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fix alphas cumprod (#475)

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Chengsong Zhang
2024-03-03 20:09:04 -06:00
committed by GitHub
parent ef35383b4a
commit 72139b000c
2 changed files with 9 additions and 1 deletions
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8
ldm_patched/modules/model_sampling.py
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@@ -76,7 +76,13 @@ class ModelSamplingDiscrete(torch.nn.Module):
def timestep(self, sigma):
log_sigma = sigma.log()
dists = log_sigma.to(self.log_sigmas.device) - self.log_sigmas[:, None]
return dists.abs().argmin(dim=0).view(sigma.shape).to(sigma.device)
low_idx = dists.ge(0).cumsum(dim=0).argmax(dim=0).clamp(max=self.log_sigmas.shape[0] - 2)
high_idx = low_idx + 1
low, high = self.log_sigmas[low_idx], self.log_sigmas[high_idx]
w = (low - log_sigma) / (low - high)
w = w.clamp(0, 1)
t = (1 - w) * low_idx + w * high_idx
return t.view(sigma.shape)
def sigma(self, timestep):
t = torch.clamp(timestep.float().to(self.log_sigmas.device), min=0, max=(len(self.sigmas) - 1))