code: def __init__(self, input_shape):
      super(ContextNet, self).__init__()
  
      # Keep same dimensions
      padding = (5 - 1) // 2
      self.context_net = nn.Sequential(
          nn.Conv2d(input_shape[0], 64, 5, padding=padding),
          nn.BatchNorm2d(64),
          nn.ReLU(),
          nn.Conv2d(64, 64, 5, padding=padding),
          nn.BatchNorm2d(64),
          nn.ReLU(),
          nn.Conv2d(64, 1, 5, padding=padding),
      )
  
imports: import torch
  import torch.nn
  import torch.nn.functional
  import torchvision.models
label_desc: Use image node_id 1 to create a new ContextNet object from inherited base classes: nn with example: obj = ContextNet(input_shape)