PyTorch 1.12 support

.github/workflows/building-conda.yml

@@ -12,27 +12,25 @@ jobs:
       matrix:
         os: [ubuntu-18.04, macos-10.15, windows-2019]
         python-version: ['3.7', '3.8', '3.9', '3.10']
-        torch-version: [1.10.0, 1.11.0]
-        cuda-version: ['cpu', 'cu102', 'cu113', 'cu115']
+        torch-version: [1.11.0, 1.12.0]
+        cuda-version: ['cpu', 'cu102', 'cu113', 'cu115', 'cu116']
         exclude:
-          - torch-version: 1.10.0
+          - torch-version: 1.11.0
+            cuda-version: 'cu116'
+          - torch-version: 1.12.0
             cuda-version: 'cu115'
-          - torch-version: 1.10.0
-            python-version: '3.10'
-          - os: windows-2019
-            torch-version: 1.11.0
-            cuda-version: 'cu102'
           - os: macos-10.15
             cuda-version: 'cu102'
           - os: macos-10.15
             cuda-version: 'cu113'
           - os: macos-10.15
             cuda-version: 'cu115'
-          # There is a weird `glibc=2.27` bug going on for this combination:
-          - os: ubuntu-18.04
-            python-version: '3.10'
-          - os: ubuntu-18.04
-            cuda-version: 'cu115'
+          - os: macos-10.15
+            cuda-version: 'cu116'
+          - os: windows-2019
+            cuda-version: 'cu102'
+          - os: windows-2019  # Complains about CUDA mismatch.
+            python-version: '3.7'
 
     steps:
       - uses: actions/checkout@v2

.github/workflows/building.yml

@@ -12,26 +12,25 @@ jobs:
       matrix:
         os: [ubuntu-18.04, macos-10.15, windows-2019]
         python-version: ['3.7', '3.8', '3.9', '3.10']
-        torch-version: [1.10.0, 1.11.0]
-        cuda-version: ['cpu', 'cu102', 'cu113', 'cu115']
+        torch-version: [1.11.0, 1.12.0]
+        cuda-version: ['cpu', 'cu102', 'cu113', 'cu115', 'cu116']
         exclude:
-          - torch-version: 1.10.0
+          - torch-version: 1.11.0
+            cuda-version: 'cu116'
+          - torch-version: 1.12.0
             cuda-version: 'cu115'
-          - torch-version: 1.10.0
-            python-version: '3.10'
-          - os: windows-2019
-            torch-version: 1.11.0
-            cuda-version: 'cu102'
           - os: macos-10.15
             cuda-version: 'cu102'
           - os: macos-10.15
             cuda-version: 'cu113'
           - os: macos-10.15
             cuda-version: 'cu115'
-          # There is a weird bug going on for this combination:
+          - os: macos-10.15
+            cuda-version: 'cu116'
           - os: windows-2019
+            cuda-version: 'cu102'
+          - os: windows-2019  # Complains about CUDA mismatch.
             python-version: '3.7'
-            cuda-version: 'cu115'
 
     steps:
       - uses: actions/checkout@v2

.github/workflows/cuda/cu116-Linux-env.sh

@@ -0,0 +1,8 @@
+#!/bin/bash
+
+CUDA_HOME=/usr/local/cuda-11.6
+LD_LIBRARY_PATH=${CUDA_HOME}/lib64:${LD_LIBRARY_PATH}
+PATH=${CUDA_HOME}/bin:${PATH}
+
+export FORCE_CUDA=1
+export TORCH_CUDA_ARCH_LIST="3.5;5.0+PTX;6.0;7.0;7.5;8.0;8.6"

.github/workflows/cuda/cu116-Linux.sh

@@ -0,0 +1,15 @@
+#!/bin/bash
+
+OS=ubuntu1804
+
+wget -nv https://developer.download.nvidia.com/compute/cuda/repos/${OS}/x86_64/cuda-${OS}.pin
+sudo mv cuda-${OS}.pin /etc/apt/preferences.d/cuda-repository-pin-600
+wget -nv https://developer.download.nvidia.com/compute/cuda/11.6.2/local_installers/cuda-repo-${OS}-11-6-local_11.6.2-510.47.03-1_amd64.deb
+sudo dpkg -i cuda-repo-${OS}-11-6-local_11.6.2-510.47.03-1_amd64.deb
+sudo apt-key add /var/cuda-repo-${OS}-11-6-local/7fa2af80.pub
+
+sudo apt-get -qq update
+sudo apt install cuda-nvcc-11-6 cuda-libraries-dev-11-6
+sudo apt clean
+
+rm -f https://developer.download.nvidia.com/compute/cuda/11.5.2/local_installers/cuda-repo-${OS}-11-6-local_11.6.2-510.47.03-1_amd64.deb

.github/workflows/cuda/cu116-Windows-env.sh

@@ -0,0 +1,8 @@
+#!/bin/bash
+
+CUDA_HOME=/c/Program\ Files/NVIDIA\ GPU\ Computing\ Toolkit/CUDA/v11.3
+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"

