code: def transformer_moe_12k():
      """Hyper parameters specifics for long sequence generation."""
      hparams = transformer_moe_8k()
      hparams.batch_size = 12000
      # At 12k, the softmax become the memory bottleneck
      hparams.factored_logit = True
      return hparams
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from tensor2tensor.layers import common_attention
  from tensor2tensor.layers import common_hparams
  from tensor2tensor.layers import common_layers
  from tensor2tensor.models import transformer
  from tensor2tensor.utils import expert_utils
  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 5 for calling a global function with example usage: transformer_moe_12k() and returns: hparams