machine learning - How do you use Keras LeakyReLU in Python?

Question

I am trying to produce a CNN using Keras, and wrote the following code:

batch_size = 64
epochs = 20
num_classes = 5

cnn_model = Sequential()
cnn_model.add(Conv2D(32, kernel_size=(3, 3), activation='linear',
                     input_shape=(380, 380, 1), padding='same'))
cnn_model.add(Activation('relu'))
cnn_model.add(MaxPooling2D((2, 2), padding='same'))
cnn_model.add(Conv2D(64, (3, 3), activation='linear', padding='same'))
cnn_model.add(Activation('relu'))
cnn_model.add(MaxPooling2D(pool_size=(2, 2), padding='same'))
cnn_model.add(Conv2D(128, (3, 3), activation='linear', padding='same'))
cnn_model.add(Activation('relu'))
cnn_model.add(MaxPooling2D(pool_size=(2, 2), padding='same'))
cnn_model.add(Flatten())
cnn_model.add(Dense(128, activation='linear'))
cnn_model.add(Activation('relu'))
cnn_model.add(Dense(num_classes, activation='softmax'))

cnn_model.compile(loss=keras.losses.categorical_crossentropy,
                  optimizer=keras.optimizers.Adam(), metrics=['accuracy'])

I want to use Keras's LeakyReLU activation layer instead of using Activation('relu'). However, I tried using LeakyReLU(alpha=0.1) in place, but this is an activation layer in Keras, and I get an error about using an activation layer and not an activation function.

How can I use LeakyReLU in this example?

Answer 1

All advanced activations in Keras, including LeakyReLU, are available as layers, and not as activations; therefore, you should use it as such:

from keras.layers import LeakyReLU

# instead of cnn_model.add(Activation('relu'))
# use
cnn_model.add(LeakyReLU(alpha=0.1))