all scripts can use them.
    -   `utilities/setup_docker.sh` creates a container called `tf` with all
        `TFCI_` variables shared to it.
3.  Top-level scripts (`wheel.sh`, etc.) reference `env` variables and call
    `utilities/` scripts.
    -   The `tfrun` function makes a command run correctly in Docker if Docker

        requires all optimizer variables to be created at the first
        `apply_gradients()` or `minimize()` call. If your workflow calls
        optimizer to update different parts of model in multiple stages,
        please call `optimizer.build(model.trainable_variables)` before the
        training loop.
    *   **Performance regression on `ParameterServerStrategy`.** This could be

//tensorflow/python/debug:grpc_tensorflow_server.par
//tensorflow/python/feature_column:vocabulary_testdata
//tensorflow/python/util:nest_test_main_lib
//tensorflow/lite/experimental/examples/lstm:rnn_cell
//tensorflow/lite/experimental/examples/lstm:rnn_cell.py
//tensorflow/lite/experimental/examples/lstm:unidirectional_sequence_lstm_test
//tensorflow/lite/experimental/examples/lstm:unidirectional_sequence_lstm_test.py
//tensorflow/lite/python:interpreter

        "tfe_monitoring_reader_internal.h",
    ],
    visibility = ["//tensorflow:internal"],
    deps = [
        ":c_api",
        "//tensorflow/c:c_api",
        "//tensorflow/core/lib/monitoring:cell_reader",
        "@com_google_absl//absl/memory",
    ],
    alwayslink = 1,
)

tf_cuda_cc_test(
    name = "c_api_experimental_test",
    size = "small",
    srcs = [

//tensorflow/python/debug:grpc_tensorflow_server.par
//tensorflow/python/feature_column:vocabulary_testdata
//tensorflow/python/util:nest_test_main_lib
//tensorflow/lite/experimental/examples/lstm:rnn_cell
//tensorflow/lite/experimental/examples/lstm:rnn_cell.py
//tensorflow/lite/experimental/examples/lstm:unidirectional_sequence_lstm_test
//tensorflow/lite/experimental/examples/lstm:unidirectional_sequence_lstm_test.py
//tensorflow/lite/python:interpreter