code: def forward(self, inp, mask, encoder_output, encoder_output_mask):
      x = self.norm1(inp)
      x = inp + self.dropout1(self.self_attn(x, x, x, mask))
      x = x + self.dropout2(
          self.cross_attn(
              self.norm2(x),
              encoder_output,
              encoder_output,
              encoder_output_mask,
          )
      )
      x = x + self.dropout3(self.ff(self.norm3(x)))
      return x
  
imports: import torch
  import torch.nn
  import torch.nn.functional
  import math
  import copy
label_desc: Use image node_id 2 for calling the TransformerDecoderLayer obj's underlying member method code with example usage: obj.forward(inp, mask, encoder_output, encoder_output_mask) and returns: x