code: def forward(self, x, targets=None):
      cnt_inputs, seq_inputs = x
      if self.use_cnt:
          cnt_outputs = self.cnt_head(cnt_inputs)
      else:
          cnt_outputs = None
      if self.use_seq:
          if self.training:
              seq_outputs = self.seq_head(
                  seq_inputs, targets[0], self.batch_max_legnth
              )
          else:
              seq_outputs = self.seq_head(
                  seq_inputs, None, self.batch_max_legnth
              )
          return cnt_outputs, seq_outputs
      else:
          return cnt_outputs
  
file_path: PaddleOCR/ppocr/modeling/heads/rec_rfl_head.py
imports: import paddle
  import paddle.nn
  from paddle.nn.initializer import TruncatedNormal, Constant, Normal, KaimingNormal
  from .rec_att_head import AttentionLSTM
label_desc: Use image node_id 3 for calling the RFLHead obj's underlying member method code with example usage: obj.forward(x, targets) and returns: cnt_outputs,  seq_outputs, cnt_outputs