code: def evolved_transformer_deep():
      """Deep parameters for Evolved Transformer model on WMT."""
      hparams = add_evolved_transformer_hparams(
          transformer.transformer_big()
      )
      hparams.num_encoder_layers = 9
      hparams.num_decoder_layers = 10
      hparams.hidden_size = 640
      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.utils import registry
  from tensor2tensor.utils import t2t_model
  import tensorflow.compat.v1
  from tensorflow.python.ops import inplace_ops
label_desc: Use image node_id 10 for calling a global function with example usage: evolved_transformer_deep() and returns: hparams