code: def __init__(
      self,
      input_shape,
      activation=torch.nn.LeakyReLU,
      dnn_blocks=2,
      dnn_neurons=512,
  ):
      super().__init__(input_shape=input_shape)
  
      for block_index in range(dnn_blocks):
          self.append(
              sb.nnet.linear.Linear,
              n_neurons=dnn_neurons,
              bias=True,
              layer_name="linear",
          )
          self.append(activation(), layer_name="act")
  
imports: import torch
  import speechbrain
label_desc: Use image node_id 1 to create a new VanillaNN object from inherited base classes: sb.nnet.containers with example: obj = VanillaNN(input_shape, activation, dnn_blocks, dnn_neurons)