code: def standardize_shapes(features, batch_size=None):
      """Set the right shapes for the features."""
      for fname in ["inputs", "targets"]:
          if fname not in features:
              continue
          f = features[fname]
          while len(f.get_shape()) < 4:
              f = tf.expand_dims(f, axis=-1)
          features[fname] = f
  
      if batch_size:
          # Ensure batch size is set on all features
          for _, t in six.iteritems(features):
              shape = t.get_shape().as_list()
              shape[0] = batch_size
              t.set_shape(t.get_shape().merge_with(shape))
              # Assert shapes are fully known
              t.get_shape().assert_is_fully_defined()
  
      return features
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import functools
  import multiprocessing
  import random
  import six
  from six.moves import range
  from tensor2tensor.utils import contrib
  from tensor2tensor.utils import mlperf_log
  import tensorflow.compat.v1
  from tensorflow.compat.v1 import estimator
label_desc: Use image node_id 11 for calling a global function with example usage: standardize_shapes(features, batch_size) and returns: features