code: def __init__(self, ch_in, ch_out):
      super().__init__()
      self.up = nn.Sequential(
          nn.Upsample(scale_factor=2, mode="bilinear"),
          nn.Conv2D(ch_in, ch_out, kernel_size=3, stride=1, padding=1),
          nn.BatchNorm2D(ch_out),
          nn.ReLU(),
      )
  
imports: import paddle
  import paddle.nn
  from paddleseg.cvlibs import manager
  from paddleseg.models import layers
  from paddleseg import utils
  import numpy
label_desc: Use image node_id 1 to create a new UpConv object from inherited base classes: nn with example: obj = UpConv(ch_in, ch_out)