hr conditioning (2ab2bce7) · Commits · github_fork / Stable Diffusion Webui

modules/processing.py

+12 −7

Original line number	Diff line number	Diff line
		@@ -235,7 +235,7 @@ class StableDiffusionProcessing:
		def init(self, all_prompts, all_seeds, all_subseeds):
		pass

		def sample(self, conditioning, unconditional_conditioning, hr_conditioning, hr_uconditional_conditioning, seeds, subseeds, subseed_strength, prompts):
		def sample(self, conditioning, unconditional_conditioning, hr_conditioning=None, hr_unconditional_conditioning=None, seeds, subseeds, subseed_strength, prompts):
		raise NotImplementedError()

		def close(self):
		@@ -517,7 +517,7 @@ 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:
		if p.enable_hr and 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:
		@@ -601,7 +601,7 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
		negative_prompts = p.all_negative_prompts[n * p.batch_size:(n + 1) * p.batch_size]

		if type(p) == StableDiffusionProcessingTxt2Img:
		if p.enable_hr:
		if p.enable_hr and p.hr_prompt != '':
		hr_prompts = p.all_hr_prompts[n * p.batch_size:(n + 1) * p.batch_size]
		hr_negative_prompts = p.all_negative_prompts[n * p.batch_size:(n + 1) * p.batch_size]

		@@ -619,7 +619,7 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
		uc = get_conds_with_caching(prompt_parser.get_learned_conditioning, negative_prompts, p.steps, cached_uc)
		c = get_conds_with_caching(prompt_parser.get_multicond_learned_conditioning, prompts, p.steps, cached_c)
		if type(p) == StableDiffusionProcessingTxt2Img:
		if p.enable_hr:
		if p.enable_hr and p.hr_prompt != '':
		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, hr_prompts, p.steps,
		@@ -635,7 +635,12 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
		with devices.autocast():
		if type(p) == StableDiffusionProcessingTxt2Img:
		if p.enable_hr:
		if p.hr_prompts != '':
		samples_ddim = p.sample(conditioning=c, unconditional_conditioning=uc, hr_conditioning=hr_c, hr_unconditional_conditioning=hr_uc, seeds=seeds, subseeds=subseeds, subseed_strength=p.subseed_strength, prompts=prompts)
		else:
		samples_ddim = p.sample(conditioning=c, unconditional_conditioning=uc, hr_conditioning=c,
		hr_unconditional_conditioning=uc, seeds=seeds, subseeds=subseeds,
		subseed_strength=p.subseed_strength, prompts=prompts)
		else:
		samples_ddim = p.sample(conditioning=c, unconditional_conditioning=uc, seeds=seeds, subseeds=subseeds,
		subseed_strength=p.subseed_strength, prompts=prompts)
		@@ -756,8 +761,8 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
		self.hr_upscale_to_x = hr_resize_x
		self.hr_upscale_to_y = hr_resize_y
		self.hr_sampler = hr_sampler
		self.hr_prompt = hr_prompt if hr_prompt != '' else self.prompt
		self.hr_negative_prompt = hr_negative_prompt if hr_negative_prompt != '' else self.negative_prompt
		self.hr_prompt = hr_prompt if hr_prompt != '' else ''
		self.hr_negative_prompt = hr_negative_prompt if hr_negative_prompt != '' else ''
		self.all_hr_prompts = None
		self.all_hr_negative_prompts = None

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