Sometimes the default standard activations like ReLU, tanh, softmax, ... and the advanced activations like LeakyReLU aren't enough. And it might also not be in keras-contrib.

How do you create your own activation function?

Credits to this Github issue comment by Ritchie Ng.

# Creating a model
from keras.models import Sequential
from keras.layers import Dense

# Custom activation function
from keras.layers import Activation
from keras import backend as K
from keras.utils.generic_utils import get_custom_objects


def custom_activation(x):
    return (K.sigmoid(x) * 5) - 1

get_custom_objects().update({'custom_activation': Activation(custom_activation)})

# Usage
model = Sequential()
model.add(Dense(32, input_dim=784))
model.add(Activation(custom_activation, name='SpecialActivation'))
print(model.summary())

Please keep in mind that you have to import this function when you save and restore the model. See the note of keras-contrib.