code: def adaptive_universal_transformer_multilayer_hard():
      """Multi-layer config for adaptive Transformer with hard attention."""
      hparams = adaptive_universal_transformer_multilayer_tpu()
      hparams.batch_size = 256
      hparams.hard_attention_k = 8
      hparams.add_step_timing_signal = True
      # hparams.add_sru = True  # This is very slow on GPUs, does it help?
      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 15 for calling a global function with example usage: adaptive_universal_transformer_multilayer_hard() and returns: hparams