code: def __init__(self, params, lr=0.11072018):
      defaults = dict(lr=lr)
      super(HybridStateOptimizer, self).__init__(params, defaults)
  
imports: import os
  import json
  import argparse
  import torch
  from collections import OrderedDict
  from deepspeed.pipe import PipelineModule, LayerSpec
  from deepspeed.moe.layer import MoE
  from deepspeed.accelerator import get_accelerator
  import deepspeed.comm
label_desc: Use image node_id 1 to create a new HybridStateOptimizer object from inherited base classes: torch.optim with example: obj = HybridStateOptimizer(params, lr)