-   type: input id: Bazel attributes: label: Bazel version description: if
    compiling from source placeholder: validations: required: false

-   type: input id: Compiler attributes: label: GCC/Compiler version
    description: if compiling from source placeholder: validations: required:
    false

-   type: input id: Cuda attributes: label: CUDA/cuDNN version description:
    placeholder: validations: required: false

#   will need to run `docker exec tf pkill bazel` to quit bazel.
#
#   Note: new files created from the container are owned by "root".
#   You can run e.g. `docker exec tf chown -R $(id -u):$(id -g) build_output`
#   to transfer ownership to your user.
#
# Docker is enabled by default on Linux. You may disable it if you prefer:
# export TFCI=py311,linux_x86,no_docker

TFCI_ARTIFACT_FINAL_PYPI_ENABLE=1
TFCI_ARTIFACT_LATEST_GCS_URI="gs://tensorflow/versions/latest/"
TFCI_ARTIFACT_STAGING_GCS_ENABLE=1
TFCI_ARTIFACT_STAGING_GCS_URI="gs://tensorflow-ci-artifact-staging/staging/versions/${_LOUHI_EXECUTION_ID:-$(git rev-parse HEAD)}/"

            "//tensorflow/core:framework",
            "//tensorflow/core:framework_lite",
            "//tensorflow/core:protos_all_cc",
            "@local_tsl//tsl/framework:device_id_utils",
            "@local_tsl//tsl/platform:statusor",
            "@local_xla//xla/stream_executor",
        ],
    }),
)

cc_library(
    name = "kernels_experimental_hdrs",

        for more details.
    *   Added `dataset_id` to `tf.data.experimental.service.register_dataset`.
        If provided, `tf.data` service will use the provided ID for the dataset.
        If the dataset ID already exists, no new dataset will be registered.
        This is useful if multiple training jobs need to use the same dataset