code: def transformer_revnet_test():
      hparams = transformer_revnet.transformer_revnet_base()
      hparams.num_hidden_layers = 2
      hparams.hidden_size = 128
      hparams.filter_size = 512
      hparams.num_heads = 2
      return hparams
  
file_path: tensor2tensor/tensor2tensor/models/research/transformer_revnet_test.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import numpy
  from tensor2tensor.data_generators import problem_hparams
  from tensor2tensor.models.research import transformer_revnet
  import tensorflow.compat.v1
  from tensorflow.compat.v1 import estimator
label_desc: Use image node_id 1 for calling a global function with example usage: transformer_revnet_test() and returns: hparams