Example: For Python 3.11, use `3_11`

The script performs the following steps:

1. Navigates to the `../requirements_updater` directory.
2. Creates a `requirements_wheel_test.in` file and specifies the path
to the actual TensorFlow wheel.
3. Creates a `requirements_lock_<python_version>.txt` file.
4. Updates the `requirements_lock_<python_version>.txt` file using
a Bazel command.

    values from those `TFCI` paths.
    -   `set -a` / `set -o allexport` exports the variables from `env` files so
        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.

  # Find all one-step dependencies of those tests which are from //tensorflow
  # (since external deps will come from Python-level pip dependencies),
  # excluding dependencies and files that are known to be unneccessary.
  # This creates a list of targets under //tensorflow that are required for
  # TensorFlow python tests.

    *   Graduated experimental APIs:
        *   [`tf.data.Dataset.counter`](https://www.tensorflow.org/api_docs/python/tf/data/Dataset/#counter),
            which creates `Dataset`s of indefinite sequences of numbers.
        *   [`tf.data.Dataset.ignore_errors`](https://www.tensorflow.org/api_docs/python/tf/data/Dataset/#ignore_errors),
            which drops erroneous elements from `Dataset`s.

  # Find all one-step dependencies of those tests which are from //tensorflow
  # (since external deps will come from Python-level pip dependencies),
  # excluding dependencies and files that are known to be unneccessary.
  # This creates a list of targets under //tensorflow that are required for
  # TensorFlow python tests.