#     tpu:          Build TF with TPU support
#     cuda:         Build with CUDA support.
#     cuda_clang    Build with CUDA Clang support.
#     rocm:         Build with AMD GPU support (rocm)
#     mkl:          Enable full mkl support.
#     nogcp:        Disable GCS support.
#     nonccl:       Disable nccl support.
#
#
# Remote build execution options (only configured to work with TF team projects for now.)

@rules_ml_toolchain//
@rules_python//
@stablehlo//stablehlo/experimental
EOF

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

  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',
      'Build with oneDNN and Compute Library for the Arm Architecture (ACL).')
  config_info_line('monolithic', 'Config for mostly static monolithic build.')

        `batch_dims` case.
    *   Removing of dtype in the constructor of initializers and partition_info
        in call.
    *   Add `tf.math.nextafter` op.
    *   Turn on MKL-DNN contraction kernels by default. MKL-DNN dynamically
        dispatches the best kernel implementation based on CPU vector
        architecture. To disable them, build with
        `--define=tensorflow_mkldnn_contraction_kernel=0`.