code: def __init__(self, in_channels):
      super(BoundaryRefine, self).__init__()
      self.layer = nn.Sequential(
          nn.Conv2d(in_channels, in_channels, kernel_size=3, padding=1),
          nn.BatchNorm2d(in_channels),
          nn.ReLU(inplace=True),
          nn.Conv2d(in_channels, in_channels, kernel_size=3, padding=1),
          nn.BatchNorm2d(in_channels),
      )
  
file_path: pywick/pywick/models/segmentation/resnet_gcn.py
imports: import torch.nn
  import torch.nn.init
  import torch.nn.functional
  import torchvision.models
  import numpy
label_desc: Use image node_id 1 to create a new BoundaryRefine object from inherited base classes: nn with example: obj = BoundaryRefine(in_channels)