code: def __init__(self, data_size, hidden_size, mlp_size, num_layers):
      super().__init__()
      self._data_size = data_size
      self._hidden_size = hidden_size
  
      # tanh is important for model performance
      self._module = MLP(
          1 + hidden_size,
          hidden_size * (1 + data_size),
          mlp_size,
          num_layers,
          tanh=True,
      )
  
imports: import fire
  import matplotlib.pyplot
  import torch
  import torch.optim.swa_utils
  import torchcde
  import torchsde
  import tqdm
label_desc: Use image node_id 1 to create a new DiscriminatorFunc object from inherited base classes: torch.nn with example: obj = DiscriminatorFunc(data_size, hidden_size, mlp_size, num_layers)