"//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

@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//

#     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.