contributions, often because we probably won't get to them right now. If you
decide to start on an issue, leave a comment so that other people know that
you're working on it. If you want to help out, but not alone, use the issue
comment thread to coordinate.

### Contribution guidelines and standards

Before sending your pull request for

# ==============================================================================
"""
Top-level module of TensorFlow. By convention, we refer to this module as
`tf` instead of `tensorflow`, following the common practice of importing
TensorFlow via the command `import tensorflow as tf`.

The primary function of this module is to import all of the public TensorFlow
interfaces into a single place. The interfaces themselves are located in

build:android --dynamic_mode=off

# Sets the default Apple platform to macOS.
build:macos --apple_platform_type=macos

# gRPC on MacOS requires this #define
build:macos --copt=-DGRPC_BAZEL_BUILD

# Avoid hitting command line argument limit
build:macos --features=archive_param_file

# Settings for MacOS on ARM CPUs.
build:macos_arm64 --cpu=darwin_arm64
build:macos_arm64 --macos_minimum_os=11.0

    *   Display summaries of numeric tensor values with the `-s` flag to command
        `print_tensor` or `pt`.
    *   Display feed values with the `print_feed` or `pf` command and clickable
        links in the curses UI.
    *   Runtime profiler at the op level and the Python source line level with
        the `run -p` command.
*   Initial release of the statistical distribution library `tf.distributions`.

                "//tensorflow/compiler/tf2tensorrt:op_converter_registry_impl",
                "//tensorflow/core/common_runtime:core_cpu_impl",
                "//tensorflow/core/common_runtime/gpu:gpu_runtime_impl",
                "//tensorflow/core/common_runtime/pluggable_device:pluggable_device_runtime_impl",
                "//tensorflow/core:framework_internal_impl",

  system_specific_test_config(environ_cp)

  configure_ios(environ_cp)

  print('Preconfigured Bazel build configs. You can use any of the below by '
        'adding "--config=<>" to your build command. See .bazelrc for more '
        'details.')
  config_info_line('mkl', 'Build with MKL support.')
  config_info_line(
      'mkl_aarch64',

            "//tensorflow/core/common_runtime/eager:attr_builder",
            "//tensorflow/core/common_runtime/eager:context",
            "//tensorflow/core/common_runtime/eager:context_distributed_manager",
            "//tensorflow/core/common_runtime/eager:core",
            "//tensorflow/core/common_runtime/eager:custom_device",
            "//tensorflow/core/common_runtime/eager:eager_executor",

  # replace tensorflow to tf_nightly in the wheel name
  export TFCI_BUILD_PIP_PACKAGE_ARGS="$(echo $TFCI_BUILD_PIP_PACKAGE_ARGS | sed 's/tensorflow/tf_nightly/')"
fi

tfrun bazel build $TFCI_BAZEL_COMMON_ARGS //tensorflow/tools/pip_package:wheel $TFCI_BUILD_PIP_PACKAGE_ARGS
tfrun find ./bazel-bin/tensorflow/tools/pip_package -iname "*.whl" -exec cp {} $TFCI_OUTPUT_DIR \;
tfrun ./ci/official/utilities/rename_and_verify_wheels.sh

#include "tensorflow/core/common_runtime/copy_tensor.h"
#include "tensorflow/core/common_runtime/device.h"
#include "tensorflow/core/common_runtime/device_factory.h"
#include "tensorflow/core/common_runtime/device_mgr.h"
#include "tensorflow/core/common_runtime/eager/attr_builder.h"
#include "tensorflow/core/common_runtime/eager/context.h"
#include "tensorflow/core/common_runtime/eager/custom_device.h"

fi
# VERY basic check to ensure the [and-cuda] package variant is installable.
# Checks TFCI_BAZEL_COMMON_ARGS for "gpu" or "cuda", implying that the test is
# relevant. All of the GPU test machines have CUDA installed via other means,
# so I am not sure how to verify that the dependencies themselves are valid for
# the moment.
if [[ "$TFCI_BAZEL_COMMON_ARGS" =~ gpu|cuda ]]; then
  echo "Checking to make sure tensorflow[and-cuda] is installable..."