code: def __init__(self, input_channels, filters):
      super().__init__()
      self.double_conv = nn.Sequential(
          layers.ConvBNReLU(input_channels, 64, 3),
          layers.ConvBNReLU(64, 64, 3),
      )
      down_channels = filters
      self.down_sample_list = nn.LayerList(
          [
              self.down_sampling(channel, channel * 2)
              for channel in down_channels
          ]
      )
  
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 Encoder object from inherited base classes: nn with example: obj = Encoder(input_channels, filters)