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https://github.com/vladmandic/automatic
synced 2026-09-19 17:24:32 +02:00
rename latent sampler
This commit is contained in:
Vladimir Mandic
@@ -93,7 +93,7 @@ def control_run(units: List[unit.Unit], inputs, inits, mask, unit_type: str, is_
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styles = styles,
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steps = steps,
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sampler_name = processing.get_sampler_name(sampler_index),
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latent_sampler = processing.get_sampler_name(sampler_index),
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hr_sampler_name = processing.get_sampler_name(sampler_index),
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seed = seed,
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subseed = subseed,
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subseed_strength = subseed_strength,
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+5
-5
@@ -114,7 +114,7 @@ def img2img(id_task: str, mode: int,
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init_img_inpaint,
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init_mask_inpaint,
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steps,
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sampler_index, latent_index,
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sampler_index, hr_sampler_index,
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mask_blur, mask_alpha,
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inpainting_fill,
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full_quality, restore_faces, tiling,
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@@ -140,7 +140,7 @@ def img2img(id_task: str, mode: int,
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shared.log.warning('Model not loaded')
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return [], '', '', 'Error: model not loaded'
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debug(f'img2img: id_task={id_task}|mode={mode}|prompt={prompt}|negative_prompt={negative_prompt}|prompt_styles={prompt_styles}|init_img={init_img}|sketch={sketch}|init_img_with_mask={init_img_with_mask}|inpaint_color_sketch={inpaint_color_sketch}|inpaint_color_sketch_orig={inpaint_color_sketch_orig}|init_img_inpaint={init_img_inpaint}|init_mask_inpaint={init_mask_inpaint}|steps={steps}|sampler_index={sampler_index}|latent_index={latent_index}|mask_blur={mask_blur}|mask_alpha={mask_alpha}|inpainting_fill={inpainting_fill}|full_quality={full_quality}|restore_faces={restore_faces}|tiling={tiling}|n_iter={n_iter}|batch_size={batch_size}|cfg_scale={cfg_scale}|image_cfg_scale={image_cfg_scale}|clip_skip={clip_skip}|denoising_strength={denoising_strength}|seed={seed}|subseed{subseed}|subseed_strength={subseed_strength}|seed_resize_from_h={seed_resize_from_h}|seed_resize_from_w={seed_resize_from_w}|selected_scale_tab={selected_scale_tab}|height={height}|width={width}|scale_by={scale_by}|resize_mode={resize_mode}|resize_name={resize_name}|inpaint_full_res={inpaint_full_res}|inpaint_full_res_padding={inpaint_full_res_padding}|inpainting_mask_invert={inpainting_mask_invert}|img2img_batch_files={img2img_batch_files}|img2img_batch_input_dir={img2img_batch_input_dir}|img2img_batch_output_dir={img2img_batch_output_dir}|img2img_batch_inpaint_mask_dir={img2img_batch_inpaint_mask_dir}|override_settings_texts={override_settings_texts}')
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debug(f'img2img: id_task={id_task}|mode={mode}|prompt={prompt}|negative_prompt={negative_prompt}|prompt_styles={prompt_styles}|init_img={init_img}|sketch={sketch}|init_img_with_mask={init_img_with_mask}|inpaint_color_sketch={inpaint_color_sketch}|inpaint_color_sketch_orig={inpaint_color_sketch_orig}|init_img_inpaint={init_img_inpaint}|init_mask_inpaint={init_mask_inpaint}|steps={steps}|sampler_index={sampler_index}|hr_sampler_index={hr_sampler_index}|mask_blur={mask_blur}|mask_alpha={mask_alpha}|inpainting_fill={inpainting_fill}|full_quality={full_quality}|restore_faces={restore_faces}|tiling={tiling}|n_iter={n_iter}|batch_size={batch_size}|cfg_scale={cfg_scale}|image_cfg_scale={image_cfg_scale}|clip_skip={clip_skip}|denoising_strength={denoising_strength}|seed={seed}|subseed{subseed}|subseed_strength={subseed_strength}|seed_resize_from_h={seed_resize_from_h}|seed_resize_from_w={seed_resize_from_w}|selected_scale_tab={selected_scale_tab}|height={height}|width={width}|scale_by={scale_by}|resize_mode={resize_mode}|resize_name={resize_name}|inpaint_full_res={inpaint_full_res}|inpaint_full_res_padding={inpaint_full_res_padding}|inpainting_mask_invert={inpainting_mask_invert}|img2img_batch_files={img2img_batch_files}|img2img_batch_input_dir={img2img_batch_input_dir}|img2img_batch_output_dir={img2img_batch_output_dir}|img2img_batch_inpaint_mask_dir={img2img_batch_inpaint_mask_dir}|override_settings_texts={override_settings_texts}')
