def softmax(real, inft, t=1):
raw = td.exp(*td.divide(real, inft, t, 0.0))
cs = td.sum(*raw, -1)
return td.divide(*raw, *cs)
def elu(real, inft):
low = td.subtract(*td.exp(real, inft), 1.0, 0.0)
return td.where(tf.greater(real, 0.0), real, inft, *low)
def logistic(real, inft):
return td.divide(1.0, 0.0, *td.add(1.0, 0.0, *td.exp(-real, -inft)))
def softplus(real, inft):
return td.log(*td.add(*td.exp(real, inft), 1.0, 0.0))
