code: def __init__(self, params: ModelArgs):
      super().__init__(params)
      self.layers = torch.nn.ModuleList()
      for layer_id in range(params.n_layers):
          self.layers.append(MoETorchTransformerBlock(layer_id, params))
  
imports: import math
  from dataclasses import dataclass
  from typing import Dict, Optional, Tuple
  import torch
  import torch.nn.functional
  from torch import nn
  from .utils import ModelArgs
  from .attention import TorchAttention, FairScaleAttention
  from .ffn import TorchFFN, FairScaleFFN
  from .transformer import TorchTransformerBlock, TorchTransformer, FairScaleTransformer
label_desc: Use image node_id 1 to create a new MoEFairScaleTransformer object from inherited base classes: FairScaleTransformer with example: obj = MoEFairScaleTransformer(params)