class_docstr: CANLoss is consist of two part:
      word_average_loss: average accuracy of the symbol
      counting_loss: counting loss of every symbol
code: def __init__(self):
      super(CANLoss, self).__init__()
  
      self.use_label_mask = False
      self.out_channel = 111
      self.cross = (
          nn.CrossEntropyLoss(reduction="none")
          if self.use_label_mask
          else nn.CrossEntropyLoss()
      )
      self.counting_loss = nn.SmoothL1Loss(reduction="mean")
      self.ratio = 16
  
file_path: PaddleOCR/ppocr/losses/rec_can_loss.py
imports: import paddle
  import paddle.nn
  import numpy
label_desc: Use image node_id 1 to create a new CANLoss object from inherited base classes: nn with example: obj = CANLoss()