in vae.py [0:0]
def sample_uncond(self, x, t=None, lvs=None):
n, c, h, w = x.shape
feats = self.prior(x)
pm, pv, xpp = feats[:, :self.zdim, ...], feats[:, self.zdim:self.zdim * 2, ...], feats[:, self.zdim * 2:, ...]
x = x + xpp
if lvs is not None:
z = lvs
else:
if t is not None:
pv = pv + torch.ones_like(pv) * np.log(t)
z = draw_gaussian_diag_samples(pm, pv)
return z, x