def __call__(self, x):
x = self.core(x)
if self.batch_norm is not None:
x = self.batch_norm(x)
return pf.Cauchy(self.mean(x), tf.exp(self.std(x)))
def __call__(self, x):
p = x @ self.w() + self.b()
means = p[:, 0]
stds = tf.exp(p[:, 1])
return pf.Cauchy(means, stds)
def __call__(self):
return pf.Cauchy(self.mu(), self.sig())