make it possible for StableDiffusionProcessing to accept multiple different negative prompts in a batch
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AUTOMATIC
parent
e35d8b493f
commit
617c5b486f
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@ -124,6 +124,7 @@ class StableDiffusionProcessing():
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self.scripts = None
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self.script_args = None
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self.all_prompts = None
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self.all_negative_prompts = None
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self.all_seeds = None
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self.all_subseeds = None
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@ -202,7 +203,7 @@ class StableDiffusionProcessing():
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class Processed:
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def __init__(self, p: StableDiffusionProcessing, images_list, seed=-1, info="", subseed=None, all_prompts=None, all_seeds=None, all_subseeds=None, index_of_first_image=0, infotexts=None):
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def __init__(self, p: StableDiffusionProcessing, images_list, seed=-1, info="", subseed=None, all_prompts=None, all_negative_prompts=None, all_seeds=None, all_subseeds=None, index_of_first_image=0, infotexts=None):
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self.images = images_list
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self.prompt = p.prompt
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self.negative_prompt = p.negative_prompt
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@ -241,16 +242,18 @@ class Processed:
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self.subseed = int(self.subseed if type(self.subseed) != list else self.subseed[0]) if self.subseed is not None else -1
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self.is_using_inpainting_conditioning = p.is_using_inpainting_conditioning
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self.all_prompts = all_prompts or [self.prompt]
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self.all_seeds = all_seeds or [self.seed]
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self.all_subseeds = all_subseeds or [self.subseed]
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self.all_prompts = all_prompts or p.all_prompts or [self.prompt]
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self.all_negative_prompts = all_negative_prompts or p.all_negative_prompts or [self.negative_prompt]
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self.all_seeds = all_seeds or p.all_seeds or [self.seed]
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self.all_subseeds = all_subseeds or p.all_subseeds or [self.subseed]
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self.infotexts = infotexts or [info]
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def js(self):
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obj = {
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"prompt": self.prompt,
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"prompt": self.all_prompts[0],
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"all_prompts": self.all_prompts,
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"negative_prompt": self.negative_prompt,
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"negative_prompt": self.all_negative_prompts[0],
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"all_negative_prompts": self.all_negative_prompts,
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"seed": self.seed,
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"all_seeds": self.all_seeds,
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"subseed": self.subseed,
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@ -411,7 +414,7 @@ def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments, iteration
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generation_params_text = ", ".join([k if k == v else f'{k}: {generation_parameters_copypaste.quote(v)}' for k, v in generation_params.items() if v is not None])
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negative_prompt_text = "\nNegative prompt: " + p.negative_prompt if p.negative_prompt else ""
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negative_prompt_text = "\nNegative prompt: " + p.all_negative_prompts[0] if p.all_negative_prompts[0] else ""
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return f"{all_prompts[index]}{negative_prompt_text}\n{generation_params_text}".strip()
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@ -440,10 +443,6 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
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else:
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assert p.prompt is not None
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with open(os.path.join(shared.script_path, "params.txt"), "w", encoding="utf8") as file:
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processed = Processed(p, [], p.seed, "")
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file.write(processed.infotext(p, 0))
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devices.torch_gc()
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seed = get_fixed_seed(p.seed)
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@ -453,15 +452,16 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
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modules.sd_hijack.model_hijack.clear_comments()
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comments = {}
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prompt_tmp = p.prompt
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negative_prompt_tmp = p.negative_prompt
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shared.prompt_styles.apply_styles(p)
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if type(p.prompt) == list:
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p.all_prompts = p.prompt
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p.all_prompts = [shared.prompt_styles.apply_styles_to_prompt(x, p.styles) for x in p.prompt]
