code: def build_self_attention(
      self, embed_dim, args, add_bias_kv=False, add_zero_attn=False
  ):
      return super().build_self_attention(
          embed_dim,
          TransformerConfig.from_namespace(args),
          add_bias_kv=add_bias_kv,
          add_zero_attn=add_zero_attn,
      )
  
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 2 for calling the TransformerDecoderLayer obj's underlying member method code with example usage: obj.build_self_attention(embed_dim, args, add_bias_kv, add_zero_attn) and returns: super