code: def transition_dataset_from_spec(
      spec: specs.EnvironmentSpec,
  ) -> tf.data.Dataset:
      """Constructs fake dataset of Reverb N-step transition samples.
  
      Args:
        spec: Constructed fake transitions match the provided specification.
  
      Returns:
        tf.data.Dataset that produces the same fake N-step transition ReverbSample
        object indefinitely.
      """
  
      observation = _generate_from_spec(spec.observations)
      action = _generate_from_spec(spec.actions)
      reward = _generate_from_spec(spec.rewards)
      discount = _generate_from_spec(spec.discounts)
      data = types.Transition(
          observation, action, reward, discount, observation
      )
  
      info = tree.map_structure(
          lambda tf_dtype: tf.ones([], tf_dtype.as_numpy_dtype),
          reverb.SampleInfo.tf_dtypes(),
      )
      sample = reverb.ReplaySample(info=info, data=data)
  
      return tf.data.Dataset.from_tensors(sample).repeat()
  
imports: import threading
  from typing import List, Mapping, Optional, Sequence, Callable, Iterator
  from acme import core
  from acme import specs
  from acme import types
  from acme import wrappers
  import dm_env
  import numpy
  import reverb
  from rlds import rlds_types
  import tensorflow
  import tree
label_desc: Use image node_id 4 for calling a global function with example usage: transition_dataset_from_spec(spec) and returns: tf