SELU in Keras and Numpy

keras_selu.py

import keras
from keras import backend as K

def kr_selu(x, alpha=1.6732632423543772848170429916717, scale=1.0507009873554804934193349852946):
	""" Scaled Exponential Linear Units
		Magic values target activations of 0 mean and 1 variance.
		See https://arxiv.org/abs/1706.02515
	"""
	return scale * K.elu(x, alpha)

# Make the activation available as "selu"
keras.activations.selu = kr_selu

numpy_selu.py

alpha = 1.6732632423543772848170429916717
scale = 1.0507009873554804934193349852946

def selu(x, alpha=1.6732632423543772848170429916717, scale=1.0507009873554804934193349852946):
	return scale * np.where(x>=0.0, x, alpha*np.exp(x)-alpha)