code: def mqp_lm1b_base():
      """Series of architectures for language modeling."""
      hparams = mtf_transformer2.mtf_unitransformer_base()
      hparams.d_model = 1024
      hparams.max_length = 256
      hparams.batch_size = 256
      # Parameters for my_layer_stack()
      hparams.num_hidden_layers = 6
      hparams.d_ff = 8192
      hparams.d_kv = 128
      hparams.num_heads = 8
      hparams.learning_rate_decay_steps = 13600
      hparams.layout = "batch:batch;vocab:model;d_ff:model;heads:model"
      hparams.mesh_shape = "batch:32"
      return hparams
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from tensor2tensor.models import mtf_transformer2
  from tensor2tensor.utils import registry
label_desc: Use image node_id 15 for calling a global function with example usage: mqp_lm1b_base() and returns: hparams