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Add PyTorch 2.4 support (#225)
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* update

* update

* update
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rusty1s authored Aug 15, 2024
1 parent 616704a commit e1e788b
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Showing 10 changed files with 87 additions and 28 deletions.
20 changes: 12 additions & 8 deletions .github/workflows/building-conda.yml
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Expand Up @@ -10,20 +10,24 @@ jobs:
strategy:
fail-fast: false
matrix:
# We have trouble building for Windows - drop for now.
os: [ubuntu-20.04] # windows-2019
os: [ubuntu-20.04, macos-14, windows-2019]
python-version: ['3.8', '3.9', '3.10', '3.11', '3.12']
torch-version: [2.3.0] # [2.1.0, 2.2.0, 2.3.0]
cuda-version: ['cpu', 'cu118', 'cu121']
torch-version: [2.4.0] # [2.3.0, 2.4.0]
cuda-version: ['cpu', 'cu118', 'cu121', 'cu124']
exclude:
- python-version: '3.12' # Python 3.12 not yet supported in `conda-build`.
- torch-version: 2.1.0
python-version: '3.12'
- torch-version: 2.3.0
cuda-version: 'cu124'
- os: macos-14
cuda-version: 'cu118'
- os: macos-14
cuda-version: 'cu121'
- os: macos-14
cuda-version: 'cu124'

steps:
- uses: actions/checkout@v2
- name: Set up Conda for Python ${{ matrix.python-version }}
uses: conda-incubator/setup-miniconda@v2
uses: conda-incubator/setup-miniconda@v3
with:
python-version: ${{ matrix.python-version }}

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12 changes: 7 additions & 5 deletions .github/workflows/building.yml
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Expand Up @@ -12,15 +12,17 @@ jobs:
matrix:
os: [ubuntu-20.04, macos-14, windows-2019]
python-version: ['3.8', '3.9', '3.10', '3.11', '3.12']
torch-version: [2.3.0] # [2.1.0, 2.2.0, 2.3.0]
cuda-version: ['cpu', 'cu118', 'cu121']
torch-version: [2.4.0] # [2.3.0, 2.4.0]
cuda-version: ['cpu', 'cu118', 'cu121', 'cu124']
exclude:
- torch-version: 2.1.0
python-version: '3.12'
- torch-version: 2.3.0
cuda-version: 'cu124'
- os: macos-14
cuda-version: 'cu118'
- os: macos-14
cuda-version: 'cu121'
- os: macos-14
cuda-version: 'cu124'

steps:
- uses: actions/checkout@v2
Expand All @@ -34,7 +36,7 @@ jobs:
pip install --upgrade setuptools
- name: Install scipy
if: ${{ matrix.python-version == '3.8' }}
if: ${{ (matrix.python-version == '3.8') || (matrix.python-version == '3.9') }}
run: |
pip install scipy==1.10.1
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8 changes: 8 additions & 0 deletions .github/workflows/cuda/cu124-Linux-env.sh
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@@ -0,0 +1,8 @@
#!/bin/bash

CUDA_HOME=/usr/local/cuda-12.4
LD_LIBRARY_PATH=${CUDA_HOME}/lib64:${LD_LIBRARY_PATH}
PATH=${CUDA_HOME}/bin:${PATH}

export FORCE_CUDA=1
export TORCH_CUDA_ARCH_LIST="5.0+PTX;6.0;7.0;7.5;8.0;8.6;9.0"
15 changes: 15 additions & 0 deletions .github/workflows/cuda/cu124-Linux.sh
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@@ -0,0 +1,15 @@
#!/bin/bash

