code: def cycle_gan_small():
      """Set of hyperparameters."""
      hparams = transformer_vae.transformer_ae_small()
      hparams.batch_size = 2048
      hparams.bottom = {
          "inputs": modalities.identity_bottom,
          "targets": modalities.identity_bottom,
      }
      hparams.top = {
          "targets": modalities.identity_top,
      }
      hparams.weight_decay = 3.0
      hparams.learning_rate = 0.05
      hparams.kl_warmup_steps = 5000
      hparams.learning_rate_warmup_steps = 3000
      hparams.add_hparam(
          "vocab_size", 66
      )  # Vocabulary size, need to set here.
      hparams.add_hparam("cycle_loss_multiplier1", 10.0)
      hparams.add_hparam("cycle_loss_multiplier2", 10.0)
      return hparams
  
file_path: tensor2tensor/tensor2tensor/models/research/cycle_gan.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from tensor2tensor.layers import common_layers
  from tensor2tensor.layers import modalities
  from tensor2tensor.models.research import transformer_vae
  from tensor2tensor.utils import registry
  from tensor2tensor.utils import t2t_model
  import tensorflow.compat.v1
label_desc: Use image node_id 6 for calling a global function with example usage: cycle_gan_small() and returns: hparams