update (#485)

Author: rusty1s

.github/workflows/building.yml

@@ -10,25 +10,31 @@ jobs:
     strategy:
       fail-fast: false
       matrix:
-        os: [ubuntu-20.04, macos-14, windows-2019, ubuntu-22.04-arm]
+        os: [ubuntu-22.04, macos-14, windows-2019, ubuntu-22.04-arm]
         python-version: ['3.9', '3.10', '3.11', '3.12', '3.13']
-        torch-version: [2.6.0]  # [2.5.0]
-        cuda-version: ['cpu', 'cu118', 'cu121', 'cu124', 'cu126']
+        torch-version: [2.7.0]  # [2.6.0]
+        cuda-version: ['cpu', 'cu118', 'cu124', 'cu126', 'cu128']
         exclude:
-          - torch-version: 2.5.0
-            python-version: '3.13'
-          - torch-version: 2.5.0
-            cuda-version: 'cu126'
           - torch-version: 2.6.0
-            cuda-version: 'cu121'
+            cuda-version: 'cu128'
+          - torch-version: 2.7.0
+            cuda-version: 'cu124'
           - os: macos-14
             cuda-version: 'cu118'
-          - os: macos-14
-            cuda-version: 'cu121'
           - os: macos-14
             cuda-version: 'cu124'
           - os: macos-14
             cuda-version: 'cu126'
+          - os: macos-14
+            cuda-version: 'cu128'
+          - os: ubuntu-22.04-arm
+            cuda-version: 'cu118'
+          - os: ubuntu-22.04-arm
+            cuda-version: 'cu124'
+          - os: ubuntu-22.04-arm
+            cuda-version: 'cu126'
+          - os: ubuntu-22.04-arm
+            cuda-version: 'cu128'
 
     steps:
       - uses: actions/checkout@v2
@@ -79,15 +85,15 @@ jobs:
       - name: Install main package for CPU
         if: ${{ matrix.cuda-version == 'cpu' }}
         run: |
-          FORCE_ONLY_CPU=1 python setup.py develop
+          FORCE_ONLY_CPU=1 pip install -e . --no-build-isolation
         shell:
           bash
 
       - name: Install main package for GPU
         if: ${{ matrix.cuda-version != 'cpu' }}
         run: |
           source .github/workflows/cuda/${{ matrix.cuda-version }}-${{ runner.os }}-env.sh
-          python setup.py develop
+          pip install -e . --no-build-isolation
         shell:
           bash
 

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

@@ -1,6 +1,6 @@
 #!/bin/bash
 
-OS=ubuntu2004
+OS=ubuntu2204
 
 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

.github/workflows/cuda/cu124-Linux.sh

@@ -1,6 +1,6 @@
 #!/bin/bash
 
-OS=ubuntu2004
+OS=ubuntu2204
 
 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

.github/workflows/cuda/cu126-Linux.sh

@@ -1,6 +1,6 @@
 #!/bin/bash
 
-OS=ubuntu2004
+OS=ubuntu2204
 
 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

.github/workflows/cuda/cu128-Linux-env.sh

@@ -0,0 +1,8 @@
+#!/bin/bash
+
+CUDA_HOME=/usr/local/cuda-12.8
+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"

.github/workflows/cuda/cu128-Linux.sh

@@ -0,0 +1,16 @@
+#!/bin/bash
+
+OS=ubuntu2204
+
+wget -nv https://developer.download.nvidia.com/compute/cuda/repos/${OS}/x86_64/cuda-${OS}.pin
+sudo mv cuda-${OS}.pin /etc/apt/preferences.d/cuda-repository-pin-600
+wget -nv https://developer.download.nvidia.com/compute/cuda/12.8.0/local_installers/cuda-repo-${OS}-12-8-local_12.8.0-570.86.10-1_amd64.deb
+
+sudo dpkg -i cuda-repo-${OS}-12-8-local_12.8.0-570.86.10-1_amd64.deb
+sudo cp /var/cuda-repo-${OS}-12-8-local/cuda-*-keyring.gpg /usr/share/keyrings/
+
+sudo apt-get -qq update
+sudo apt install cuda-nvcc-12-8 cuda-libraries-dev-12-8
+sudo apt clean
+
+rm -f https://developer.download.nvidia.com/compute/cuda/12.8.0/local_installers/cuda-repo-${OS}-12-8-local_12.8.0-570.86.10-1_amd64.deb

