorial-series-get-started-with-flower-pytorch.ipynb:470 msgid "" -"To implement the Flower client, we create a subclass of " -"``flwr.client.NumPyClient`` and implement the three methods " -"``get_parameters``, ``fit``, and ``evaluate``:" +"To implement the Flower client, we create a subclass of ``flwr.client." +"NumPyClient`` and implement the three methods ``get_parameters``, ``fit``, " +"and ``evaluate``:" msgstr "" #: ../../source/tutorial-series-get-started-with-flower-pytorch.ipynb:472 @@ -21532,15 +21840,14 @@ msgstr "" #: ../../source/tutorial-series-get-started-with-flower-pytorch.ipynb:473 msgid "" "``fit``: Receive model parameters from the server, train the model " -"parameters on the local data, and return the (updated) model parameters " -"to the server" +"parameters on the local data, and return the (updated) model parameters to " +"the server" msgstr "" #: ../../source/tutorial-series-get-started-with-flower-pytorch.ipynb:474 msgid "" -"``evaluate``: Receive model parameters from the server, evaluate the " -"model parameters on the local data, and return the evaluation result to " -"the server" +"``evaluate``: Receive model parameters from the server, evaluate the model " +"parameters on the local data, and return the evaluation result to the server" msgstr "" #: ../../source/tutorial-series-get-started-with-flower-pytorch.ipynb:476 @@ -21553,16 +21860,15 @@ msgstr "" #: ../../source/tutorial-series-get-started-with-flower-pytorch.ipynb:513 msgid "" "Our class ``FlowerClient`` defines how local training/evaluation will be " -"performed and allows Flower to call the local training/evaluation through" -" ``fit`` and ``evaluate``. Each instance of ``FlowerClient`` represents a" -" *single client* in our federated learning system. Federated learning " -"systems have multiple clients (otherwise, there's not much to federate), " -"so each client will be represented by its own instance of " -"``FlowerClient``. If we have, for example, three clients in our workload," -" then we'd have three instances of ``FlowerClient``. Flower calls " -"``FlowerClient.fit`` on the respective instance when the server selects a" -" particular client for training (and ``FlowerClient.evaluate`` for " -"evaluation)." +"performed and allows Flower to call the local training/evaluation through " +"``fit`` and ``evaluate``. Each instance of ``FlowerClient`` represents a " +"*single client* in our federated learning system. Federated learning systems " +"have multiple clients (otherwise, there's not much to federate), so each " +"client will be represented by its own instance of ``FlowerClient``. If we " +"have, for example, three clients in our workload, then we'd have three " +"instances of ``FlowerClient``. Flower calls ``FlowerClient.fit`` on the " +"respective instance when the server selects a particular client for training " +"(and ``FlowerClient.evaluate`` for evaluation)." msgstr "" #: ../../source/tutorial-series-get-started-with-flower-pytorch.ipynb:517 @@ -21571,13 +21877,13 @@ msgstr "" #: ../../source/tutorial-series-get-started-with-flower-pytorch.ipynb:519 msgid "" -"In this notebook, we want to simulate a federated learning system with 10" -" clients on a single machine. This means that the server and all 10 " -"clients will live on a single machine and share resources such as CPU, " -"GPU, and memory. Having 10 clients would mean having 10 instances of " -"``FlowerClient`` in memory. Doing this on a single machine can quickly " -"exhaust the available memory resources, even if only a subset of these " -"clients participates in a single round of federated learning." +"In this notebook, we want to simulate a federated learning system with 10 " +"clients on a single machine. This means that the server and all 10 clients " +"will live on a single machine and share resources such as CPU, GPU, and " +"memory. Having 10 clients would mean having 10 instances of ``FlowerClient`` " +"in memory. Doing this on a single machine can quickly exhaust the available " +"memory resources, even if only a subset of these clients participates in a " +"single round of federated learning." msgstr "" #: ../../source/tutorial-series-get-started-with-flower-pytorch.ipynb:521 @@ -21586,14 +21892,14 @@ msgid "" "multiple machines, Flower, therefore, provides special simulation " "capabilities that create ``FlowerClient`` instances only when they are " "actually necessary for training or evaluation. To enable the Flower " -"framework to create clients when necessary, we need to implement a " -"function called ``client_fn`` that creates a ``FlowerClient`` instance on" -" demand. Flower calls ``client_fn`` whenever it needs an instance of one " -"particular client to call ``fit`` or ``evaluate`` (those instances are " -"usually discarded after use, so they should not keep any local state). " -"Clients are identified by a client ID, or short ``cid``. The ``cid`` can " -"be used, for example, to load different local data partitions for " -"different clients, as can be seen below:" +"framework to create clients when necessary, we need to implement a function " +"called ``client_fn`` that creates a ``FlowerClient`` instance on demand. " +"Flower calls ``client_fn`` whenever it needs an instance of one particular " +"client to call ``fit`` or ``evaluate`` (those instances are usually " +"discarded after use, so they should not keep any local state). Clients are " +"identified by a client ID, or short ``cid``. The ``cid`` can be used, for " +"example, to load different local data partitions for different clients, as " +"can be seen below:" msgstr "" #: ../../source/tutorial-series-get-started-with-flower-pytorch.ipynb:556 @@ -21602,31 +21908,31 @@ msgstr "" #: ../../source/tutorial-series-get-started-with-flower-pytorch.ipynb:558 msgid "" -"We now have the class ``FlowerClient`` which defines client-side " -"training/evaluation and ``client_fn`` which allows Flower to create " -"``FlowerClient`` instances whenever it needs to call ``fit`` or " -"``evaluate`` on one particular client. The last step is to start the " -"actual simulation using ``flwr.simulation.start_simulation``." +"We now have the class ``FlowerClient`` which defines client-side training/" +"evaluation and ``client_fn`` which allows Flower to create ``FlowerClient`` " +"instances whenever it needs to call ``fit`` or ``evaluate`` on one " +"particular client. The last step is to start the actual simulation using " +"``flwr.simulation.start_simulation``." msgstr "" #: ../../source/tutorial-series-get-started-with-flower-pytorch.ipynb:560 msgid "" "The function ``start_simulation`` accepts a number of arguments, amongst " -"them the ``client_fn`` used to create ``FlowerClient`` instances, the " -"number of clients to simulate (``num_clients``), the number of federated " -"learning rounds (``num_rounds``), and the strategy. The strategy " -"encapsulates the federated learning approach/algorithm, for example, " -"*Federated Averaging* (FedAvg)." +"them the ``client_fn`` used to create ``FlowerClient`` instances, the number " +"of clients to simulate (``num_clients``), the number of federated learning " +"rounds (``num_rounds``), and the strategy. The strategy encapsulates the " +"federated learning approach/algorithm, for example, *Federated Averaging* " +"(FedAvg)." msgstr "" #: ../../source/tutorial-series-get-started-with-flower-pytorch.ipynb:562 msgid "" "Flower has a number of built-in strategies, but we can also use our own " -"strategy implementations to customize nearly all aspects of the federated" -" learning approach. For this example, we use the built-in ``FedAvg`` " -"implementation and customize it using a few basic parameters. The last " -"step is the actual call to ``start_simulation`` which - you guessed it - " -"starts the simulation:" +"strategy implementations to customize nearly all aspects of the federated " +"learning approach. For this example, we use the built-in ``FedAvg`` " +"implementation and customize it using a few basic parameters. The last step " +"is the actual call to ``start_simulation`` which - you guessed it - starts " +"the simulation:" msgstr "" #: ../../source/tutorial-series-get-started-with-flower-pytorch.ipynb:608 @@ -21640,20 +21946,20 @@ msgstr "" #: ../../source/tutorial-series-get-started-with-flower-pytorch.ipynb:612 #, python-format msgid "" -"When we call ``start_simulation``, we tell Flower that there are 10 " -"clients (``num_clients=10``). Flower then goes ahead an asks the " -"``FedAvg`` strategy to select clients. ``FedAvg`` knows that it should " -"select 100% of the available clients (``fraction_fit=1.0``), so it goes " -"ahead and selects 10 random clients (i.e., 100% of 10)." +"When we call ``start_simulation``, we tell Flower that there are 10 clients " +"(``num_clients=10``). Flower then goes ahead an asks the ``FedAvg`` strategy " +"to select clients. ``FedAvg`` knows that it should select 100% of the " +"available clients (``fraction_fit=1.0``), so it goes ahead and selects 10 " +"random clients (i.e., 100% of 10)." msgstr "" #: ../../source/tutorial-series-get-started-with-flower-pytorch.ipynb:614 msgid "" -"Flower then asks the selected 10 clients to train the model. When the " -"server receives the model parameter updates from the clients, it hands " -"those updates over to the strategy (*FedAvg*) for aggregation. The " -"strategy aggregates those updates and returns the new global model, which" -" then gets used in the next round of federated learning." +"Flower then asks the selected 10 clients to train the model. When the server " +"receives the model parameter updates from the clients, it hands those " +"updates over to the strategy (*FedAvg*) for aggregation. The strategy " +"aggregates those updates and returns the new global model, which then gets " +"used in the next round of federated learning." msgstr "" #: ../../source/tutorial-series-get-started-with-flower-pytorch.ipynb:626 @@ -21662,28 +21968,27 @@ msgstr "" #: ../../source/tutorial-series-get-started-with-flower-pytorch.ipynb:628 msgid "" -"You may have noticed that all metrics except for ``losses_distributed`` " -"are empty. Where did the ``{\"accuracy\": float(accuracy)}`` go?" +"You may have noticed that all metrics except for ``losses_distributed`` are " +"empty. Where did the ``{\"accuracy\": float(accuracy)}`` go?" msgstr "" #: ../../source/tutorial-series-get-started-with-flower-pytorch.ipynb:630 msgid "" -"Flower can automatically aggregate losses returned by individual clients," -" but it cannot do the same for metrics in the generic metrics dictionary " -"(the one with the ``accuracy`` key). Metrics dictionaries can contain " -"very different kinds of metrics and even key/value pairs that are not " -"metrics at all, so the framework does not (and can not) know how to " -"handle these automatically." +"Flower can automatically aggregate losses returned by individual clients, " +"but it cannot do the same for metrics in the generic metrics dictionary (the " +"one with the ``accuracy`` key). Metrics dictionaries can contain very " +"different kinds of metrics and even key/value pairs that are not metrics at " +"all, so the framework does not (and can not) know how to handle these " +"automatically." msgstr "" #: ../../source/tutorial-series-get-started-with-flower-pytorch.ipynb:632 msgid "" -"As users, we need to tell the framework how to handle/aggregate these " -"custom metrics, and we do so by passing metric aggregation functions to " -"the strategy. The strategy will then call these functions whenever it " -"receives fit or evaluate metrics from clients. The two possible functions" -" are ``fit_metrics_aggregation_fn`` and " -"``evaluate_metrics_aggregation_fn``." +"As users, we need to tell the framework how to handle/aggregate these custom " +"metrics, and we do so by passing metric aggregation functions to the " +"strategy. The strategy will then call these functions whenever it receives " +"fit or evaluate metrics from clients. The two possible functions are " +"``fit_metrics_aggregation_fn`` and ``evaluate_metrics_aggregation_fn``." msgstr "" #: ../../source/tutorial-series-get-started-with-flower-pytorch.ipynb:634 @@ -21701,17 +22006,17 @@ msgstr "" #: ../../source/tutorial-series-get-started-with-flower-pytorch.ipynb:697 msgid "" "We now have a full system that performs federated training and federated " -"evaluation. It uses the ``weighted_average`` function to aggregate custom" -" evaluation metrics and calculates a single ``accuracy`` metric across " -"all clients on the server side." +"evaluation. It uses the ``weighted_average`` function to aggregate custom " +"evaluation metrics and calculates a single ``accuracy`` metric across all " +"clients on the server side." msgstr "" #: ../../source/tutorial-series-get-started-with-flower-pytorch.ipynb:699 msgid "" "The other two categories of metrics (``losses_centralized`` and " "``metrics_centralized``) are still empty because they only apply when " -"centralized evaluation is being used. Part two of the Flower tutorial " -"will cover centralized evaluation." +"centralized evaluation is being used. Part two of the Flower tutorial will " +"cover centralized evaluation." msgstr "" #: ../../source/tutorial-series-get-started-with-flower-pytorch.ipynb:711 @@ -21721,28 +22026,28 @@ msgstr "" #: ../../source/tutorial-series-get-started-with-flower-pytorch.ipynb:713 msgid "" -"Congratulations, you just trained a convolutional neural network, " -"federated over 10 clients! With that, you understand the basics of " -"federated learning with Flower. The same approach you've seen can be used" -" with other machine learning frameworks (not just PyTorch) and tasks (not" -" just CIFAR-10 images classification), for example NLP with Hugging Face " -"Transformers or speech with SpeechBrain." +"Congratulations, you just trained a convolutional neural network, federated " +"over 10 clients! With that, you understand the basics of federated learning " +"with Flower. The same approach you've seen can be used with other machine " +"learning frameworks (not just PyTorch) and tasks (not just CIFAR-10 images " +"classification), for example NLP with Hugging Face Transformers or speech " +"with SpeechBrain." msgstr "" #: ../../source/tutorial-series-get-started-with-flower-pytorch.ipynb:715 msgid "" -"In the next notebook, we're going to cover some more advanced concepts. " -"Want to customize your strategy? Initialize parameters on the server " -"side? Or evaluate the aggregated model on the server side? We'll cover " -"all this and more in the next tutorial." +"In the next notebook, we're going to cover some more advanced concepts. Want " +"to customize your strategy? Initialize parameters on the server side? Or " +"evaluate the aggregated model on the server side? We'll cover all this and " +"more in the next tutorial." msgstr "" #: ../../source/tutorial-series-get-started-with-flower-pytorch.ipynb:733 msgid "" -"The `Flower Federated Learning Tutorial - Part 2 " -"`__ goes into more depth about strategies and all " -"the advanced things you can build with them." +"The `Flower Federated Learning Tutorial - Part 2 `__ goes " +"into more depth about strategies and all the advanced things you can build " +"with them." msgstr "" #: ../../source/tutorial-series-use-a-federated-learning-strategy-pytorch.ipynb:9 @@ -21752,16 +22057,16 @@ msgstr "" #: ../../source/tutorial-series-use-a-federated-learning-strategy-pytorch.ipynb:11 msgid "" "Welcome to the next part of the federated learning tutorial. In previous " -"parts of this tutorial, we introduced federated learning with PyTorch and" -" Flower (`part 1 `__)." +"parts of this tutorial, we introduced federated learning with PyTorch and " +"Flower (`part 1 `__)." msgstr "" #: ../../source/tutorial-series-use-a-federated-learning-strategy-pytorch.ipynb:13 msgid "" -"In this notebook, we'll begin to customize the federated learning system " -"we built in the introductory notebook (again, using `Flower " -"`__ and `PyTorch `__)." +"In this notebook, we'll begin to customize the federated learning system we " +"built in the introductory notebook (again, using `Flower `__ and `PyTorch `__)." msgstr "" #: ../../source/tutorial-series-use-a-federated-learning-strategy-pytorch.ipynb:17 @@ -21775,8 +22080,8 @@ msgstr "" #: ../../source/tutorial-series-use-a-federated-learning-strategy-pytorch.ipynb:311 msgid "" "So far, everything should look familiar if you've worked through the " -"introductory notebook. With that, we're ready to introduce a number of " -"new features." +"introductory notebook. With that, we're ready to introduce a number of new " +"features." msgstr "" #: ../../source/tutorial-series-use-a-federated-learning-strategy-pytorch.ipynb:323 @@ -21785,16 +22090,16 @@ msgstr "" #: ../../source/tutorial-series-use-a-federated-learning-strategy-pytorch.ipynb:325 msgid "" -"Flower, by default, initializes the global model by asking one random " -"client for the initial parameters. In many cases, we want more control " -"over parameter initialization though. Flower therefore allows you to " -"directly pass the initial parameters to the Strategy:" +"Flower, by default, initializes the global model by asking one random client " +"for the initial parameters. In many cases, we want more control over " +"parameter initialization though. Flower therefore allows you to directly " +"pass the initial parameters to the Strategy:" msgstr "" #: ../../source/tutorial-series-use-a-federated-learning-strategy-pytorch.ipynb:370 msgid "" -"Passing ``initial_parameters`` to the ``FedAvg`` strategy prevents Flower" -" from asking one of the clients for the initial parameters. If we look " +"Passing ``initial_parameters`` to the ``FedAvg`` strategy prevents Flower " +"from asking one of the clients for the initial parameters. If we look " "closely, we can see that the logs do not show any calls to the " "``FlowerClient.get_parameters`` method." msgstr "" @@ -21805,17 +22110,17 @@ msgstr "" #: ../../source/tutorial-series-use-a-federated-learning-strategy-pytorch.ipynb:384 msgid "" -"We've seen the function ``start_simulation`` before. It accepts a number " -"of arguments, amongst them the ``client_fn`` used to create " -"``FlowerClient`` instances, the number of clients to simulate " -"``num_clients``, the number of rounds ``num_rounds``, and the strategy." +"We've seen the function ``start_simulation`` before. It accepts a number of " +"arguments, amongst them the ``client_fn`` used to create ``FlowerClient`` " +"instances, the number of clients to simulate ``num_clients``, the number of " +"rounds ``num_rounds``, and the