code: def __init__(self, *args, **kwargs):
      self.params_list = None
      super(LSHFTransformerEncoderLayer, self).__init__(*args, **kwargs)
  
imports: import torch
  from torch import nn
  from dataclasses import dataclass
  from lightseq.training.ops.pytorch.transformer_encoder_layer import LSTransformerEncoderLayer
  from lightseq.training.ops.pytorch.transformer_decoder_layer import LSTransformerDecoderLayer
  from lightseq.training.ops.pytorch.quantization import weight_quant_config, act_quant_config, relu_quant_config
  from transformers import BartPretrainedModel, BartForConditionalGeneration, BartForSequenceClassification, BartForQuestionAnswering
  from transformers.models.bart.modeling_bart import BartEncoderLayer, BartDecoderLayer
label_desc: Use image node_id 1 to create a new LSHFTransformerEncoderLayer object from inherited base classes: TransformerEncoderLayer with example: obj = LSHFTransformerEncoderLayer()