test:nonpip_filters --test_lang_filters=py --flaky_test_attempts=3 --test_size_filters=small,medium
test:nonpip --config=nonpip_filters -- //tensorflow/... -//tensorflow/python/integration_testing/... -//tensorflow/compiler/tf2tensorrt/... -//tensorflow/core/tpu/... -//tensorflow/lite/... -//tensorflow/tools/toolchains/...

# "pip tests" run a similar suite of tests the "nonpip" tests, but do something

test:nonpip_filters --test_lang_filters=py --flaky_test_attempts=3 --test_size_filters=small,medium
test:nonpip --config=nonpip_filters -- //tensorflow/... -//tensorflow/python/integration_testing/... -//tensorflow/compiler/tf2tensorrt/... -//tensorflow/core/tpu/... -//tensorflow/lite/... -//tensorflow/tools/toolchains/...

# "pip tests" run a similar suite of tests the "nonpip" tests, but do something

# TensorFlow continuous integration

> **Warning** This folder is still under construction. It is part of an ongoing
> effort to improve the structure of CI and build related files within the
> TensorFlow repo. This warning will be removed when the contents of this
> directory are stable and appropriate documentation around its usage is in
> place.

Maintainer: TensorFlow DevInfra

# 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

    *   Added a new `rerandomize_each_iteration` argument for the `tf.data.Dataset.random()` operation, which controls whether the sequence of generated random numbers should be re-randomized every epoch or not (the default behavior). If `seed` is set and `rerandomize_each_iteration=True`, the `random()` operation will produce a different (deterministic) sequence of numbers every epoch.

        "//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/...",