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Simplified pip env setup #27

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Simplified pip env setup #27

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15 changes: 3 additions & 12 deletions README.md
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Expand Up @@ -56,19 +56,10 @@ Below follows instructions on how to use Neural-LAM to train and evaluate models
## Installation
Follow the steps below to create the necessary python environment.

1. Install GEOS for your system. For example with `sudo apt-get install libgeos-dev`. This is necessary for the Cartopy requirement.
2. Use python 3.9.
3. Install version 2.0.1 of PyTorch. Follow instructions on the [PyTorch webpage](https://pytorch.org/get-started/previous-versions/) for how to set this up with GPU support on your system.
4. Install required packages specified in `requirements.txt`.
5. Install PyTorch Geometric version 2.2.0. This can be done by running
```
TORCH="2.0.1"
CUDA="cu117"
1. Use python >= 3.9.
2. Install PyTorch by following instructions on the [PyTorch webpage](https://pytorch.org/get-started/previous-versions/) for how to set this up with GPU support on your system.
3. Install required packages specified in `requirements.txt`.

pip install pyg-lib==0.2.0 torch-scatter==2.1.1 torch-sparse==0.6.17 torch-cluster==1.6.1\
torch-geometric==2.3.1 -f https://pytorch-geometric.com/whl/torch-${TORCH}+${CUDA}.html
```
You will have to adjust the `CUDA` variable to match the CUDA version on your system or to run on CPU. See the [installation webpage](https://pytorch-geometric.readthedocs.io/en/latest/install/installation.html) for more information.

## Data
Datasets should be stored in a directory called `data`.
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10 changes: 8 additions & 2 deletions requirements.txt
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@@ -1,15 +1,21 @@
# for all
numpy>=1.24.2
wandb>=0.13.10
matplotlib>=3.7.0
scipy>=1.10.0
pytorch-lightning>=2.0.3
shapely>=2.0.1
networkx>=3.0
Cartopy>=0.22.0
Cartopy>=0.20.0
pyproj>=3.4.1
tueplots>=0.0.8
plotly>=5.15.0
torch>=2.0.1
--find-links https://data.pyg.org/whl/torch-${TORCH}.html
torch-scatter>=2.1.0
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@sadamov I don't quite understand how this is supposed to work if CUDA isn't installed. Doesn't this method require that the TORCH environment variable is set? Or is it just that if TORCH isn't set that pip fill try to fetch a page that doesn't exist and then will default to the cpu version available on pypi?

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@sadamov sadamov May 17, 2024 •
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I think you are right Leif, this doesn't work on CPU only on GPU. I must have gotten confused, because I always install pytorch with conda beforehand (then it works, but --find-links is then useless). Short answer, my solution sucks and we should find a working solution for the soon-to-be packaged repo. Did you already find a way to install torch with pip that is both flexible and robust enough across various machines?

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Ah I see :) ok, thanks for the clarification. I will think about this a bit more and give a proposition

torch-sparse>=0.6.15
torch-cluster>=1.6.0
torch-spline-conv>=1.2.1
torch-geometric>=2.3.0
# for dev
codespell>=2.0.0
black>=21.9b0
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