strategy." msgstr "" #: ../../source/tutorial-series-use-a-federated-learning-strategy-pytorch.ipynb:386 msgid "" "The strategy encapsulates the federated learning approach/algorithm, for " -"example, ``FedAvg`` or ``FedAdagrad``. Let's try to use a different " -"strategy this time:" +"example, ``FedAvg`` or ``FedAdagrad``. Let's try to use a different strategy " +"this time:" msgstr "" #: ../../source/tutorial-series-use-a-federated-learning-strategy-pytorch.ipynb:424 @@ -21824,9 +22129,9 @@ msgstr "" #: ../../source/tutorial-series-use-a-federated-learning-strategy-pytorch.ipynb:426 msgid "" -"Flower can evaluate the aggregated model on the server-side or on the " -"client-side. Client-side and server-side evaluation are similar in some " -"ways, but different in others." +"Flower can evaluate the aggregated model on the server-side or on the client-" +"side. Client-side and server-side evaluation are similar in some ways, but " +"different in others." msgstr "" #: ../../source/tutorial-series-use-a-federated-learning-strategy-pytorch.ipynb:428 @@ -21834,33 +22139,33 @@ msgid "" "**Centralized Evaluation** (or *server-side evaluation*) is conceptually " "simple: it works the same way that evaluation in centralized machine " "learning does. If there is a server-side dataset that can be used for " -"evaluation purposes, then that's great. We can evaluate the newly " -"aggregated model after each round of training without having to send the " -"model to clients. We're also fortunate in the sense that our entire " -"evaluation dataset is available at all times." +"evaluation purposes, then that's great. We can evaluate the newly aggregated " +"model after each round of training without having to send the model to " +"clients. We're also fortunate in the sense that our entire evaluation " +"dataset is available at all times." msgstr "" #: ../../source/tutorial-series-use-a-federated-learning-strategy-pytorch.ipynb:430 msgid "" -"**Federated Evaluation** (or *client-side evaluation*) is more complex, " -"but also more powerful: it doesn't require a centralized dataset and " -"allows us to evaluate models over a larger set of data, which often " -"yields more realistic evaluation results. In fact, many scenarios require" -" us to use **Federated Evaluation** if we want to get representative " -"evaluation results at all. But this power comes at a cost: once we start " -"to evaluate on the client side, we should be aware that our evaluation " -"dataset can change over consecutive rounds of learning if those clients " -"are not always available. Moreover, the dataset held by each client can " -"also change over consecutive rounds. This can lead to evaluation results " -"that are not stable, so even if we would not change the model, we'd see " -"our evaluation results fluctuate over consecutive rounds." +"**Federated Evaluation** (or *client-side evaluation*) is more complex, but " +"also more powerful: it doesn't require a centralized dataset and allows us " +"to evaluate models over a larger set of data, which often yields more " +"realistic evaluation results. In fact, many scenarios require us to use " +"**Federated Evaluation** if we want to get representative evaluation results " +"at all. But this power comes at a cost: once we start to evaluate on the " +"client side, we should be aware that our evaluation dataset can change over " +"consecutive rounds of learning if those clients are not always available. " +"Moreover, the dataset held by each client can also change over consecutive " +"rounds. This can lead to evaluation results that are not stable, so even if " +"we would not change the model, we'd see our evaluation results fluctuate " +"over consecutive rounds." msgstr "" #: ../../source/tutorial-series-use-a-federated-learning-strategy-pytorch.ipynb:433 msgid "" "We've seen how federated evaluation works on the client side (i.e., by " -"implementing the ``evaluate`` method in ``FlowerClient``). Now let's see " -"how we can evaluate aggregated model parameters on the server-side:" +"implementing the ``evaluate`` method in ``FlowerClient``). Now let's see how " +"we can evaluate aggregated model parameters on the server-side:" msgstr "" #: ../../source/tutorial-series-use-a-federated-learning-strategy-pytorch.ipynb:490 @@ -21869,50 +22174,48 @@ msgstr "" #: ../../source/tutorial-series-use-a-federated-learning-strategy-pytorch.ipynb:492 msgid "" -"In some situations, we want to configure client-side execution (training," -" evaluation) from the server-side. One example for that is the server " -"asking the clients to train for a certain number of local epochs. Flower " -"provides a way to send configuration values from the server to the " -"clients using a dictionary. Let's look at an example where the clients " -"receive values from the server through the ``config`` parameter in " -"``fit`` (``config`` is also available in ``evaluate``). The ``fit`` " -"method receives the configuration dictionary through the ``config`` " -"parameter and can then read values from this dictionary. In this example," -" it reads ``server_round`` and ``local_epochs`` and uses those values to " -"improve the logging and configure the number of local training epochs:" +"In some situations, we want to configure client-side execution (training, " +"evaluation) from the server-side. One example for that is the server asking " +"the clients to train for a certain number of local epochs. Flower provides a " +"way to send configuration values from the server to the clients using a " +"dictionary. Let's look at an example where the clients receive values from " +"the server through the ``config`` parameter in ``fit`` (``config`` is also " +"available in ``evaluate``). The ``fit`` method receives the configuration " +"dictionary through the ``config`` parameter and can then read values from " +"this dictionary. In this example, it reads ``server_round`` and " +"``local_epochs`` and uses those values to improve the logging and configure " +"the number of local training epochs:" msgstr "" #: ../../source/tutorial-series-use-a-federated-learning-strategy-pytorch.ipynb:546 msgid "" -"So how can we send this config dictionary from server to clients? The " -"built-in Flower Strategies provide way to do this, and it works similarly" -" to the way server-side evaluation works. We provide a function to the " -"strategy, and the strategy calls this function for every round of " -"federated learning:" +"So how can we send this config dictionary from server to clients? The built-" +"in Flower Strategies provide way to do this, and it works similarly to the " +"way server-side evaluation works. We provide a function to the strategy, and " +"the strategy calls this function for every round of federated learning:" msgstr "" #: ../../source/tutorial-series-use-a-federated-learning-strategy-pytorch.ipynb:576 msgid "" -"Next, we'll just pass this function to the FedAvg strategy before " -"starting the simulation:" +"Next, we'll just pass this function to the FedAvg strategy before starting " +"the simulation:" msgstr "" #: ../../source/tutorial-series-use-a-federated-learning-strategy-pytorch.ipynb:613 msgid "" -"As we can see, the client logs now include the current round of federated" -" learning (which they read from the ``config`` dictionary). We can also " -"configure local training to run for one epoch during the first and second" -" round of federated learning, and then for two epochs during the third " -"round." +"As we can see, the client logs now include the current round of federated " +"learning (which they read from the ``config`` dictionary). We can also " +"configure local training to run for one epoch during the first and second " +"round of federated learning, and then for two epochs during the third round." msgstr "" #: ../../source/tutorial-series-use-a-federated-learning-strategy-pytorch.ipynb:615 msgid "" "Clients can also return arbitrary values to the server. To do so, they " -"return a dictionary from ``fit`` and/or ``evaluate``. We have seen and " -"used this concept throughout this notebook without mentioning it " -"explicitly: our ``FlowerClient`` returns a dictionary containing a custom" -" key/value pair as the third return value in ``evaluate``." +"return a dictionary from ``fit`` and/or ``evaluate``. We have seen and used " +"this concept throughout this notebook without mentioning it explicitly: our " +"``FlowerClient`` returns a dictionary containing a custom key/value pair as " +"the third return value in ``evaluate``." msgstr "" #: ../../source/tutorial-series-use-a-federated-learning-strategy-pytorch.ipynb:627 @@ -21929,14 +22232,13 @@ msgstr "" #, python-format msgid "" "We now have 1000 partitions, each holding 45 training and 5 validation " -"examples. Given that the number of training examples on each client is " -"quite small, we should probably train the model a bit longer, so we " -"configure the clients to perform 3 local training epochs. We should also " -"adjust the fraction of clients selected for training during each round " -"(we don't want all 1000 clients participating in every round), so we " -"adjust ``fraction_fit`` to ``0.05``, which means that only 5% of " -"available clients (so 50 clients) will be selected for training each " -"round:" +"examples. Given that the number