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use sigma_max/min in model if sigma_max/min is 0

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Kohaku-Blueleaf 2023-05-23 00:29:38 +08:00
parent 65a87ccc9b
commit 403b304162
2 changed files with 5 additions and 4 deletions
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5
modules/sd_samplers_kdiffusion.py
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@ -318,10 +318,11 @@ class KDiffusionSampler:
if p.sampler_noise_scheduler_override:
sigmas = p.sampler_noise_scheduler_override(steps)
elif p.enable_custom_k_sched:
sigma_min, sigma_max = (0.1, 10) if opts.use_old_karras_scheduler_sigmas else (self.model_wrap.sigmas[0].item(), self.model_wrap.sigmas[-1].item())
sigmas_func = k_diffusion_scheduler[p.k_sched_type]
sigmas_kwargs = {
'sigma_min': p.sigma_min,
'sigma_max': p.sigma_max
'sigma_min': p.sigma_min or sigma_min,
'sigma_max': p.sigma_max or sigma_max
}
if p.k_sched_type != 'exponential':
sigmas_kwargs['rho'] = p.rho

4
modules/ui.py
View File

@ -516,7 +516,7 @@ def create_ui():
with FormRow(elem_id="txt2img_kdiffusion_scheduler_row1", variant="compact"):
t2i_k_sched_type = gr.Dropdown(label="Type", elem_id="t2i_k_sched_type", choices=['karras', 'exponential', 'polyexponential'], value='karras')
t2i_k_sched_sigma_min = gr.Slider(minimum=0.0, maximum=0.5, step=0.05, label='sigma min', value=0.1, elem_id="txt2img_sigma_min")
t2i_k_sched_sigma_max = gr.Slider(minimum=5.0, maximum=50.0, step=0.1, label='sigma max', value=10.0, elem_id="txt2img_sigma_max")
t2i_k_sched_sigma_max = gr.Slider(minimum=0.0, maximum=50.0, step=0.1, label='sigma max', value=10.0, elem_id="txt2img_sigma_max")
t2i_k_sched_rho = gr.Slider(minimum=0.5, maximum=10.0, step=0.1, label='rho', value=7.0, elem_id="txt2img_rho")
elif category == "batch":
@ -879,7 +879,7 @@ def create_ui():
with FormRow(elem_id="img2img_kdiffusion_scheduler_row1", variant="compact"):
i2i_k_sched_type = gr.Dropdown(label="Type", elem_id="t2i_k_sched_type", choices=['karras', 'exponential', 'polyexponential'], value='karras')
i2i_k_sched_sigma_min = gr.Slider(minimum=0.0, maximum=0.5, step=0.05, label='sigma min', value=0.1, elem_id="txt2img_sigma_min")
i2i_k_sched_sigma_max = gr.Slider(minimum=5.0, maximum=50.0, step=0.1, label='sigma max', value=10.0, elem_id="txt2img_sigma_max")
i2i_k_sched_sigma_max = gr.Slider(minimum=0.0, maximum=50.0, step=0.1, label='sigma max', value=10.0, elem_id="txt2img_sigma_max")
i2i_k_sched_rho = gr.Slider(minimum=0.5, maximum=10.0, step=0.1, label='rho', value=7.0, elem_id="txt2img_rho")
elif category == "batch":