code: def get_vocabulary(mixture_or_task_name=None):
      """Return vocabulary from the mixture or task."""
      if not mixture_or_task_name:
          # Attempt to extract the mixture/task name from the gin config.
          try:
              mixture_or_task_name = gin.query_parameter(
                  "%MIXTURE_NAME"
              )
          except ValueError:
              logging.warning(
                  "Could not extract mixture/task name from gin config."
              )
      if mixture_or_task_name:
          provider = t5.data.get_mixture_or_task(mixture_or_task_name)
          features = provider.output_features
          if "inputs" in features and "targets" in features:
              return (
                  features["inputs"].vocabulary,
                  features["targets"].vocabulary,
              )
          else:
              feature_values = list(features.values())
              vocabulary = feature_values[0].vocabulary
              for feature in feature_values[1:]:
                  if feature.vocabulary != vocabulary:
                      logging.warning(
                          "No feature_name was provided to get_vocabulary, but "
                          "output_features have different vocabularies."
                      )
                      vocabulary = None
                      break
              if vocabulary:
                  return vocabulary
      logging.warning("Using default vocabulary.")
      return t5.data.get_default_vocabulary()
  
imports: import functools
  import os
  import re
  from typing import Any, Callable, Iterable, Mapping, MutableSequence, Optional, Sequence, Tuple, Union
  from absl import logging
  import gin
  import numpy
  import seqio
  import t5.data
  import tensorflow.compat.v1
  import tensorflow_datasets
  import typing_extensions
label_desc: Use image node_id 5 for calling a global function with example usage: get_vocabulary(mixture_or_task_name) and returns: t5, features,  features, vocabulary