pytorch 1.9.0

.github/workflows/building.yml

+name: Building Wheels
+
+on: [workflow_dispatch]
+
+jobs:
+
+  wheel:
+    runs-on: ${{ matrix.os }}
+
+    strategy:
+      fail-fast: false
+      matrix:
+        os: [ubuntu-18.04, macos-10.15, windows-latest]
+        python-version: [3.6, 3.7, 3.8, 3.9]
+        torch-version: [1.8.0, 1.9.0]
+        cuda-version: ['cpu', 'cu101', 'cu102', 'cu111']
+        exclude:
+          - torch-version: 1.9.0
+            cuda-version: 'cu101'
+          - os: macos-10.15
+            cuda-version: 'cu101'
+          - os: macos-10.15
+            cuda-version: 'cu102'
+          - os: macos-10.15
+            cuda-version: 'cu111'
+          - os: windows-latest
+            cuda-version: 'cu101'
+
+    steps:
+      - uses: actions/checkout@v2
+      - name: Set up Python ${{ matrix.python-version }}
+        uses: actions/setup-python@v2
+        with:
+          python-version: ${{ matrix.python-version }}
+
+      - name: Update pip
+        run: |
+          pip install --upgrade pip
+
+      - name: Install CUDA ${{ matrix.cuda-version }}
+        if: ${{ matrix.cuda-version != 'cpu' }}
+        run: |
+          bash .github/workflows/cuda/${{ matrix.cuda-version }}-${{ runner.os }}.sh
+
+      - name: Install PyTorch ${{ matrix.torch-version }}+${{ matrix.cuda-version }}
+        run: |
+          pip install numpy typing-extensions dataclasses
+          pip install --no-index --no-cache-dir torch==${{ matrix.torch-version}} -f https://download.pytorch.org/whl/${{ matrix.cuda-version }}/torch_stable.html
+          python -c "import torch; print('PyTorch:', torch.__version__)"
+          python -c "import torch; print('CUDA:', torch.version.cuda)"
+
+      - name: Install main package for CPU
+        if: ${{ matrix.cuda-version == 'cpu' }}
+        run: |
+          FORCE_ONLY_CPU=1 pip install -e .
+        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
+          FORCE_CUDA=1 pip install -e .
+        shell:
+          bash
+
+      - name: Build wheel
+        run: |
+          pip install wheel
+          python setup.py bdist_wheel --dist-dir=dist
+
+      - name: Configure AWS
+        uses: aws-actions/configure-aws-credentials@v1
+        with:
+          aws-access-key-id: ${{ secrets.AWS_KEY_ID }}
+          aws-secret-access-key: ${{ secrets.AWS_SECRET_ACCESS_KEY }}
+          aws-region: us-east-1
+
+      - name: Upload wheel
+        run: |
+          aws s3 sync dist s3://pytorch-geometric.com/whl/torch-${{ matrix.torch-version }}+${{ matrix.cuda-version }} --grants read=uri=http://acs.amazonaws.com/groups/global/AllUsers

.github/workflows/cuda/cu101-Linux-env.sh

+#!/bin/bash
+
+CUDA_HOME=/usr/local/cuda-10.1
+LD_LIBRARY_PATH=${CUDA_HOME}/lib64:${LD_LIBRARY_PATH}
+PATH=${CUDA_HOME}/bin:${PATH}

.github/workflows/cuda/cu101-Linux.sh

+#!/bin/bash
+
+wget -nv https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/cuda-ubuntu1804.pin
+sudo mv cuda-ubuntu1804.pin /etc/apt/preferences.d/cuda-repository-pin-600
+wget -nv https://developer.download.nvidia.com/compute/cuda/10.1/Prod/local_installers/cuda-repo-ubuntu1804-10-1-local-10.1.243-418.87.00_1.0-1_amd64.deb
+sudo dpkg -i cuda-repo-ubuntu1804-10-1-local-10.1.243-418.87.00_1.0-1_amd64.deb
+sudo apt-key add /var/cuda-repo-10-1-local-10.1.243-418.87.00/7fa2af80.pub
+
+sudo apt-get -qq update
+sudo apt install cuda-nvcc-10-1 cuda-libraries-dev-10-1
+sudo apt clean
+
+rm -f https://developer.download.nvidia.com/compute/cuda/10.1/Prod/local_installers/cuda-repo-ubuntu1804-10-1-local-10.1.243-418.87.00_1.0-1_amd64.deb

.github/workflows/cuda/cu101-Windows-env.sh

+#!/bin/bash
+
+CUDA_HOME=/c/Program\ Files/NVIDIA\ GPU\ Computing\ Toolkit/CUDA/v10.1
+PATH=${CUDA_HOME}/bin:$PATH
+PATH=/c/Program\ Files\ \(x86\)/Microsoft\ Visual\ Studio/2017/BuildTools/MSBuild/15.0/Bin:$PATH

