#
# This file is autogenerated by pip-compile with Python 3.9
# by the following command:
#
#    bazel run //ci/official/requirements_updater:requirements.update
#
absl-py==2.2.2 \
    --hash=sha256:bf25b2c2eed013ca456918c453d687eab4e8309fba81ee2f4c1a6aa2494175eb \
    --hash=sha256:e5797bc6abe45f64fd95dc06394ca3f2bedf3b5d895e9da691c9ee3397d70092
    # via
    #   keras-nightly
    #   tb-nightly
astor==0.7.1 \

#
# This file is autogenerated by pip-compile with Python 3.11
# by the following command:
#
#    bazel run //ci/official/requirements_updater:requirements.update
#
absl-py==2.2.2 \
    --hash=sha256:bf25b2c2eed013ca456918c453d687eab4e8309fba81ee2f4c1a6aa2494175eb \
    --hash=sha256:e5797bc6abe45f64fd95dc06394ca3f2bedf3b5d895e9da691c9ee3397d70092
    # via
    #   keras-nightly
    #   tb-nightly
astor==0.7.1 \

* Hermetic CUDA support is added.

  Hermetic CUDA uses a specific downloadable version of CUDA instead of the user’s locally installed CUDA. Bazel will download CUDA, CUDNN and NCCL distributions, and then use CUDA libraries and tools as dependencies in various Bazel targets. This enables more reproducible builds for Google ML projects and supported CUDA versions.