code: def __init__(self, in_channels, filters, is_batchnorm):
      super(Encoder, self).__init__()
      self.conv1 = UnetConv2D(in_channels, filters[0], is_batchnorm)
      self.poolconv2 = MaxPoolConv2D(
          filters[0], filters[1], is_batchnorm
      )
      self.poolconv3 = MaxPoolConv2D(
          filters[1], filters[2], is_batchnorm
      )
      self.poolconv4 = MaxPoolConv2D(
          filters[2], filters[3], is_batchnorm
      )
      self.poolconv5 = MaxPoolConv2D(
          filters[3], filters[4], is_batchnorm
      )
  
imports: import paddle
  import paddle.nn
  import paddle.nn.functional
  from paddleseg.cvlibs import manager
  from paddleseg.models.layers.layer_libs import SyncBatchNorm
  from paddleseg.cvlibs.param_init import kaiming_normal_init
label_desc: Use image node_id 1 to create a new Encoder object from inherited base classes: nn with example: obj = Encoder(in_channels, filters, is_batchnorm)