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‎.github/workflows/building-conda.yml

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# We have trouble building for Windows - drop for now.
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os: [ubuntu-18.04, macos-10.15] # windows-2019
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python-version: ['3.7', '3.8', '3.9', '3.10']
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torch-version: [1.12.0, 1.13.0]
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cuda-version: ['cpu', 'cu102', 'cu113', 'cu116', 'cu117']
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torch-version: [1.13.0, 2.0.0]
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# We have trouble building for `cu116` due to PyTorch 1.13.0 bugs
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cuda-version: ['cpu', 'cu117', 'cu118']
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exclude:
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- torch-version: 1.12.0
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cuda-version: 'cu117'
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- torch-version: 1.13.0
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cuda-version: 'cu102'
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- torch-version: 2.0.0
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python-version: '3.7'
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- torch-version: 1.13.0
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cuda-version: 'cu113'
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- os: macos-10.15
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cuda-version: 'cu102'
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- os: macos-10.15
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cuda-version: 'cu113'
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- os: macos-10.15
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cuda-version: 'cu116'
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cuda-version: 'cu118'
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- os: macos-10.15
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cuda-version: 'cu117'
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- os: windows-2019
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cuda-version: 'cu102'
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- os: macos-10.15
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cuda-version: 'cu118'
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steps:
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- uses: actions/checkout@v2

‎.github/workflows/building.yml

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fail-fast: false
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matrix:
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os: [ubuntu-18.04, macos-10.15, windows-2019]
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python-version: ['3.7', '3.8', '3.9', '3.10']
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torch-version: [1.12.0, 1.13.0]
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cuda-version: ['cpu', 'cu102', 'cu113', 'cu116', 'cu117']
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python-version: ['3.7', '3.8', '3.9', '3.10', '3.11']
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torch-version: [1.13.0, 2.0.0]
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cuda-version: ['cpu', 'cu116', 'cu117', 'cu118']
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exclude:
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- torch-version: 1.12.0
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cuda-version: 'cu117'
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- torch-version: 1.13.0
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cuda-version: 'cu102'
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python-version: '3.11'
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- torch-version: 2.0.0
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python-version: '3.7'
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- torch-version: 1.13.0
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cuda-version: 'cu113'
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- os: macos-10.15
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cuda-version: 'cu102'
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- os: macos-10.15
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cuda-version: 'cu113'
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cuda-version: 'cu118'
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- torch-version: 2.0.0
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cuda-version: 'cu116'
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- os: macos-10.15
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cuda-version: 'cu116'
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- os: macos-10.15
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cuda-version: 'cu117'
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- os: windows-2019
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cuda-version: 'cu102'
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- os: macos-10.15
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cuda-version: 'cu118'
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steps:
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- uses: actions/checkout@v2

‎.github/workflows/cuda/cu118-Linux-env.sh

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#!/bin/bash
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CUDA_HOME=/usr/local/cuda-11.8
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LD_LIBRARY_PATH=${CUDA_HOME}/lib64:${LD_LIBRARY_PATH}
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PATH=${CUDA_HOME}/bin:${PATH}
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export FORCE_CUDA=1
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export TORCH_CUDA_ARCH_LIST="3.5;5.0+PTX;6.0;7.0;7.5;8.0;8.6"

‎.github/workflows/cuda/cu118-Linux.sh

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#!/bin/bash
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OS=ubuntu1804
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wget -nv https://developer.download.nvidia.com/compute/cuda/repos/${OS}/x86_64/cuda-${OS}.pin
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sudo mv cuda-${OS}.pin /etc/apt/preferences.d/cuda-repository-pin-600
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wget -nv https://developer.download.nvidia.com/compute/cuda/11.8.0/local_installers/cuda-repo-${OS}-11-8-local_11.8.0-520.61.05-1_amd64.deb
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sudo dpkg -i cuda-repo-${OS}-11-8-local_11.8.0-520.61.05-1_amd64.deb
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sudo cp /var/cuda-repo-${OS}-11-8-local/cuda-*-keyring.gpg /usr/share/keyrings/
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sudo apt-get -qq update
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sudo apt install cuda-nvcc-11-8 cuda-libraries-dev-11-8
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sudo apt clean
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rm -f https://developer.download.nvidia.com/compute/cuda/11.8.0/local_installers/cuda-repo-${OS}-11-8-local_11.8.0-520.61.05-1_amd64.deb

‎.github/workflows/cuda/cu118-Windows-env.sh

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#!/bin/bash
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CUDA_HOME=/c/Program\ Files/NVIDIA\ GPU\ Computing\ Toolkit/CUDA/v11.8
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PATH=${CUDA_HOME}/bin:$PATH
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PATH=/c/Program\ Files\ \(x86\)/Microsoft\ Visual\ Studio/2017/BuildTools/MSBuild/15.0/Bin:$PATH
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export FORCE_CUDA=1
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export TORCH_CUDA_ARCH_LIST="6.0+PTX"

