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@ -92,6 +92,7 @@ class Scheduler:
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def _is_apply_noise(self, t) -> bool:
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"""Return True if scheduler in noise range."""
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apply_noise = False
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if self.noise_range_t is not None:
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if isinstance(self.noise_range_t, (list, tuple)):
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apply_noise = self.noise_range_t[0] <= t < self.noise_range_t[1]
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@ -104,7 +105,7 @@ class Scheduler:
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g.manual_seed(self.noise_seed + t)
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if self.noise_type == 'normal':
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while True:
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# resample if noise out of percent limit, brute force but shouldn't spin much
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# resample if noise out of percent limit, brute force but shouldn't spin much
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noise = torch.randn(1, generator=g).item()
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if abs(noise) < self.noise_pct:
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return noise
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