/tensorflow/python/debug @caisq
/tensorflow/python/eager @rohan100jain
/tensorflow/tools/docs/ @markdaoust
/tensorflow/compiler/mlir/ @aminim
/tensorflow/core/ir/ @aminim
/tensorflow/core/transforms/ @aminim

if _running_from_pip_package():
  # TODO(gunan): Add sanity checks to loaded modules here.

  # Load first party dynamic kernels.
  _tf_dir = _os.path.dirname(_current_file_location)
  _kernel_dir = _os.path.join(_tf_dir, "core", "kernels")
  if _os.path.exists(_kernel_dir):
    _ll.load_library(_kernel_dir)

  # Load third party dynamic kernels.
  for _s in _site_packages_dirs:
    _plugin_dir = _os.path.join(_s, "tensorflow-plugins")

        "//third_party/cloud_tpu/convergence_tools/sdc_monitoring/...",
        "//third_party/cloud_tpu/inference_converter/...",
        "//third_party/py/cloud_ml_autoflow/...",
        "//third_party/py/envlogger/...",
        "//third_party/py/gldm/...",
        "//third_party/py/guesslang/...",
        "//third_party/py/keras/...",
        "//third_party/py/tf_keras/...",

        `_tpu_estimator_embedding.py`. This allows embedding lookup statistics
        gathered at runtime to be used in embedding layer partitioning
        decisions.
*   PluggableDevice
    *   Third-party devices can now connect to TensorFlow as plug-ins through
        [StreamExecutor C API](https://github.com/tensorflow/community/blob/master/rfcs/20200612-stream-executor-c-api.md).
        and

@absl_py//absl
@bazel_tools//platforms
@bazel_tools//third_party/
@bazel_tools//tools
@local
@com_google_absl//absl
@org_tensorflow//
@com_github_googlecloudplatform_google_cloud_cpp//google
@com_github_grpc_grpc//src/compiler
@platforms//os
@ruy//
EOF

  # grep patterns for targets which are allowed to be extra licenses
  cat > $BATS_TEST_TMPDIR/allowed_to_be_extra <<EOF
//third_party/mkl
//third_party/mkl_dnn
@absl_py//

if _running_from_pip_package():
  # TODO(gunan): Add sanity checks to loaded modules here.

  # Load first party dynamic kernels.
  _tf_dir = _os.path.dirname(_current_file_location)
  _kernel_dir = _os.path.join(_tf_dir, "core", "kernels")
  if _os.path.exists(_kernel_dir):
    _ll.load_library(_kernel_dir)

  # Load third party dynamic kernels.
  for _s in _site_packages_dirs:
    _plugin_dir = _os.path.join(_s, "tensorflow-plugins")

@ruy//
@stablehlo//stablehlo/experimental
EOF

  # grep patterns for targets which are allowed to be extra licenses
  cat > $BATS_TEST_TMPDIR/allowed_to_be_extra <<EOF
//third_party/mkl
//third_party/mkl_dnn
@absl_py//
@bazel_tools//src
@bazel_tools//platforms
@bazel_tools//tools/
@org_tensorflow//tensorflow
@com_google_absl//
@pybind11_abseil//pybind11_abseil
//external
@local
@com_github_googlecloudplatform_google_cloud_cpp//

  if is_windows():
    if int(environ_cp.get('TF_NEED_TENSORRT', False)):
      cuda_libraries.append('tensorrt')
      print('WARNING: TensorRT support on Windows is experimental\n')

  paths = glob.glob('**/third_party/gpus/find_cuda_config.py', recursive=True)
  if not paths:
    raise FileNotFoundError(
        "Can't find 'find_cuda_config.py' script inside working directory")
  proc = subprocess.Popen(

#     dynamic_kernels:  Try to link all kernels dynamically (experimental).
#     dbg:              Build with debug info
#
# TF version options;
#     v2: Build TF v2
#
# Feature and Third party library support options:
#     xla:          Build TF with XLA
#     tpu:          Build TF with TPU support
#     cuda:         Build with CUDA support.
#     cuda_clang    Build with CUDA Clang support.