‎.github/workflows/cuda/cu118-Windows.sh

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#!/bin/bash
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# Install NVIDIA drivers, see:
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# https://github.com/pytorch/vision/blob/master/packaging/windows/internal/cuda_install.bat#L99-L102
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curl -k -L "https://drive.google.com/u/0/uc?id=1injUyo3lnarMgWyRcXqKg4UGnN0ysmuq&export=download" --output "/tmp/gpu_driver_dlls.zip"
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7z x "/tmp/gpu_driver_dlls.zip" -o"/c/Windows/System32"
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export CUDA_SHORT=11.8
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export CUDA_URL=https://developer.download.nvidia.com/compute/cuda/${CUDA_SHORT}.0/local_installers
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export CUDA_FILE=cuda_${CUDA_SHORT}.0_522.06_windows.exe
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# Install CUDA:
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curl -k -L "${CUDA_URL}/${CUDA_FILE}" --output "${CUDA_FILE}"
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echo ""
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echo "Installing from ${CUDA_FILE}..."
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PowerShell -Command "Start-Process -FilePath \"${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"
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echo "Done!"
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rm -f "${CUDA_FILE}"

‎.github/workflows/linting.yml

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- name: Set up Python
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uses: actions/setup-python@v2
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with:
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python-version: 3.9
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python-version: 3.8
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- name: Install dependencies
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run: |
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- name: Run linting
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run: |
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flake8 .
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pyroma:
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runs-on: ubuntu-latest
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strategy:
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matrix:
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torch-version: [1.13.0]
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steps:
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- uses: actions/checkout@v2
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- name: Set up Python
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uses: actions/setup-python@v2
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with:
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python-version: 3.9
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- name: Install PyTorch ${{ matrix.torch-version }}
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run: |
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pip install torch==${{ matrix.torch-version }} --extra-index-url https://download.pytorch.org/whl/cpu
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- name: Install dependencies
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run: |
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pip install pyroma
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- name: Check package metadata
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run: |
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pyroma --min=10 .

‎.github/workflows/testing.yml

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fail-fast: false
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matrix:
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os: [ubuntu-latest, windows-2019]
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python-version: [3.7]
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torch-version: [1.12.0, 1.13.0]
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python-version: [3.8]
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torch-version: [1.13.0, 2.0.0]
2020

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steps:
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- uses: actions/checkout@v2

‎CMakeLists.txt

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cmake_minimum_required(VERSION 3.10)
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project(torchsparse)
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set(CMAKE_CXX_STANDARD 14)
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set(TORCHSPARSE_VERSION 0.6.16)
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set(TORCHSPARSE_VERSION 0.6.17)
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set(CMAKE_MODULE_PATH ${CMAKE_MODULE_PATH} ${CMAKE_CURRENT_SOURCE_DIR}/cmake)
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option(WITH_CUDA "Enable CUDA support" OFF)

‎README.md

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We alternatively provide pip wheels for all major OS/PyTorch/CUDA combinations, see [here](https://data.pyg.org/whl).
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#### PyTorch 1.13
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#### PyTorch 2.0
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To install the binaries for PyTorch 1.13.0, simply run
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To install the binaries for PyTorch 2.0.0, simply run
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```
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pip install torch-scatter torch-sparse -f https://data.pyg.org/whl/torch-1.13.0+${CUDA}.html
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pip install torch-scatter torch-sparse -f https://data.pyg.org/whl/torch-2.0.0+${CUDA}.html
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```
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where `${CUDA}` should be replaced by either `cpu`, `cu116`, or `cu117` depending on your PyTorch installation.
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where `${CUDA}` should be replaced by either `cpu`, `cu117`, or `cu118` depending on your PyTorch installation.
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| | `cpu` | `cu116` | `cu117` |
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| | `cpu` | `cu117` | `cu118` |
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|-------------|-------|---------|---------|
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| **Linux** | ✅ | ✅ | ✅ |
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| **Windows** | ✅ | ✅ | ✅ |
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| **macOS** | ✅ | | |
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#### PyTorch 1.12
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#### PyTorch 1.13
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To install the binaries for PyTorch 1.12.0, simply run
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To install the binaries for PyTorch 1.13.0, simply run
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```
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pip install torch-scatter torch-sparse -f https://data.pyg.org/whl/torch-1.12.0+${CUDA}.html
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pip install torch-scatter torch-sparse -f https://data.pyg.org/whl/torch-1.13.0+${CUDA}.html
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```
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where `${CUDA}` should be replaced by either `cpu`, `cu102`, `cu113`, or `cu116` depending on your PyTorch installation.
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where `${CUDA}` should be replaced by either `cpu`, `cu116`, or `cu117` depending on your PyTorch installation.
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| | `cpu` | `cu102` | `cu113` | `cu116` |
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|-------------|-------|---------|---------|---------|
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| **Linux** | ✅ | ✅ | ✅ | ✅ |
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| **Windows** | ✅ | | ✅ | ✅ |
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| **macOS** | ✅ | | | |
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| | `cpu` | `cu116` | `cu117` |
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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 and PyTorch 1.11.0 (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 and PyTorch 1.12.0/1.12.1 (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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