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revise "send distilled_cfg_scale when generating hires conds"

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layerdiffusion
2024-08-22 06:35:13 -07:00
parent bfd7fb1d9f
commit 08f7487590
1 changed files with 6 additions and 1 deletions
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7
modules/processing.py
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@@ -1500,7 +1500,12 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
steps = self.hr_second_pass_steps or self.steps
total_steps = sampler_config.total_steps(steps) if sampler_config else steps
self.hr_uc = self.get_conds_with_caching(prompt_parser.get_learned_conditioning, hr_negative_prompts, self.firstpass_steps, [self.cached_hr_uc, self.cached_uc], self.hr_extra_network_data, total_steps)
if self.cfg_scale == 1:
self.hr_uc = None
print('Skipping unconditional conditioning (HR pass) when CFG = 1. Negative Prompts are ignored.')
else:
self.hr_uc = self.get_conds_with_caching(prompt_parser.get_learned_conditioning, hr_negative_prompts, self.firstpass_steps, [self.cached_hr_uc, self.cached_uc], self.hr_extra_network_data, total_steps)
self.hr_c = self.get_conds_with_caching(prompt_parser.get_multicond_learned_conditioning, hr_prompts, self.firstpass_steps, [self.cached_hr_c, self.cached_c], self.hr_extra_network_data, total_steps)
def setup_conds(self):