code: def shuffle_network_baseline():
      """Large Shuffle-Exchange configuration.
  
      Returns:
        dict: Neural Shuffle-Exchange configuration
      """
  
      hparams = common_hparams.basic_params1()
      hparams.hidden_size = 48 * 8  # feature maps
      hparams.num_hidden_layers = 2  # block count
  
      hparams.clip_grad_norm = 0.0  # no gradient clipping
  
      hparams.optimizer = "adam"
      hparams.optimizer_adam_epsilon = 1e-5
      hparams.learning_rate_schedule = "legacy"
      hparams.learning_rate_decay_scheme = "noam"
      hparams.learning_rate = 0.1
      hparams.initializer_gain = 1.0
      hparams.initializer = "uniform_unit_scaling"
      hparams.optimizer_adam_beta1 = 0.9
      hparams.optimizer_adam_beta2 = 0.999
      hparams.add_hparam(
          "force_max_length", False
      )  # use fixed max length
      hparams.max_length = 256  # use when targets are not known
  
      hparams.dropout = 0.1
      hparams.label_smoothing = 0.0
      hparams.weight_decay = 0.0
  
      return hparams
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import math
  from tensor2tensor.layers import common_hparams
  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 7 for calling a global function with example usage: shuffle_network_baseline() and returns: hparams