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else:
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p.all_prompts = p.batch_size * p.n_iter * [p.prompt]
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p.all_prompts = p.batch_size * p.n_iter * [shared.prompt_styles.apply_styles_to_prompt(p.prompt, p.styles)]
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if type(p.negative_prompt) == list:
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p.all_negative_prompts = [shared.prompt_styles.apply_negative_styles_to_prompt(x, p.styles) for x in p.negative_prompt]
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else:
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p.all_negative_prompts = p.batch_size * p.n_iter * [shared.prompt_styles.apply_negative_styles_to_prompt(p.negative_prompt, p.styles)]
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if type(seed) == list:
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p.all_seeds = seed
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@ -476,6 +476,10 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
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def infotext(iteration=0, position_in_batch=0):
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return create_infotext(p, p.all_prompts, p.all_seeds, p.all_subseeds, comments, iteration, position_in_batch)
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with open(os.path.join(shared.script_path, "params.txt"), "w", encoding="utf8") as file:
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processed = Processed(p, [], p.seed, "")
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file.write(processed.infotext(p, 0))
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if os.path.exists(cmd_opts.embeddings_dir) and not p.do_not_reload_embeddings:
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model_hijack.embedding_db.load_textual_inversion_embeddings()
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@ -500,6 +504,7 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
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break
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prompts = p.all_prompts[n * p.batch_size:(n + 1) * p.batch_size]
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negative_prompts = p.all_negative_prompts[n * p.batch_size:(n + 1) * p.batch_size]
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seeds = p.all_seeds[n * p.batch_size:(n + 1) * p.batch_size]
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subseeds = p.all_subseeds[n * p.batch_size:(n + 1) * p.batch_size]
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@ -510,7 +515,7 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
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p.scripts.process_batch(p, batch_number=n, prompts=prompts, seeds=seeds, subseeds=subseeds)
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with devices.autocast():
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uc = prompt_parser.get_learned_conditioning(shared.sd_model, len(prompts) * [p.negative_prompt], p.steps)
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uc = prompt_parser.get_learned_conditioning(shared.sd_model, negative_prompts, p.steps)
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c = prompt_parser.get_multicond_learned_conditioning(shared.sd_model, prompts, p.steps)
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if len(model_hijack.comments) > 0:
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@ -596,14 +601,11 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
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devices.torch_gc()
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res = Processed(p, output_images, p.all_seeds[0], infotext() + "".join(["\n\n" + x for x in comments]), subseed=p.all_subseeds[0], all_prompts=p.all_prompts, all_seeds=p.all_seeds, all_subseeds=p.all_subseeds, index_of_first_image=index_of_first_image, infotexts=infotexts)
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res = Processed(p, output_images, p.all_seeds[0], infotext() + "".join(["\n\n" + x for x in comments]), subseed=p.all_subseeds[0], index_of_first_image=index_of_first_image, infotexts=infotexts)
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if p.scripts is not None:
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p.scripts.postprocess(p, res)
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p.prompt = prompt_tmp
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p.negative_prompt = negative_prompt_tmp
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return res
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@ -65,17 +65,6 @@ class StyleDatabase:
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def apply_negative_styles_to_prompt(self, prompt, styles):
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return apply_styles_to_prompt(prompt, [self.styles.get(x, self.no_style).negative_prompt for x in styles])
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def apply_styles(self, p: StableDiffusionProcessing) -> None:
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if isinstance(p.prompt, list):
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p.prompt = [self.apply_styles_to_prompt(prompt, p.styles) for prompt in p.prompt]
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else:
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p.prompt = self.apply_styles_to_prompt(p.prompt, p.styles)
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if isinstance(p.negative_prompt, list):
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p.negative_prompt = [self.apply_negative_styles_to_prompt(prompt, p.styles) for prompt in p.negative_prompt]
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else:
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p.negative_prompt = self.apply_negative_styles_to_prompt(p.negative_prompt, p.styles)
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def save_styles(self, path: str) -> None:
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# Write to temporary file first, so we don't nuke the file if something goes wrong
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fd, temp_path = tempfile.mkstemp(".csv")
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