code: def __init__(self, args: dict):
      BaseDiscriminator.__init__(self)
  
      self.discriminator_input_dim = args.latent_dim
  
      layers = nn.ModuleList()
  
      layers.append(
          nn.Sequential(
              nn.Linear(np.prod(self.discriminator_input_dim), 512),
              nn.ReLU(),
              nn.Linear(512, 512),
              nn.ReLU(),
              nn.Linear(512, 512),
              nn.ReLU(),
              nn.Linear(512, 512),
              nn.ReLU(),
          )
      )
  
      layers.append(nn.Sequential(nn.Linear(512, 1), nn.Sigmoid()))
  
      self.layers = layers
      self.depth = len(layers)
  
imports: import logging
  import os
  from typing import List
  import numpy
  import torch
  import torch.nn
  from pythae.data.preprocessors import DataProcessor
  from pythae.models import Adversarial_AE, Adversarial_AE_Config
  from pythae.models.base.base_utils import ModelOutput
  from pythae.models.nn import BaseDecoder, BaseDiscriminator, BaseEncoder
  from pythae.trainers import AdversarialTrainer, AdversarialTrainerConfig
label_desc: Use image node_id 1 to create a new Discriminator object from inherited base classes: BaseDiscriminator with example: obj = Discriminator(args)