code: def forward(self, x, padding_mask):
      x = self.pos_encoder(x)
      x = self.transformer_encoder(x, src_key_padding_mask=padding_mask)
  
      bos_embedding = x[0, :]
      logits = self.classifier(bos_embedding)
      return F.log_softmax(logits, dim=-1)
  
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 Classifier obj's underlying member method code with example usage: obj.forward(x, padding_mask) and returns: F