code: def mtf_image_transformer_base_imagenet():
      """Data parallel CIFAR parameters."""
      hparams = mtf_image_transformer_base_cifar()
      hparams.mesh_shape = "batch:32"
      hparams.layout = "batch:batch"
      hparams.batch_size = 128
      hparams.d_ff = 2048
      hparams.hidden_size = 512
      hparams.num_decoder_layers = 12
      hparams.learning_rate = 0.5
      hparams.learning_rate_warmup_steps = 31250
      hparams.layer_preprocess_sequence = "none"
      hparams.layer_postprocess_sequence = "dan"
      hparams.layer_prepostprocess_dropout = 0.1
      hparams.unconditional = True
      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.layers import common_layers
  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 14 for calling a global function with example usage: mtf_image_transformer_base_imagenet() and returns: hparams