class_docstr: Multi-Head Attention layer of Transformer.
  Args:
      n_head (int): number of heads
      n_feat (int): size of the features
      dropout_rate (float): dropout rate
      proj_dim (int, optional): Optional integer value for projection before computing attention.
         If None, then there is no projection (equivalent to proj_dim = n_feat).
         If > 0, then will project the n_feat to proj_dim before calculating attention.
         If <0, then will equal n_head, so that each head has a projected dimension of 1.
     adapter_strategy: By default, MHAResidualAddAdapterStrategyConfig. An adapter composition function object.
code: def get_default_strategy_config(self) -> "dataclass":
      return MHAResidualAddAdapterStrategyConfig()
  
imports: import math
  from dataclasses import dataclass, field
  from typing import Any, Optional
  import torch
  from torch import nn
  from nemo.collections.asr.parts.submodules import multi_head_attention
  from nemo.collections.common.parts import adapter_modules
  from nemo.core.classes.mixins import adapter_mixin_strategies
label_desc: Use image node_id 4 for calling the MultiHeadAttentionAdapter obj's underlying member method code with example usage: obj.get_default_strategy_config() and returns: MHAResidualAddAdapterStrategyConfig