code: def remove_singleton_batch_spec_dim(
      spec: tf.TypeSpec, outer_ndim: int
  ) -> tf.TypeSpec:
      """Look for `spec`'s shape, check that outer dim is 1, and remove it.
  
      If `spec.shape[i] != 1` for any `i in range(outer_ndim)`, we stop removing
      singleton batch dimensions at `i` and return what's left.  This is necessary
      to handle the outputs of inconsistent layers like `tf.keras.layers.LSTM()`
      which may take as input `(batch, time, dim) = (1, 1, Nin)` and emits only the
      batch entry if `time == 1`: output shape is `(1, Nout)`.  We log an error
      in these cases.
  
      Args:
        spec: A `tf.TypeSpec`.
        outer_ndim: The maximum number of outer singleton dims to remove.
  
      Returns:
        A `tf.TypeSpec`, the spec without its outer batch dimension(s).
  
      Raises:
        ValueError: If `spec` lacks a `shape` property.
      """
      shape = getattr(spec, "shape", None)
      if shape is None:
          shape = getattr(spec, "_shape", None)
      if shape is None:
          raise ValueError(
              "Could not remove singleton batch dim from spec; it lacks a shape: {}".format(
                  spec
              )
          )
      for i in range(outer_ndim):
          if len(shape) <= i:
              logging.error(
                  "Could not remove singleton batch dim from spec; len(shape) < %d.  "
                  "Shape: %s.  Skipping.",
                  i + 1,
                  shape,
              )
              break
          if tf.compat.dimension_value(shape[i]) != 1:
              logging.error(
                  "Could not remove singleton batch dim from spec; shape[%d] != 1: %s "
                  "(shape: %s).  Skipping.",
                  i,
                  spec,
                  shape,
              )
              break
          spec = spec._unbatch()  # pylint: disable=protected-access
      return spec
  
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 33 for calling a global function with example usage: remove_singleton_batch_spec_dim(spec, outer_ndim) and returns: spec