class_docstr: DUsampling module
code: def __init__(
      self, in_channels, out_channels, scale_factor=2, **kwargs
  ):
      super(DUpsampling, self).__init__()
      self.scale_factor = scale_factor
      self.conv_w = nn.Conv2d(
          in_channels,
          out_channels * scale_factor * scale_factor,
          1,
          bias=False,
      )
  
imports: import torch
  import torch.nn
  import torch.nn.functional
  from pywick.models.segmentation.da_basenets.segbase import SegBaseModel
  from pywick.models.segmentation.da_basenets.fcn import _FCNHead
label_desc: Use image node_id 1 to create a new DUpsampling object from inherited base classes: nn with example: obj = DUpsampling(in_channels, out_channels, scale_factor)