Build both cpu and gpu binaries

.travis.yml

@@ -112,13 +112,13 @@ install:
   - source script/torch.sh
   - pip install flake8
   - pip install codecov
-  - pip install .[test]
+  - travis_wait 30 pip install -e .
 script:
   - flake8 .
   - python setup.py test
 after_success:
-  - python setup.py bdist_wheel --dist-dir=dist/torch-${TORCH_VERSION}
-  - python script/rename_wheel.py ${IDX}
+  - python setup.py bdist_wheel --dist-dir=dist
+  - ls -lah dist/
   - codecov
 deploy:
   provider: s3
@@ -127,8 +127,8 @@ deploy:
   access_key_id: ${S3_ACCESS_KEY}
   secret_access_key: ${S3_SECRET_ACCESS_KEY}
   bucket: pytorch-geometric.com
-  local_dir: dist/torch-${TORCH_VERSION}
-  upload_dir: whl/torch-${TORCH_VERSION}
+  local_dir: dist
+  upload_dir: whl/torch-${TORCH_VERSION}+${IDX}
   acl: public_read
   on:
     all_branches: true

CMakeLists.txt

@@ -1,7 +1,7 @@
 cmake_minimum_required(VERSION 3.0)
 project(torchscatter)
 set(CMAKE_CXX_STANDARD 14)
-set(TORCHSCATTER_VERSION 2.0.5)
+set(TORCHSCATTER_VERSION 2.0.6)
 
 option(WITH_CUDA "Enable CUDA support" OFF)
 

csrc/scatter.cpp

@@ -9,7 +9,11 @@
 #endif
 
 #ifdef _WIN32
-PyMODINIT_FUNC PyInit__scatter(void) { return NULL; }
+#ifdef WITH_CUDA
+PyMODINIT_FUNC PyInit__scatter_cuda(void) { return NULL; }
+#else
+PyMODINIT_FUNC PyInit__scatter_cpu(void) { return NULL; }
+#endif
 #endif
 
 torch::Tensor broadcast(torch::Tensor src, torch::Tensor other, int64_t dim) {

csrc/segment_coo.cpp

@@ -9,7 +9,11 @@
 #endif
 
 #ifdef _WIN32
-PyMODINIT_FUNC PyInit__segment_coo(void) { return NULL; }
+#ifdef WITH_CUDA
+PyMODINIT_FUNC PyInit__segment_coo_cuda(void) { return NULL; }
+#else
+PyMODINIT_FUNC PyInit__segment_coo_cpu(void) { return NULL; }
+#endif
 #endif
 
 std::tuple<torch::Tensor, torch::optional<torch::Tensor>>

csrc/segment_csr.cpp

@@ -9,7 +9,11 @@
 #endif
 
 #ifdef _WIN32
-PyMODINIT_FUNC PyInit__segment_csr(void) { return NULL; }
+#ifdef WITH_CUDA
+PyMODINIT_FUNC PyInit__segment_csr_cuda(void) { return NULL; }
+#else
+PyMODINIT_FUNC PyInit__segment_csr_cpu(void) { return NULL; }
+#endif
 #endif
 
 std::tuple<torch::Tensor, torch::optional<torch::Tensor>>

csrc/version.cpp

@@ -6,7 +6,11 @@
 #endif
 
 #ifdef _WIN32
-PyMODINIT_FUNC PyInit__version(void) { return NULL; }
+#ifdef WITH_CUDA
+PyMODINIT_FUNC PyInit__version_cuda(void) { return NULL; }
+#else
+PyMODINIT_FUNC PyInit__version_cpu(void) { return NULL; }
+#endif
 #endif
 
 int64_t cuda_version() {

script/cuda.sh

@@ -69,7 +69,7 @@ if [ "${TRAVIS_OS_NAME}" = "osx" ] && [ "$IDX" = "cpu" ]; then
 fi
 
 if [ "${IDX}" = "cpu" ]; then
-  export FORCE_CPU=1
+  export FORCE_ONLY_CPU=1
 else
   export FORCE_CUDA=1
 fi

setup.py

@@ -1,53 +1,69 @@
 import os
-import os.path as osp
+import sys
 import glob
+import os.path as osp
+from itertools import product
 from setuptools import setup, find_packages
 
 import torch
+from torch.__config__ import parallel_info
 from torch.utils.cpp_extension import BuildExtension
 from torch.utils.cpp_extension import CppExtension, CUDAExtension, CUDA_HOME
 