of training examples on each client is quite " +"small, we should probably train the model a bit longer, so we configure the " +"clients to perform 3 local training epochs. We should also adjust the " +"fraction of clients selected for training during each round (we don't want " +"all 1000 clients participating in every round), so we adjust " +"``fraction_fit`` to ``0.05``, which means that only 5% of available clients " +"(so 50 clients) will be selected for training each round:" msgstr "" #: ../../source/tutorial-series-use-a-federated-learning-strategy-pytorch.ipynb:699 @@ -21949,94 +22251,111 @@ msgstr "" #: ../../source/tutorial-series-use-a-federated-learning-strategy-pytorch.ipynb:701 msgid "" -"In the later sections, we've seen how we can communicate arbitrary values" -" between server and clients to fully customize client-side execution. " -"With that capability, we built a large-scale Federated Learning " -"simulation using the Flower Virtual Client Engine and ran an experiment " -"involving 1000 clients in the same workload - all in a Jupyter Notebook!" +"In the later sections, we've seen how we can communicate arbitrary values " +"between server and clients to fully customize client-side execution. With " +"that capability, we built a large-scale Federated Learning simulation using " +"the Flower Virtual Client Engine and ran an experiment involving 1000 " +"clients in the same workload - all in a Jupyter Notebook!" msgstr "" #: ../../source/tutorial-series-use-a-federated-learning-strategy-pytorch.ipynb:719 msgid "" -"The `Flower Federated Learning Tutorial - Part 3 " -"`__ shows how to build a fully custom ``Strategy`` from " -"scratch." +"The `Flower Federated Learning Tutorial - Part 3 `__ shows how " +"to build a fully custom ``Strategy`` from scratch." msgstr "" #: ../../source/tutorial-series-what-is-federated-learning.ipynb:9 msgid "What is Federated Learning?" -msgstr "" +msgstr "연합 학습이란 무엇입니까?" #: ../../source/tutorial-series-what-is-federated-learning.ipynb:13 msgid "" "In this tutorial, you will learn what federated learning is, build your " "first system in Flower, and gradually extend it. If you work through all " -"parts of the tutorial, you will be able to build advanced federated " -"learning systems that approach the current state of the art in the field." +"parts of the tutorial, you will be able to build advanced federated learning " +"systems that approach the current state of the art in the field." msgstr "" +"이 튜토리얼에서 연합 학습이 무엇인지 배우고 Flower로 첫 번째 시스템을 " +"구축하고 점진적으로 확장해 나갈 것입니다. 본 튜토리얼의 모든 부분을 완성할 " +"수 있다면, 당신은 고급 연방 학습 시스템을 구축하여 그 분야의 현재 기술 " +"수준에 접근할 수 있을 것입니다." #: ../../source/tutorial-series-what-is-federated-learning.ipynb:15 msgid "" -"🧑‍🏫 This tutorial starts at zero and expects no familiarity with " -"federated learning. Only a basic understanding of data science and Python" -" programming is assumed." +"🧑‍🏫 This tutorial starts at zero and expects no familiarity with federated " +"learning. Only a basic understanding of data science and Python programming " +"is assumed." msgstr "" +"🧑‍🏫이 튜토리얼은 제로베이부터 시작되며 연방 학습에 상세히 아는 필요가 " +"없습니다. 데이터 과학과 파이썬 프로그래밍에 대한 기본적인 이해만 가정합니다." #: ../../source/tutorial-series-what-is-federated-learning.ipynb:17 msgid "" -"`Star Flower on GitHub `__ ⭐️ and join " -"the open-source Flower community on Slack to connect, ask questions, and " -"get help: `Join Slack `__ 🌼 We'd love to " -"hear from you in the ``#introductions`` channel! And if anything is " -"unclear, head over to the ``#questions`` channel." +"`Star Flower on GitHub `__ ⭐️ and join the " +"open-source Flower community on Slack to connect, ask questions, and get " +"help: `Join Slack `__ 🌼 We'd love to hear " +"from you in the ``#introductions`` channel! And if anything is unclear, head " +"over to the ``#questions`` channel." msgstr "" +"`Star Flower on GitHub `__ ⭐️ Slack의 " +"오픈소스 Flower 커뮤니티에 가입하여 소통하고 질문하고 도움을 받을 수 " +"있습니다: `Slack 가입`__ 🌼 ``#introductions``" +"채널에서 당신의 목소리를 듣고 싶습니다! 궁금한 점이 있으시면``#questions`` " +"채널로 방문해 주시기 바랍니다." #: ../../source/tutorial-series-what-is-federated-learning.ipynb:31 msgid "Classic machine learning" -msgstr "" +msgstr "클래식 머신러닝" #: ../../source/tutorial-series-what-is-federated-learning.ipynb:33 msgid "" -"Before we begin to discuss federated learning, let us quickly recap how " -"most machine learning works today." -msgstr "" +"Before we begin to discuss federated learning, let us quickly recap how most " +"machine learning works today." +msgstr "연방 학습에 대해 논의하기 전에 현재 대부분의 머신러닝이 어떻게 작동하는지 " +"간략히 요약하겠습니다." #: ../../source/tutorial-series-what-is-federated-learning.ipynb:35 msgid "" -"In machine learning, we have a model, and we have data. The model could " -"be a neural network (as depicted here), or something else, like classical" -" linear regression." +"In machine learning, we have a model, and we have data. The model could be a " +"neural network (as depicted here), or something else, like classical linear " +"regression." msgstr "" +"기계 학습에서 우리는 모델과 데이터를 가지고 있습니다.모델은 신경망((그림과 " +"같이))일 수도 있고 고전적인 선형 회귀와 같은 다른 것일 수도 있습니다." #: ../../source/tutorial-series-what-is-federated-learning.ipynb:41 msgid "|93b02017c78049bbbd5ae456dcb2c91b|" -msgstr "" +msgstr "|93b02017c78049bbbd5ae456dcb2c91b|" #: ../../source/tutorial-series-what-is-federated-learning.ipynb:109 msgid "Model and data" -msgstr "" +msgstr "모델과 데이터" #: ../../source/tutorial-series-what-is-federated-learning.ipynb:47 msgid "" -"We train the model using the data to perform a useful task. A task could " -"be to detect objects in images, transcribe an audio recording, or play a " -"game like Go." +"We train the model using the data to perform a useful task. A task could be " +"to detect objects in images, transcribe an audio recording, or play a game " +"like Go." msgstr "" +"우리는 유용한 작업을 수행하기 위해 데이터를 사용하여 모델을 훈련합니다. " +"작업은 이미지 속 물체를 감지하거나 음성 녹음을 기록하거나 바둑과 같은 게임을 " +"하는 것일 수 있습니다." #: ../../source/tutorial-series-what-is-federated-learning.ipynb:53 msgid "|01471150fd5144c080a176b43e92a3ff|" -msgstr "" +msgstr "|01471150fd5144c080a176b43e92a3ff|" #: ../../source/tutorial-series-what-is-federated-learning.ipynb:111 msgid "Train model using data" -msgstr "" +msgstr "데이터를 이용한 모델 훈련" #: ../../source/tutorial-series-what-is-federated-learning.ipynb:59 msgid "" -"Now, in practice, the training data we work with doesn't originate on the" -" machine we train the model on. It gets created somewhere else." -msgstr "" +"Now, in practice, the training data we work with doesn't originate on the " +"machine we train the model on. It gets created somewhere else." +msgstr "실제로 우리가 사용하는 훈련 데이터는 모델을 훈련시키는 기계에서 비롯된 것이 " +"아닙니다. 그 데이터는 다른 곳에서 만들어졌습니다." #: ../../source/tutorial-series-what-is-federated-learning.ipynb:61 msgid "" @@ -22044,46 +22363,54 @@ msgid "" "collecting sensor data, a laptop receiving input via the keyboard, or a " "smart speaker listening to someone trying to sing a song." msgstr "" +"스마트폰에서 사용자와 앱의 상호 작용, 센서 데이터를 수집하는 자동차, " +"키보드를 통해 입력을 받는 노트북 또는 누군가 노래를 부르리는 것을 듣는 " +"스마트 스피커에서 비롯됩니다." #: ../../source/tutorial-series-what-is-federated-learning.ipynb:67 msgid "|9bc21c7dbd17444a8f070c60786e3484|" -msgstr "" +msgstr "|9bc21c7dbd17444a8f070c60786e3484|" #: ../../source/tutorial-series-what-is-federated-learning.ipynb:113 msgid "Data on a phone" -msgstr "" +msgstr "핸드푼에 있는 데이터" #: ../../source/tutorial-series-what-is-federated-learning.ipynb:73 msgid "" "What's also important to mention, this \"somewhere else\" is usually not " -"just one place, it's many places. It could be several devices all running" -" the same app. But it could also be several organizations, all generating" -" data for the same task." +"just one place, it's many places. It could be several devices all running " +"the same app. But it could also be several organizations, all generating " +"data for the same task." msgstr "" +"또한 중요한 것은 이 \"다른 곳\"이 보통 한 곳만 아니라 여러 곳이라는 " +"것입니다. 같은 앱을 실행하는 여러 기기일 수도 있습니다. 하지만 여러 조직이 " +"모두 같은 작업을 위해 데이터를 생성하는 것일 수도 있습니다." #: ../../source/tutorial-series-what-is-federated-learning.ipynb:79 msgid "|3047bbce54b34099ae559963d0420d79|" -msgstr "" +msgstr "|3047bbce54b34099ae559963d0420d79|" #: ../../source/tutorial-series-what-is-federated-learning.ipynb:115 msgid "Data is on many devices" -msgstr "" +msgstr "데이터가 여러 장치에 있습니다" #: ../../source/tutorial-series-what-is-federated-learning.ipynb:85 msgid "" -"So to use machine learning, or any kind of data analysis, the approach " -"that has been used in the past was to collect all data on a central " -"server. This server can be somewhere in a data center, or somewhere in " -"the cloud." +"So to use machine learning, or any kind of data analysis, the approach that " +"has been used in the past was to collect all data on a central server. This " +"server can be somewhere in a data center, or somewhere in the cloud." msgstr "" +"따라서 머신러닝이나 어떤 종류의 데이터 분석을 이용하려면 과거에는 중앙 " +"서버에서 모든 데이터를 수집하는 방법이 사용되었습니다.이 서버는 데이터 센터 " +"어딘가에 있을 수도 있고 클라우드 어딘가에 있을 수도 있습니다." #: ../../source/tutorial-series-what-is-federated-learning.ipynb:91 msgid "|e9f8ce948593444fb838d2f354c7ec5d|" -msgstr "" +msgstr "|e9f8ce948593444fb838d2f354c7ec5d|" #: ../../source/tutorial-series-what-is-federated-learning.ipynb:117 msgid "Central data collection" -msgstr "" +msgstr "중앙 데이터 수집" #: ../../source/tutorial-series-what-is-federated-learning.ipynb:97 msgid "" @@ -22091,56 +22418,68 @@ msgid "" "learning algorithms to train our model on the data. This is the machine " "learning approach that we've basically always relied on." msgstr "" +"모든 데이터가 한 곳에 모이면, 우리는 궁극적으로 머신러닝 알고리즘을 사용하여 " +"데이터에서 모델을 훈련시킬 수 있습니다.