.github/workflows/cuda/cu101-Windows.sh

+#!/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=10.1
+export CUDA_URL=https://developer.download.nvidia.com/compute/cuda/${CUDA_SHORT}/Prod/local_installers/
+export CUDA_FILE=cuda_${CUDA_SHORT}.243_426.00_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} npp_dev_${CUDA_SHORT} nvrtc_dev_${CUDA_SHORT} nvml_dev_${CUDA_SHORT}\" -Wait -NoNewWindow"
+echo "Done!"
+rm -f "${CUDA_FILE}"

.github/workflows/cuda/cu102-Linux-env.sh

+#!/bin/bash
+
+CUDA_HOME=/usr/local/cuda-10.2
+LD_LIBRARY_PATH=${CUDA_HOME}/lib64:${LD_LIBRARY_PATH}
+PATH=${CUDA_HOME}/bin:${PATH}

.github/workflows/cuda/cu102-Linux.sh

+#!/bin/bash
+
+wget -nv https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/cuda-ubuntu1804.pin
+sudo mv cuda-ubuntu1804.pin /etc/apt/preferences.d/cuda-repository-pin-600
+wget -nv https://developer.download.nvidia.com/compute/cuda/10.2/Prod/local_installers/cuda-repo-ubuntu1804-10-2-local-10.2.89-440.33.01_1.0-1_amd64.deb
+sudo dpkg -i cuda-repo-ubuntu1804-10-2-local-10.2.89-440.33.01_1.0-1_amd64.deb
+sudo apt-key add /var/cuda-repo-10-2-local-10.2.89-440.33.01/7fa2af80.pub
+
+sudo apt-get -qq update
+sudo apt install cuda-nvcc-10-2 cuda-libraries-dev-10-2
+sudo apt clean
+
+rm -f https://developer.download.nvidia.com/compute/cuda/10.2/Prod/local_installers/cuda-repo-ubuntu1804-10-2-local-10.2.89-440.33.01_1.0-1_amd64.deb

.github/workflows/cuda/cu102-Windows-env.sh

+#!/bin/bash
+
+CUDA_HOME=/c/Program\ Files/NVIDIA\ GPU\ Computing\ Toolkit/CUDA/v10.2
+PATH=${CUDA_HOME}/bin:$PATH
+PATH=/c/Program\ Files\ \(x86\)/Microsoft\ Visual\ Studio/2017/BuildTools/MSBuild/15.0/Bin:$PATH

.github/workflows/cuda/cu102-Windows.sh

+#!/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=10.2
+export CUDA_URL=https://developer.download.nvidia.com/compute/cuda/${CUDA_SHORT}/Prod/local_installers
+export CUDA_FILE=cuda_${CUDA_SHORT}.89_441.22_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} npp_dev_${CUDA_SHORT} nvrtc_dev_${CUDA_SHORT} nvml_dev_${CUDA_SHORT}\" -Wait -NoNewWindow"
+echo "Done!"
+rm -f "${CUDA_FILE}"

.github/workflows/cuda/cu111-Linux-env.sh

+#!/bin/bash
+
+CUDA_HOME=/usr/local/cuda-11.1
+LD_LIBRARY_PATH=${CUDA_HOME}/lib64:${LD_LIBRARY_PATH}
+PATH=${CUDA_HOME}/bin:${PATH}

.github/workflows/cuda/cu111-Linux.sh

+#!/bin/bash
+
+wget -nv https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/cuda-ubuntu1804.pin
+sudo mv cuda-ubuntu1804.pin /etc/apt/preferences.d/cuda-repository-pin-600
+wget -nv https://developer.download.nvidia.com/compute/cuda/11.1.1/local_installers/cuda-repo-ubuntu1804-11-1-local_11.1.1-455.32.00-1_amd64.deb
+sudo dpkg -i cuda-repo-ubuntu1804-11-1-local_11.1.1-455.32.00-1_amd64.deb
+sudo apt-key add /var/cuda-repo-ubuntu1804-11-1-local/7fa2af80.pub
+
+sudo apt-get -qq update
+sudo apt install cuda-nvcc-11-1 cuda-libraries-dev-11-1
+sudo apt clean
+
+rm -f https://developer.download.nvidia.com/compute/cuda/11.1.1/local_installers/cuda-repo-ubuntu1804-11-1-local_11.1.1-455.32.00-1_amd64.deb

.github/workflows/cuda/cu111-Windows-env.sh

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

.github/workflows/cuda/cu111-Windows.sh

+#!/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=11.1
+export CUDA_URL=https://developer.download.nvidia.com/compute/cuda/${CUDA_SHORT}.1/local_installers
+export CUDA_FILE=cuda_${CUDA_SHORT}.1_456.81_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} npp_dev_${CUDA_SHORT} nvrtc_dev_${CUDA_SHORT} nvml_dev_${CUDA_SHORT}\" -Wait -NoNewWindow"
+echo "Done!"
+rm -f "${CUDA_FILE}"

