code: def spec_shape(t):
      if isinstance(t, tf.SparseTensor):
          rank = tf.compat.dimension_value(t.dense_shape.shape[0])
          return tf.TensorShape([None] * rank)
      else:
          return t.shape
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import collections
  import numbers
  from typing import Optional, Text
  from absl import logging
  import numpy
  from six.moves import zip
  import tensorflow
  from tf_agents.typing import types
  from tf_agents.utils import composite
  import wrapt
  from tensorflow.python.util import nest
label_desc: Use image node_id 13 for calling a global function with example usage: spec_shape(t) and returns: tf, t