code: def forward(self, inp, mask):
      x = self.norm1(inp)
      x = inp + self.dropout1(self.self_attn(x, x, x, mask))
      x = x + self.dropout2(self.ff_layer(self.norm2(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 TransformerEncoderLayer obj's underlying member method code with example usage: obj.forward(inp, mask) and returns: x