.github/workflows/linting.yml

+name: Linting
+
+on: [push, pull_request]
+
+jobs:
+
+  flake8:
+    runs-on: ${{ matrix.os }}
+
+    strategy:
+      matrix:
+        os: [ubuntu-latest]
+        python-version: [3.6]
+
+    steps:
+      - uses: actions/checkout@v2
+      - name: Set up Python ${{ matrix.python-version }}
+        uses: actions/setup-python@v2
+        with:
+          python-version: ${{ matrix.python-version }}
+
+      - name: Install dependencies
+        run: |
+          pip install flake8
+
+      - name: Run linting
+        run: |
+          flake8 .

.github/workflows/testing.yml

+name: Testing
+
+on: [push, pull_request]
+
+jobs:
+
+  pytest:
+    runs-on: ${{ matrix.os }}
+
+    strategy:
+      matrix:
+        os: [ubuntu-latest, windows-latest]
+        python-version: [3.6]
+        torch-version: [1.8.0, 1.9.0]
+
+    steps:
+      - uses: actions/checkout@v2
+      - name: Set up Python ${{ matrix.python-version }}
+        uses: actions/setup-python@v2
+        with:
+          python-version: ${{ matrix.python-version }}
+
+      - name: Update pip
+        run: |
+          pip install --upgrade pip
+
+      - name: Install PyTorch ${{ matrix.torch-version }}
+        run: |
+          pip install torch==${{ matrix.torch-version}}+cpu -f https://download.pytorch.org/whl/torch_stable.html
+
+      - name: Install main package
+        run: |
+          pip install -e .[test]
+
+      - name: Run test-suite
+        run: |
+          python setup.py test
+
+      - name: Generate coverage report
+        if: success()
+        run: |
+          pip install coverage
+          coverage xml
+
+      - name: Upload coverage report to codecov
+        uses: codecov/codecov-action@v1
+        if: success()
+        with:
+          file: coverage.xml

