code: def __init__(
      self,
      num_filters=12,
      input_channels=3,
      n_layers=2,
      norm_layer="instance_norm",
      use_bias=True,
  ):
      super().__init__()
  
      self.num_filters = num_filters
  
      self.input_channels = input_channels
      self.use_bias = use_bias
  
      if norm_layer == "batch_norm":
          self.norm_layer = nn.BatchNorm2d
      else:
          self.norm_layer = nn.InstanceNorm2d
      self.net = self.make_net(
          n_layers, self.input_channels, 1, 4, 2, self.use_bias
      )
  
imports: import torch
  import torch.nn
  from torch.autograd import Variable
  from torch.nn import functional
  import torchvision
  from torchvision import models
  import pytorch_lightning
label_desc: Use image node_id 1 to create a new Discriminator object from inherited base classes: nn with example: obj = Discriminator(num_filters, input_channels, n_layers, norm_layer, use_bias)