text: from keras.layers import LSTM, Dense, Dropout, Input, Bidirectional, Flatten
  from keras.models import Model
  from keras.optimizers import Adam
  from keras.regularizers import l2
  
  
  def FasNet(input_num):
      """ for binary classification
      """
      input_video = Input(batch_shape=(None, input_num, 2048))
      encoded_video = Bidirectional(LSTM(128, return_sequences=True))(input_video)
      dense_video = Dense(256, activation='relu', kernel_regularizer=l2(0.01))(Flatten()(encoded_video))
      dense_video = Dropout(0.5)(dense_video)
      real = Dense(1, activation='sigmoid', name='real')(dense_video)
  
      model = Model(inputs=[input_video], outputs=[real])
  
      model.compile(
          loss=['binary_crossentropy'],
          optimizer=Adam(lr=0.0001, decay=1e-6),
          metrics=['accuracy']
      )
      return model
  