code: def transformer_moe_8k():
      """Hyper parameters specifics for long sequence generation."""
      hparams = transformer_moe_base()
  
      hparams.batch_size = 8192
      hparams.max_length = 0  # max_length == batch_size
      hparams.eval_drop_long_sequences = True
      hparams.min_length_bucket = (
          256  # Avoid cyclic problems for big batches
      )
  
      hparams.default_ff = "sep"
      hparams.hidden_size = 1024
  
      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 2 for calling a global function with example usage: transformer_moe_8k() and returns: hparams