code: def __init__(
      self,
      in_features,
      hidden_features=None,
      out_features=None,
      act_layer=nn.GELU,
      drop=0.0,
  ):
      super().__init__()
      out_features = out_features or in_features
      hidden_features = hidden_features or in_features
      self.fc1 = nn.Linear(in_features, hidden_features)
      self.act = act_layer()
      self.fc2 = nn.Linear(hidden_features, out_features)
      self.drop = nn.Dropout(drop)
  
imports: import numpy
  import paddle
  import paddle.nn
  import paddle.nn.functional
  from paddle.nn import Layer
  from paddle.nn import Linear
  from paddle.nn.initializer import Constant
  from paddle.nn.initializer import Normal
  from paddle.nn.initializer import TruncatedNormal
label_desc: Use image node_id 1 to create a new Mlp object from inherited base classes: nn with example: obj = Mlp(in_features, hidden_features, out_features, act_layer, drop)