code: def mtf_resnet_tiny():
      """Catch bugs locally..."""
      hparams = mtf_resnet_base()
      hparams.num_layers = 2
      hparams.hidden_size = 64
      hparams.filter_size = 64
      hparams.batch_size = 16
      # data parallelism and model-parallelism
      hparams.col_blocks = 1
      hparams.mesh_shape = "batch:2"
      hparams.layout = "batch:batch"
      hparams.layer_sizes = [1, 2, 3]
      hparams.filter_sizes = [64, 64, 64]
      return hparams
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import copy
  import mesh_tensorflow
  from tensor2tensor.layers import common_hparams
  from tensor2tensor.utils import mtf_model
  from tensor2tensor.utils import registry
  import tensorflow.compat.v1
  from tensorflow.compat.v1 import estimator
label_desc: Use image node_id 5 for calling a global function with example usage: mtf_resnet_tiny() and returns: hparams