code: def xmoe2_v1_x128():
      """128 experts, ~25B params - Train for 131072 steps on 8x8."""
      hparams = xmoe2_v1()
      hparams.moe_num_experts = [16, 8]
      hparams.outer_batch_size = 8
      hparams.mesh_shape = "b0:8;b1:16"
      hparams.batch_size = 512
      hparams.learning_rate_decay_steps = 16384
      return hparams
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from tensor2tensor.models import mtf_transformer
  from tensor2tensor.models import mtf_transformer2
  from tensor2tensor.models.research import moe
  from tensor2tensor.utils import registry
label_desc: Use image node_id 20 for calling a global function with example usage: xmoe2_v1_x128() and returns: hparams