OS=ubuntu2004

wget -nv https://developer.download.nvidia.com/compute/cuda/repos/${OS}/x86_64/cuda-${OS}.pin
sudo mv cuda-${OS}.pin /etc/apt/preferences.d/cuda-repository-pin-600
wget -nv https://developer.download.nvidia.com/compute/cuda/12.4.1/local_installers/cuda-repo-${OS}-12-4-local_12.4.1-550.54.15-1_amd64.deb
sudo dpkg -i cuda-repo-${OS}-12-4-local_12.4.1-550.54.15-1_amd64.deb
sudo cp /var/cuda-repo-${OS}-12-4-local/cuda-*-keyring.gpg /usr/share/keyrings/

sudo apt-get -qq update
sudo apt install cuda-nvcc-12-4 cuda-libraries-dev-12-4
sudo apt clean

rm -f https://developer.download.nvidia.com/compute/cuda/12.4.0/local_installers/cuda-repo-${OS}-12-4-local_12.4.1-550.54.15-1_amd64.deb
8 changes: 8 additions & 0 deletions .github/workflows/cuda/cu124-Windows-env.sh
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@@ -0,0 +1,8 @@
#!/bin/bash

CUDA_HOME=/c/Program\ Files/NVIDIA\ GPU\ Computing\ Toolkit/CUDA/v12.4
PATH=${CUDA_HOME}/bin:$PATH
PATH=/c/Program\ Files\ \(x86\)/Microsoft\ Visual\ Studio/2017/BuildTools/MSBuild/15.0/Bin:$PATH

export FORCE_CUDA=1
export TORCH_CUDA_ARCH_LIST="6.0+PTX"
18 changes: 18 additions & 0 deletions .github/workflows/cuda/cu124-Windows.sh
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@@ -0,0 +1,18 @@
#!/bin/bash

# Install NVIDIA drivers, see:
# https://github.com/pytorch/vision/blob/master/packaging/windows/internal/cuda_install.bat#L99-L102
curl -k -L "https://drive.google.com/u/0/uc?id=1injUyo3lnarMgWyRcXqKg4UGnN0ysmuq&export=download" --output "/tmp/gpu_driver_dlls.zip"
7z x "/tmp/gpu_driver_dlls.zip" -o"/c/Windows/System32"

export CUDA_SHORT=12.4
export CUDA_URL=https://developer.download.nvidia.com/compute/cuda/${CUDA_SHORT}.1/local_installers
export CUDA_FILE=cuda_${CUDA_SHORT}.1_551.78_windows.exe

# Install CUDA:
curl -k -L "${CUDA_URL}/${CUDA_FILE}" --output "${CUDA_FILE}"
echo ""
echo "Installing from ${CUDA_FILE}..."
PowerShell -Command "Start-Process -FilePath \"${CUDA_FILE}\" -ArgumentList \"-s nvcc_${CUDA_SHORT} cuobjdump_${CUDA_SHORT} nvprune_${CUDA_SHORT} cupti_${CUDA_SHORT} cublas_dev_${CUDA_SHORT} cudart_${CUDA_SHORT} cufft_dev_${CUDA_SHORT} curand_dev_${CUDA_SHORT} cusolver_dev_${CUDA_SHORT} cusparse_dev_${CUDA_SHORT} thrust_${CUDA_SHORT} npp_dev_${CUDA_SHORT} nvrtc_dev_${CUDA_SHORT} nvml_dev_${CUDA_SHORT}\" -Wait -NoNewWindow"
echo "Done!"
rm -f "${CUDA_FILE}"
2 changes: 1 addition & 1 deletion .github/workflows/testing.yml
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Expand Up @@ -16,7 +16,7 @@ jobs:
matrix:
os: [ubuntu-latest, windows-latest]
python-version: [3.8]
torch-version: [2.2.0, 2.3.0]
torch-version: [2.3.0, 2.4.0]

steps:
- uses: actions/checkout@v2
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27 changes: 14 additions & 13 deletions README.md
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Expand Up @@ -43,28 +43,29 @@ conda install pytorch-cluster -c pyg

We alternatively provide pip wheels for all major OS/PyTorch/CUDA combinations, see [here](https://data.pyg.org/whl).

