build wheels

Author: rusty1s

.travis.yml

@@ -1,32 +1,90 @@
+language: shell
+
+os:
+  - linux
+  - osx
+  - windows
+
+env:
+  global:
+    - CUDA_HOME=/usr/local/cuda
+  jobs:
+    - TORCH_VERSION=1.4.0 PYTHON_VERSION=3.8 IDX=cpu
+    - TORCH_VERSION=1.4.0 PYTHON_VERSION=3.8 IDX=cu92
+    - TORCH_VERSION=1.4.0 PYTHON_VERSION=3.8 IDX=cu100
+    - TORCH_VERSION=1.4.0 PYTHON_VERSION=3.8 IDX=cu101
+    - TORCH_VERSION=1.4.0 PYTHON_VERSION=3.7 IDX=cpu
+    - TORCH_VERSION=1.4.0 PYTHON_VERSION=3.7 IDX=cu92
+    - TORCH_VERSION=1.4.0 PYTHON_VERSION=3.7 IDX=cu100
+    - TORCH_VERSION=1.4.0 PYTHON_VERSION=3.7 IDX=cu101
+    - TORCH_VERSION=1.4.0 PYTHON_VERSION=3.6 IDX=cpu
+    - TORCH_VERSION=1.4.0 PYTHON_VERSION=3.6 IDX=cu92
+    - TORCH_VERSION=1.4.0 PYTHON_VERSION=3.6 IDX=cu100
+    - TORCH_VERSION=1.4.0 PYTHON_VERSION=3.6 IDX=cu101
+
 jobs:
-  include:
-    - os: linux
-      language: python
-      python: 3.7
-      addons:
-        apt:
-          sources:
-            - ubuntu-toolchain-r-test
-          packages:
-            - gcc-5
-            - g++-5
-      env:
-        - CC=gcc-5
-        - CXX=g++-5
+  exclude:  # Exclude *all* macOS CUDA jobs and Windows CUDA 9.2/10.0 jobs.
+    - os: osx
+      env: TORCH_VERSION=1.4.0 PYTHON_VERSION=3.8 IDX=cu92
+    - os: osx
+      env: TORCH_VERSION=1.4.0 PYTHON_VERSION=3.8 IDX=cu100
+    - os: osx
+      env: TORCH_VERSION=1.4.0 PYTHON_VERSION=3.8 IDX=cu101
+    - os: osx
+      env: TORCH_VERSION=1.4.0 PYTHON_VERSION=3.7 IDX=cu92
+    - os: osx
+      env: TORCH_VERSION=1.4.0 PYTHON_VERSION=3.7 IDX=cu100
+    - os: osx
+      env: TORCH_VERSION=1.4.0 PYTHON_VERSION=3.7 IDX=cu101
+    - os: osx
+      env: TORCH_VERSION=1.4.0 PYTHON_VERSION=3.6 IDX=cu92
+    - os: osx
+      env: TORCH_VERSION=1.4.0 PYTHON_VERSION=3.6 IDX=cu100
+    - os: osx
+      env: TORCH_VERSION=1.4.0 PYTHON_VERSION=3.6 IDX=cu101
+    - os: windows
+      env: TORCH_VERSION=1.4.0 PYTHON_VERSION=3.8 IDX=cu92
+    - os: windows
+      env: TORCH_VERSION=1.4.0 PYTHON_VERSION=3.8 IDX=cu100
+    - os: windows
+      env: TORCH_VERSION=1.4.0 PYTHON_VERSION=3.7 IDX=cu92
+    - os: windows
+      env: TORCH_VERSION=1.4.0 PYTHON_VERSION=3.7 IDX=cu100
+    - os: windows
+      env: TORCH_VERSION=1.4.0 PYTHON_VERSION=3.6 IDX=cu92
+    - os: windows
+      env: TORCH_VERSION=1.4.0 PYTHON_VERSION=3.6 IDX=cu100
+
+
 install:
-  - pip install numpy
-  - pip install --pre torch torchvision -f https://download.pytorch.org/whl/nightly/cpu/torch_nightly.html
-  - pip install pycodestyle
-  - pip install flake8
-  - pip install codecov
-  - pip install torch-scatter
+  - source script/cuda.sh
+  - source script/conda.sh
+  - conda create --yes -n test python="${PYTHON_VERSION}"
+  - source activate test
+  - conda install pytorch=${TORCH_VERSION} ${TOOLKIT} -c pytorch --yes
+  - source script/torch.sh
+  - pip install torch-scatter==latest+${IDX} -f http://pytorch-scatter.s3-website.eu-central-1.amazonaws.com/whl/torch-${TORCH_VERSION}.html --trusted-host pytorch-scatter.s3-website.eu-central-1.amazonaws.com
+  - pip install flake8 codecov
+  - python setup.py install
 script:
-  - python -c "import torch; print(torch.__version__)"
-  - pycodestyle --ignore=E731,W504 .
   - flake8 .
-  - python setup.py install
   - python setup.py test
 after_success:
+  - python setup.py bdist_wheel --dist-dir=dist/torch-${TORCH_VERSION}
+  - python script/rename_wheel.py ${IDX}
   - codecov
+deploy:
+  provider: s3
+  region: eu-central-1
+  edge: true
+  access_key_id: AKIAJB7S6NJ5OM5MAAGA
+  secret_access_key: ${S3_SECRET_ACCESS_KEY}
+  bucket: pytorch-sparse
+  local_dir: dist/torch-${TORCH_VERSION}
+  upload_dir: whl/torch-${TORCH_VERSION}
+  acl: public_read
+  on:
+    repo: rusty1s/pytorch_sparse
+    branch: master
 notifications:
   email: false