.travis.yml

-language: shell
-
-os:
-  - linux
-  - osx
-  - windows
-
-env:
-  global:
-    - CUDA_HOME=/usr/local/cuda
-  jobs:
-    # Python 3.6
-    - PYTHON_VERSION=3.6 TORCH_VERSION=1.8.0 IDX=cpu
-    - PYTHON_VERSION=3.6 TORCH_VERSION=1.8.0 IDX=cu101
-    - PYTHON_VERSION=3.6 TORCH_VERSION=1.8.0 IDX=cu102
-    - PYTHON_VERSION=3.6 TORCH_VERSION=1.8.0 IDX=cu111
-    - PYTHON_VERSION=3.6 TORCH_VERSION=1.7.0 IDX=cpu
-    - PYTHON_VERSION=3.6 TORCH_VERSION=1.7.0 IDX=cu92
-    - PYTHON_VERSION=3.6 TORCH_VERSION=1.7.0 IDX=cu101
-    - PYTHON_VERSION=3.6 TORCH_VERSION=1.7.0 IDX=cu102
-    - PYTHON_VERSION=3.6 TORCH_VERSION=1.7.0 IDX=cu110
-    # Python 3.7
-    - PYTHON_VERSION=3.7 TORCH_VERSION=1.8.0 IDX=cpu
-    - PYTHON_VERSION=3.7 TORCH_VERSION=1.8.0 IDX=cu101
-    - PYTHON_VERSION=3.7 TORCH_VERSION=1.8.0 IDX=cu102
-    - PYTHON_VERSION=3.7 TORCH_VERSION=1.8.0 IDX=cu111
-    - PYTHON_VERSION=3.7 TORCH_VERSION=1.7.0 IDX=cpu
-    - PYTHON_VERSION=3.7 TORCH_VERSION=1.7.0 IDX=cu92
-    - PYTHON_VERSION=3.7 TORCH_VERSION=1.7.0 IDX=cu101
-    - PYTHON_VERSION=3.7 TORCH_VERSION=1.7.0 IDX=cu102
-    - PYTHON_VERSION=3.7 TORCH_VERSION=1.7.0 IDX=cu110
-    # Python 3.8
-    - PYTHON_VERSION=3.8 TORCH_VERSION=1.8.0 IDX=cpu
-    - PYTHON_VERSION=3.8 TORCH_VERSION=1.8.0 IDX=cu101
-    - PYTHON_VERSION=3.8 TORCH_VERSION=1.8.0 IDX=cu102
-    - PYTHON_VERSION=3.8 TORCH_VERSION=1.8.0 IDX=cu111
-    - PYTHON_VERSION=3.8 TORCH_VERSION=1.7.0 IDX=cpu
-    - PYTHON_VERSION=3.8 TORCH_VERSION=1.7.0 IDX=cu92
-    - PYTHON_VERSION=3.8 TORCH_VERSION=1.7.0 IDX=cu101
-    - PYTHON_VERSION=3.8 TORCH_VERSION=1.7.0 IDX=cu102
-    - PYTHON_VERSION=3.8 TORCH_VERSION=1.7.0 IDX=cu110
-
-jobs:
-  # For daily builds, we only test on Python 3.6 with 11.0/11.1.
-  # For deployment, we exclude *all* macOS CUDA and Windows CUDA 9.2 jobs.
-  exclude:
-    # Python 3.6 / PyTorch 1.8.0
-    - if: not (tag is present or commit_message =~ ci-deploy) and os != osx
-      env: PYTHON_VERSION=3.6 TORCH_VERSION=1.8.0 IDX=cpu
-    - if: not (tag is present or commit_message =~ ci-deploy) or os = osx
-      env: PYTHON_VERSION=3.6 TORCH_VERSION=1.8.0 IDX=cu101
-    - if: not (tag is present or commit_message =~ ci-deploy) or os = osx
-      env: PYTHON_VERSION=3.6 TORCH_VERSION=1.8.0 IDX=cu102
-    - if: os = osx
-      env: PYTHON_VERSION=3.6 TORCH_VERSION=1.8.0 IDX=cu111
-    # Python 3.6 / PyTorch 1.7.0
-    - if: not (tag is present or commit_message =~ ci-deploy) and os != osx
-      env: PYTHON_VERSION=3.6 TORCH_VERSION=1.7.0 IDX=cpu
-    - if: not (tag is present or commit_message =~ ci-deploy) or os != linux
-      env: PYTHON_VERSION=3.6 TORCH_VERSION=1.7.0 IDX=cu92
-    - if: not (tag is present or commit_message =~ ci-deploy) or os = osx
-      env: PYTHON_VERSION=3.6 TORCH_VERSION=1.7.0 IDX=cu101
-    - if: not (tag is present or commit_message =~ ci-deploy) or os = osx
-      env: PYTHON_VERSION=3.6 TORCH_VERSION=1.7.0 IDX=cu102
-    - if: os = osx
-      env: PYTHON_VERSION=3.6 TORCH_VERSION=1.7.0 IDX=cu110
-    # Python 3.7 / PyTorch 1.8.0
-    - if: not (tag is present or commit_message =~ ci-deploy)
-      env: PYTHON_VERSION=3.7 TORCH_VERSION=1.8.0 IDX=cpu
-    - if: not (tag is present or commit_message =~ ci-deploy) or os = osx
-      env: PYTHON_VERSION=3.7 TORCH_VERSION=1.8.0 IDX=cu101
-    - if: not (tag is present or commit_message =~ ci-deploy) or os = osx
-      env: PYTHON_VERSION=3.7 TORCH_VERSION=1.8.0 IDX=cu102
-    - if: not (tag is present or commit_message =~ ci-deploy) or os = osx
-      env: PYTHON_VERSION=3.7 TORCH_VERSION=1.8.0 IDX=cu111
-    - if: not (tag is present or commit_message =~ ci-deploy)
-    # Python 3.7 / PyTorch 1.7.0
-      env: PYTHON_VERSION=3.7 TORCH_VERSION=1.7.0 IDX=cpu
-    - if: not (tag is present or commit_message =~ ci-deploy) or os != linux
-      env: PYTHON_VERSION=3.7 TORCH_VERSION=1.7.0 IDX=cu92
-    - if: not (tag is present or commit_message =~ ci-deploy) or os = osx
-      env: PYTHON_VERSION=3.7 TORCH_VERSION=1.7.0 IDX=cu101
-    - if: not (tag is present or commit_message =~ ci-deploy) or os = osx
-      env: PYTHON_VERSION=3.7 TORCH_VERSION=1.7.0 IDX=cu102
-    - if: not (tag is present or commit_message =~ ci-deploy) or os = osx
-      env: PYTHON_VERSION=3.7 TORCH_VERSION=1.7.0 IDX=cu110
-    # Python 3.8 / PyTorch 1.8.0
-    - if: not (tag is present or commit_message =~ ci-deploy)
-      env: PYTHON_VERSION=3.8 TORCH_VERSION=1.8.0 IDX=cpu
-    - if: not (tag is present or commit_message =~ ci-deploy) or os = osx
-      env: PYTHON_VERSION=3.8 TORCH_VERSION=1.8.0 IDX=cu101
-    - if: not (tag is present or commit_message =~ ci-deploy) or os = osx
-      env: PYTHON_VERSION=3.8 TORCH_VERSION=1.8.0 IDX=cu102
-    - if: not (tag is present or commit_message =~ ci-deploy) or os = osx
-      env: PYTHON_VERSION=3.8 TORCH_VERSION=1.8.0 IDX=cu111
-    - if: not (tag is present or commit_message =~ ci-deploy)
-    # Python 3.8 / PyTorch 1.7.0
-      env: PYTHON_VERSION=3.8 TORCH_VERSION=1.7.0 IDX=cpu
-    - if: not (tag is present or commit_message =~ ci-deploy) or os != linux
-      env: PYTHON_VERSION=3.8 TORCH_VERSION=1.7.0 IDX=cu92
-    - if: not (tag is present or commit_message =~ ci-deploy) or os = osx
-      env: PYTHON_VERSION=3.8 TORCH_VERSION=1.7.0 IDX=cu101
-    - if: not (tag is present or commit_message =~ ci-deploy) or os = osx
-      env: PYTHON_VERSION=3.8 TORCH_VERSION=1.7.0 IDX=cu102
-    - if: not (tag is present or commit_message =~ ci-deploy) or os = osx
-      env: PYTHON_VERSION=3.8 TORCH_VERSION=1.7.0 IDX=cu110
-
-install:
-  - source script/gcc.sh
-  - source script/cuda.sh
-  - source script/conda.sh
-  - conda create --yes -n test python="${PYTHON_VERSION}"
-  - source activate test
-  - conda install pytorch=${TORCH_VERSION} ${TOOLKIT} -c pytorch -c conda-forge --yes
-  - source script/torch.sh
-  - pip install flake8
-  - pip install codecov
-  - pip install scipy==1.4.1
-  - travis_wait 30 pip install -e .[test]
-script:
-  - flake8 .
-  - python setup.py test
-after_success:
-  - python setup.py bdist_wheel --dist-dir=dist
-  - ls -lah dist/
-  - codecov
-deploy:
-  provider: s3
-  region: eu-central-1
-  edge: true
-  access_key_id: ${S3_ACCESS_KEY}
-  secret_access_key: ${S3_SECRET_ACCESS_KEY}
-  bucket: pytorch-geometric.com
-  local_dir: dist
-  upload_dir: whl/torch-${TORCH_VERSION}+${IDX}
-  acl: public_read
-  on:
-    all_branches: true
-    repo: rusty1s/pytorch_cluster
-    condition: $TRAVIS_TAG != "" || $TRAVIS_COMMIT_MESSAGE =~ ci-deploy
-notifications:
-  email: false