#### PyTorch 2.3
#### PyTorch 2.4

To install the binaries for PyTorch 2.3.0, simply run
To install the binaries for PyTorch 2.4.0, simply run

```
pip install torch-cluster -f https://data.pyg.org/whl/torch-2.3.0+${CUDA}.html
pip install torch-cluster -f https://data.pyg.org/whl/torch-2.4.0+${CUDA}.html
```

where `${CUDA}` should be replaced by either `cpu`, `cu118`, or `cu121` depending on your PyTorch installation.
where `${CUDA}` should be replaced by either `cpu`, `cu118`, `cu121`, or `cu124` depending on your PyTorch installation.

| | `cpu` | `cu118` | `cu121` | `cu124` |
|-------------|-------|---------|---------|---------|
| **Linux** |||||
| **Windows** |||||
| **macOS** || | | |

| | `cpu` | `cu118` | `cu121` |
|-------------|-------|---------|---------|
| **Linux** ||||
| **Windows** ||||
| **macOS** || | |

#### PyTorch 2.2
#### PyTorch 2.3

To install the binaries for PyTorch 2.2.0, simply run
To install the binaries for PyTorch 2.3.0, simply run

```
pip install torch-cluster -f https://data.pyg.org/whl/torch-2.2.0+${CUDA}.html
pip install torch-cluster -f https://data.pyg.org/whl/torch-2.3.0+${CUDA}.html
```

where `${CUDA}` should be replaced by either `cpu`, `cu118`, or `cu121` depending on your PyTorch installation.
Expand All @@ -75,7 +76,7 @@ where `${CUDA}` should be replaced by either `cpu`, `cu118`, or `cu121` dependin
| **Windows** ||||
| **macOS** || | |

**Note:** Binaries of older versions are also provided for PyTorch 1.4.0, PyTorch 1.5.0, PyTorch 1.6.0, PyTorch 1.7.0/1.7.1, PyTorch 1.8.0/1.8.1, PyTorch 1.9.0, PyTorch 1.10.0/1.10.1/1.10.2, PyTorch 1.11.0, PyTorch 1.12.0/1.12.1, PyTorch 1.13.0/1.13.1, PyTorch 2.0.0/2.0.1, and PyTorch 2.1.0/2.1.1/2.1.2 (following the same procedure).
**Note:** Binaries of older versions are also provided for PyTorch 1.4.0, PyTorch 1.5.0, PyTorch 1.6.0, PyTorch 1.7.0/1.7.1, PyTorch 1.8.0/1.8.1, PyTorch 1.9.0, PyTorch 1.10.0/1.10.1/1.10.2, PyTorch 1.11.0, PyTorch 1.12.0/1.12.1, PyTorch 1.13.0/1.13.1, PyTorch 2.0.0/2.0.1, PyTorch 2.1.0/2.1.1/2.1.2, and PyTorch 2.2.0/2.2.1/2.2.2 (following the same procedure).
For older versions, you need to explicitly specify the latest supported version number or install via `pip install --no-index` in order to prevent a manual installation from source.
You can look up the latest supported version number [here](https://data.pyg.org/whl).

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2 changes: 1 addition & 1 deletion conda/pytorch-cluster/README.md
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@@ -1,3 +1,3 @@
```
./build_conda.sh 3.11 2.3.0 cu118 # python, pytorch and cuda version
./build_conda.sh 3.11 2.4.0 cu118 # python, pytorch and cuda version
```
3 changes: 3 additions & 0 deletions conda/pytorch-cluster/build_conda.sh
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Expand Up @@ -10,6 +10,9 @@ if [ "${CUDA_VERSION}" = "cpu" ]; then
export CONDA_CUDATOOLKIT_CONSTRAINT="cpuonly # [not osx]"
else
case $CUDA_VERSION in
cu124)
export CONDA_CUDATOOLKIT_CONSTRAINT="pytorch-cuda==12.4.*"
;;
cu121)
export CONDA_CUDATOOLKIT_CONSTRAINT="pytorch-cuda==12.1.*"
;;
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