.github/workflows/cuda/cu116-Windows.sh

@@ -0,0 +1,20 @@
+#!/bin/bash
+
+# TODO We currently use CUDA 11.3 to build CUDA 11.5 Windows wheels
+
+# 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=11.3
+export CUDA_URL=https://developer.download.nvidia.com/compute/cuda/${CUDA_SHORT}.0/local_installers
+export CUDA_FILE=cuda_${CUDA_SHORT}.0_465.89_win10.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}"

.github/workflows/linting.yml

@@ -32,7 +32,7 @@ jobs:
 
     strategy:
       matrix:
-        torch-version: [1.11.0]
+        torch-version: [1.12.0]
 
     steps:
       - uses: actions/checkout@v2

.github/workflows/testing.yml

@@ -16,7 +16,7 @@ jobs:
       matrix:
         os: [ubuntu-latest, windows-latest]
         python-version: [3.7]
-        torch-version: [1.10.0, 1.11.0]
+        torch-version: [1.11.0, 1.12.0]
 
     steps:
       - uses: actions/checkout@v2

README.md

@@ -54,39 +54,39 @@ conda install pytorch-scatter -c pyg
 
 We alternatively provide pip wheels for all major OS/PyTorch/CUDA combinations, see [here](https://data.pyg.org/whl).
 
-#### PyTorch 1.11
+#### PyTorch 1.12
 
-To install the binaries for PyTorch 1.11.0, simply run
+To install the binaries for PyTorch 1.12.0, simply run
 
 ```
-pip install torch-scatter -f https://data.pyg.org/whl/torch-1.11.0+${CUDA}.html
+pip install torch-scatter -f https://data.pyg.org/whl/torch-1.12.0+${CUDA}.html
 ```
 
-where `${CUDA}` should be replaced by either `cpu`, `cu102`, `cu113`, or `cu115` depending on your PyTorch installation.
+where `${CUDA}` should be replaced by either `cpu`, `cu102`, `cu113`, or `cu116` depending on your PyTorch installation.
 
-|             | `cpu` | `cu102` | `cu113` | `cu115` |
+|             | `cpu` | `cu102` | `cu113` | `cu116` |
 |-------------|-------|---------|---------|---------|
 | **Linux**   | ✅    | ✅      | ✅      | ✅      |
 | **Windows** | ✅    |         | ✅      | ✅      |
 | **macOS**   | ✅    |         |         |         |
 
-#### PyTorch 1.10
+#### PyTorch 1.11
 
-To install the binaries for PyTorch 1.10.0, PyTorch 1.10.1 and PyTorch 1.10.2, simply run
+To install the binaries for PyTorch 1.11.0, simply run
 
 ```
-pip install torch-scatter -f https://data.pyg.org/whl/torch-1.10.0+${CUDA}.html
+pip install torch-scatter -f https://data.pyg.org/whl/torch-1.11.0+${CUDA}.html
 ```
 
-where `${CUDA}` should be replaced by either `cpu`, `cu102`, `cu111`, or `cu113` depending on your PyTorch installation.
+where `${CUDA}` should be replaced by either `cpu`, `cu102`, `cu113`, or `cu115` depending on your PyTorch installation.
 
-|             | `cpu` | `cu102` | `cu111` | `cu113` |
+|             | `cpu` | `cu102` | `cu113` | `cu115` |
 |-------------|-------|---------|---------|---------|
 | **Linux**   | ✅    | ✅      | ✅      | ✅      |
-| **Windows** | ✅    | ✅      | ✅      | ✅      |
+| **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 and PyTorch 1.9.0 (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, and PyTorch 1.10.0/1.10.1/1.10.2 (following the same procedure).
 For older versions, you might need to explicitly specify the latest supported version number in order to prevent a manual installation from source.
 You can look up the latest supported version number [here](https://data.pyg.org/whl).
 

conda/pytorch-scatter/README.md

@@ -1,3 +1,3 @@
 ```
-./build_conda.sh 3.9 1.11.0 cu113  # python, pytorch and cuda version
+./build_conda.sh 3.9 1.12.0 cu113  # python, pytorch and cuda version
 ```

conda/pytorch-scatter/build_conda.sh

@@ -10,6 +10,9 @@ if [ "${CUDA_VERSION}" = "cpu" ]; then
   export CONDA_CUDATOOLKIT_CONSTRAINT="cpuonly  # [not osx]"
 else
   case $CUDA_VERSION in
+    cu116)
+      export CONDA_CUDATOOLKIT_CONSTRAINT="cudatoolkit==11.6.*"
+      ;;
     cu115)
       export CONDA_CUDATOOLKIT_CONSTRAINT="cudatoolkit==11.5.*"
       ;;
@@ -36,4 +39,4 @@ echo "PyTorch $TORCH_VERSION+$CUDA_VERSION"
 echo "- $CONDA_PYTORCH_CONSTRAINT"
 echo "- $CONDA_CUDATOOLKIT_CONSTRAINT"
 
-conda build . -c pytorch -c default -c nvidia --output-folder "$HOME/conda-bld"
+conda build . -c pytorch -c default -c nvidia -c conda-forge --output-folder "$HOME/conda-bld"