13 lines
367 B
Python
13 lines
367 B
Python
import torch
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def sgm_uniform(n, sigma_min, sigma_max, inner_model, device):
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start = inner_model.sigma_to_t(torch.tensor(sigma_max))
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end = inner_model.sigma_to_t(torch.tensor(sigma_min))
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sigs = [
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inner_model.t_to_sigma(ts)
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for ts in torch.linspace(start, end, n)[:-1]
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]
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sigs += [0.0]
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return torch.FloatTensor(sigs).to(device)
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