class_docstr: The U^2-Net implementation based on PaddlePaddle.
  
  The original article refers to
  Xuebin Qin, et, al. "U^2-Net: Going Deeper with Nested U-Structure for Salient Object Detection"
  (https://arxiv.org/abs/2005.09007).
  
  Args:
      num_classes (int): The unique number of target classes.
      in_channels (int, optional): Input channels. Default: 3.
      pretrained (str, optional): The path or url of pretrained model for fine tuning. Default: None.
code: def init_weight(self):
      if self.pretrained is not None:
          utils.load_entire_model(self, self.pretrained)
  
imports: import paddle
  import paddle.nn
  import paddle.nn.functional
  from paddleseg.cvlibs import manager
  from paddleseg.models import layers
  from paddleseg.utils import utils
label_desc: Use image node_id 3 for calling the U2Net obj's underlying member method code with example usage: obj.init_weight() without return types