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CUB conda instructions
Summary: We have already uploaded a conda package of the cub 1.10.0 sources to our channel on anaconda. Here is the code we used. Reviewed By: nikhilaravi Differential Revision: D25395358 fbshipit-source-id: b58fd473fcafd425c98c9d7a7c32574f651383a0
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packaging/cub_conda/README.md
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packaging/cub_conda/README.md
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## For building conda package for NVIDIA CUB
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CUB is required for building PyTorch3D so it makes sense
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to provide a conda package to make its header files available.
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This directory is used to do that, it is independent of the rest
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of this repo.
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Make sure you are in a conda environment with
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anaconda-client and conda-build installed.
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From this directory, build the package with the following.
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```
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mkdir -p ./out
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conda build --no-anaconda-upload --output-folder ./out cub
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```
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You can then upload the package with the following.
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```
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retry () {
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# run a command, and try again if it fails
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$* || (echo && sleep 8 && echo retrying && $*)
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}
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file=out/linux-64/nvidiacub-1.10.0-0.tar.bz2
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retry anaconda --verbose -t ${TOKEN} upload -u pytorch3d --force ${file} --no-progress
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```
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packaging/cub_conda/cub/meta.yaml
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packaging/cub_conda/cub/meta.yaml
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package:
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name: nvidiacub
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version: 1.10.0
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source:
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url: https://github.com/NVIDIA/cub/archive/1.10.0.tar.gz
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folder: source
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build:
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script: mkdir $PREFIX/include && cp -r source/cub $PREFIX/include/cub
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about:
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home: https://github.com/NVIDIA/cub
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summary: CUB provides state-of-the-art, reusable software components for every layer of the CUDA programming model.
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