code: def _check_spec(spec):
      """Checks for missing or colliding names in specs."""
      spec_names = set()
      checked = [
          _true_if_missing_or_collision(s, spec_names)
          for s in tf.nest.flatten(spec)
      ]
      if any(checked):
          raise ValueError(
              "Specs contain either a missing name or a name collision.\n  "
              "Spec names: %s\n"
              % (
                  tf.nest.map_structure(
                      lambda s: s.name or "<MISSING>", spec
                  ),
              )
          )
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import copy
  import functools
  import os
  from typing import Any, Callable, Dict, Tuple, Optional, Text, cast, Sequence
  from absl import logging
  import tensorflow
  import tensorflow_probability
  from tf_agents.policies import tf_policy
  from tf_agents.specs import tensor_spec
  from tf_agents.trajectories import time_step
  from tf_agents.typing import types
  from tf_agents.utils import common
  from tf_agents.utils import nest_utils
  from tensorflow.python.eager import def_function
label_desc: Use image node_id 3 for calling a global function with example usage: _check_spec(spec) without return types