Match Comfy H3 timestep precision
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@ -79,7 +79,7 @@ class H3PromptPacker:
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video_sigma = torch.tensor(float(sigma), device=hidden.device).clamp(min=1e-6)
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video_sigma = torch.tensor(float(sigma), device=hidden.device).clamp(min=1e-6)
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base = video_sigma / (12.0 + video_sigma * (1.0 - 12.0))
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base = video_sigma / (12.0 + video_sigma * (1.0 - 12.0))
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audio_sigma = 3.0 * base / (1.0 + (3.0 - 1.0) * base)
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audio_sigma = 3.0 * base / (1.0 + (3.0 - 1.0) * base)
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video_time, audio_time = 1 - float(video_sigma), 1 - float(audio_sigma)
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video_time, audio_time = (1.0 - video_sigma).item(), (1.0 - audio_sigma).item()
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unique_times = sorted({video_time, audio_time})
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unique_times = sorted({video_time, audio_time})
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row = {value: index for index, value in enumerate(unique_times)}
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row = {value: index for index, value in enumerate(unique_times)}
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video_row, audio_row = row[video_time] * 3, row[audio_time] * 3
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video_row, audio_row = row[video_time] * 3, row[audio_time] * 3
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