dill == 0.3.7
astor == 0.7.1
typing_extensions == 4.8.0
gast == 0.4.0
termcolor == 2.3.0
wrapt == 1.16.0
tblib == 2.0.0

# Install tensorboard, and keras
# Note that here we want the latest version that matches TF major.minor version
# Note that we must use nightly here as these are used in nightly jobs
# For release jobs, we will pin these on the release branch
keras-nightly ~= 3.0.0.dev
tb-nightly ~= 2.17.0.a

# Test dependencies

    and
    [tensorflow/python](https://github.com/tensorflow/tensorflow/tree/master/tensorflow/python).
    TensorFlow has passed version 1.0 and hence cannot make
    non-backward-compatible API changes without a major release. Reviewers of
    your pull request will comment on any API compatibility issues
    [following API review practices](https://github.com/tensorflow/community/blob/master/governance/api-reviews.md).

### Known Caveats

* <CAVEATS REGARDING THE RELEASE (BUT NOT BREAKING CHANGES).>
* <ADDING/BUMPING DEPENDENCIES SHOULD GO HERE>
* <KNOWN LACK OF SUPPORT ON SOME PLATFORM, SHOULD GO HERE>

### Major Features and Improvements

*   <INSERT MAJOR FEATURE HERE, USING MARKDOWN SYNTAX>
*   <IF RELEASE CONTAINS MULTIPLE FEATURES FROM SAME AREA, GROUP THEM TOGETHER>

### Bug Fixes and Other Changes

load("@bazel_skylib//rules:common_settings.bzl", "bool_flag", "bool_setting")
load("@local_config_cuda//cuda:build_defs.bzl", "if_cuda")
load(
    "//tensorflow:tensorflow.bzl",
    "VERSION",
    "VERSION_MAJOR",
    "check_deps",
    "if_google",
    "if_oss",
    "if_xla_available",
    "tf_cc_shared_object",
    "tf_custom_op_library_additional_deps_impl",
    "tf_monitoring_python_deps",
    "tf_native_cc_binary",

# See https://developer.nvidia.com/cuda-gpus#compute
# `compute_XY` enables PTX embedding in addition to SASS. PTX
# is forward compatible beyond the current compute capability major
# release while SASS is only forward compatible inside the current
# major release. Example: sm_80 kernels can run on sm_89 GPUs but
# not on sm_90 GPUs. compute_80 kernels though can also run on sm_90 GPUs.