code: def __init__(
      self,
      in_features,
      hidden_features=None,
      out_features=None,
      act_layer=nn.ReLU,
      drop=0.0,
  ):
      super().__init__()
  
      out_features = out_features or in_features
      hidden_features = hidden_features or in_features
      self.fc1 = layers.ConvBN(
          in_features, hidden_features, 1, bias_attr=False
      )
      self.dwconv = nn.Conv2D(
          hidden_features,
          hidden_features,
          3,
          1,
          1,
          bias_attr=True,
          groups=hidden_features,
      )
      self.act = act_layer()
      self.fc2 = layers.ConvBN(
          hidden_features, out_features, 1, bias_attr=False
      )
      self.drop = nn.Dropout(drop)
  
imports: import paddle
  import paddle.nn
  import paddle.nn.functional
  from paddleseg.cvlibs import manager, param_init
  from paddleseg.models import layers
  from paddleseg.models.backbones.transformer_utils import DropPath, zeros_, ones_
  from paddleseg.utils import utils
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)