code: def forward(self, x):
      assert x.size(0) < self.pe.size(
          0
      ), f"{x.size()=} {self.pe.size()=}"
  
      x = x + self.pe[: x.size(0), :]
      return self.dropout(x)
  
imports: import math
  import torch
  import torch.nn
  from torch.nn import TransformerEncoder, TransformerEncoderLayer
  import torch.nn.functional
label_desc: Use image node_id 2 for calling the PositionalEncoding obj's underlying member method code with example usage: obj.forward(x) and returns: self