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Improve build from source instructions #89
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* provide a conda environment * update build instructions in README
README.md
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- Minconda https://docs.conda.io/en/latest/miniconda.html#linux-installers | ||
- CUDA Toolkit https://developer.nvidia.com/cuda-downloads | ||
- LibTorch which is the PyTorch C++ API, by following the instructions at https://pytorch.org/cppdocs/installing.html and https://pytorch.org. | ||
- to get a version for CUDA 1.16 used in our build example we use the commands: |
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Please, don't use stuff from pytorch.org. Their binaries are incompatible with conda-forge
.
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We probably want to reconsider the build process and possibly make corresponding changes to the CMake script. If you set TORCH_DIR
(not PYTORCH_DIR
) to the directory containing TorchConfig.cmake
, it should be able to automatically find everything it needs.
environment.yaml
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@@ -0,0 +1,7 @@ | |||
channels: |
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Just reuse the one from CI: https://github.com/openmm/openmm-torch/blob/master/devtools/conda-envs/build-ubuntu-18.04.yml
README.md
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1. Create a directory in which to build the plugin. | ||
- Minconda https://docs.conda.io/en/latest/miniconda.html#linux-installers | ||
- CUDA Toolkit https://developer.nvidia.com/cuda-downloads |
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CUDA is only needed if you have a NVIDIA GPU you want to use with it.
These instructions seem to be Linux specific. We also support Mac and Windows. Note that conda-forge does not currently provide PyTorch builds for WIndows, so in that case it's necessary to get it from the PyTorch website or the |
* Separate instructions for linux, linux with cuda, and MacOS * conda environment files for each build
I have made specific instructions for Linux (with and without CUDA) and MacOS. |
We should put the from-source installation instructions to a separate file (e.g. |
That's because conda-forge doesn't provide PyTorch builds for Windows. That makes building from source especially important, since it's the only option for Windows. |
For instructions for a building on Windows we will need to update I have been able to compile the c++ code on Windows (CPU only) using visual studio and this environment:
One quirk is that |
Address #64