def forward(self, z, mu, sig):
self.save_for_backward(z, mu, sig)
p = st.norm(mu.cpu().numpy(),sig.cpu().numpy())
return torch.DoubleTensor((self.gamma_under + self.gamma_over) * p.cdf(
z.cpu().numpy()) - self.gamma_under).cuda()
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