code: def __init__(self, headers, d_model, dropout):
      super(MultiHeadAttention, self).__init__()
  
      assert d_model % headers == 0
      self.d_k = int(d_model / headers)
      self.headers = headers
      self.linears = clones(nn.Linear(d_model, d_model), 4)
      self.attn = None
      self.dropout = nn.Dropout(dropout)
  
imports: import copy
  import math
  import paddle
  from paddle import nn
  from paddle.nn import functional
label_desc: Use image node_id 1 to create a new MultiHeadAttention object from inherited base classes: nn with example: obj = MultiHeadAttention(headers, d_model, dropout)