code: def __init__(self, hidden_size, mlp_dim, dropout_rate):
      super(Mlp, self).__init__()
      self.fc1 = nn.Linear(hidden_size, mlp_dim)
      self.fc2 = nn.Linear(mlp_dim, hidden_size)
      self.act_fn = ACT2FN["gelu"]
      self.dropout = nn.Dropout(dropout_rate)
  
      self._init_weights()
  
imports: import copy
  import math
  import numpy
  import paddle
  import paddle.nn
  import paddle.nn.functional
  from medicalseg.cvlibs import manager
  from medicalseg.utils import load_pretrained_model
label_desc: Use image node_id 1 to create a new Mlp object from inherited base classes: nn with example: obj = Mlp(hidden_size, mlp_dim, dropout_rate)