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if mode == 5:
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if img2img_batch_files is None or len(img2img_batch_files) == 0:
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@@ -150,8 +150,8 @@ def img2img(id_task: str, mode: int,
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if sampler_index is None:
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sampler_index = 0
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if latent_index is None:
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latent_index = 0
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if hr_sampler_index is None:
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hr_sampler_index = 0
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override_settings = create_override_settings_dict(override_settings_texts)
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@@ -213,7 +213,7 @@ def img2img(id_task: str, mode: int,
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seed_resize_from_w=seed_resize_from_w,
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seed_enable_extras=True,
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sampler_name = processing.get_sampler_name(sampler_index, img=True),
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latent_sampler = processing.get_sampler_name(latent_index, img=True),
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hr_sampler_name = processing.get_sampler_name(hr_sampler_index, img=True),
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batch_size=batch_size,
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n_iter=n_iter,
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steps=steps,
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@@ -135,7 +135,7 @@ class StableDiffusionProcessing:
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"""
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The first set of paramaters: sd_models -> do_not_reload_embeddings represent the minimum required to create a StableDiffusionProcessing
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"""
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def __init__(self, sd_model=None, outpath_samples=None, outpath_grids=None, prompt: str = "", styles: List[str] = None, seed: int = -1, subseed: int = -1, subseed_strength: float = 0, seed_resize_from_h: int = -1, seed_resize_from_w: int = -1, seed_enable_extras: bool = True, sampler_name: str = None, latent_sampler: str = None, batch_size: int = 1, n_iter: int = 1, steps: int = 50, cfg_scale: float = 7.0, image_cfg_scale: float = None, clip_skip: int = 1, width: int = 512, height: int = 512, full_quality: bool = True, restore_faces: bool = False, tiling: bool = False, do_not_save_samples: bool = False, do_not_save_grid: bool = False, extra_generation_params: Dict[Any, Any] = None, overlay_images: Any = None, negative_prompt: str = None, eta: float = None, do_not_reload_embeddings: bool = False, denoising_strength: float = 0, diffusers_guidance_rescale: float = 0.7, resize_mode: int = 0, resize_name: str = 'None', scale_by: float = 0, selected_scale_tab: int = 0, hdr_clamp: bool = False, hdr_boundary: float = 4.0, hdr_threshold: float = 3.5, hdr_center: bool = False, hdr_channel_shift: float = 0.8, hdr_full_shift: float = 0.8, hdr_maximize: bool = False, hdr_max_center: float = 0.6, hdr_max_boundry: float = 1.0, override_settings: Dict[str, Any] = None, override_settings_restore_afterwards: bool = True, sampler_index: int = None, script_args: list = None): # pylint: disable=unused-argument
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def __init__(self, sd_model=None, outpath_samples=None, outpath_grids=None, prompt: str = "", styles: List[str] = None, seed: int = -1, subseed: int = -1, subseed_strength: float = 0, seed_resize_from_h: int = -1, seed_resize_from_w: int = -1, seed_enable_extras: bool = True, sampler_name: str = None, hr_sampler_name: str = None, batch_size: int = 1, n_iter: int = 1, steps: int = 50, cfg_scale: float = 7.0, image_cfg_scale: float = None, clip_skip: int = 1, width: int = 512, height: int = 512, full_quality: bool = True, restore_faces: bool = False, tiling: bool = False, do_not_save_samples: bool = False, do_not_save_grid: bool = False, extra_generation_params: Dict[Any, Any] = None, overlay_images: Any = None, negative_prompt: str = None, eta: float = None, do_not_reload_embeddings: bool = False, denoising_strength: float = 0, diffusers_guidance_rescale: float = 0.7, resize_mode: int = 0, resize_name: str = 'None', scale_by: float = 0, selected_scale_tab: int = 0, hdr_clamp: bool = False, hdr_boundary: float = 4.0, hdr_threshold: float = 3.5, hdr_center: bool = False, hdr_channel_shift: float = 0.8, hdr_full_shift: float = 0.8, hdr_maximize: bool = False, hdr_max_center: float = 0.6, hdr_max_boundry: float = 1.0, override_settings: Dict[str, Any] = None, override_settings_restore_afterwards: bool = True, sampler_index: int = None, script_args: list = None): # pylint: disable=unused-argument
