# conda create --name torch_env python=3.9
# conda activate torch_env
# conda install -c anaconda ipykernel
# python -m ipykernel install --user --name=torch_env
# conda install -c "nvidia/label/cuda-11.6.0" cuda-toolkit
# pip install torch==1.12.1+cu116 torchvision==0.13.1+cu116 torchaudio==0.12.1 --extra-index-url https://download.pytorch.org/whl/cu116
# python -c "import torch; print(torch.version.cuda)"
# pip install torch-sparse -f https://data.pyg.org/whl/torch-1.12.1+cu116.html
# pip install torch-scatter -f https://data.pyg.org/whl/torch-1.12.1+cu116.html
# pip install torch-geometric
# pip install torch-spline-conv -f https://data.pyg.org/whl/torch-1.12.1+cu116.html
# pip install torch-cluster -f https://data.pyg.org/whl/torch-1.12.1+cu116.html
# pip install pyyaml tomli matplotlib sympy ipywidgets scikit-image
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A Pytorch based SPH simulation framework for deep learning research
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A Pytorch based SPH simulation framework for deep learning research
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