diff options
Diffstat (limited to 'modules')
| -rw-r--r-- | modules/processing.py | 34 |
1 files changed, 13 insertions, 21 deletions
diff --git a/modules/processing.py b/modules/processing.py index 21886bb5..6b49b4e3 100644 --- a/modules/processing.py +++ b/modules/processing.py @@ -517,24 +517,16 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed: p.all_negative_prompts = p.batch_size * p.n_iter * [shared.prompt_styles.apply_negative_styles_to_prompt(p.negative_prompt, p.styles)]
if type(p) == StableDiffusionProcessingTxt2Img:
- if p.enable_hr and p.is_hr_pass:
- logging.info("Running hr pass with custom prompt")
- if p.hr_prompt:
- if type(p.prompt) == list:
- p.all_hr_prompts = [shared.prompt_styles.apply_styles_to_prompt(x, p.styles) for x in p.hr_prompt]
- else:
- p.all_hr_prompts = p.batch_size * p.n_iter * [
- shared.prompt_styles.apply_styles_to_prompt(p.hr_prompt, p.styles)]
- logging.info(p.all_prompts)
-
- if p.hr_negative_prompt:
- if type(p.negative_prompt) == list:
- p.all_hr_negative_prompts = [shared.prompt_styles.apply_negative_styles_to_prompt(x, p.styles) for x in
- p.hr_negative_prompt]
- else:
- p.all_hr_negative_prompts = p.batch_size * p.n_iter * [
- shared.prompt_styles.apply_negative_styles_to_prompt(p.hr_negative_prompt, p.styles)]
- logging.info(p.all_negative_prompts)
+ if p.enable_hr:
+ if type(p.prompt) == list:
+ p.all_hr_prompts = [shared.prompt_styles.apply_styles_to_prompt(x, p.styles) for x in p.hr_prompt]
+ else:
+ p.all_hr_prompts = p.batch_size * p.n_iter * [shared.prompt_styles.apply_styles_to_prompt(p.hr_prompt, p.styles)]
+
+ if type(p.negative_prompt) == list:
+ p.all_hr_negative_prompts = [shared.prompt_styles.apply_negative_styles_to_prompt(x, p.styles) for x in p.hr_negative_prompt]
+ else:
+ p.all_hr_negative_prompts = p.batch_size * p.n_iter * [shared.prompt_styles.apply_negative_styles_to_prompt(p.hr_negative_prompt, p.styles)]
if type(seed) == list:
p.all_seeds = seed
@@ -628,9 +620,9 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed: c = get_conds_with_caching(prompt_parser.get_multicond_learned_conditioning, prompts, p.steps, cached_c)
if type(p) == StableDiffusionProcessingTxt2Img:
if p.enable_hr:
- hr_uc = get_conds_with_caching(prompt_parser.get_learned_conditioning, negative_prompts, p.steps,
+ hr_uc = get_conds_with_caching(prompt_parser.get_learned_conditioning, hr_negative_prompts, p.steps,
cached_uc)
- hr_c = get_conds_with_caching(prompt_parser.get_multicond_learned_conditioning, prompts, p.steps,
+ hr_c = get_conds_with_caching(prompt_parser.get_multicond_learned_conditioning, hr_prompts, p.steps,
cached_c)
if len(model_hijack.comments) > 0:
@@ -840,7 +832,7 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing): if self.hr_upscaler is not None:
self.extra_generation_params["Hires upscaler"] = self.hr_upscaler
- def sample(self, conditioning, unconditional_conditioning, hr_conditioning, hr_uconditional_conditioning, seeds, subseeds, subseed_strength, prompts):
+ def sample(self, conditioning, unconditional_conditioning, hr_conditioning, hr_unconditional_conditioning, seeds, subseeds, subseed_strength, prompts):
self.sampler = sd_samplers.create_sampler(self.sampler_name, self.sd_model)
latent_scale_mode = shared.latent_upscale_modes.get(self.hr_upscaler, None) if self.hr_upscaler is not None else shared.latent_upscale_modes.get(shared.latent_upscale_default_mode, "nearest")
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