이것이 바로 우리가 기본적으로 " +"의지해왔던 머신러닝 방법입니다." #: ../../source/tutorial-series-what-is-federated-learning.ipynb:103 msgid "|c24c1478b30e4f74839208628a842d1e|" -msgstr "" +msgstr "|c24c1478b30e4f74839208628a842d1e|" #: ../../source/tutorial-series-what-is-federated-learning.ipynb:119 msgid "Central model training" -msgstr "" +msgstr "중앙 데이터 훈련" #: ../../source/tutorial-series-what-is-federated-learning.ipynb:130 msgid "Challenges of classical machine learning" -msgstr "" +msgstr "클래식 머신러닝이 만난 도전" #: ../../source/tutorial-series-what-is-federated-learning.ipynb:132 msgid "" -"The classic machine learning approach we've just seen can be used in some" -" cases. Great examples include categorizing holiday photos, or analyzing " -"web traffic. Cases, where all the data is naturally available on a " -"centralized server." +"The classic machine learning approach we've just seen can be used in some " +"cases. Great examples include categorizing holiday photos, or analyzing web " +"traffic. Cases, where all the data is naturally available on a centralized " +"server." msgstr "" +"우리가 방금 본 클래식 머신러닝 접근 방식은 경우에 따라 사용될 수 있습니다. " +"좋은 예로는 휴일 사진을 분류하거나 웹 트래픽을 분석하는 것이 있습니다. " +"이러한 사례에서 모든 데이터는 자연스럽게 중앙 서버에서 사용할 수 있습니다." #: ../../source/tutorial-series-what-is-federated-learning.ipynb:138 msgid "|1b3613d7a58847b59e1d3180802dbc09|" -msgstr "" +msgstr "|1b3613d7a58847b59e1d3180802dbc09|" #: ../../source/tutorial-series-what-is-federated-learning.ipynb:173 msgid "Centralized possible" -msgstr "" +msgstr "집중화 가능" #: ../../source/tutorial-series-what-is-federated-learning.ipynb:144 msgid "" -"But the approach can not be used in many other cases. Cases, where the " -"data is not available on a centralized server, or cases where the data " -"available on one server is not enough to train a good model." +"But the approach can not be used in many other cases. Cases, where the data " +"is not available on a centralized server, or cases where the data available " +"on one server is not enough to train a good model." msgstr "" +"그러나 이 방법은 다른 많은 경우에 적용되지 않습니다.예를 들어, 중앙 집중식 " +"서버에 데이터가 없거나 서버의 데이터가 좋은 모델을 훈련하기에 충분하지 " +"않습니다." #: ../../source/tutorial-series-what-is-federated-learning.ipynb:150 msgid "|9980b5213db547d0b8024a50992b9e3f|" -msgstr "" +msgstr "|9980b5213db547d0b8024a50992b9e3f|" #: ../../source/tutorial-series-what-is-federated-learning.ipynb:175 msgid "Centralized impossible" -msgstr "" +msgstr "집중화 가능" #: ../../source/tutorial-series-what-is-federated-learning.ipynb:156 msgid "" -"There are many reasons why the classic centralized machine learning " -"approach does not work for a large number of highly important real-world " -"use cases. Those reasons include:" +"There are many reasons why the classic centralized machine learning approach " +"does not work for a large number of highly important real-world use cases. " +"Those reasons include:" msgstr "" +"클래식 중앙 집중식 머신러닝 방법이 현실 세계에서 매우 중요한 수많은 사용 " +"사례를 충족시킬 수 없는 이유가 있습니다.이유는 다음과 같은 여러 가지가 " +"있습니다:" #: ../../source/tutorial-series-what-is-federated-learning.ipynb:158 msgid "" @@ -22149,32 +22488,39 @@ msgid "" "(Russia), CDPR (China), PDPB (India), PIPA (Korea), APPI (Japan), PDP " "(Indonesia), PDPA (Singapore), APP (Australia), and other regulations " "protect sensitive data from being moved. In fact, those regulations " -"sometimes even prevent single organizations from combining their own " -"users' data for artificial intelligence training because those users live" -" in different parts of the world, and their data is governed by different" -" data protection regulations." -msgstr "" +"sometimes even prevent single organizations from combining their own users' " +"data for artificial intelligence training because those users live in " +"different parts of the world, and their data is governed by different data " +"protection regulations." +msgstr "" +"**규정**: GDPR (유럽), CCPA (캘리포니아), PIPEDA (캐나다), LGPD (브라질), " +"PDPL (아르헨티나), KVKK (터키), POPI (남아프리카공화국), FSS (러시아), CDPR " +"(중국), PDPB (인도), PIPA (한국), APPI (일본), PDP (인도네시아), PDPA " +"(싱가포르), APP (호주)등의 법규로 민감한 데이터가 이동하지 않도록 보호하고 " +"있습니 다. 실제 로이러한 규정은 사용자가 세계의 다른 지역에 살고 데이터가 " +"다른 데이터 보호 규정에 의해 통제되기 때문에 단일 조직이 자체 사용자 " +"데이터를 인공 지능 교육에 사용하는 것을 방지하기도 합니다." #: ../../source/tutorial-series-what-is-federated-learning.ipynb:160 msgid "" -"**User preference**: In addition to regulation, there are use cases where" -" users just expect that no data leaves their device, ever. If you type " -"your passwords and credit card info into the digital keyboard of your " -"phone, you don't expect those passwords to end up on the server of the " -"company that developed that keyboard, do you? In fact, that use case was " -"the reason federated learning was invented in the first place." +"**User preference**: In addition to regulation, there are use cases where " +"users just expect that no data leaves their device, ever. If you type your " +"passwords and credit card info into the digital keyboard of your phone, you " +"don't expect those passwords to end up on the server of the company that " +"developed that keyboard, do you? In fact, that use case was the reason " +"federated learning was invented in the first place." msgstr "" #: ../../source/tutorial-series-what-is-federated-learning.ipynb:161 msgid "" -"**Data volume**: Some sensors, like cameras, produce such a high data " -"volume that it is neither feasible nor economic to collect all the data " -"(due to, for example, bandwidth or communication efficiency). Think about" -" a national rail service with hundreds of train stations across the " -"country. If each of these train stations is outfitted with a number of " -"security cameras, the volume of raw on-device data they produce requires " -"incredibly powerful and exceedingly expensive infrastructure to process " -"and store. And most of the data isn't even useful." +"**Data volume**: Some sensors, like cameras, produce such a high data volume " +"that it is neither feasible nor economic to collect all the data (due to, " +"for example, bandwidth or communication efficiency). Think about a national " +"rail service with hundreds of train stations across the country. If each of " +"these train stations is outfitted with a number of security cameras, the " +"volume of raw on-device data they produce requires incredibly powerful and " +"exceedingly expensive infrastructure to process and store. And most of the " +"data isn't even useful." msgstr "" #: ../../source/tutorial-series-what-is-federated-learning.ipynb:164 @@ -22189,8 +22535,7 @@ msgstr "" #: ../../source/tutorial-series-what-is-federated-learning.ipynb:167 msgid "" -"Financial information from different organizations to detect financial " -"fraud" +"Financial information from different organizations to detect financial fraud" msgstr "" #: ../../source/tutorial-series-what-is-federated-learning.ipynb:168 @@ -22203,13 +22548,13 @@ msgstr "" #: ../../source/tutorial-series-what-is-federated-learning.ipynb:171 msgid "" -"The popularity of privacy-enhancing systems like the `Brave " -"`__ browser or the `Signal `__ " -"messenger shows that users care about privacy. In fact, they choose the " -"privacy-enhancing version over other alternatives, if such an alternative" -" exists. But what can we do to apply machine learning and data science to" -" these cases to utilize private data? After all, these are all areas that" -" would benefit significantly from recent advances in AI." +"The popularity of privacy-enhancing systems like the `Brave `__ browser or the `Signal `__ messenger shows " +"that users care about privacy. In fact, they choose the privacy-enhancing " +"version over other alternatives, if such an alternative exists. But what can " +"we do to apply machine learning and data science to these cases to utilize " +"private data? After all, these are all areas that would benefit " +"significantly from recent advances in AI." msgstr "" #: ../../source/tutorial-series-what-is-federated-learning.ipynb:186 @@ -22219,9 +22564,8 @@ msgstr "" #: ../../source/tutorial-series-what-is-federated-learning.ipynb:188 msgid "" "Federated learning simply reverses this approach. It enables machine " -"learning on distributed data by moving the training to the data, instead " -"of moving the data to the training. Here's the single-sentence " -"explanation:" +"learning on distributed data by moving the training to the data, instead of " +"moving the data to the training. Here's the single-sentence explanation:" msgstr "" #: ../../source/tutorial-series-what-is-federated-learning.ipynb:190 @@ -22234,22 +22578,22 @@ msgstr "" #: ../../source/tutorial-series-what-is-federated-learning.ipynb:193 msgid "" -"By doing so, it enables us to use machine learning (and other data " -"science approaches) in areas where it wasn't possible before. We can now " -"train excellent medical AI models by enabling different hospitals to work" -" together. We can solve financial fraud by training AI models on the data" -" of different financial institutions. We can build novel privacy-" -"enhancing applications (such as