def grad(self, inputs, grads):
(k, x) = inputs
(gz, ) = grads
return [
gz * gammaincc_der(k, x),
gz * -exp(-x + (k - 1) * log(x) - gammaln(k)),
]
def grad(self, inp, grads):
a, b, x = inp
(gz, ) = grads
return [
gz * betainc_der(a, b, x, True),
gz * betainc_der(a, b, x, False),
gz * exp(
log1p(-x) * (b - 1) + log(x) * (a - 1) -
(gammaln(a) + gammaln(b) - gammaln(a + b))),
]