version up

.github/workflows/building-conda.yml

@@ -10,7 +10,7 @@ jobs:
     strategy:
       fail-fast: false
       matrix:
-        os: [ubuntu-16.04, macos-10.15, windows-latest]
+        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']
@@ -66,7 +66,7 @@ jobs:
       - name: Build Conda package for CPU
         if: ${{ matrix.cuda-version == 'cpu' }}
         run: |
-          FORCE_CUDA=0 ./conda/pytorch-sparse/build_conda.sh ${{ matrix.python-version }} ${{ matrix.torch-version }} ${{ matrix.cuda-version }}
+          FORCE_CUDA=0 TORCH_CUDA_ARCH_LIST=0 ./conda/pytorch-sparse/build_conda.sh ${{ matrix.python-version }} ${{ matrix.torch-version }} ${{ matrix.cuda-version }}
         shell:
           bash -l {0}
 
@@ -74,15 +74,24 @@ jobs:
         if: ${{ matrix.cuda-version != 'cpu' }}
         run: |
           source .github/workflows/cuda/${{ matrix.cuda-version }}-${{ runner.os }}-env.sh
-          FORCE_CUDA=1 ./conda/pytorch-sparse/build_conda.sh ${{ matrix.python-version }} ${{ matrix.torch-version }} ${{ matrix.cuda-version }}
+          ./conda/pytorch-sparse/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

@@ -10,7 +10,7 @@ jobs:
     strategy:
       fail-fast: false
       matrix:
-        os: [ubuntu-16.04, macos-10.15, windows-latest]
+        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']
@@ -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: |
@@ -47,7 +52,7 @@ jobs:
 
       - name: Install torch-scatter
         run: |
-          pip install torch-scatter -f https://pytorch-geometric.com/whl/torch-${{ matrix.torch-version }}+${{ matrix.cuda-version }}.html
+          pip install torch-scatter -f https://data.pyg.org/whl/torch-${{ matrix.torch-version }}+${{ matrix.cuda-version }}.html
 
       - name: Install METIS
         if: ${{ runner.os != 'Windows' }}
@@ -70,7 +75,7 @@ jobs:
         if: ${{ matrix.cuda-version != 'cpu' }}
         run: |
           source .github/workflows/cuda/${{ matrix.cuda-version }}-${{ runner.os }}-env.sh
-          FORCE_CUDA=1 WITH_METIS=1 TORCH_CUDA_ARCH_LIST="5.2 6.0 6.1 7.0 7.5 8.0 8.6+PTX" pip install -e .
+          WITH_METIS=1 pip install -e .
         shell:
           bash
 
@@ -84,8 +89,8 @@ jobs:
         with:
           aws-access-key-id: ${{ secrets.AWS_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-Linux.sh

 #!/bin/bash
 
-OS=ubuntu1604
+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

.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-Linux.sh

 #!/bin/bash
 
-OS=ubuntu1604
+OS=ubuntu1804
 
-# Ubuntu-18.04
 wget -nv https://developer.download.nvidia.com/compute/cuda/repos/${OS}/x86_64/cuda-${OS}.pin
 sudo mv cuda-${OS}.pin /etc/apt/preferences.d/cuda-repository-pin-600
 wget -nv https://developer.download.nvidia.com/compute/cuda/10.2/Prod/local_installers/cuda-repo-${OS}-10-2-local-10.2.89-440.33.01_1.0-1_amd64.deb

.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-Linux.sh

 #!/bin/bash
 
-OS=ubuntu1604
+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

.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"

.github/workflows/linting.yml

@@ -9,7 +9,7 @@ jobs:
 
     strategy:
       matrix:
-        os: [ubuntu-16.04]
+        os: [ubuntu-latest]
         python-version: [3.6]
 
     steps:

.github/workflows/testing.yml

@@ -9,7 +9,7 @@ jobs:
 
     strategy:
       matrix:
-        os: [ubuntu-16.04, windows-latest]
+        os: [ubuntu-latest, windows-latest]
         python-version: [3.6]
         torch-version: [1.8.0, 1.9.0]
 
