DeepLabV3Decoder(
  (aspp): ASPPv3Plus(
    (conv1): ConvBNReLU(
      (conv): Conv2d(2048, 256, kernel_size=(1, 1), stride=(1, 1))
      (bn): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
    )
    (conv2): ConvBNReLU(
      (conv): Conv2d(2048, 256, kernel_size=(3, 3), stride=(1, 1), padding=(6, 6), dilation=(6, 6))
      (bn): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
    )
    (conv3): ConvBNReLU(
      (conv): Conv2d(2048, 256, kernel_size=(3, 3), stride=(1, 1), padding=(12, 12), dilation=(12, 12))
      (bn): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
    )
    (conv4): ConvBNReLU(
      (conv): Conv2d(2048, 256, kernel_size=(3, 3), stride=(1, 1), padding=(18, 18), dilation=(18, 18))
      (bn): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
    )
    (conv_out): ConvBNReLU(
      (conv): Conv2d(1024, 256, kernel_size=(1, 1), stride=(1, 1), padding=(1, 1))
      (bn): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
    )
  )
  (decoder): Decoder(
    (conv_low): ConvBNReLU(
      (conv): Conv2d(256, 48, kernel_size=(1, 1), stride=(1, 1))
      (bn): BatchNorm2d(48, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
    )
    (conv_cat): Sequential(
      (0): ConvBNReLU(
        (conv): Conv2d(304, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
        (bn): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
      )
      (1): ConvBNReLU(
        (conv): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
        (bn): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
      )
    )
    (conv_out): Conv2d(256, 11, kernel_size=(1, 1), stride=(1, 1), bias=False)
  )
)