.github/workflows/cuda/cu128-Windows-env.sh

@@ -0,0 +1,8 @@
+#!/bin/bash
+
+CUDA_HOME=/c/Program\ Files/NVIDIA\ GPU\ Computing\ Toolkit/CUDA/v12.8
+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/cu128-Windows.sh

@@ -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=12.8
+export CUDA_URL=https://developer.download.nvidia.com/compute/cuda/${CUDA_SHORT}.0/local_installers
+export CUDA_FILE=cuda_${CUDA_SHORT}.0_571.96_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}"

.github/workflows/testing.yml

@@ -14,9 +14,9 @@ jobs:
     strategy:
       fail-fast: false
       matrix:
-        os: [ubuntu-latest, windows-latest, ubuntu-22.04-arm]
+        os: [ubuntu-latest, windows-latest]
         python-version: [3.9]
-        torch-version: [2.5.0, 2.6.0]
+        torch-version: [2.6.0, 2.7.0]
 
     steps:
       - uses: actions/checkout@v2

README.md

@@ -45,40 +45,39 @@ All included operations are broadcastable, work on varying data types, are imple
 
 We provide pip wheels for all major OS/PyTorch/CUDA combinations, see [here](https://data.pyg.org/whl).
 
-#### PyTorch 2.6
+#### PyTorch 2.7
 
-To install the binaries for PyTorch 2.6.0, simply run
+To install the binaries for PyTorch 2.7.0, simply run
 
 ```
 pip install torch-scatter -f https://data.pyg.org/whl/torch-2.6.0+${CUDA}.html
 ```
 
-where `${CUDA}` should be replaced by either `cpu`, `cu118`, `cu124`, or `cu126` depending on your PyTorch installation.
+where `${CUDA}` should be replaced by either `cpu`, `cu118`, `cu126`, or `cu128` depending on your PyTorch installation.
 
-|             | `cpu` | `cu118` | `cu124` | `cu126` |
+|             | `cpu` | `cu118` | `cu126` | `cu128` |
 |-------------|-------|---------|---------|---------|
 | **Linux**   | ✅    | ✅      | ✅      | ✅      |
 | **Windows** | ✅    | ✅      | ✅      | ✅      |
 | **macOS**   | ✅    |         |         |         |
 
+#### PyTorch 2.6
 
-#### PyTorch 2.5
-
-To install the binaries for PyTorch 2.5.0/2.5.1, simply run
+To install the binaries for PyTorch 2.6.0, simply run
 
 ```
-pip install torch-scatter -f https://data.pyg.org/whl/torch-2.5.0+${CUDA}.html
+pip install torch-scatter -f https://data.pyg.org/whl/torch-2.6.0+${CUDA}.html
 ```
 
-where `${CUDA}` should be replaced by either `cpu`, `cu118`, `cu121`, or `cu124` depending on your PyTorch installation.
+where `${CUDA}` should be replaced by either `cpu`, `cu118`, `cu124`, or `cu126` depending on your PyTorch installation.
 
-|             | `cpu` | `cu118` | `cu121` | `cu124` |
+|             | `cpu` | `cu118` | `cu124` | `cu126` |
 |-------------|-------|---------|---------|---------|
 | **Linux**   | ✅    | ✅      | ✅      | ✅      |
 | **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, 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, and PyTorch 2.4.0/2.4.1 (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, PyTorch 2.2.0/2.2.1/2.2.2, PyTorch 2.3.0/2.3.1, PyTorch 2.4.0/2.4.1, and PyTorch 2.5.0/2.5.1 (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).