README.md

 [pypi-image]: https://badge.fury.io/py/torch-cluster.svg
 [pypi-url]: https://pypi.python.org/pypi/torch-cluster
-[build-image]: https://travis-ci.org/rusty1s/pytorch_cluster.svg?branch=master
-[build-url]: https://travis-ci.org/rusty1s/pytorch_cluster
+[testing-image]: https://github.com/rusty1s/pytorch_cluster/actions/workflows/testing.yml/badge.svg
+[testing-url]: https://github.com/rusty1s/pytorch_cluster/actions/workflows/testing.yml
+[linting-image]: https://github.com/rusty1s/pytorch_cluster/actions/workflows/linting.yml/badge.svg
+[linting-url]: https://github.com/rusty1s/pytorch_cluster/actions/workflows/linting.yml
 [coverage-image]: https://codecov.io/gh/rusty1s/pytorch_cluster/branch/master/graph/badge.svg
 [coverage-url]: https://codecov.io/github/rusty1s/pytorch_cluster?branch=master
 
 # PyTorch Cluster
 
 [![PyPI Version][pypi-image]][pypi-url]
-[![Build Status][build-image]][build-url]
+[![Testing Status][testing-image]][testing-url]
+[![Linting Status][linting-image]][linting-url]
 [![Code Coverage][coverage-image]][coverage-url]
 
 --------------------------------------------------------------------------------
@@ -31,39 +34,39 @@ All included operations work on varying data types and are implemented both for
 
 We provide pip wheels for all major OS/PyTorch/CUDA combinations, see [here](https://s3.eu-central-1.amazonaws.com/pytorch-geometric.com/whl/index.html).
 
-#### PyTorch 1.8.0
+#### PyTorch 1.9.0
 
-To install the binaries for PyTorch 1.8.0, simply run
+To install the binaries for PyTorch 1.9.0, simply run
 
 ```
-pip install torch-cluster -f https://pytorch-geometric.com/whl/torch-1.8.0+${CUDA}.html
+pip install torch-cluster -f https://pytorch-geometric.com/whl/torch-1.9.0+${CUDA}.html
 ```
 
-where `${CUDA}` should be replaced by either `cpu`, `cu101`, `cu102`, or `cu111` depending on your PyTorch installation.
+where `${CUDA}` should be replaced by either `cpu`, `cu102`, or `cu111` depending on your PyTorch installation.
 
-|             | `cpu` | `cu101` | `cu102` | `cu111` |
-|-------------|-------|---------|---------|---------|
-| **Linux**   | ✅    | ✅      | ✅      | ✅      |
-| **Windows** | ✅    | ✅      | ✅      | ✅      |
-| **macOS**   | ✅    |         |         |         |
+|             | `cpu` | `cu102` | `cu111` |
+|-------------|-------|---------|---------|
+| **Linux**   | ✅    | ✅      | ✅      |
+| **Windows** | ✅    | ✅      | ✅      |
+| **macOS**   | ✅    |         |         |
 
-#### PyTorch 1.7.0/1.7.1
+#### PyTorch 1.8.0/1.8.1
 
-To install the binaries for PyTorch 1.7.0 and 1.7.1, simply run
+To install the binaries for PyTorch 1.8.0 and 1.8.1, simply run
 
 ```
-pip install torch-cluster -f https://pytorch-geometric.com/whl/torch-1.7.0+${CUDA}.html
+pip install torch-cluster -f https://pytorch-geometric.com/whl/torch-1.8.0+${CUDA}.html
 ```
 
-where `${CUDA}` should be replaced by either `cpu`, `cu92`, `cu101`, `cu102`, or `cu110` depending on your PyTorch installation.
+where `${CUDA}` should be replaced by either `cpu`,`cu101`, `cu102`, or `cu111` depending on your PyTorch installation.
 
-|             | `cpu` | `cu92` | `cu101` | `cu102` | `cu110` |
-|-------------|-------|--------|---------|---------|---------|
-| **Linux**   | ✅    | ✅     | ✅      | ✅      | ✅      |
-| **Windows** | ✅    | ❌     | ✅      | ✅      | ✅      |
-| **macOS**   | ✅    |        |         |         |         |
+|             | `cpu` | `cu101` | `cu102` | `cu111` |
+|-------------|-------|---------|---------|---------|
+| **Linux**   | ✅    | ✅      | ✅      | ✅      |
+| **Windows** | ✅    | ❌      | ✅      | ✅      |
+| **macOS**   | ✅    |         |         |         |
 
-**Note:** Binaries of older versions are also provided for PyTorch 1.4.0, PyTorch 1.5.0 and PyTorch 1.6.0 (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 and PyTorch 1.7.0/1.7.1 (following the same procedure).
 
 ### From source
 

script/conda.sh

-#!/bin/bash
-
-if [ "${TRAVIS_OS_NAME}" = "linux" ]; then
-  wget -nv https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh -O miniconda.sh
-  chmod +x miniconda.sh
-  ./miniconda.sh -b
-  PATH=/home/travis/miniconda3/bin:${PATH}
-fi
-
-if [ "${TRAVIS_OS_NAME}" = "osx" ]; then
-  wget -nv https://repo.anaconda.com/miniconda/Miniconda3-latest-MacOSX-x86_64.sh -O miniconda.sh
-  chmod +x miniconda.sh
-  ./miniconda.sh -b
-  PATH=/Users/travis/miniconda3/bin:${PATH}
-fi
-
-
-if [ "${TRAVIS_OS_NAME}" = "windows" ]; then
-  choco install openssl.light
-  choco install miniconda3
-  PATH=/c/tools/miniconda3/Scripts:$PATH
-fi
-
-conda update --yes conda
-
-conda create --yes -n test python="${PYTHON_VERSION}"

