final build

.travis.yml

@@ -3,24 +3,24 @@ language: shell
 os:
   - linux
   - osx
-  # - windows
+  - 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=3.8 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
+    - 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:
   exclude:  # Exclude *all* macOS CUDA jobs and Windows CUDA 9.2/10.0 jobs.

README.md

@@ -36,7 +36,25 @@ In addition, we provide the following **composite functions** which make use of
 
 All included operations are broadcastable, work on varying data types, are implemented both for CPU and GPU with corresponding backward implementations, and are fully traceable.
 
-## Installation
+# Installation
+
+### Binaries
+
+We provide pip wheels for all major OS/PyTorch/CUDA combinations, see [here](http://pytorch-scatter.s3-website.eu-central-1.amazonaws.com/whl).
+
+```
+pip install torch-scatter==latest+${CUDA} -f http://pytorch-scatter.s3-website.eu-central-1.amazonaws.com/whl/torch-1.4.0.html --trusted-host pytorch-scatter.s3-website.eu-central-1.amazonaws.com
+```
+
+where `${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.*:
 
@@ -51,19 +69,18 @@ $ echo $CPATH
 >>> /usr/local/cuda/include:...
 ```
 
-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`
+Then run:
 
 ```
-export TORCH_CUDA_ARCH_LIST = "6.0 6.1 7.2+PTX 7.5+PTX"
+python setup.py install
 ```
 
-### Windows
-
-If you are installing this on Windows specifically, **you will need to point the setup to your Visual Studio installation** for some neccessary libraries and header files.
-To do this, add the include and library paths of your installation to the path lists in setup.py as described in the respective comments in the code.
+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.*:
 
-If you are running into any installation problems, please create an [issue](https://github.com/rusty1s/pytorch_scatter/issues).
-Be sure to import `torch` first before using this package to resolve symbols the dynamic linker must see.
+```
+export TORCH_CUDA_ARCH_LIST = "6.0 6.1 7.2+PTX 7.5+PTX"
+```
 
 ## Example
 

test/utils.py

@@ -7,7 +7,7 @@ grad_dtypes = [torch.float, torch.double]
 
 devices = [torch.device('cpu')]
 if torch.cuda.is_available():
-    devices += [torch.device('cuda:{}'.format(torch.cuda.current_device()))]
+    devices += [torch.device(f'cuda:{torch.cuda.current_device()}')]
 
 
 def tensor(x, dtype, device):