@@ -26,7 +26,7 @@ jobs:
 
       - name: Install torch-scatter
         run: |
-          pip install torch-scatter -f https://pytorch-geometric.com/whl/torch-${{ matrix.torch-version }}+cpu.html
+          pip install torch-scatter -f https://data.pyg.org/whl/torch-${{ matrix.torch-version }}+cpu.html
 
       - name: Install METIS
         if: ${{ runner.os != 'Windows' }}

CMakeLists.txt

 cmake_minimum_required(VERSION 3.0)
 project(torchsparse)
 set(CMAKE_CXX_STANDARD 14)
-set(TORCHSPARSE_VERSION 0.6.11)
+set(TORCHSPARSE_VERSION 0.6.12)
 
 option(WITH_CUDA "Enable CUDA support" OFF)
 

README.md

@@ -32,23 +32,23 @@ Note that only `value` comes with autograd support, as `index` is discrete and t
 
 ### Anaconda
 
-**Update:** You can now install `pytorch-sparse` via [Anaconda](https://anaconda.org/rusty1s/pytorch-sparse) for all major OS/PyTorch/CUDA combinations 🤗
+**Update:** You can now install `pytorch-sparse` via [Anaconda](https://anaconda.org/pyg/pytorch-sparse) 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-sparse -c rusty1s
+conda install pytorch-sparse -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-scatter torch-sparse -f https://pytorch-geometric.com/whl/torch-1.9.0+${CUDA}.html
+pip install torch-scatter torch-sparse -f https://data.pyg.org/whl/torch-1.9.0+${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-scatter torch-sparse -f https://pytorch-geometric.com/whl/torch-1.8.0+${CUDA}.html
+pip install torch-scatter torch-sparse -f https://data.pyg.org/whl/torch-1.8.0+${CUDA}.html
 ```
 
 where `${CUDA}` should be replaced by either `cpu`, `cu101`, `cu102`, or `cu111` depending on your PyTorch installation.

conda/pytorch-sparse/build_conda.sh

@@ -30,4 +30,4 @@ echo "PyTorch $TORCH_VERSION+$CUDA_VERSION"
 echo "- $CONDA_PYTORCH_CONSTRAINT"
 echo "- $CONDA_CUDATOOLKIT_CONSTRAINT"
 
-conda build . -c pytorch -c nvidia -c rusty1s -c defaults -c conda-forge --output-folder "$HOME/conda-bld"
+conda build . -c pytorch -c nvidia -c pyg -c defaults -c conda-forge --output-folder "$HOME/conda-bld"

conda/pytorch-sparse/meta.yaml

 package:
   name: pytorch-sparse
-  version: 0.6.11
+  version: 0.6.12
 
 source:
   path: ../..
@@ -26,8 +26,8 @@ build:
   string: py{{ environ.get('PYTHON_VERSION').replace('.', '') }}_torch_{{ environ['TORCH_VERSION'] }}_{{ environ['CUDA_VERSION'] }}
   script_env:
     - FORCE_CUDA
+    - TORCH_CUDA_ARCH_LIST
     - WITH_METIS=1
-    - TORCH_CUDA_ARCH_LIST="5.2 6.0 6.1 7.0 7.5 8.0 8.6+PTX"
   preserve_egg_dir: True
 
 test:

setup.py

@@ -102,7 +102,7 @@ tests_require = ['pytest', 'pytest-runner', 'pytest-cov']
 
 setup(
     name='torch_sparse',
-    version='0.6.11',
+    version='0.6.12',
     author='Matthias Fey',
     author_email='matthias.fey@tu-dortmund.de',
     url='https://github.com/rusty1s/pytorch_sparse',

torch_sparse/__init__.py

@@ -3,7 +3,7 @@ import os.path as osp
 
 import torch
 
-__version__ = '0.6.11'
+__version__ = '0.6.12'
 
 suffix = 'cuda' if torch.cuda.is_available() else 'cpu'