script/cuda.sh

-#!/bin/bash
-
-if [ "${TRAVIS_OS_NAME}" = "linux" ] && [ "$IDX" = "cpu" ]; then
-  export TOOLKIT=cpuonly
-fi
-
-if [ "${TRAVIS_OS_NAME}" = "linux" ] && [ "$IDX" = "cu92" ]; then
-  export CUDA_SHORT=9.2
-  export CUDA=9.2.148-1
-  export UBUNTU_VERSION=ubuntu1604
-  export TOOLKIT="cudatoolkit=${CUDA_SHORT}"
-fi
-
-if [ "${TRAVIS_OS_NAME}" = "linux" ] && [ "$IDX" = "cu101" ]; then
-  export IDX=cu101
-  export CUDA_SHORT=10.1
-  export CUDA=10.1.243-1
-  export UBUNTU_VERSION=ubuntu1804
-  export TOOLKIT="cudatoolkit=${CUDA_SHORT}"
-fi
-
-
-if [ "${TRAVIS_OS_NAME}" = "linux" ] && [ "$IDX" = "cu102" ]; then
-  export CUDA_SHORT=10.2
-  export CUDA=10.2.89-1
-  export UBUNTU_VERSION=ubuntu1804
-  export TOOLKIT="cudatoolkit=${CUDA_SHORT}"
-fi
-
-if [ "${TRAVIS_OS_NAME}" = "linux" ] && [ "$IDX" = "cu110" ]; then
-  export CUDA_SHORT=11.0
-  export TOOLKIT="cudatoolkit=${CUDA_SHORT}"
-fi
-
-if [ "${TRAVIS_OS_NAME}" = "linux" ] && [ "$IDX" = "cu111" ]; then
-  export CUDA_SHORT=11.1
-  export TOOLKIT="cudatoolkit=${CUDA_SHORT}"
-fi
-
-if [ "${TRAVIS_OS_NAME}" = "windows" ] && [ "$IDX" = "cpu" ]; then
-  export TOOLKIT=cpuonly
-fi
-
-if [ "${TRAVIS_OS_NAME}" = "windows" ] && [ "$IDX" = "cu92" ]; then
-  export CUDA_SHORT=9.2
-  export CUDA_URL=https://developer.nvidia.com/compute/cuda/${CUDA_SHORT}/Prod2/local_installers2
-  export CUDA_FILE=cuda_${CUDA_SHORT}.148_win10
-  export TOOLKIT="cudatoolkit=${CUDA_SHORT}"
-fi
-
-if [ "${TRAVIS_OS_NAME}" = "windows" ] && [ "$IDX" = "cu101" ]; then
-  export CUDA_SHORT=10.1
-  export CUDA_URL=https://developer.nvidia.com/compute/cuda/${CUDA_SHORT}/Prod/local_installers
-  export CUDA_FILE=cuda_${CUDA_SHORT}.105_418.96_win10.exe
-  export TOOLKIT="cudatoolkit=${CUDA_SHORT}"
-fi
-
-if [ "${TRAVIS_OS_NAME}" = "windows" ] && [ "$IDX" = "cu102" ]; then
-  export CUDA_SHORT=10.2
-  export CUDA_URL=https://developer.download.nvidia.com/compute/cuda/${CUDA_SHORT}/Prod/local_installers
-  export CUDA_FILE=cuda_${CUDA_SHORT}.89_441.22_win10.exe
-  export TOOLKIT="cudatoolkit=${CUDA_SHORT}"
-fi
-
-if [ "${TRAVIS_OS_NAME}" = "windows" ] && [ "$IDX" = "cu110" ]; then
-  export CUDA_SHORT=11.0
-  export CUDA_URL=https://developer.download.nvidia.com/compute/cuda/${CUDA_SHORT}.2/local_installers
-  export CUDA_FILE=cuda_${CUDA_SHORT}.2_451.48_win10.exe
-  export TOOLKIT="cudatoolkit=${CUDA_SHORT}"
-fi
-
-if [ "${TRAVIS_OS_NAME}" = "windows" ] && [ "$IDX" = "cu111" ]; then
-  export CUDA_SHORT=11.1
-  export CUDA_URL=https://developer.download.nvidia.com/compute/cuda/${CUDA_SHORT}.1/local_installers
-  export CUDA_FILE=cuda_${CUDA_SHORT}.1_456.81_win10.exe
-  export TOOLKIT="cudatoolkit=${CUDA_SHORT}"
-fi
-
-if [ "${TRAVIS_OS_NAME}" = "osx" ] && [ "$IDX" = "cpu" ]; then
-  export TOOLKIT=""
-fi
-
-if [ "${IDX}" = "cpu" ]; then
-  export FORCE_ONLY_CPU=1
-else
-  export FORCE_CUDA=1
-fi
-
-if [ "${TRAVIS_OS_NAME}" = "linux" ] && { [ "${IDX}" = "cu92" ] || [ "${IDX}" = "cu101" ] || [ "${IDX}" = "cu102" ]; }; then
-  INSTALLER="cuda-repo-${UBUNTU_VERSION}_${CUDA}_amd64.deb"
-  wget -nv "http://developer.download.nvidia.com/compute/cuda/repos/${UBUNTU_VERSION}/x86_64/${INSTALLER}"
-  sudo dpkg -i "${INSTALLER}"
-  wget -nv "https://developer.download.nvidia.com/compute/cuda/repos/${UBUNTU_VERSION}/x86_64/7fa2af80.pub"
-  sudo apt-key add 7fa2af80.pub
-  sudo apt update -qq
-  sudo apt install "cuda-core-${CUDA_SHORT/./-}" "cuda-nvcc-${CUDA_SHORT/./-}" "cuda-libraries-dev-${CUDA_SHORT/./-}"