secure messaging) that have better built-" -"in AI than their non-privacy-enhancing alternatives. And those are just a" -" few of the examples that come to mind. As we deploy federated learning, " -"we discover more and more areas that can suddenly be reinvented because " -"they now have access to vast amounts of previously inaccessible data." +"By doing so, it enables us to use machine learning (and other data science " +"approaches) in areas where it wasn't possible before. We can now train " +"excellent medical AI models by enabling different hospitals to work " +"together. We can solve financial fraud by training AI models on the data of " +"different financial institutions. We can build novel privacy-enhancing " +"applications (such as secure messaging) that have better built-in AI than " +"their non-privacy-enhancing alternatives. And those are just a few of the " +"examples that come to mind. As we deploy federated learning, we discover " +"more and more areas that can suddenly be reinvented because they now have " +"access to vast amounts of previously inaccessible data." msgstr "" #: ../../source/tutorial-series-what-is-federated-learning.ipynb:196 msgid "" -"So how does federated learning work, exactly? Let's start with an " -"intuitive explanation." +"So how does federated learning work, exactly? Let's start with an intuitive " +"explanation." msgstr "" #: ../../source/tutorial-series-what-is-federated-learning.ipynb:199 @@ -22262,9 +22606,9 @@ msgstr "" #: ../../source/tutorial-series-what-is-federated-learning.ipynb:204 msgid "" -"We start by initializing the model on the server. This is exactly the " -"same in classic centralized learning: we initialize the model parameters," -" either randomly or from a previously saved checkpoint." +"We start by initializing the model on the server. This is exactly the same " +"in classic centralized learning: we initialize the model parameters, either " +"randomly or from a previously saved checkpoint." msgstr "" #: ../../source/tutorial-series-what-is-federated-learning.ipynb:210 @@ -22277,18 +22621,18 @@ msgstr "" #: ../../source/tutorial-series-what-is-federated-learning.ipynb:217 msgid "" -"Step 1: Send model to a number of connected organizations/devices (client" -" nodes)" +"Step 1: Send model to a number of connected organizations/devices (client " +"nodes)" msgstr "" #: ../../source/tutorial-series-what-is-federated-learning.ipynb:219 msgid "" "Next, we send the parameters of the global model to the connected client " "nodes (think: edge devices like smartphones or servers belonging to " -"organizations). This is to ensure that each participating node starts " -"their local training using the same model parameters. We often use only a" -" few of the connected nodes instead of all nodes. The reason for this is " -"that selecting more and more client nodes has diminishing returns." +"organizations). This is to ensure that each participating node starts their " +"local training using the same model parameters. We often use only a few of " +"the connected nodes instead of all nodes. The reason for this is that " +"selecting more and more client nodes has diminishing returns." msgstr "" #: ../../source/tutorial-series-what-is-federated-learning.ipynb:225 @@ -22301,18 +22645,18 @@ msgstr "" #: ../../source/tutorial-series-what-is-federated-learning.ipynb:232 msgid "" -"Step 2: Train model locally on the data of each organization/device " -"(client node)" +"Step 2: Train model locally on the data of each organization/device (client " +"node)" msgstr "" #: ../../source/tutorial-series-what-is-federated-learning.ipynb:234 msgid "" -"Now that all (selected) client nodes have the latest version of the " -"global model parameters, they start the local training. They use their " -"own local dataset to train their own local model. They don't train the " -"model until full convergence, but they only train for a little while. " -"This could be as little as one epoch on the local data, or even just a " -"few steps (mini-batches)." +"Now that all (selected) client nodes have the latest version of the global " +"model parameters, they start the local training. They use their own local " +"dataset to train their own local model. They don't train the model until " +"full convergence, but they only train for a little while. This could be as " +"little as one epoch on the local data, or even just a few steps (mini-" +"batches)." msgstr "" #: ../../source/tutorial-series-what-is-federated-learning.ipynb:240 @@ -22329,13 +22673,12 @@ msgstr "" #: ../../source/tutorial-series-what-is-federated-learning.ipynb:249 msgid "" -"After local training, each client node has a slightly different version " -"of the model parameters they originally received. The parameters are all " +"After local training, each client node has a slightly different version of " +"the model parameters they originally received. The parameters are all " "different because each client node has different examples in its local " -"dataset. The client nodes then send those model updates back to the " -"server. The model updates they send can either be the full model " -"parameters or just the gradients that were accumulated during local " -"training." +"dataset. The client nodes then send those model updates back to the server. " +"The model updates they send can either be the full model parameters or just " +"the gradients that were accumulated during local training." msgstr "" #: ../../source/tutorial-series-what-is-federated-learning.ipynb:255 @@ -22353,27 +22696,26 @@ msgstr "" #: ../../source/tutorial-series-what-is-federated-learning.ipynb:264 msgid "" "The server receives model updates from the selected client nodes. If it " -"selected 100 client nodes, it now has 100 slightly different versions of " -"the original global model, each trained on the local data of one client. " -"But didn't we want to have one model that contains the learnings from the" -" data of all 100 client nodes?" +"selected 100 client nodes, it now has 100 slightly different versions of the " +"original global model, each trained on the local data of one client. But " +"didn't we want to have one model that contains the learnings from the data " +"of all 100 client nodes?" msgstr "" #: ../../source/tutorial-series-what-is-federated-learning.ipynb:266 msgid "" -"In order to get one single model, we have to combine all the model " -"updates we received from the client nodes. This process is called " -"*aggregation*, and there are many different ways to do it. The most basic" -" way to do it is called *Federated Averaging* (`McMahan et al., 2016 " -"`__), often abbreviated as *FedAvg*. " -"*FedAvg* takes the 100 model updates and, as the name suggests, averages " -"them. To be more precise, it takes the *weighted average* of the model " -"updates, weighted by the number of examples each client used for " -"training. The weighting is important to make sure that each data example " -"has the same \"influence\" on the resulting global model. If one client " -"has 10 examples, and another client has 100 examples, then - without " -"weighting - each of the 10 examples would influence the global model ten " -"times as much as each of the 100 examples." +"In order to get one single model, we have to combine all the model updates " +"we received from the client nodes. This process is called *aggregation*, and " +"there are many different ways to do it. The most basic way to do it is " +"called *Federated Averaging* (`McMahan et al., 2016 `__), often abbreviated as *FedAvg*. *FedAvg* takes the 100 " +"model updates and, as the name suggests, averages them. To be more precise, " +"it takes the *weighted average* of the model updates, weighted by the number " +"of examples each client used for training. The weighting is important to " +"make sure that each data example has the same \"influence\" on the resulting " +"global model. If one client has 10 examples, and another client has 100 " +"examples, then - without weighting - each of the 10 examples would influence " +"the global model ten times as much as each of the 100 examples." msgstr "" #: ../../source/tutorial-series-what-is-federated-learning.ipynb:273 @@ -22391,41 +22733,39 @@ msgstr "" #: ../../source/tutorial-series-what-is-federated-learning.ipynb:282 msgid "" "Steps 1 to 4 are what we call a single round of federated learning. The " -"global model parameters get sent to the participating client nodes (step " -"1), the client nodes train on their local data (step 2), they send their " -"updated models to the server (step 3), and the server then aggregates the" -" model updates to get a new version of the global model (step 4)." +"global model parameters get sent to the participating client nodes (step 1), " +"the client nodes train on their local data (step 2), they send their updated " +"models to the server (step 3), and the server then aggregates the model " +"updates to get a new version of the global model (step 4)." msgstr "" #: ../../source/tutorial-series-what-is-federated-learning.ipynb:284 msgid "" -"During a single round, each client node that participates in that " -"iteration only trains for a little while. This means that after the " -"aggregation step (step 4), we have a model that has been trained on all " -"the data of all participating client