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Jeremy Reizenstein 5fbdb99aec builds for pytorch 1.10.0 
Summary:
Add builds corresponding to the new pytorch 1.10.0. We omit CUDA 11.3 testing because it fails with current hardware, and omit the main build too for the moment.

Also move to the newer GPU circle CI executors.

Reviewed By: gkioxari

Differential Revision: D32335934

fbshipit-source-id: 416d92a8eecd06ef7fc742664a5f2d46f93415f8
2021-11-11 02:03:37 -08:00
..
after.sh
License lint codebase
2021-06-22 03:45:27 -07:00
go.sh
License lint codebase
2021-06-22 03:45:27 -07:00
inside.sh
builds for pytorch 1.10.0
2021-11-11 02:03:37 -08:00
publish.py
License lint codebase
2021-06-22 03:45:27 -07:00
README.md
Build wheels for s3
2021-02-05 05:52:36 -08:00

README.md

Building Linux pip Packages

  1. Make sure this directory is on a filesystem which docker can use - e.g. not NFS. If you are using a local hard drive there is nothing to do here.

  2. You may want to docker pull pytorch/conda-cuda:latest.

  3. Run bash go.sh in this directory. This takes ages and writes packages to inside/output.

  4. You can upload the packages to s3, along with basic html files which enable them to be used, with bash after.sh.

In particular, if you are in a jupyter/colab notebook you can then install using these wheels with the following series of commands.

import sys
import torch
version_str="".join([
    f"py3{sys.version_info.minor}_cu",
    torch.version.cuda.replace(".",""),
    f"_pyt{torch.__version__[0:5:2]}"
])
!pip install pytorch3d -f https://dl.fbaipublicfiles.com/pytorch3d/packaging/wheels/{version_str}/download.html