-  sudo apt clean
-  CUDA_HOME=/usr/local/cuda-${CUDA_SHORT}
-  LD_LIBRARY_PATH=${CUDA_HOME}/lib64:${LD_LIBRARY_PATH}
-  PATH=${CUDA_HOME}/bin:${PATH}
-  nvcc --version
-
-  # Fix cublas on CUDA 10.2:
-  if [ -d "/usr/local/cuda-10.2/targets/x86_64-linux/include" ]; then
-    sudo cp -r /usr/local/cuda-10.2/targets/x86_64-linux/include/* "${CUDA_HOME}/include/"
-  fi
-  if [ -d "/usr/local/cuda-10.2/targets/x86_64-linux/lib" ]; then
-    sudo cp -r /usr/local/cuda-10.2/targets/x86_64-linux/lib/* "${CUDA_HOME}/lib/"
-  fi
-fi
-
-if [ "${TRAVIS_OS_NAME}" = "linux" ] && [ "${IDX}" = "cu110" ]; then
-  wget -nv https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/cuda-ubuntu1804.pin
-  sudo mv cuda-ubuntu1804.pin /etc/apt/preferences.d/cuda-repository-pin-600
-  wget -nv https://developer.download.nvidia.com/compute/cuda/11.0.3/local_installers/cuda-repo-ubuntu1804-11-0-local_11.0.3-450.51.06-1_amd64.deb
-  sudo dpkg -i cuda-repo-ubuntu1804-11-0-local_11.0.3-450.51.06-1_amd64.deb
-  sudo apt-key add /var/cuda-repo-ubuntu1804-11-0-local/7fa2af80.pub
-  sudo apt update -qq
-  sudo apt install cuda-nvcc-11-0 cuda-libraries-dev-11-0
-  sudo apt clean
-  CUDA_HOME=/usr/local/cuda-${CUDA_SHORT}
-  LD_LIBRARY_PATH=${CUDA_HOME}/lib64:${LD_LIBRARY_PATH}
-  PATH=${CUDA_HOME}/bin:${PATH}
-  nvcc --version
-fi
-
-if [ "${TRAVIS_OS_NAME}" = "linux" ] && [ "${IDX}" = "cu111" ]; then
-  wget -nv https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/cuda-ubuntu1804.pin
-  sudo mv cuda-ubuntu1804.pin /etc/apt/preferences.d/cuda-repository-pin-600
-  wget -nv https://developer.download.nvidia.com/compute/cuda/11.1.1/local_installers/cuda-repo-ubuntu1804-11-1-local_11.1.1-455.32.00-1_amd64.deb
-  sudo dpkg -i cuda-repo-ubuntu1804-11-1-local_11.1.1-455.32.00-1_amd64.deb
-  sudo apt-key add /var/cuda-repo-ubuntu1804-11-1-local/7fa2af80.pub
-  sudo apt update -qq
-  sudo apt install cuda-nvcc-11-1 cuda-libraries-dev-11-1
-  sudo apt clean
-  CUDA_HOME=/usr/local/cuda-${CUDA_SHORT}
-  LD_LIBRARY_PATH=${CUDA_HOME}/lib64:${LD_LIBRARY_PATH}
-  PATH=${CUDA_HOME}/bin:${PATH}
-  nvcc --version
-fi
-
-if [ "${TRAVIS_OS_NAME}" = "windows" ] && [ "${IDX}" != "cpu" ]; then
-  # Install NVIDIA drivers, see:
-  # https://github.com/pytorch/vision/blob/master/packaging/windows/internal/cuda_install.bat#L99-L102
-  curl -k -L "https://drive.google.com/u/0/uc?id=1injUyo3lnarMgWyRcXqKg4UGnN0ysmuq&export=download" --output "/tmp/gpu_driver_dlls.zip"
-  7z x "/tmp/gpu_driver_dlls.zip" -o"/c/Windows/System32"
-
-  # Install CUDA:
-  wget -nv "${CUDA_URL}/${CUDA_FILE}"
-  PowerShell -Command "Start-Process -FilePath \"${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} npp_dev_${CUDA_SHORT} nvrtc_dev_${CUDA_SHORT} nvml_dev_${CUDA_SHORT}\" -Wait -NoNewWindow"
-  CUDA_HOME=/c/Program\ Files/NVIDIA\ GPU\ Computing\ Toolkit/CUDA/v${CUDA_SHORT}
-  PATH=${CUDA_HOME}/bin:$PATH
-  PATH=/c/Program\ Files\ \(x86\)/Microsoft\ Visual\ Studio/2017/BuildTools/MSBuild/15.0/Bin:$PATH
-  nvcc --version
-fi

script/gcc.sh

-#!/bin/bash
-
-if [ "${TRAVIS_OS_NAME}" = "linux" ]; then
-  sudo add-apt-repository ppa:ubuntu-toolchain-r/test --yes
-  sudo apt update
-  sudo apt install gcc-7 g++-7 --yes
-  sudo update-alternatives --install /usr/bin/gcc gcc /usr/bin/gcc-7 60 \
-                           --slave /usr/bin/g++ g++ /usr/bin/g++-7
-  sudo update-alternatives --config gcc
-  gcc --version
-  g++ --version
-fi
-