code: def nas_seq2seq_base():
      """Base parameters for Nas Seq2Seq model.
  
      The default parameters are set to create the Transformer.
  
      Returns:
        Hyperparameters for Nas Seq2Seq model.
      """
      hparams = transformer.transformer_base()
  
      hparams.add_hparam("encoder_num_cells", 6)
      hparams.add_hparam("encoder_left_inputs", [0, 1, 2, 3])
      hparams.add_hparam(
          "encoder_left_layers",
          [
              "standard_attention",
              "standard_conv_1x1",
              "standard_conv_1x1",
              "identity",
          ],
      )
      hparams.add_hparam(
          "encoder_left_output_dims", [512, 2048, 512, 512]
      )
      hparams.add_hparam(
          "encoder_left_activations", ["none", "relu", "none", "none"]
      )
      hparams.add_hparam(
          "encoder_left_norms",
          ["layer_norm", "layer_norm", "none", "none"],
      )
      hparams.add_hparam("encoder_right_inputs", [0, 1, 1, 1])
      hparams.add_hparam(
          "encoder_right_layers",
          ["identity", "dead_branch", "identity", "dead_branch"],
      )
      hparams.add_hparam(
          "encoder_right_activations", ["none", "none", "none", "none"]
      )
      hparams.add_hparam(
          "encoder_right_output_dims", [512, 512, 512, 512]
      )
      hparams.add_hparam(
          "encoder_right_norms", ["none", "none", "none", "none"]
      )
      hparams.add_hparam(
          "encoder_combiner_functions", ["add", "add", "add", "add"]
      )
      hparams.add_hparam("encoder_final_combiner_function", "add")
  
      hparams.add_hparam("decoder_num_cells", 6)
      hparams.add_hparam("decoder_left_inputs", [0, 1, 2, 3, 4])
      hparams.add_hparam(
          "decoder_left_layers",
          [
              "standard_attention",
              "attend_to_encoder",
              "standard_conv_1x1",
              "standard_conv_1x1",
              "identity",
          ],
      )
      hparams.add_hparam(
          "decoder_left_activations",
          ["none", "none", "relu", "none", "none"],
      )
      hparams.add_hparam(
          "decoder_left_output_dims", [512, 512, 2048, 512, 512]
      )
      hparams.add_hparam(
          "decoder_left_norms",
          ["layer_norm", "layer_norm", "layer_norm", "none", "none"],
      )
      hparams.add_hparam("decoder_right_inputs", [0, 1, 2, 2, 4])
      hparams.add_hparam(
          "decoder_right_layers",
          [
              "identity",
              "identity",
              "dead_branch",
              "identity",
              "dead_branch",
          ],
      )
      hparams.add_hparam(
          "decoder_right_activations",
          ["none", "none", "none", "none", "none"],
      )
      hparams.add_hparam(
          "decoder_right_output_dims", [512, 512, 512, 512, 512]
      )
      hparams.add_hparam(
          "decoder_right_norms",
          ["none", "none", "none", "none", "none"],
      )
      hparams.add_hparam(
          "decoder_combiner_functions",
          ["add", "add", "add", "add", "add"],
      )
      hparams.add_hparam("decoder_final_combiner_function", "add")
  
      return hparams
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import abc
  import six
  from tensor2tensor.layers import common_attention
  from tensor2tensor.layers import common_layers
  from tensor2tensor.models import transformer
  from tensor2tensor.models.neural_architecture_search import nas_layers
  from tensor2tensor.utils import contrib
  from tensor2tensor.utils import metrics
  from tensor2tensor.utils import registry
  from tensor2tensor.utils import t2t_model
  import tensorflow.compat.v1
  from tensorflow.compat.v1 import estimator
label_desc: Use image node_id 10 for calling a global function with example usage: nas_seq2seq_base() and returns: hparams