code: def __init__(self, input_dim, hidden_dim, output_dim, num_layers):
      super().__init__()
      self.num_layers = num_layers
      h = [hidden_dim] * (num_layers - 1)
      self.layers = nn.LayerList(
          nn.Linear(n, k)
          for n, k in zip([input_dim] + h, h + [output_dim])
      )
      self.init_weight()
  
imports: import math
  import copy
  import paddle
  import paddle.nn
  import paddle.nn.functional
  from paddleseg.models import layers
  from paddleseg.cvlibs import manager, param_init
  from paddleseg.utils import utils
  from paddleseg.core.train import check_logits_losses
label_desc: Use image node_id 1 to create a new MLP object from inherited base classes: nn with example: obj = MLP(input_dim, hidden_dim, output_dim, num_layers)