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self.outpath_samples: str = outpath_samples
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self.outpath_grids: str = outpath_grids
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self.prompt: str = prompt
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@@ -148,7 +148,7 @@ class StableDiffusionProcessing:
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self.seed_resize_from_h: int = seed_resize_from_h
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self.seed_resize_from_w: int = seed_resize_from_w
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self.sampler_name: str = sampler_name
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self.latent_sampler: str = latent_sampler
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self.hr_sampler_name: str = hr_sampler_name
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self.batch_size: int = batch_size
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self.n_iter: int = n_iter
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self.steps: int = steps
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@@ -633,7 +633,7 @@ def create_infotext(p: StableDiffusionProcessing, all_prompts=None, all_seeds=No
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args["Hires resize"] = f"{p.hr_resize_x}x{p.hr_resize_y}"
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args["Hires size"] = f"{p.hr_upscale_to_x}x{p.hr_upscale_to_y}"
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args["Denoising strength"] = p.denoising_strength
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args["Latent sampler"] = p.latent_sampler
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args["Hires sampler"] = p.hr_sampler_name
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args["Image CFG scale"] = p.image_cfg_scale
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args["CFG rescale"] = p.diffusers_guidance_rescale
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if 'refine' in p.ops:
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@@ -643,7 +643,7 @@ def create_infotext(p: StableDiffusionProcessing, all_prompts=None, all_seeds=No
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args['Refiner steps'] = p.refiner_steps
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args['Refiner start'] = p.refiner_start
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args["Hires steps"] = p.hr_second_pass_steps
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args["Latent sampler"] = p.latent_sampler
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args["Hires sampler"] = p.hr_sampler_name
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args["CFG rescale"] = p.diffusers_guidance_rescale
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if 'img2img' in p.ops or 'inpaint' in p.ops:
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args["Init image size"] = f"{getattr(p, 'init_img_width', 0)}x{getattr(p, 'init_img_height', 0)}"
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@@ -1129,7 +1129,7 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
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self.is_hr_pass = True
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hypertile_set(self, hr=True)
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shared.state.job_count = 2 * self.n_iter
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shared.log.debug(f'Init hires: upscaler="{self.hr_upscaler}" sampler="{self.latent_sampler}" resize={self.hr_resize_x}x{self.hr_resize_y} upscale={self.hr_upscale_to_x}x{self.hr_upscale_to_y}')
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shared.log.debug(f'Init hires: upscaler="{self.hr_upscaler}" sampler="{self.hr_sampler_name}" resize={self.hr_resize_x}x{self.hr_resize_y} upscale={self.hr_upscale_to_x}x{self.hr_upscale_to_y}')
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def sample(self, conditioning, unconditional_conditioning, seeds, subseeds, subseed_strength, prompts):
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@@ -1198,14 +1198,14 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
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image_conditioning = self.img2img_image_conditioning(decode_first_stage(self.sd_model, samples.to(dtype=devices.dtype_vae), self.full_quality), samples)
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else:
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image_conditioning = self.txt2img_image_conditioning(samples.to(dtype=devices.dtype_vae))
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if self.latent_sampler == "PLMS":
