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Add s_tmax
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@ -148,7 +148,7 @@ class StableDiffusionProcessing:
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self.s_min_uncond = s_min_uncond or opts.s_min_uncond
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self.s_churn = s_churn or opts.s_churn
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self.s_tmin = s_tmin or opts.s_tmin
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self.s_tmax = s_tmax or float('inf') # not representable as a standard ui option
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self.s_tmax = opts.data.get('s_tmax', 0) or float('inf') # not representable as a standard ui option
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self.s_noise = s_noise or opts.s_noise
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self.override_settings = {k: v for k, v in (override_settings or {}).items() if k not in shared.restricted_opts}
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self.override_settings_restore_afterwards = override_settings_restore_afterwards
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@ -608,6 +608,7 @@ options_templates.update(options_section(('sampler-params', "Sampler parameters"
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"ddim_discretize": OptionInfo('uniform', "img2img DDIM discretize", gr.Radio, {"choices": ['uniform', 'quad']}),
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's_churn': OptionInfo(0.0, "sigma churn", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}),
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's_tmin': OptionInfo(0.0, "sigma tmin", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}),
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's_tmax': OptionInfo(0.0, "sigma tmax", gr.Slider, {"minimum": 0.0, "maximum": 999.0, "step": 0.01}).info("0 = inf"),
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's_noise': OptionInfo(1.0, "sigma noise", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}),
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'k_sched_type': OptionInfo("Automatic", "scheduler type", gr.Dropdown, {"choices": ["Automatic", "karras", "exponential", "polyexponential"]}).info("lets you override the noise schedule for k-diffusion samplers; choosing Automatic disables the three parameters below"),
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'sigma_min': OptionInfo(0.0, "sigma min", gr.Number).info("0 = default (~0.03); minimum noise strength for k-diffusion noise scheduler"),
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