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version: 2.1 | ||
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jobs: | ||
python_lint: | ||
docker: | ||
- image: circleci/python:3.7 | ||
steps: | ||
- checkout | ||
- run: | ||
command: | | ||
pip install --user --progress-bar off flake8 typing | ||
flake8 . | ||
test: | ||
docker: | ||
- image: circleci/python:3.7 | ||
steps: | ||
- checkout | ||
- run: | ||
command: | | ||
pip install --user --progress-bar off scipy pytest | ||
pip install --user --progress-bar off --pre torch torchvision -f https://download.pytorch.org/whl/nightly/cpu/torch_nightly.html | ||
pip install --user --progress-bar off onnx onnxruntime | ||
pytest . | ||
workflows: | ||
build: | ||
jobs: | ||
- python_lint | ||
- test |
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# Code of Conduct | ||
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Facebook has adopted a Code of Conduct that we expect project participants to adhere to. | ||
Please read the [full text](https://code.fb.com/codeofconduct/) | ||
so that you can understand what actions will and will not be tolerated. |
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# Contributing to DETR | ||
We want to make contributing to this project as easy and transparent as | ||
possible. | ||
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## Our Development Process | ||
Minor changes and improvements will be released on an ongoing basis. Larger changes (e.g., changesets implementing a new paper) will be released on a more periodic basis. | ||
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## Pull Requests | ||
We actively welcome your pull requests. | ||
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1. Fork the repo and create your branch from `master`. | ||
2. If you've added code that should be tested, add tests. | ||
3. If you've changed APIs, update the documentation. | ||
4. Ensure the test suite passes. | ||
5. Make sure your code lints. | ||
6. If you haven't already, complete the Contributor License Agreement ("CLA"). | ||
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## Contributor License Agreement ("CLA") | ||
In order to accept your pull request, we need you to submit a CLA. You only need | ||
to do this once to work on any of Facebook's open source projects. | ||
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Complete your CLA here: <https://code.facebook.com/cla> | ||
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## Issues | ||
We use GitHub issues to track public bugs. Please ensure your description is | ||
clear and has sufficient instructions to be able to reproduce the issue. | ||
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Facebook has a [bounty program](https://www.facebook.com/whitehat/) for the safe | ||
disclosure of security bugs. In those cases, please go through the process | ||
outlined on that page and do not file a public issue. | ||
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## Coding Style | ||
* 4 spaces for indentation rather than tabs | ||
* 80 character line length | ||
* PEP8 formatting following [Black](https://black.readthedocs.io/en/stable/) | ||
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## License | ||
By contributing to DETR, you agree that your contributions will be licensed | ||
under the LICENSE file in the root directory of this source tree. |
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--- | ||
name: "🐛 Bugs" | ||
about: Report bugs in DETR | ||
title: Please read & provide the following | ||
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--- | ||
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## Instructions To Reproduce the 🐛 Bug: | ||
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1. what changes you made (`git diff`) or what code you wrote | ||
``` | ||
<put diff or code here> | ||
``` | ||
2. what exact command you run: | ||
3. what you observed (including __full logs__): | ||
``` | ||
<put logs here> | ||
``` | ||
4. please simplify the steps as much as possible so they do not require additional resources to | ||
run, such as a private dataset. | ||
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## Expected behavior: | ||
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If there are no obvious error in "what you observed" provided above, | ||
please tell us the expected behavior. | ||
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## Environment: | ||
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Provide your environment information using the following command: | ||
``` | ||
python -m torch.utils.collect_env | ||
``` |
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--- | ||
name: "How to do something❓" | ||
about: How to do something using DETR? | ||
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--- | ||
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## ❓ How to do something using DETR | ||
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Describe what you want to do, including: | ||
1. what inputs you will provide, if any: | ||
2. what outputs you are expecting: | ||
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NOTE: | ||
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1. Only general answers are provided. | ||
If you want to ask about "why X did not work", please use the | ||
[Unexpected behaviors](https://github.com/facebookresearch/detr/issues/new/choose) issue template. | ||
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2. About how to implement new models / new dataloader / new training logic, etc., check documentation first. | ||
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3. We do not answer general machine learning / computer vision questions that are not specific to DETR, such as how a model works, how to improve your training/make it converge, or what algorithm/methods can be used to achieve X. |
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--- | ||
name: "Unexpected behaviors" | ||
about: Run into unexpected behaviors when using DETR | ||
title: Please read & provide the following | ||
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--- | ||
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If you do not know the root cause of the problem, and wish someone to help you, please | ||
post according to this template: | ||
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## Instructions To Reproduce the Issue: | ||
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1. what changes you made (`git diff`) or what code you wrote | ||
``` | ||
<put diff or code here> | ||
``` | ||
2. what exact command you run: | ||
3. what you observed (including __full logs__): | ||
``` | ||
<put logs here> | ||
``` | ||
4. please simplify the steps as much as possible so they do not require additional resources to | ||
run, such as a private dataset. | ||
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## Expected behavior: | ||
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If there are no obvious error in "what you observed" provided above, | ||
please tell us the expected behavior. | ||
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If you expect the model to converge / work better, note that we do not give suggestions | ||
on how to train a new model. | ||
Only in one of the two conditions we will help with it: | ||
(1) You're unable to reproduce the results in DETR model zoo. | ||
(2) It indicates a DETR bug. | ||
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## Environment: | ||
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Provide your environment information using the following command: | ||
``` | ||
python -m torch.utils.collect_env | ||
``` |
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.nfs* | ||
*.ipynb | ||
*.pyc | ||
.dumbo.json | ||
.DS_Store | ||
.*.swp | ||
*.pth | ||
**/__pycache__/** | ||
.ipynb_checkpoints/ | ||
datasets/data/ | ||
experiment-* | ||
*.tmp | ||
*.pkl | ||
**/.mypy_cache/* | ||
.mypy_cache/* | ||
not_tracked_dir/ | ||
.vscode |
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FROM pytorch/pytorch:1.5-cuda10.1-cudnn7-runtime | ||
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ENV DEBIAN_FRONTEND=noninteractive | ||
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RUN apt-get update -qq && \ | ||
apt-get install -y git vim libgtk2.0-dev && \ | ||
rm -rf /var/cache/apk/* | ||
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RUN pip --no-cache-dir install Cython | ||
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COPY requirements.txt /workspace | ||
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RUN pip --no-cache-dir install -r /workspace/requirements.txt |