def _make_fake_dataset_fn():
    'Returns a dataset that emulates a remote storage data source.\n\n  Returns a dataset factory which creates a dataset with 100 elements that\n  emulates the performance characteristic of a file-based dataset stored in a\n  remote storage. In particular, the first element will take an order of\n  magnitude longer to produce than the remaining elements (1s vs. 1ms).\n  '

    def fake_dataset_fn(unused):
        del unused

        def make_dataset(time_us, num_elements):
            return dataset_ops.Dataset.range(num_elements).apply(sleep.sleep(time_us))
        return make_dataset((1000 * 1000), 0).concatenate(make_dataset(1000, 100)).take(100)
    return fake_dataset_fn
Returns a dataset that emulates a remote storage data source.

Returns a dataset factory which creates a dataset with 100 elements that
emulates the performance characteristic of a file-based dataset stored in a
remote storage. In particular, the first element will take an order of
magnitude longer to produce than the remaining elements (1s vs. 1ms).
def _make_fake_dataset_fn():
    'Returns a dataset that emulates a remote storage data source.\n\n  Returns a dataset factory which creates a dataset with 100 elements that\n  emulates the performance characteristic of a file-based dataset stored in a\n  remote storage. In particular, the first element will take an order of\n  magnitude longer to produce than the remaining elements (1s vs. 1ms).\n  '

    def fake_dataset_fn(unused):
        del unused

        def make_dataset(time_us, num_elements):
            return dataset_ops.Dataset.range(num_elements).apply(sleep.sleep(time_us))
        return make_dataset((1000 * 1000), 0).concatenate(make_dataset(1000, 100)).take(100)
    return fake_dataset_fn