code: def forward(self, inputs, targets=None):
      cnn_features, images_mask, labels = inputs
  
      counting_mask = images_mask[:, :, :: self.ratio, :: self.ratio]
      counting_preds1, _ = self.counting_decoder1(
          cnn_features, counting_mask
      )
      counting_preds2, _ = self.counting_decoder2(
          cnn_features, counting_mask
      )
      counting_preds = (counting_preds1 + counting_preds2) / 2
  
      word_probs = self.decoder(
          cnn_features, labels, counting_preds, images_mask
      )
      return (
          word_probs,
          counting_preds,
          counting_preds1,
          counting_preds2,
      )
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import paddle.nn
  import paddle
  import math
label_desc: Use image node_id 2 for calling the CANHead obj's underlying member method code with example usage: obj.forward(inputs, targets) and returns: word_probs,  counting_preds,  counting_preds1,  counting_preds2