code: def adaptive_universal_transformer_multilayer_tpu():
      """Multi-layer config for adaptive Transformer on TPU."""
      hparams = adaptive_universal_transformer_base_tpu()
      hparams.num_inrecurrence_layers = 2
      hparams.mix_with_transformer = "before_ut,after_ut"
      hparams.num_mixedin_layers = 1
      hparams.transformer_ffn_type = "sepconv"
      # TODO(lukaszkaiser): the options below don't work on TPU yet, make them work.
      # hparams.add_step_timing_signal = True
      # hparams.add_sru = True
      # hparams.self_attention_type = "dot_product_relative_v2"
      # hparams.max_relative_position = 256
      return hparams
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from tensor2tensor.layers import common_attention
  from tensor2tensor.layers import common_layers
  from tensor2tensor.models import transformer
  from tensor2tensor.models.research import universal_transformer_util
  from tensor2tensor.utils import contrib
  from tensor2tensor.utils import registry
  import tensorflow.compat.v1
label_desc: Use image node_id 14 for calling a global function with example usage: adaptive_universal_transformer_multilayer_tpu() and returns: hparams