[ci skip]

.github/workflows/building-conda.yml

@@ -54,7 +54,7 @@ jobs:
       - name: Build Conda package for CPU
         if: ${{ matrix.cuda-version == 'cpu' }}
         run: |
-          FORCE_CUDA=0 ./conda/pytorch-cluster/build_conda.sh ${{ matrix.python-version }} ${{ matrix.torch-version }} ${{ matrix.cuda-version }}
+          FORCE_CUDA=0 TORCH_CUDA_ARCH_LIST=0 ./conda/pytorch-cluster/build_conda.sh ${{ matrix.python-version }} ${{ matrix.torch-version }} ${{ matrix.cuda-version }}
         shell:
           bash -l {0}
 
@@ -62,15 +62,24 @@ jobs:
         if: ${{ matrix.cuda-version != 'cpu' }}
         run: |
           source .github/workflows/cuda/${{ matrix.cuda-version }}-${{ runner.os }}-env.sh
-          FORCE_CUDA=1 ./conda/pytorch-cluster/build_conda.sh ${{ matrix.python-version }} ${{ matrix.torch-version }} ${{ matrix.cuda-version }}
+          ./conda/pytorch-cluster/build_conda.sh ${{ matrix.python-version }} ${{ matrix.torch-version }} ${{ matrix.cuda-version }}
         shell:
           bash -l {0}
 
-      - name: Publish Conda package
+      - name: Publish Conda package on organization channel
         run: |
           conda install anaconda-client --yes
           anaconda upload --force --label main $HOME/conda-bld/*/*.tar.bz2
         env:
-          ANACONDA_API_TOKEN: ${{ secrets.ANACONDA_TOKEN }}
+          ANACONDA_API_TOKEN: ${{ secrets.PYG_ANACONDA_TOKEN }}
+        shell:
+          bash -l {0}
+
+      - name: Publish Conda package on personal channel
+        run: |
+          conda install anaconda-client --yes
+          anaconda upload --force --label main $HOME/conda-bld/*/*.tar.bz2
+        env:
+          ANACONDA_API_TOKEN: ${{ secrets.RUSTY1S_ANACONDA_TOKEN }}
         shell:
           bash -l {0}

.github/workflows/building.yml

@@ -33,6 +33,11 @@ jobs:
         with:
           python-version: ${{ matrix.python-version }}
 
+      - name: Free up disk space
+        if: ${{ runner.os == 'Linux' }}
+        run: |
+          sudo rm -rf /usr/share/dotnet
+
       - name: Install CUDA ${{ matrix.cuda-version }}
         if: ${{ matrix.cuda-version != 'cpu' }}
         run: |
@@ -56,7 +61,7 @@ jobs:
         if: ${{ matrix.cuda-version != 'cpu' }}
         run: |
           source .github/workflows/cuda/${{ matrix.cuda-version }}-${{ runner.os }}-env.sh
-          FORCE_CUDA=1 TORCH_CUDA_ARCH_LIST="5.2 6.0 6.1 7.0 7.5 8.0 8.6+PTX" pip install -e .
+          pip install -e .
         shell:
           bash
 
@@ -68,10 +73,10 @@ jobs:
       - name: Configure AWS
         uses: aws-actions/configure-aws-credentials@v1
         with:
-          aws-access-key-id: ${{ secrets.AWS_KEY_ID }}
+          aws-access-key-id: ${{ secrets.AWS_ACCESS_KEY_ID }}
           aws-secret-access-key: ${{ secrets.AWS_SECRET_ACCESS_KEY }}
-          aws-region: us-east-1
+          aws-region: us-west-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
+          aws s3 sync dist s3://data.pyg.org/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

@@ -3,3 +3,6 @@
 CUDA_HOME=/usr/local/cuda-10.1
 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"

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

@@ -3,3 +3,6 @@
 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
+
+export FORCE_CUDA=1
+export TORCH_CUDA_ARCH_LIST="3.5;5.0+PTX;6.0;7.0;7.5"

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

@@ -3,3 +3,6 @@
 CUDA_HOME=/usr/local/cuda-10.2
 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"

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

@@ -3,3 +3,6 @@
 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
+
+export FORCE_CUDA=1
+export TORCH_CUDA_ARCH_LIST="3.5;5.0+PTX;6.0;7.0;7.5"

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

@@ -3,3 +3,6 @@
 CUDA_HOME=/usr/local/cuda-11.1
 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/cu111-Windows-env.sh

@@ -3,3 +3,6 @@
 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
+
+export FORCE_CUDA=1
+export TORCH_CUDA_ARCH_LIST="3.5;5.0+PTX;6.0;7.0;7.5;8.0;8.6"

README.md

@@ -32,23 +32,23 @@ All included operations work on varying data types and are implemented both for
 
 ### Anaconda
 
-**Update:** You can now install `pytorch-cluster` via [Anaconda](https://anaconda.org/rusty1s/pytorch-cluster) for all major OS/PyTorch/CUDA combinations 🤗
+**Update:** You can now install `pytorch-cluster` via [Anaconda](https://anaconda.org/pyg/pytorch-cluster) for all major OS/PyTorch/CUDA combinations 🤗
 Given that you have [`pytorch >= 1.8.0` installed](https://pytorch.org/get-started/locally/), simply run
 
 ```
-conda install pytorch-cluster -c rusty1s
+conda install pytorch-cluster -c pyg
 ```
 
 ### Binaries
 
-We alternatively provide pip wheels for all major OS/PyTorch/CUDA combinations, see [here](https://pytorch-geometric.com/whl).
+We alternatively provide pip wheels for all major OS/PyTorch/CUDA combinations, see [here](https://data.pyg.org/whl).
 
 #### PyTorch 1.9.0
 
 To install the binaries for PyTorch 1.9.0, simply run
 
 ```
-pip install torch-cluster -f https://pytorch-geometric.com/whl/torch-1.9.0+${CUDA}.html
+pip install torch-cluster -f https://data.pyg.org/whl/torch-1.9.0+${CUDA}.html
 ```
 
 where `${CUDA}` should be replaced by either `cpu`, `cu102`, or `cu111` depending on your PyTorch installation.
@@ -64,7 +64,7 @@ where `${CUDA}` should be replaced by either `cpu`, `cu102`, or `cu111` dependin
 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-1.8.0+${CUDA}.html
+pip install torch-cluster -f https://data.pyg.org/whl/torch-1.8.0+${CUDA}.html
 ```
 
 where `${CUDA}` should be replaced by either `cpu`,`cu101`, `cu102`, or `cu111` depending on your PyTorch installation.

conda/pytorch-cluster/build_conda.sh

@@ -30,4 +30,4 @@ echo "PyTorch $TORCH_VERSION+$CUDA_VERSION"
 echo "- $CONDA_PYTORCH_CONSTRAINT"
 echo "- $CONDA_CUDATOOLKIT_CONSTRAINT"
 
-conda build . -c defaults -c nvidia -c pytorch -c conda-forge --output-folder "$HOME/conda-bld"
+conda build . -c nvidia -c pytorch -c default -c conda-forge --output-folder "$HOME/conda-bld"

conda/pytorch-cluster/meta.yaml

@@ -25,7 +25,7 @@ build:
   script: pip install .
   script_env:
     - FORCE_CUDA
-    - TORCH_CUDA_ARCH_LIST="5.2 6.0 6.1 7.0 7.5 8.0 8.6+PTX"
+    - TORCH_CUDA_ARCH_LIST
 
 test:
   imports: