code: def pad_for_tpu(shapes_dict, hparams, max_length):
      """Pads unknown features' dimensions for TPU."""
      padded_shapes = {}
  
      def get_filler(specified_max_length):
          if not specified_max_length:
              return max_length
          return min(specified_max_length, max_length)
  
      inputs_none_filler = get_filler(hparams.max_input_seq_length)
      targets_none_filler = get_filler(hparams.max_target_seq_length)
  
      def pad_one_shape(shape, none_filler):
          return [
              (dim if dim is not None else none_filler)
              for dim in shape.as_list()
          ]
  
      for key, shape in six.iteritems(shapes_dict):
          if key == "inputs":
              padded_shapes[key] = pad_one_shape(
                  shape, inputs_none_filler
              )
          elif key == "targets":
              padded_shapes[key] = pad_one_shape(
                  shape, targets_none_filler
              )
          else:
              padded_shapes[key] = pad_one_shape(shape, max_length)
      return padded_shapes
  
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 8 for calling a global function with example usage: pad_for_tpu(shapes_dict, hparams, max_length) and returns: padded_shapes, min, unknown, max_length