[Docs] De-flake doctests

[bveeramani]

Why are these changes needed?

This PR fixes three flaky examples.

Flaky example #1

This example is flaky because multiple examples write to /tmp/iris. In this case, there can be more than two files in the directory.

.. testcode::

    import os

    transformed_ds.write_parquet("/tmp/iris")

    print(sorted(os.listdir("/tmp/iris")))

.. testoutput::

    ['..._000000.parquet', '..._000001.parquet']

Flaky example #2

This example might produce output if the model weights aren't already downloaded.

        .. testcode::

            from ray.train.tensorflow import TensorflowCheckpoint
            import tensorflow as tf

            model = tf.keras.applications.resnet.ResNet101()
            checkpoint = TensorflowCheckpoint.from_model(model)

Flaky examples #3

If this test is re-run, it fails because "example.db" isn't cleaned up.

        .. testcode::

            import sqlite3

            import ray

            # Create a simple database
            connection = sqlite3.connect("example.db")
            connection.execute("CREATE TABLE movie(title, year, score)")

Related issue number

Checks

• I've signed off every commit(by using the -s flag, i.e., git commit -s) in this PR.
• I've run scripts/format.sh to lint the changes in this PR.
• I've included any doc changes needed for https://docs.ray.io/en/master/.
  • I've added any new APIs to the API Reference. For example, if I added a
    method in Tune, I've added it in doc/source/tune/api/ under the
    corresponding .rst file.
• I've made sure the tests are passing. Note that there might be a few flaky tests, see the recent failures at https://flakey-tests.ray.io/
• Testing Strategy
  • Unit tests
  • Release tests
  • This PR is not tested :(