MANIFEST.in

@@ -1,2 +1,5 @@
+include README.md
 include LICENSE
+
+recursive-exclude test *
 recursive-include csrc *

README.md

@@ -13,8 +13,7 @@
 
 --------------------------------------------------------------------------------
 
-[PyTorch](http://pytorch.org/) completely lacks autograd support and operations such as sparse sparse matrix multiplication, but is heavily working on improvement (*cf.* [this issue](https://github.com/pytorch/pytorch/issues/9674)).
-In the meantime, this package consists of a small extension library of optimized sparse matrix operations with autograd support.
+This package consists of a small extension library of optimized sparse matrix operations with autograd support.
 This package currently consists of the following methods:
 
 * **[Coalesce](#coalesce)**
@@ -28,6 +27,26 @@ Note that only `value` comes with autograd support, as `index` is discrete and t
 
 ## Installation
 
+### Binaries
+
+We provide pip wheels for all major OS/PyTorch/CUDA combinations, see [here](http://pytorch-sparse.s3-website.eu-central-1.amazonaws.com/whl).
+To install from binaries, simply run
+
+```
+pip install torch-scatter==latest+${CUDA} -f http://pytorch-scatter.s3-website.eu-central-1.amazonaws.com/whl/torch-1.4.0.html --trusted-host pytorch-scatter.s3-website.eu-central-1.amazonaws.com
+pip install torch-sparse==latest+${CUDA} -f http://pytorch-sparse.s3-website.eu-central-1.amazonaws.com/whl/torch-1.4.0.html --trusted-host pytorch-sparse.s3-website.eu-central-1.amazonaws.com
+```
+
+where `${CUDA}` should be replaced by either `cpu`, `cu92`, `cu100` or `cu101` depending on your PyTorch installation.
+
+|             | `cpu` | `cu92` | `cu100` | `cu101` |
+|-------------|-------|--------|---------|---------|
+| **Linux**   | ✅    | ✅     | ✅      | ✅      |
+| **Windows** | ✅    | ❌     | ❌      | ✅      |
+| **macOS**   | ✅    | ❌     | ❌      | ❌      |
+
+### From source
+
 Ensure that at least PyTorch 1.4.0 is installed and verify that `cuda/bin` and `cuda/include` are in your `$PATH` and `$CPATH` respectively, *e.g.*:
 
 ```
@@ -47,10 +66,16 @@ Then run:
 pip install torch-scatter torch-sparse
 ```
 
-If you are running into any installation problems, please create an [issue](https://github.com/rusty1s/pytorch_sparse/issues).
-Be sure to import `torch` first before using this package to resolve symbols the dynamic linker must see.
+When running in a docker container without nvidia driver, PyTorch needs to evaluate the compute capabilities and may fail.
+In this case, ensure that the compute capabilities are set via `TORCH_CUDA_ARCH_LIST`, *e.g.*:
+
+```
+export TORCH_CUDA_ARCH_LIST = "6.0 6.1 7.2+PTX 7.5+PTX"
+```
+
+## Functions
 
-## Coalesce
+### Coalesce
 
 ```
 torch_sparse.coalesce(index, value, m, n, op="add") -> (torch.LongTensor, torch.Tensor)
@@ -60,20 +85,20 @@ Row-wise sorts `index` and removes duplicate entries.
 Duplicate entries are removed by scattering them together.
 For scattering, any operation of [`torch_scatter`](https://github.com/rusty1s/pytorch_scatter) can be used.
 
-### Parameters
+#### Parameters
 
 * **index** *(LongTensor)* - The index tensor of sparse matrix.
 * **value** *(Tensor)* - The value tensor of sparse matrix.
 * **m** *(int)* - The first dimension of corresponding dense matrix.
 * **n** *(int)* - The second dimension of corresponding dense matrix.
 * **op** *(string, optional)* - The scatter operation to use. (default: `"add"`)
 
-### Returns
+#### Returns
 
 * **index** *(LongTensor)* - The coalesced index tensor of sparse matrix.
 * **value** *(Tensor)* - The coalesced value tensor of sparse matrix.
 
-### Example
+#### Example
 
