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Add PyTorch 2.11 support (#505)
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.github/workflows/building.yml

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matrix:
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os: [ubuntu-22.04, macos-14, windows-2022, ubuntu-22.04-arm]
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python-version: ['3.10', '3.11', '3.12', '3.13', '3.14']
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torch-version: [2.9.0, 2.10.0]
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torch-version: [2.11.0]
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cuda-version: ['cpu', 'cu126', 'cu128', 'cu130']
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exclude:
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- os: windows-2022

.github/workflows/testing.yml

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strategy:
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fail-fast: false
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matrix:
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os: [ubuntu-latest, windows-latest]
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os: [ubuntu-latest, macos-latest, windows-latest]
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python-version: ['3.10']
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torch-version: [2.9.0, 2.10.0]
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torch-version: [2.11.0]
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steps:
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- uses: actions/checkout@v2

README.md

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We provide pip wheels for all major OS/PyTorch/CUDA combinations, see [here](https://data.pyg.org/whl).
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#### PyTorch 2.10
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#### PyTorch 2.11
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To install the binaries for PyTorch 2.10, simply run
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To install the binaries for PyTorch 2.11, simply run
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```
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pip install torch-scatter -f https://data.pyg.org/whl/torch-2.10.0+${CUDA}.html
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pip install torch-scatter -f https://data.pyg.org/whl/torch-2.11.0+${CUDA}.html
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```
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where `${CUDA}` should be replaced by either `cpu`, `cu126`, `cu128`, or `cu130` depending on your PyTorch installation.
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| **Windows** |||||
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| **macOS** || | | |
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#### PyTorch 2.9
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#### PyTorch 2.10
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To install the binaries for PyTorch 2.9, simply run
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To install the binaries for PyTorch 2.10, simply run
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```
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pip install torch-scatter -f https://data.pyg.org/whl/torch-2.9.0+${CUDA}.html
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pip install torch-scatter -f https://data.pyg.org/whl/torch-2.10.0+${CUDA}.html
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```
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where `${CUDA}` should be replaced by either `cpu`, `cu126`, `cu128`, or `cu130` depending on your PyTorch installation.
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| **Windows** |||||
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| **macOS** || | | |
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#### PyTorch 2.8
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#### PyTorch 2.9
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To install the binaries for PyTorch 2.8, simply run
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To install the binaries for PyTorch 2.9, simply run
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```
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pip install torch-scatter -f https://data.pyg.org/whl/torch-2.8.0+${CUDA}.html
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pip install torch-scatter -f https://data.pyg.org/whl/torch-2.9.0+${CUDA}.html
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```
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where `${CUDA}` should be replaced by either `cpu`, `cu126`, `cu128`, or `cu129` depending on your PyTorch installation.
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where `${CUDA}` should be replaced by either `cpu`, `cu126`, `cu128`, or `cu130` depending on your PyTorch installation.
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| | `cpu` | `cu126` | `cu128` | `cu129` |
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| | `cpu` | `cu126` | `cu128` | `cu130` |
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|-------------|-------|---------|---------|---------|
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| **Linux** |||||
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| **Windows** |||||
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| **macOS** || | | |
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**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, PyTorch 2.2.0/2.2.1/2.2.2, PyTorch 2.3.0/2.3.1, PyTorch 2.4.0/2.4.1, PyTorch 2.5.0/2.5.1, PyTorch 2.6.0, and PyTorch 2.7.0/2.7.1 (following the same procedure).
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**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, PyTorch 2.2.0/2.2.1/2.2.2, PyTorch 2.3.0/2.3.1, PyTorch 2.4.0/2.4.1, PyTorch 2.5.0/2.5.1, PyTorch 2.6.0, PyTorch 2.7.0/2.7.1, and PyTorch 2.8.0 (following the same procedure).
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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.
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You can look up the latest supported version number [here](https://data.pyg.org/whl).
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