# TODO(kanglan): Update windows configs after b/289091160 is fixed
build:release_cpu_windows --config=avx_win
build:release_cpu_windows --define=no_tensorflow_py_deps=true

# Exclude TFRT integration for anything but Linux.
build:android --config=no_tfrt
build:macos   --config=no_tfrt
build:windows --config=no_tfrt
build:rocm --config=no_tfrt

just getting started, GitHub has a
[how-to](https://help.github.com/articles/using-pull-requests/).

TensorFlow team members will be assigned to review your pull requests. Once the
pull requests are approved and pass continuous integration checks, a TensorFlow
team member will apply `ready to pull` label to your change. This means we are
working on getting your pull request submitted to our internal repository. After

        "//learning/serving/contrib/tfrt/mlir/canonical_ops/...",
        "//learning/serving/experimental/remote_predict/...",
        "//perftools/accelerators/xprof/convert/...",
        "//perftools/accelerators/xprof/integration_tests/...",
        "//smartass/brain/configure/...",
        "//tensorflow/...",
        "//tensorflow_decision_forests/...",
        "//tensorflow_federated/...",
        "//tensorflow_models/google/recml/...",

    large-scale modeling with minimal changes to user code. You are welcome to
    try it out, though be aware that the DTensor API is experimental and up-to
    backward-incompatible changes. DTensor and Keras integration is published
    under `tf.keras.dtensor` in this release (refer to the `tf.keras` entry).
    The tutoral and guide for DTensor will be published on
    https://www.tensorflow.org/. Please stay tuned.