 ```python
 import torch
@@ -97,28 +122,28 @@ tensor([[6.0, 8.0],
         [5.0, 6.0]])
 ```
 
-## Transpose
+### Transpose
 
 ```
 torch_sparse.transpose(index, value, m, n) -> (torch.LongTensor, torch.Tensor)
 ```
 
 Transposes dimensions 0 and 1 of a sparse matrix.
 
-### Parameters
+#### Parameters
 
 * **index** *(LongTensor)* - The index tensor of sparse matrix.
 * **value** *(Tensor)* - The value tensor of sparse matrix.
 * **m** *(int)* - The first dimension of corresponding dense matrix.
 * **n** *(int)* - The second dimension of corresponding dense matrix.
 * **coalesced** *(bool, optional)* - If set to `False`, will not coalesce the output. (default: `True`)
 
-### Returns
+#### Returns
 
 * **index** *(LongTensor)* - The transposed index tensor of sparse matrix.
 * **value** *(Tensor)* - The transposed value tensor of sparse matrix.
 
-### Example
+#### Example
 
 ```python
 import torch
@@ -142,27 +167,27 @@ tensor([[7.0, 9.0],
         [3.0, 4.0]])
 ```
 
-## Sparse Dense Matrix Multiplication
+### Sparse Dense Matrix Multiplication
 
 ```
 torch_sparse.spmm(index, value, m, n, matrix) -> torch.Tensor
 ```
 
 Matrix product of a sparse matrix with a dense matrix.
 
-### Parameters
+#### Parameters
 
 * **index** *(LongTensor)* - The index tensor of sparse matrix.
 * **value** *(Tensor)* - The value tensor of sparse matrix.
 * **m** *(int)* - The first dimension of corresponding dense matrix.
 * **n** *(int)* - The second dimension of corresponding dense matrix.
 * **matrix** *(Tensor)* - The dense matrix.
 
-### Returns
+#### Returns
 
 * **out** *(Tensor)* - The dense output matrix.
 
-### Example
+#### Example
 
 ```python
 import torch
@@ -183,7 +208,7 @@ tensor([[7.0, 16.0],
         [7.0, 19.0]])
 ```
 
-## Sparse Sparse Matrix Multiplication
+### Sparse Sparse Matrix Multiplication
 
 ```
 torch_sparse.spspmm(indexA, valueA, indexB, valueB, m, k, n) -> (torch.LongTensor, torch.Tensor)
@@ -192,7 +217,7 @@ torch_sparse.spspmm(indexA, valueA, indexB, valueB, m, k, n) -> (torch.LongTenso
 Matrix product of two sparse tensors.
 Both input sparse matrices need to be **coalesced** (use the `coalesced` attribute to force).
 
-### Parameters
+#### Parameters
 
 * **indexA** *(LongTensor)* - The index tensor of first sparse matrix.
 * **valueA** *(Tensor)* - The value tensor of first sparse matrix.
@@ -203,12 +228,12 @@ Both input sparse matrices need to be **coalesced** (use the `coalesced` attribu
 * **n** *(int)* - The second dimension of second corresponding dense matrix.
 * **coalesced** *(bool, optional)*: If set to `True`, will coalesce both input sparse matrices. (default: `False`)
 
-### Returns
+#### Returns
 
 * **index** *(LongTensor)* - The output index tensor of sparse matrix.
 * **value** *(Tensor)* - The output value tensor of sparse matrix.
 
-### Example
+#### Example
 
 ```python
 import torch

csrc/version.cpp

@@ -0,0 +1,21 @@
+#include <Python.h>
+#include <torch/script.h>
+
+#ifdef WITH_CUDA
+#include <cuda.h>
+#endif
+
+#ifdef _WIN32
+PyMODINIT_FUNC PyInit__version(void) { return NULL; }
+#endif
+
+int64_t cuda_version() {
+#ifdef WITH_CUDA
+  return CUDA_VERSION;
+#else
+  return -1;
+#endif
+}
+
+static auto registry =
+    torch::RegisterOperators().op("torch_scatter::cuda_version", &cuda_version);

script/.gitignore

@@ -0,0 +1 @@
+*.html

script/conda.sh

@@ -0,0 +1,26 @@
+#!/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}"