code: def __init__(
      self,
      args,
      no_encoder_attn=False,
      add_bias_kv=False,
      add_zero_attn=False,
  ):
      super().__init__(
          TransformerConfig.from_namespace(args),
          no_encoder_attn=no_encoder_attn,
          add_bias_kv=add_bias_kv,
          add_zero_attn=add_zero_attn,
      )
      self.args = args
  
imports: from typing import Dict, List, Optional
  import torch
  import torch.nn
  from torch import Tensor
  from fairseq import utils
  from fairseq.models.transformer import TransformerConfig
  from fairseq.modules import LayerNorm, MultiheadAttention
  from fairseq.modules.fairseq_dropout import FairseqDropout
  from fairseq.modules.quant_noise import quant_noise
label_desc: Use image node_id 1 to create a new TransformerDecoderLayer object from inherited base classes: TransformerDecoderLayerBase with example: obj = TransformerDecoderLayer(args, no_encoder_attn, add_bias_kv, add_zero_attn)