commit 2c71fe1ff34af5277673db7b67320e6796823e0b
author Austin Anderson <angerson@google.com> Mon Apr 27 16:50:08 2020 -0700
committer Austin Anderson <angerson@google.com> Wed Apr 29 16:07:31 2020 -0700
tree ac99ad56d250b47e77bef9bed7474edf28da9fb2
parent 06473adb2dd0eadfef0ce72ae70714eae215e556

Provide NVIDIA CUDA build data in metadata and API

This change:

First exposes //third_party/gpus:find_cuda_config as a library.

Then, it extends gen_build_info.py with find_cuda_config to provide package
build information within TensorFlow's API. This is accessible as a
dictionary:

    from tensorflow.python.platform import build_info
    print(build_info.cuda_build_info)
    {'cuda_version': '10.2', 'cudnn_version': '7', 'tensorrt_version': None, 'nccl_version': None}

Finally, setup.py pulls that into package metadata. The same wheel's
long description ends with:

    TensorFlow 2.1.0 for NVIDIA GPUs was built with these platform
    and library versions:

      - NVIDIA CUDA 10.2
      - NVIDIA cuDNN 7
      - NVIDIA NCCL not enabled
      - NVIDIA TensorRT not enabled

In lieu of NVIDIA CUDA classifiers [1], the same metadata is exposed in the
normally-unused "platform" tag:

    >>> import pkginfo
    >>> a = pkginfo.Wheel('./tf_nightly_gpu-2.1.0-cp36-cp36m-linux_x86_64.whl')
    >>> a.platforms
    ['cuda_version:10.2', 'cudnn_version:7', 'tensorrt_version:None', 'nccl_version:None']

I'm not 100% confident this is the best way to accomplish this. It
seems odd to import like this setup.py, even though it works, even in
an environment with TensorFlow installed.

One caveat for RBE: the contents of genrules still run on the local
system, so I had to syncronize my local environment with the RBE
environment I used to build TensorFlow. I'm not sure if this is going to
require intervention on TensorFlow's current CI.

Currently tested only on Linux GPU (Remote Build) for Python 3.6. I'd
like to see more tests before merging.

[1]: (https://github.com/pypa/trove-classifiers/issues/25),