code: def revnet_cifar_base():
      """Tiny hparams suitable for CIFAR/etc."""
      hparams = revnet_base()
      hparams.num_channels_init_block = 32
      hparams.first_batch_norm = [False, True, True]
      hparams.init_stride = 1
      hparams.init_kernel_size = 3
      hparams.init_maxpool = False
      hparams.strides = [1, 2, 2]
      hparams.batch_size = 128
      hparams.weight_decay = 1e-4
  
      hparams.learning_rate = 0.1
      hparams.learning_rate_cosine_cycle_steps = 5000
      return hparams
  
imports: import functools
  from tensor2tensor.layers import common_hparams
  from tensor2tensor.utils import contrib
  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 11 for calling a global function with example usage: revnet_cifar_base() and returns: hparams