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@ -25,6 +25,7 @@ class AlignYourStepsScheduler:
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return {"required": |
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{"model_type": (["SD1", "SDXL", "SVD"], ), |
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"steps": ("INT", {"default": 10, "min": 10, "max": 10000}), |
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"denoise": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01}), |
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} |
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} |
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RETURN_TYPES = ("SIGMAS",) |
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@ -32,11 +33,18 @@ class AlignYourStepsScheduler:
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FUNCTION = "get_sigmas" |
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def get_sigmas(self, model_type, steps): |
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def get_sigmas(self, model_type, steps, denoise): |
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total_steps = steps |
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if denoise < 1.0: |
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if denoise <= 0.0: |
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return (torch.FloatTensor([]),) |
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total_steps = round(steps * denoise) |
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sigmas = NOISE_LEVELS[model_type][:] |
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if (steps + 1) != len(sigmas): |
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sigmas = loglinear_interp(sigmas, steps + 1) |
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sigmas = sigmas[-(total_steps + 1):] |
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sigmas[-1] = 0 |
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return (torch.FloatTensor(sigmas), ) |
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