code: def __init__(
      self,
      depth,
      norm_layer=nn.BatchNorm2d,
      batchnorm_from=2,
      attend_from=3,
      image_fusion=False,
      ch=64,
      max_channels=512,
      backbone_from=-1,
      backbone_channels=None,
      backbone_mode="",
  ):
      super(ISEUNetV1, self).__init__()
      self.depth = depth
      self.encoder = UNetEncoder(
          depth,
          ch,
          norm_layer,
          batchnorm_from,
          max_channels,
          backbone_from,
          backbone_channels,
          backbone_mode,
      )
      self.decoder = UNetDecoder(
          depth,
          self.encoder.block_channels,
          norm_layer,
          attention_layer=MaskedChannelAttention,
          attend_from=attend_from,
          image_fusion=image_fusion,
      )
  
file_path: carefree-learn/cflearn/api/cv/third_party/iharm/model/base/iseunet_v1.py
imports: import torch
  import torch.nn
  from ..ops import MaskedChannelAttention
  from ..modeling.unet import UNetDecoder
  from ..modeling.unet import UNetEncoder
label_desc: Use image node_id 1 to create a new ISEUNetV1 object from inherited base classes: nn with example: obj = ISEUNetV1(depth, norm_layer, batchnorm_from, attend_from, image_fusion, ch, max_channels, backbone_from, backbone_channels, backbone_mode)