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| author | AUTOMATIC1111 <16777216c@gmail.com> | 2022-09-28 05:31:40 +0000 |
|---|---|---|
| committer | GitHub <noreply@github.com> | 2022-09-28 05:31:40 +0000 |
| commit | d4e36db6de55320952e9270a2162065cf8177dd5 (patch) | |
| tree | 0cfbf71e6015b3052cc06fa7f8ce86abf12b21e4 | |
| parent | f2a4a2c3a672e22f088a7455d6039557370dd3f2 (diff) | |
| parent | 047ca73388dbfbd5986639678170715ff220bf5b (diff) | |
| download | stable-diffusion-webui-gfx803-d4e36db6de55320952e9270a2162065cf8177dd5.tar.gz stable-diffusion-webui-gfx803-d4e36db6de55320952e9270a2162065cf8177dd5.tar.bz2 stable-diffusion-webui-gfx803-d4e36db6de55320952e9270a2162065cf8177dd5.zip | |
Merge pull request #1199 from C43H66N12O12S2/k-eta
Add Eta parameter to K Ancestral samplers
| -rw-r--r-- | modules/processing.py | 4 | ||||
| -rw-r--r-- | modules/sd_samplers.py | 6 | ||||
| -rw-r--r-- | modules/shared.py | 2 |
3 files changed, 7 insertions, 5 deletions
diff --git a/modules/processing.py b/modules/processing.py index 8d043f4d..90e00bf8 100644 --- a/modules/processing.py +++ b/modules/processing.py @@ -79,7 +79,7 @@ class StableDiffusionProcessing: self.color_corrections = None
self.denoising_strength: float = 0
- self.ddim_eta = opts.ddim_eta
+ self.eta = opts.eta
self.ddim_discretize = opts.ddim_discretize
self.s_churn = opts.s_churn
self.s_tmin = opts.s_tmin
@@ -124,7 +124,7 @@ class Processed: self.extra_generation_params = p.extra_generation_params
self.index_of_first_image = index_of_first_image
- self.ddim_eta = p.ddim_eta
+ self.eta = p.eta
self.ddim_discretize = p.ddim_discretize
self.s_churn = p.s_churn
self.s_tmin = p.s_tmin
diff --git a/modules/sd_samplers.py b/modules/sd_samplers.py index 666ee1ee..17faeab1 100644 --- a/modules/sd_samplers.py +++ b/modules/sd_samplers.py @@ -39,8 +39,10 @@ samplers_for_img2img = [x for x in samplers if x.name != 'PLMS'] sampler_extra_params = {
'sample_euler':['s_churn','s_tmin','s_tmax','s_noise'],
+ 'sample_euler_ancestral':['eta'],
'sample_heun' :['s_churn','s_tmin','s_tmax','s_noise'],
'sample_dpm_2':['s_churn','s_tmin','s_tmax','s_noise'],
+ 'sample_dpm_2_ancestral':['eta'],
}
def setup_img2img_steps(p, steps=None):
@@ -154,9 +156,9 @@ class VanillaStableDiffusionSampler: # existing code fails with cetin step counts, like 9
try:
- samples_ddim, _ = self.sampler.sample(S=steps, conditioning=conditioning, batch_size=int(x.shape[0]), shape=x[0].shape, verbose=False, unconditional_guidance_scale=p.cfg_scale, unconditional_conditioning=unconditional_conditioning, x_T=x, eta=p.ddim_eta)
+ samples_ddim, _ = self.sampler.sample(S=steps, conditioning=conditioning, batch_size=int(x.shape[0]), shape=x[0].shape, verbose=False, unconditional_guidance_scale=p.cfg_scale, unconditional_conditioning=unconditional_conditioning, x_T=x, eta=p.eta)
except Exception:
- samples_ddim, _ = self.sampler.sample(S=steps+1, conditioning=conditioning, batch_size=int(x.shape[0]), shape=x[0].shape, verbose=False, unconditional_guidance_scale=p.cfg_scale, unconditional_conditioning=unconditional_conditioning, x_T=x, eta=p.ddim_eta)
+ samples_ddim, _ = self.sampler.sample(S=steps+1, conditioning=conditioning, batch_size=int(x.shape[0]), shape=x[0].shape, verbose=False, unconditional_guidance_scale=p.cfg_scale, unconditional_conditioning=unconditional_conditioning, x_T=x, eta=p.eta)
return samples_ddim
diff --git a/modules/shared.py b/modules/shared.py index 84302438..2502fe2d 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -221,7 +221,7 @@ options_templates.update(options_section(('ui', "User interface"), { }))
options_templates.update(options_section(('sampler-params', "Sampler parameters"), {
- "ddim_eta": OptionInfo(0.0, "DDIM eta", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}),
+ "eta": OptionInfo(0.0, "DDIM and K Ancestral eta", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}),
"ddim_discretize": OptionInfo('uniform', "img2img DDIM discretize", gr.Radio, {"choices": ['uniform','quad']}),
's_churn': OptionInfo(0.0, "sigma churn", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}),
's_tmin': OptionInfo(0.0, "sigma tmin", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}),
|