code: def choose_from_datasets_v2(
      datasets, choice_dataset, stop_on_empty_dataset=False
  ):
      """Creates a dataset that deterministically chooses elements from `datasets`.
  
      For example, given the following datasets:
  
      ```python
      datasets = [tf.data.Dataset.from_tensors("foo").repeat(),
                  tf.data.Dataset.from_tensors("bar").repeat(),
                  tf.data.Dataset.from_tensors("baz").repeat()]
  
      # Define a dataset containing `[0, 1, 2, 0, 1, 2, 0, 1, 2]`.
      choice_dataset = tf.data.Dataset.range(3).repeat(3)
  
      result = tf.data.experimental.choose_from_datasets(datasets, choice_dataset)
      ```
  
      The elements of `result` will be:
  
      ```
      "foo", "bar", "baz", "foo", "bar", "baz", "foo", "bar", "baz"
      ```
  
      Args:
        datasets: A non-empty list of `tf.data.Dataset` objects with compatible
          structure.
        choice_dataset: A `tf.data.Dataset` of scalar `tf.int64` tensors between `0`
          and `len(datasets) - 1`.
        stop_on_empty_dataset: If `True`, selection stops if it encounters an empty
          dataset. If `False`, it skips empty datasets. It is recommended to set it
          to `True`. Otherwise, the selected elements start off as the user intends,
          but may change as input datasets become empty. This can be difficult to
          detect since the dataset starts off looking correct. Default to `False`
          for backward compatibility.
  
      Returns:
        A dataset that interleaves elements from `datasets` according to the values
        of `choice_dataset`.
  
      Raises:
        TypeError: If `datasets` or `choice_dataset` has the wrong type.
        ValueError: If `datasets` is empty.
      """
      return dataset_ops.Dataset.choose_from_datasets(
          datasets=datasets,
          choice_dataset=choice_dataset,
          stop_on_empty_dataset=stop_on_empty_dataset,
      )
  
file_path: tensorflow/tensorflow/python/data/experimental/ops/interleave_ops.py
imports: from tensorflow.python import tf2
  from tensorflow.python.compat import v2_compat
  from tensorflow.python.data.ops import dataset_ops
  from tensorflow.python.data.ops import readers
  from tensorflow.python.util import deprecation
  from tensorflow.python.util.tf_export import tf_export
label_desc: Use image node_id 4 for calling a global function with example usage: choose_from_datasets_v2(datasets, choice_dataset, stop_on_empty_dataset) and returns: dataset_ops