code: def __init__(self, hidden_dim, empty_grad=False, nlayers=1):
      super(SimpleModel, self).__init__()
      self.linears = torch.nn.ModuleList(
          [
              torch.nn.Linear(hidden_dim, hidden_dim)
              for i in range(nlayers)
          ]
      )
      if empty_grad:
          self.linear2 = torch.nn.Linear(hidden_dim, hidden_dim)
      self.cross_entropy_loss = torch.nn.CrossEntropyLoss()
      self.empty_grad = empty_grad
  
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 SimpleModel object from inherited base classes: torch.nn with example: obj = SimpleModel(hidden_dim, empty_grad, nlayers)