class_docstr: MLP as used in Vision Transformer, MLP-Mixer and related networks
class_docstr_tok: ["MLP","as","used","in","Vision","Transformer",",","MLP-Mixer","and","related","networks"]
code: def __init__(self, in_features, mlp_ratio=4.0, drop=0.0, name=None):
      super(MLP, self).__init__(name=name)
      self.fc1 = layers.Dense(
          int(in_features * mlp_ratio),
          name="Dense_0",
          kernel_initializer=self.k_ini,
          bias_initializer=self.b_ini,
      )
      self.act = layers.Activation("gelu")
      self.fc2 = layers.Dense(
          in_features,
          name="Dense_1",
          kernel_initializer=self.k_ini,
          bias_initializer=self.b_ini,
      )
      self.drop = layers.Dropout(drop)
  
imports: import tensorflow
  from tensorflow.keras import Model, layers, initializers
  import numpy
label_desc: Use image node_id 1 to create a new MLP object from inherited base classes: layers with example: obj = MLP(in_features, mlp_ratio, drop, name)