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 paddle
  import paddle.nn
  import paddle.nn.functional
  from paddleseg.cvlibs import param_init
  from paddlepanseg.models.param_init import c2_xavier_fill, THLinearInitMixin, th_linear_fill, th_multihead_fill
  from .common import Conv2D, PositionEmbeddingSine
label_desc: Use image node_id 1 to create a new MLP object from inherited base classes: nn, THLinearInitMixin with example: obj = MLP(input_dim, hidden_dim, output_dim, num_layers)