code: def mtf_image_transformer_base_imagenet_mp():
      """Model parallel ImageNet parameters."""
      hparams = mtf_image_transformer_base_imagenet()
      hparams.mesh_shape = "model:4;batch:8"
      hparams.layout = "batch:batch;d_ff:model;heads:model"
      hparams.batch_size = 32
      hparams.num_heads = 8
      hparams.d_ff = 8192
      hparams.learning_rate_warmup_steps = 31250
      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 15 for calling a global function with example usage: mtf_image_transformer_base_imagenet_mp() and returns: hparams