nodes, but only for a little while. " -"We then have to repeat this training process over and over again to " -"eventually arrive at a fully trained model that performs well across the " -"data of all client nodes." +"During a single round, each client node that participates in that iteration " +"only trains for a little while. This means that after the aggregation step " +"(step 4), we have a model that has been trained on all the data of all " +"participating client nodes, but only for a little while. We then have to " +"repeat this training process over and over again to eventually arrive at a " +"fully trained model that performs well across the data of all client nodes." msgstr "" #: ../../source/tutorial-series-what-is-federated-learning.ipynb:289 msgid "" "Congratulations, you now understand the basics of federated learning. " -"There's a lot more to discuss, of course, but that was federated learning" -" in a nutshell. In later parts of this tutorial, we will go into more " -"detail. Interesting questions include: How can we select the best client " -"nodes that should participate in the next round? What's the best way to " -"aggregate model updates? How can we handle failing client nodes " -"(stragglers)?" +"There's a lot more to discuss, of course, but that was federated learning in " +"a nutshell. In later parts of this tutorial, we will go into more detail. " +"Interesting questions include: How can we select the best client nodes that " +"should participate in the next round? What's the best way to aggregate model " +"updates? How can we handle failing client nodes (stragglers)?" msgstr "" #: ../../source/tutorial-series-what-is-federated-learning.ipynb:294 msgid "" -"Just like we can train a model on the decentralized data of different " -"client nodes, we can also evaluate the model on that data to receive " -"valuable metrics. This is called federated evaluation, sometimes " -"abbreviated as FE. In fact, federated evaluation is an integral part of " -"most federated learning systems." +"Just like we can train a model on the decentralized data of different client " +"nodes, we can also evaluate the model on that data to receive valuable " +"metrics. This is called federated evaluation, sometimes abbreviated as FE. " +"In fact, federated evaluation is an integral part of most federated learning " +"systems." msgstr "" #: ../../source/tutorial-series-what-is-federated-learning.ipynb:297 @@ -22434,25 +22774,24 @@ msgstr "" #: ../../source/tutorial-series-what-is-federated-learning.ipynb:299 msgid "" -"In many cases, machine learning isn't necessary to derive value from " -"data. Data analysis can yield valuable insights, but again, there's often" -" not enough data to get a clear answer. What's the average age at which " -"people develop a certain type of health condition? Federated analytics " -"enables such queries over multiple client nodes. It is usually used in " -"conjunction with other privacy-enhancing technologies like secure " -"aggregation to prevent the server from seeing the results submitted by " -"individual client nodes." +"In many cases, machine learning isn't necessary to derive value from data. " +"Data analysis can yield valuable insights, but again, there's often not " +"enough data to get a clear answer. What's the average age at which people " +"develop a certain type of health condition? Federated analytics enables such " +"queries over multiple client nodes. It is usually used in conjunction with " +"other privacy-enhancing technologies like secure aggregation to prevent the " +"server from seeing the results submitted by individual client nodes." msgstr "" #: ../../source/tutorial-series-what-is-federated-learning.ipynb:305 msgid "" "Differential privacy (DP) is often mentioned in the context of Federated " -"Learning. It is a privacy-preserving method used when analyzing and " -"sharing statistical data, ensuring the privacy of individual " -"participants. DP achieves this by adding statistical noise to the model " -"updates, ensuring any individual participants’ information cannot be " -"distinguished or re-identified. This technique can be considered an " -"optimization that provides a quantifiable privacy protection measure." +"Learning. It is a privacy-preserving method used when analyzing and sharing " +"statistical data, ensuring the privacy of individual participants. DP " +"achieves this by adding statistical noise to the model updates, ensuring any " +"individual participants’ information cannot be distinguished or re-" +"identified. This technique can be considered an optimization that provides a " +"quantifiable privacy protection measure." msgstr "" #: ../../source/tutorial-series-what-is-federated-learning.ipynb:326 @@ -22461,13 +22800,13 @@ msgstr "" #: ../../source/tutorial-series-what-is-federated-learning.ipynb:328 msgid "" -"Federated learning, federated evaluation, and federated analytics require" -" infrastructure to move machine learning models back and forth, train and" -" evaluate them on local data, and then aggregate the updated models. " -"Flower provides the infrastructure to do exactly that in an easy, " -"scalable, and secure way. In short, Flower presents a unified approach to" -" federated learning, analytics, and evaluation. It allows the user to " -"federate any workload, any ML framework, and any programming language." +"Federated learning, federated evaluation, and federated analytics require " +"infrastructure to move machine learning models back and forth, train and " +"evaluate them on local data, and then aggregate the updated models. Flower " +"provides the infrastructure to do exactly that in an easy, scalable, and " +"secure way. In short, Flower presents a unified approach to federated " +"learning, analytics, and evaluation. It allows the user to federate any " +"workload, any ML framework, and any programming language." msgstr "" #: ../../source/tutorial-series-what-is-federated-learning.ipynb:334 @@ -22476,49 +22815,41 @@ msgstr "" #: ../../source/tutorial-series-what-is-federated-learning.ipynb:340 msgid "" -"Flower federated learning server and client nodes (car, scooter, personal" -" computer, roomba, and phone)" +"Flower federated learning server and client nodes (car, scooter, personal " +"computer, roomba, and phone)" msgstr "" #: ../../source/tutorial-series-what-is-federated-learning.ipynb:353 msgid "" -"Congratulations, you just learned the basics of federated learning and " -"how it relates to the classic (centralized) machine learning!" +"Congratulations, you just learned the basics of federated learning and how " +"it relates to the classic (centralized) machine learning!" msgstr "" #: ../../source/tutorial-series-what-is-federated-learning.ipynb:355 msgid "" -"In the next part of this tutorial, we are going to build a first " -"federated learning system with Flower." +"In the next part of this tutorial, we are going to build a first federated " +"learning system with Flower." msgstr "" #: ../../source/tutorial-series-what-is-federated-learning.ipynb:373 msgid "" -"The `Flower Federated Learning Tutorial - Part 1 " -"`__ shows how to build a simple federated learning system " -"with PyTorch and Flower." +"The `Flower Federated Learning Tutorial - Part 1 `__ shows how to " +"build a simple federated learning system with PyTorch and Flower." msgstr "" #~ msgid "" -#~ "Currently, Flower provides two images, a" -#~ " ``base`` image and a ``superlink`` " -#~ "image. The base image, as the name" -#~ " suggests, contains basic dependencies that" -#~ " the SuperLink needs. This includes " -#~ "system dependencies, Python and Python " -#~ "tools. The SuperLink image is based " -#~ "on the base image, but it " -#~ "additionally installs the SuperLink using " -#~ "``pip``." +#~ "Currently, Flower provides two images, a ``base`` image and a " +#~ "``superlink`` image. The base image, as the name suggests, contains basic " +#~ "dependencies that the SuperLink needs. This includes system dependencies, " +#~ "Python and Python tools. The SuperLink image is based on the base image, " +#~ "but it additionally installs the SuperLink using ``pip``." #~ msgstr "" -#~ "현재, Flower는 \"base\" 이미지 그리고 " -#~ "\"superlink\" 이미지를 제공합니다. base 이미지는 이름에서" -#~ " 알 수 있듯이 SuperLink가 필요로 하는 기본" -#~ " dependencies를 포함하고 있습니다. 여기에는 시스템 " -#~ "dependencies, Python 및 Python 도구가 포함됩니다." -#~ " SuperLink 이미지는 base 이미지를 기반으로 하지만" -#~ " \"pip\"을 사용하여 SuperLink를 추가로 설치합니다." +#~ "현재, Flower는 \"base\" 이미지 그리고 \"superlink\" 이미지를 제공합니다. " +#~ "base 이미지는 이름에서 알 수 있듯이 SuperLink가 필요로 하는 기본 " +#~ "dependencies를 포함하고 있습니다. 여기에는 시스템 dependencies, Python 및 " +#~ "Python 도구가 포함됩니다. SuperLink 이미지는 base 이미지를 기반으로 하지" +#~ "만 \"pip\"을 사용하여 SuperLink를 추가로 설치합니다." #~ msgid "``3.11``" #~ msgstr "``3.11``" @@ -22542,278 +22873,10 @@ msgstr "" #~ msgstr "``flwr``이 기본값." #~ msgid "" -#~ "The name of image is ``flwr_superlink``" -#~ " and the tag ``0.1.0``. Remember that" -#~ " the build arguments as well as " -#~ "the name and tag can be adapted" -#~ " to your needs. These values serve" -#~ " as examples only." -#~ msgstr "" -#~ "이미지의 이름은 ``flwr_superlink``이고 태그는 " -#~ "``0.1.0``입니다. 필요에 따라 빌드 argument들 뿐만 " -#~ "아니라 이름과 태그도 정할 수 있습니다. 