From 2f8976e28dfe73d110a8570799e087fcbdd6ac56 Mon Sep 17 00:00:00 2001 From: awsr <43862868+awsr@users.noreply.github.com> Date: Wed, 21 Jan 2026 16:35:19 -0800 Subject: [PATCH] Type standardization in `processing_class` --- modules/face/faceid.py | 2 +- modules/face/instantid.py | 6 +++--- modules/face/photomaker.py | 4 ++-- modules/processing.py | 10 +++++----- modules/processing_class.py | 13 ++++++------- modules/processing_diffusers.py | 4 ++-- 6 files changed, 19 insertions(+), 20 deletions(-) diff --git a/modules/face/faceid.py b/modules/face/faceid.py index fade0f854..bbb53f729 100644 --- a/modules/face/faceid.py +++ b/modules/face/faceid.py @@ -205,7 +205,7 @@ def face_id( ip_model_dict["faceid_embeds"] = face_embeds # overwrite placeholder faceid_model.set_scale(scale) - if p.all_prompts is None or len(p.all_prompts) == 0: + if not p.all_prompts: processing.process_init(p) p.init(p.all_prompts, p.all_seeds, p.all_subseeds) for n in range(p.n_iter): diff --git a/modules/face/instantid.py b/modules/face/instantid.py index 158c2f577..c991e8d7d 100644 --- a/modules/face/instantid.py +++ b/modules/face/instantid.py @@ -63,7 +63,7 @@ def instant_id(p: processing.StableDiffusionProcessing, app, source_images, stre sd_models.move_model(shared.sd_model, devices.device) # move pipeline to device # pipeline specific args - if p.all_prompts is None or len(p.all_prompts) == 0: + if not p.all_prompts: processing.process_init(p) p.init(p.all_prompts, p.all_seeds, p.all_subseeds) orig_prompt_attention = shared.opts.prompt_attention @@ -73,8 +73,8 @@ def instant_id(p: processing.StableDiffusionProcessing, app, source_images, stre p.task_args['controlnet_conditioning_scale'] = float(conditioning) p.task_args['ip_adapter_scale'] = float(strength) shared.log.debug(f"InstantID args: {p.task_args}") - p.task_args['prompt'] = p.all_prompts[0] if p.all_prompts is not None else p.prompt - p.task_args['negative_prompt'] = p.all_negative_prompts[0] if p.all_negative_prompts is not None else p.negative_prompt + p.task_args['prompt'] = p.all_prompts[0] if p.all_prompts else p.prompt + p.task_args['negative_prompt'] = p.all_negative_prompts[0] if p.all_negative_prompts else p.negative_prompt p.task_args['image_embeds'] = face_embeds[0] # overwrite placeholder # run processing diff --git a/modules/face/photomaker.py b/modules/face/photomaker.py index 19a62b913..cbb737b58 100644 --- a/modules/face/photomaker.py +++ b/modules/face/photomaker.py @@ -34,7 +34,7 @@ def photo_maker(p: processing.StableDiffusionProcessing, app, model: str, input_ return None # validate prompt - if p.all_prompts is None or len(p.all_prompts) == 0: + if not p.all_prompts: processing.process_init(p) p.init(p.all_prompts, p.all_seeds, p.all_subseeds) trigger_ids = shared.sd_model.tokenizer.encode(trigger) + shared.sd_model.tokenizer_2.encode(trigger) @@ -61,7 +61,7 @@ def photo_maker(p: processing.StableDiffusionProcessing, app, model: str, input_ shared.opts.data['prompt_attention'] = 'fixed' # otherwise need to deal with class_tokens_mask p.task_args['input_id_images'] = input_images p.task_args['start_merge_step'] = int(start * p.steps) - p.task_args['prompt'] = p.all_prompts[0] if p.all_prompts is not None else p.prompt + p.task_args['prompt'] = p.all_prompts[0] if p.all_prompts else p.prompt is_v2 = 'v2' in model if is_v2: diff --git a/modules/processing.py b/modules/processing.py