code: def __init__(
      self, input_channels, output_channels=(64, 128, 256, 512)
  ):
      super().__init__()
      self.deconv6 = nn.Conv2D(
          input_channels, input_channels, kernel_size=1, bias_attr=False
      )
      self.deconv5 = Up(input_channels, output_channels[-1])
      self.deconv4 = Up(output_channels[-1], output_channels[-2])
      self.deconv3 = Up(output_channels[-2], output_channels[-3])
      self.deconv2 = Up(output_channels[-3], output_channels[-4])
      self.deconv1 = Up(output_channels[-4], 64)
  
      self.alpha_conv = nn.Conv2D(
          64, 1, kernel_size=5, padding=2, bias_attr=False
      )
  
imports: from collections import defaultdict
  import paddle
  import paddle.nn
  import paddle.nn.functional
  from paddleseg.models import layers
  from paddleseg import utils
  from paddleseg.cvlibs import manager
  from ppmatting.models.losses import MRSD
label_desc: Use image node_id 1 to create a new Decoder object from inherited base classes: nn with example: obj = Decoder(input_channels, output_channels)