code: def forward(self, inputs):
      token_ids = inputs["token_ids"]
      type_ids = inputs["type_ids"]
      pos_ids = inputs["pos_ids"]
      attention_mask = inputs["attention_mask"]
      label_pos = inputs["label_pos"]
  
      out, self_attn_mask = self.gen_input(
          token_ids, type_ids, pos_ids, attention_mask
      )
      # [-1, seq_len, hidden_size]
      enc_out = self.encoder(out, self_attn_mask)
  
      enc_out = paddle.reshape(enc_out, [-1, self.hidden_size])
      label_pos = paddle.cast(label_pos, "int64")
      out = paddle.gather(enc_out, label_pos)
      pooled_out = self.fc1(out)
      pooled_out = self.tanh_layer(pooled_out)
  
      # [-1, 2]
      logits = self.fc2(pooled_out)
      probs = self.softmax(logits)
  
      return probs
  
imports: from collections import namedtuple
  import paddle
  import paddle.nn
  import paddle.nn.functional
label_desc: Use image node_id 2 for calling the NSP obj's underlying member method code with example usage: obj.forward(inputs) and returns: probs