class_docstr: Please Refer to U2Net above.
code: def __init__(self, num_classes, in_channels=3, pretrained=None):
      super(U2Netp, self).__init__()
  
      self.stage1 = RSU7(in_channels, 16, 64)
      self.pool12 = nn.MaxPool2D(2, stride=2, ceil_mode=True)
  
      self.stage2 = RSU6(64, 16, 64)
      self.pool23 = nn.MaxPool2D(2, stride=2, ceil_mode=True)
  
      self.stage3 = RSU5(64, 16, 64)
      self.pool34 = nn.MaxPool2D(2, stride=2, ceil_mode=True)
  
      self.stage4 = RSU4(64, 16, 64)
      self.pool45 = nn.MaxPool2D(2, stride=2, ceil_mode=True)
  
      self.stage5 = RSU4F(64, 16, 64)
      self.pool56 = nn.MaxPool2D(2, stride=2, ceil_mode=True)
  
      self.stage6 = RSU4F(64, 16, 64)
  
      # decoder
      self.stage5d = RSU4F(128, 16, 64)
      self.stage4d = RSU4(128, 16, 64)
      self.stage3d = RSU5(128, 16, 64)
      self.stage2d = RSU6(128, 16, 64)
      self.stage1d = RSU7(128, 16, 64)
  
      self.side1 = nn.Conv2D(64, num_classes, 3, padding=1)
      self.side2 = nn.Conv2D(64, num_classes, 3, padding=1)
      self.side3 = nn.Conv2D(64, num_classes, 3, padding=1)
      self.side4 = nn.Conv2D(64, num_classes, 3, padding=1)
      self.side5 = nn.Conv2D(64, num_classes, 3, padding=1)
      self.side6 = nn.Conv2D(64, num_classes, 3, padding=1)
  
      self.outconv = nn.Conv2D(6 * num_classes, num_classes, 1)
  
      self.pretrained = pretrained
      self.init_weight()
  
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 1 to create a new U2Netp object from inherited base classes: nn with example: obj = U2Netp(num_classes, in_channels, pretrained)