code: def _create_nonpadding_list():
      """Creates the `nonpadding_list` for applying the encoder layers."""
      nonpadding_list = []
      for i in range(_BATCH_SIZE):
          nonpadding_list.append(
              [1.0] * min(i + 2, _TOTAL_SEQUENCE_LENGTH)
              + [0.0] * max((_TOTAL_SEQUENCE_LENGTH - i - 2), 0)
          )
      return nonpadding_list
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import copy
  import itertools
  from absl.testing import parameterized
  import numpy
  from tensor2tensor.layers import common_attention
  from tensor2tensor.models import transformer
  from tensor2tensor.models.neural_architecture_search import nas_layers
  import tensorflow.compat.v1
label_desc: Use image node_id 5 for calling a global function with example usage: _create_nonpadding_list() and returns: nonpadding_list