code: def forward(self, inp, mask, encoder_output, encoder_output_mask):
      x = self.embedding(inp)
      x = self.posencoding(x)
      for i in range(self.n_layers):
          x = self.layers[i](
              x, mask, encoder_output, encoder_output_mask
          )
      return self.layernorm(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 TransformerDecoder obj's underlying member method code with example usage: obj.forward(inp, mask, encoder_output, encoder_output_mask) and returns: self