From b96cfdcd7d6dc3be11280de3aee3c0831e71cdf7 Mon Sep 17 00:00:00 2001 From: Leif Denby Date: Tue, 20 Aug 2024 10:17:53 +0200 Subject: [PATCH] quote the skip step the install readme --- README.md | 6 ++++-- 1 file changed, 4 insertions(+), 2 deletions(-) diff --git a/README.md b/README.md index b0705377..7dc6c7ab 100644 --- a/README.md +++ b/README.md @@ -77,14 +77,16 @@ setup](.github/workflows/) which you can use as a reference. ### Using `pdm` 1. Clone this repository and navigate to the root directory. -2. Install `pdm` if you don't have it installed on your system (either with `pip install pdm` or [following the install instructions](https://pdm-project.org/latest/#installation)). If you are happy using the latest version of `torch` with GPU support (expecting the latest version of CUDA is installed on your system) you can skip to step 5. +2. Install `pdm` if you don't have it installed on your system (either with `pip install pdm` or [following the install instructions](https://pdm-project.org/latest/#installation)). +> If you are happy using the latest version of `torch` with GPU support (expecting the latest version of CUDA is installed on your system) you can skip to step 5. 3. Create a virtual environment for pdm to use with `pdm venv create --with-pip`. 4. Install a specific version of `torch` with `pdm run python -m pip install torch --index-url https://download.pytorch.org/whl/cpu` for a CPU-only version or `pdm run python -m pip install torch --index-url https://download.pytorch.org/whl/cu111` for CUDA 11.1 support (you can find the correct URL for the variant you want on [PyTorch webpage](https://pytorch.org/get-started/locally/)). 5. Install the dependencies with `pdm install` (by default this in include the). If you will be developing `neural-lam` we recommend to install the development dependencies with `pdm install --group dev`. By default `pdm` installs the `neural-lam` package in editable mode, so you can make changes to the code and see the effects immediately. ### Using `pip` -1. Clone this repository and navigate to the root directory. If you are happy using the latest version of `torch` with GPU support (expecting the latest version of CUDA is installed on your system) you can skip to step 3. +1. Clone this repository and navigate to the root directory. +> If you are happy using the latest version of `torch` with GPU support (expecting the latest version of CUDA is installed on your system) you can skip to step 3. 2. Install a specific version of `torch` with `python -m pip install torch --index-url https://download.pytorch.org/whl/cpu` for a CPU-only version or `python -m pip install torch --index-url https://download.pytorch.org/whl/cu111` for CUDA 11.1 support (you can find the correct URL for the variant you want on [PyTorch webpage](https://pytorch.org/get-started/locally/)). 3. Install the dependencies with `python -m pip install .`. If you will be developing `neural-lam` we recommend to install in editable mode and install the development dependencies with `python -m pip install -e ".[dev]"` so you can make changes to the code and see the effects immediately.