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Fix duplicate sigmas on beta scheduler.
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@ -358,8 +358,11 @@ def beta_scheduler(model_sampling, steps, alpha=0.6, beta=0.6):
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ts = numpy.rint(scipy.stats.beta.ppf(ts, alpha, beta) * total_timesteps)
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sigs = []
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last_t = -1
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for t in ts:
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sigs += [float(model_sampling.sigmas[int(t)])]
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if t != last_t:
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sigs += [float(model_sampling.sigmas[int(t)])]
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last_t = t
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sigs += [0.0]
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return torch.FloatTensor(sigs)
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