code: def check_single_floating_network_output(
      output_spec: types.NestedSpec,
      expected_output_shape: typing.Tuple[int, ...],
      label: typing.Text,
  ):
      expected_output_shape = tuple(
          int(x) for x in expected_output_shape
      )
      if not (
          isinstance(output_spec, tf.TensorSpec)
          and output_spec.shape == expected_output_shape
          and output_spec.dtype.is_floating
      ):
          raise ValueError(
              "Expected {} to emit a floating point tensor with inner dims "
              "{}; but saw network output spec: {}".format(
                  label, expected_output_shape, output_spec
              )
          )
  
file_path: agents/tf_agents/networks/utils.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import typing
  import numpy
  import tensorflow
  from tf_agents.keras_layers import permanent_variable_rate_dropout
  from tf_agents.typing import types
  from tf_agents.utils import composite
label_desc: Use image node_id 1 for calling a global function with example usage: check_single_floating_network_output(output_spec, expected_output_shape, label) without return types