index 523915942..0a4fc33fe 100644 --- a/modules/processing.py +++ b/modules/processing.py @@ -243,13 +243,13 @@ def process_init(p: StableDiffusionProcessing): seed = get_fixed_seed(p.seed) subseed = get_fixed_seed(p.subseed) reset_prompts = False - if p.all_prompts is None: + if not p.all_prompts: p.all_prompts = p.prompt if isinstance(p.prompt, list) else p.batch_size * p.n_iter * [p.prompt] reset_prompts = True - if p.all_negative_prompts is None: + if not p.all_negative_prompts: p.all_negative_prompts = p.negative_prompt if isinstance(p.negative_prompt, list) else p.batch_size * p.n_iter * [p.negative_prompt] reset_prompts = True - if p.all_seeds is None: + if not p.all_seeds: reset_prompts = True if type(seed) == list: p.all_seeds = [int(s) for s in seed] @@ -262,7 +262,7 @@ def process_init(p: StableDiffusionProcessing): for i in range(len(p.all_prompts)): seed = get_fixed_seed(p.seed) p.all_seeds.append(int(seed) + (i if p.subseed_strength == 0 else 0)) - if p.all_subseeds is None: + if not p.all_subseeds: if type(subseed) == list: p.all_subseeds = [int(s) for s in subseed] else: @@ -433,7 +433,7 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed: p.subseeds = p.all_subseeds[n * p.batch_size:(n+1) * p.batch_size] if p.scripts is not None and isinstance(p.scripts, scripts_manager.ScriptRunner): p.scripts.before_process_batch(p, batch_number=n, prompts=p.prompts, seeds=p.seeds, subseeds=p.subseeds) - if len(p.prompts) == 0: + if not p.prompts: break p.prompts, p.network_data = extra_networks.parse_prompts(p.prompts) if p.scripts is not None and isinstance(p.scripts, scripts_manager.ScriptRunner): diff --git a/modules/processing_class.py b/modules/processing_class.py index d4305d52f..09c0bf5c1 100644 --- a/modules/processing_class.py +++ b/modules/processing_class.py @@ -308,15 +308,14 @@ class StableDiffusionProcessing: shared.log.error(f'Override: {override_settings} {e}') self.override_settings = {} - # null items initialized later - self.prompts = None - self.negative_prompts = None - self.all_prompts = None - self.all_negative_prompts = None + self.prompts = [] + self.negative_prompts = [] + self.all_prompts = [] + self.all_negative_prompts = [] self.seeds = [] self.subseeds = [] - self.all_seeds = None - self.all_subseeds = None + self.all_seeds = [] + self.all_subseeds = [] # a1111 compatibility items self.seed_enable_extras: bool = True diff --git a/modules/processing_diffusers.py b/modules/processing_diffusers.py index 269351120..a410497e2 100644 --- a/modules/processing_diffusers.py +++ b/modules/processing_diffusers.py @@ -563,9 +563,9 @@ def process_diffusers(p: processing.StableDiffusionProcessing): shared.sd_model = sd_models.set_diffuser_pipe(shared.sd_model, sd_models.DiffusersTaskType.INPAINTING) # force pipeline if len(getattr(p, 'init_images', [])) == 0: p.init_images = [TF.to_pil_image(torch.rand((3, getattr(p, 'height', 512), getattr(p, 'width', 512))))] - if p.prompts is None or len(p.prompts) == 0: + if not p.prompts: p.prompts = p.all_prompts[p.iteration * p.batch_size:(p.iteration+1) * p.batch_size] - if p.negative_prompts is None or len(p.negative_prompts) == 0: + if not p.negative_prompts: p.negative_prompts = p.all_negative_prompts[p.iteration * p.batch_size:(p.iteration+1) * p.batch_size] sd_models_compile.openvino_recompile_model(p, hires=False, refiner=False) # recompile if a parameter changes