 WITH_CUDA = torch.cuda.is_available() and CUDA_HOME is not None
+suffices = ['cpu', 'cuda'] if WITH_CUDA else ['cpu']
 if os.getenv('FORCE_CUDA', '0') == '1':
-    WITH_CUDA = True
-if os.getenv('FORCE_CPU', '0') == '1':
-    WITH_CUDA = False
+    suffices = ['cuda', 'cpu']
+if os.getenv('FORCE_ONLY_CUDA', '0') == '1':
+    suffices = ['cuda']
+if os.getenv('FORCE_ONLY_CPU', '0') == '1':
+    suffices = ['cpu']
 
 BUILD_DOCS = os.getenv('BUILD_DOCS', '0') == '1'
 
 
 def get_extensions():
-    Extension = CppExtension
-    define_macros = []
-    extra_compile_args = {'cxx': ['-O2']}
-    extra_link_args = ['-s']
-
-    if WITH_CUDA:
-        Extension = CUDAExtension
-        define_macros += [('WITH_CUDA', None)]
-        nvcc_flags = os.getenv('NVCC_FLAGS', '')
-        nvcc_flags = [] if nvcc_flags == '' else nvcc_flags.split(' ')
-        nvcc_flags += ['-arch=sm_35', '--expt-relaxed-constexpr', '-O2']
-        extra_compile_args['nvcc'] = nvcc_flags
+    extensions = []
 
     extensions_dir = osp.join(osp.dirname(osp.abspath(__file__)), 'csrc')
     main_files = glob.glob(osp.join(extensions_dir, '*.cpp'))
-    extensions = []
-    for main in main_files:
-        name = main.split(os.sep)[-1][:-4]
 
+    for main, suffix in product(main_files, suffices):
+        define_macros = []
+        extra_compile_args = {'cxx': ['-O2']}
+        extra_link_args = ['-s']
+
+        info = parallel_info()
+        if 'backend: OpenMP' in info and 'OpenMP not found' not in info:
+            extra_compile_args['cxx'] += ['-DAT_PARALLEL_OPENMP']
+            if sys.platform == 'win32':
+                extra_compile_args['cxx'] += ['/openmp']
+            else:
+                extra_compile_args['cxx'] += ['-fopenmp']
+        else:
+            print('Compiling without OpenMP...')
+
+        if suffix == 'cuda':
+            define_macros += [('WITH_CUDA', None)]
+            nvcc_flags = os.getenv('NVCC_FLAGS', '')
+            nvcc_flags = [] if nvcc_flags == '' else nvcc_flags.split(' ')
+            nvcc_flags += ['-arch=sm_35', '--expt-relaxed-constexpr']
+            extra_compile_args['nvcc'] = nvcc_flags
+
+        name = main.split(os.sep)[-1][:-4]
         sources = [main]
 
         path = osp.join(extensions_dir, 'cpu', f'{name}_cpu.cpp')
         if osp.exists(path):
             sources += [path]
 
         path = osp.join(extensions_dir, 'cuda', f'{name}_cuda.cu')
-        if WITH_CUDA and osp.exists(path):
+        if suffix == 'cuda' and osp.exists(path):
             sources += [path]
 
+        Extension = CppExtension if suffix == 'cpu' else CUDAExtension
         extension = Extension(
-            'torch_scatter._' + name,
+            f'torch_scatter._{name}_{suffix}',
             sources,
             include_dirs=[extensions_dir],
             define_macros=define_macros,
@@ -65,7 +81,7 @@ def get_extensions():
 
 setup(
     name='torch_scatter',
-    version='2.0.5',
+    version='2.0.6',
     author='Matthias Fey',
     author_email='matthias.fey@tu-dortmund.de',
     url='https://github.com/rusty1s/pytorch_scatter',

torch_scatter/__init__.py

@@ -4,12 +4,14 @@
 
 import torch
 
-__version__ = '2.0.5'
+__version__ = '2.0.6'
+
+suffix = 'cuda' if torch.cuda.is_available() else 'cpu'
 
 try:
     for library in ['_version', '_scatter', '_segment_csr', '_segment_coo']:
         torch.ops.load_library(importlib.machinery.PathFinder().find_spec(
-            library, [osp.dirname(__file__)]).origin)
+            f'{library}_{suffix}', [osp.dirname(__file__)]).origin)
 except AttributeError as e:
     if os.getenv('BUILD_DOCS', '0') != '1':
         raise AttributeError(e)
@@ -42,7 +44,7 @@
     torch.ops.torch_scatter.segment_max_coo = segment_coo_arg_placeholder
     torch.ops.torch_scatter.gather_coo = gather_coo_placeholder
 
-if torch.cuda.is_available() and torch.version.cuda:  # pragma: no cover
+if torch.cuda.is_available():  # pragma: no cover
     cuda_version = torch.ops.torch_scatter.cuda_version()
 
     if cuda_version == -1: