def true_nll_gaussian(params, mu, sigma):
params = convert_to_container(params, container=tuple)
mu = convert_to_container(mu, container=tuple)
sigma = convert_to_container(sigma, container=tuple)
constraint = ztf.constant(0.)
if not len(params) == len(mu) == len(sigma):
raise ValueError("params, mu and sigma have to have the same length.")
for param, mean, sig in zip(params, mu, sigma):
constraint += ztf.reduce_sum(
ztf.square(param - mean) / (2. * ztf.square(sig)))
return constraint
def indefinite_integral(limits):
max_degree = model.degree + 1
polys = do_recurrence(x=limits,
polys=chebyshev_polys,
degree=max_degree,
recurrence=chebyshev_recurrence)
one_limit_integrals = []
for degree in range(2, max_degree):
coeff = model.params[f"c_{degree}"]
n_float = ztf.convert_to_tensor(degree)
integral = (n_float * polys[degree + 1] /
(ztf.square(n_float) - 1) -
limits * polys[degree] / (n_float - 1))
one_limit_integrals.append(coeff * integral)
return ztf.reduce_sum(one_limit_integrals, axis=0)
def _func(self, x):
mu = self.params['mu']
sigma = self.params['sigma']
x = ztf.unstack_x(x)
return ztf.exp(-ztf.square((x - mu) / sigma))
def _unnormalized_pdf(self, x):
mu = self.params['mu']
sigma = self.params['sigma']
x = ztf.unstack_x(x)
return ztf.exp(-ztf.square((x - mu) / sigma))
