i am not getting the error for the regularizer? :     model = Sequential()
    model.add(Conv2D(32, kernel_size=(3, 3),  kernel_regularizer=regularizers.l2(w_l2),
                     input_shape=input_shape))
    model.add(BatchNormalization())
    model.add(Activation('sigmoid'))
    model.add(Conv2D(64, (3, 3),  kernel_regularizer=regularizers.l2(w_l2)))
    model.add(BatchNormalization())
    model.add(Activation('sigmoid'))
    model.add(MaxPooling2D(pool_size=(2, 2)))
    model.add(Dropout(0.25))
    model.add(Flatten())
    model.add(Dense(128, kernel_regularizer=regularizers.l2(w_l2)))
    model.add(BatchNormalization())
    model.add(Activation('sigmoid'))
    model.add(Dropout(0.5))
    model.add(Dense(num_classes, activation='softmax'))
    
    model.compile(loss=keras.losses.categorical_crossentropy,
                  optimizer=keras.optimizers.Adam(),
                  metrics=['accuracy'])
    model.summary()


[enter image description here][1]


[enter image description here][2]
 the code needed more challenges for the architecture and also I am also working on my own architecture so I asked this as the semantics are changing every day is the presentsymantics ok.

  [1]: https://i.stack.imgur.com/u8yf0.png
  [2]: https://i.stack.imgur.com/FS3oF.png