이 값들은" -#~ " 예시일 뿐입니다." - -#~ msgid "Creating New Messages" -#~ msgstr "" - -#~ msgid "" -#~ "This is a simple guide for " -#~ "creating a new type of message " -#~ "between the server and clients in " -#~ "Flower." -#~ msgstr "" - -#~ msgid "" -#~ "Let's suppose we have the following " -#~ "example functions in :code:`server.py` and " -#~ ":code:`numpy_client.py`..." -#~ msgstr "" - -#~ msgid "Server's side:" -#~ msgstr "" - -#~ msgid "Client's side:" -#~ msgstr "" - -#~ msgid "" -#~ "Let's now see what we need to " -#~ "implement in order to get this " -#~ "simple function between the server and" -#~ " client to work!" -#~ msgstr "" - -#~ msgid "Message Types for Protocol Buffers" -#~ msgstr "" - -#~ msgid "" -#~ "The first thing we need to do " -#~ "is to define a message type for" -#~ " the RPC system in :code:`transport.proto`." -#~ " Note that we have to do it " -#~ "for both the request and response " -#~ "messages. For more details on the " -#~ "syntax of proto3, please see the " -#~ "`official documentation `_." -#~ msgstr "" - -#~ msgid "Within the :code:`ServerMessage` block:" -#~ msgstr "" - -#~ msgid "Within the ClientMessage block:" -#~ msgstr "" - -#~ msgid "" -#~ "Make sure to also add a field " -#~ "of the newly created message type " -#~ "in :code:`oneof msg`." -#~ msgstr "" - -#~ msgid "Once that is done, we will compile the file with:" -#~ msgstr "" - -#~ msgid "If it compiles successfully, you should see the following message:" -#~ msgstr "" - -#~ msgid "Serialization and Deserialization Functions" -#~ msgstr "" - -#~ msgid "" -#~ "Our next step is to add functions" -#~ " to serialize and deserialize Python " -#~ "datatypes to or from our defined " -#~ "RPC message types. You should add " -#~ "these functions in :code:`serde.py`." -#~ msgstr "" - -#~ msgid "The four functions:" -#~ msgstr "" - -#~ msgid "Sending the Message from the Server" -#~ msgstr "" - -#~ msgid "" -#~ "Now write the request function in " -#~ "your Client Proxy class (e.g., " -#~ ":code:`grpc_client_proxy.py`) using the serde " -#~ "functions you just created:" -#~ msgstr "" - -#~ msgid "Receiving the Message by the Client" -#~ msgstr "" - -#~ msgid "" -#~ "Last step! Modify the code in " -#~ ":code:`message_handler.py` to check the field" -#~ " of your message and call the " -#~ ":code:`example_response` function. Remember to " -#~ "use the serde functions!" -#~ msgstr "" - -#~ msgid "Within the handle function:" -#~ msgstr "" - -#~ msgid "And add a new function:" -#~ msgstr "" - -#~ msgid "Hopefully, when you run your program you will get the intended result!" -#~ msgstr "" - -#~ msgid "" -#~ "The simplest way to get started " -#~ "with Flower is by using the " -#~ "pre-made Docker images, which you can" -#~ " find on `Docker Hub " -#~ "`__." -#~ msgstr "" - -#~ msgid "" -#~ "If you want to persist the state" -#~ " of the SuperLink on your host " -#~ "system, all you need to do is " -#~ "specify a path where you want to" -#~ " save the file on your host " -#~ "system and a name for the database" -#~ " file. In the example below, we " -#~ "tell Docker via the flag ``--volume``" -#~ " to mount the user's home directory" -#~ " (``~/`` on your host) into the " -#~ "``/app/`` directory of the container. " -#~ "Furthermore, we use the flag " -#~ "``--database`` to specify the name of" -#~ " the database file." -#~ msgstr "" - -#~ msgid "" -#~ "As soon as the SuperLink starts, " -#~ "the file ``state.db`` is created in " -#~ "the user's home directory on your " -#~ "host system. If the file already " -#~ "exists, the SuperLink tries to restore" -#~ " the state from the file. To " -#~ "start the SuperLink with an empty " -#~ "database, simply remove the ``state.db`` " -#~ "file." -#~ msgstr "" - -#~ msgid "" -#~ "Assuming all files we need are in" -#~ " the local ``certificates`` directory, we" -#~ " can use the flag ``--volume`` to " -#~ "mount the local directory into the " -#~ "``/app/`` directory of the container. " -#~ "This allows the SuperLink to access " -#~ "the files within the container. Finally," -#~ " we pass the names of the " -#~ "certificates to the SuperLink with the" -#~ " ``--certificates`` flag." -#~ msgstr "" - -#~ msgid "" -#~ "``--server 192.168.1.100:9092``: This option " -#~ "specifies the address of the SuperLinks" -#~ " Fleet" -#~ msgstr "" - -#~ msgid "" -#~ "Assuming the certificate already exists " -#~ "locally, we can use the flag " -#~ "``--volume`` to mount the local " -#~ "certificate into the container's ``/app/`` " -#~ "directory. This allows the SuperNode to" -#~ " access the certificate within the " -#~ "container. Use the ``--certificates`` flag " -#~ "when starting the container." -#~ msgstr "" - -#~ msgid "" -#~ "``--server 192.168.1.100:9091``: This option " -#~ "specifies the address of the SuperLinks" -#~ " Driver" -#~ msgstr "" - -#~ msgid "" -#~ "Assuming the certificate already exists " -#~ "locally, we can use the flag " -#~ "``--volume`` to mount the local " -#~ "certificate into the container's ``/app/`` " -#~ "directory. This allows the ServerApp to" -#~ " access the certificate within the " -#~ "container. Use the ``--certificates`` flag " -#~ "when starting the container." -#~ msgstr "" - -#~ msgid "" -#~ "If you want to use a different " -#~ "version of Flower, for example Flower" -#~ " nightly, you can do so by " -#~ "changing the tag. All available versions" -#~ " are on `Docker Hub " -#~ "`__." -#~ msgstr "" - -#~ msgid "" -#~ "Here's another example to start with " -#~ "HTTPS. Use the ``--certificates`` command " -#~ "line argument to pass paths to (CA" -#~ " certificate, server certificate, and " -#~ "server private key)." -#~ msgstr "" - -#~ msgid ":py:obj:`run_driver_api `\\ \\(\\)" -#~ msgstr "" - -#~ msgid "Run Flower server (Driver API)." -#~ msgstr "" - -#~ msgid ":py:obj:`run_fleet_api `\\ \\(\\)" -#~ msgstr "" - -#~ msgid "Run Flower server (Fleet API)." -#~ msgstr "" - -#~ msgid "Unreleased" -#~ msgstr "" - -#~ msgid "|d8bf04f23d9b46d8a23cc6f4887d7873|" -#~ msgstr "" - -#~ msgid "|5aa1711387d74d0f8b9c499e1a51627e|" -#~ msgstr "" - -#~ msgid "|2bc8e069228d4873804061ff4a95048c|" -#~ msgstr "" - -#~ msgid "|c258488766324dc9a6807f0e7c4fd5f4|" -#~ msgstr "" - -#~ msgid "|d5f962c3f4ec48529efda980868c14b0|" -#~ msgstr "" - -#~ msgid "|a5eccea18d4c43a68b54b65043cabef8|" -#~ msgstr "" - -#~ msgid "|f17662f7df2d42f68cac70a1fdeda8a7|" -#~ msgstr "" - -#~ msgid "|241fc906441a4f038c625a19d30d01b2|" -#~ msgstr "" - -#~ msgid "|0aa5aa05810b44b6a835cecce28f3137|" -#~ msgstr "" - -#~ msgid "|c742940dd4bf4de09d8d0d5e8d179638|" -#~ msgstr "" - -#~ msgid "|1f169ab4601a47e1a226f1628f4ebddb|" -#~ msgstr "" - -#~ msgid "|12cfa9cde14440ecb8c8f6c1d7185bec|" -#~ msgstr "" - -#~ msgid "|72939caf6e294b0986fee6dde96614d7|" -#~ msgstr "" - -#~ msgid "|83a8daee45da4a98b8d6f24ae098fc50|" +#~ "The name of image is ``flwr_superlink`` and the tag ``0.1.0``. Remember " +#~ "that the build arguments as well as the name and tag can be adapted to " +#~ "your needs. These values serve as examples only." #~ msgstr "" +#~ "이미지의 이름은 ``flwr_superlink``이고 태그는 ``0.1.0``입니다. 필요에 따" +#~ "라 빌드 argument들 뿐만 아니라 이름과 태그도 정할 수 있습니다. 이 값들은 " +#~ "예시일 뿐입니다." diff --git a/examples/xgboost-comprehensive/client.py b/examples/xgboost-comprehensive/client.py index 2d54c3fd63c7..08dd548a386b 100644 --- a/examples/xgboost-comprehensive/client.py +++ b/examples/xgboost-comprehensive/client.py @@ -32,7 +32,7 @@ fds = FederatedDataset( dataset="jxie/higgs", partitioners={"train": partitioner}, - resplitter=resplit, + preprocessor=resplit, ) # Load the partition for this `partition_id` diff --git a/examples/xgboost-comprehensive/pyproject.toml b/examples/xgboost-comprehensive/pyproject.toml index 2d44c06d6e3f..c9259ffa1db4 100644 --- a/examples/xgboost-comprehensive/pyproject.toml +++ b/examples/xgboost-comprehensive/pyproject.toml @@ -11,5 +11,5 @@ authors = ["The Flower Authors "] [tool.poetry.dependencies] python = ">=3.8,<3.11" flwr = { extras = ["simulation"], version = ">=1.7.0,<2.0" } -flwr-datasets = ">=0.1.0,<1.0.0" +flwr-datasets = ">=0.2.0,<1.0.0" xgboost = ">=2.0.0,<3.0.0" diff --git a/examples/xgboost-comprehensive/requirements.txt b/examples/xgboost-comprehensive/requirements.txt index 16eb78f484e3..840e19529953 100644 --- a/examples/xgboost-comprehensive/requirements.txt +++ b/examples/xgboost-comprehensive/requirements.txt @@ -1,3 +1,3 @@ flwr[simulation]>=1.7.0, <2.0 -flwr-datasets>=0.1.0, <1.0.0 +flwr-datasets>=0.2.0, <1.0.0 xgboost>=2.0.0, <3.0.0 diff --git a/examples/xgboost-comprehensive/server.py b/examples/xgboost-comprehensive/server.py index 939819641438..07dc4bed6db4 100644 --- a/examples/xgboost-comprehensive/server.py +++ b/examples/xgboost-comprehensive/server.py @@ -32,7 +32,7 @@ # Load centralised test set if centralised_eval: fds = FederatedDataset( - dataset="jxie/higgs", partitioners={"train": 20}, resplitter=resplit + dataset="jxie/higgs", partitioners={"train": 20}, preprocessor=resplit ) log(INFO, "Loading centralised test set...") test_set = fds.load_split("test") diff --git a/examples/xgboost-comprehensive/sim.py b/examples/xgboost-comprehensive/sim.py index c9481f1cdd5d..09ebbb81fcb4 100644 --- a/examples/xgboost-comprehensive/sim.py +++ b/examples/xgboost-comprehensive/sim.py @@ -80,7 +80,7 @@ def main(): fds = FederatedDataset( dataset="jxie/higgs", partitioners={"train": partitioner}, - resplitter=resplit, + preprocessor=resplit, ) # Load centralised test set