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self.latent_sampler = 'UniPC'
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if self.hr_sampler_name == "PLMS":
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self.hr_sampler_name = 'UniPC'
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if self.hr_force or latent_scale_mode is not None:
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shared.state.job = 'hires'
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if self.denoising_strength > 0:
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self.ops.append('hires')
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devices.torch_gc() # GC now before running the next img2img to prevent running out of memory
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self.sampler = modules.sd_samplers.create_sampler(self.latent_sampler or self.sampler_name, self.sd_model)
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self.sampler = modules.sd_samplers.create_sampler(self.hr_sampler_name or self.sampler_name, self.sd_model)
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if hasattr(self.sampler, "initialize"):
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self.sampler.initialize(self)
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samples = samples[:, :, self.truncate_y//2:samples.shape[2]-(self.truncate_y+1)//2, self.truncate_x//2:samples.shape[3]-(self.truncate_x+1)//2]
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@@ -357,7 +357,7 @@ def process_diffusers(p: StableDiffusionProcessing):
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devices.torch_gc(force=True)
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def update_sampler(sd_model, second_pass=False):
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sampler_selection = p.latent_sampler if second_pass else p.sampler_name
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sampler_selection = p.hr_sampler_name if second_pass else p.sampler_name
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if sd_model.__class__.__name__ in ['AmusedPipeline']:
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return # models with their own schedulers
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if hasattr(sd_model, 'scheduler') and sampler_selection != 'Default':
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+5
-5
@@ -11,7 +11,7 @@ debug('Trace: PROCESS')
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def txt2img(id_task,
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prompt, negative_prompt, prompt_styles,
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steps, sampler_index, latent_index,
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steps, sampler_index, hr_sampler_index,
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full_quality, restore_faces, tiling,
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n_iter, batch_size,
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cfg_scale, image_cfg_scale, diffusers_guidance_rescale,
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@@ -25,7 +25,7 @@ def txt2img(id_task,
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override_settings_texts,
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*args):
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debug(f'txt2img: id_task={id_task}|prompt={prompt}|negative={negative_prompt}|styles={prompt_styles}|steps={steps}|sampler_index={sampler_index}|latent_index={latent_index}|full_quality={full_quality}|restore_faces={restore_faces}|tiling={tiling}|batch_count={n_iter}|batch_size={batch_size}|cfg_scale={cfg_scale}|clip_skip={clip_skip}|seed={seed}|subseed={subseed}|subseed_strength={subseed_strength}|seed_resize_from_h={seed_resize_from_h}|seed_resize_from_w={seed_resize_from_w}|height={height}|width={width}|enable_hr={enable_hr}|denoising_strength={denoising_strength}|hr_scale={hr_scale}|hr_upscaler={hr_upscaler}|hr_force={hr_force}|hr_second_pass_steps={hr_second_pass_steps}|hr_resize_x={hr_resize_x}|hr_resize_y={hr_resize_y}|image_cfg_scale={image_cfg_scale}|diffusers_guidance_rescale={diffusers_guidance_rescale}|refiner_steps={refiner_steps}|refiner_start={refiner_start}|refiner_prompt={refiner_prompt}|refiner_negative={refiner_negative}|override_settings={override_settings_texts}')
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debug(f'txt2img: id_task={id_task}|prompt={prompt}|negative={negative_prompt}|styles={prompt_styles}|steps={steps}|sampler_index={sampler_index}|hr_sampler_index={hr_sampler_index}|full_quality={full_quality}|restore_faces={restore_faces}|tiling={tiling}|batch_count={n_iter}|batch_size={batch_size}|cfg_scale={cfg_scale}|clip_skip={clip_skip}|seed={seed}|subseed={subseed}|subseed_strength={subseed_strength}|seed_resize_from_h={seed_resize_from_h}|seed_resize_from_w={seed_resize_from_w}|height={height}|width={width}|enable_hr={enable_hr}|denoising_strength={denoising_strength}|hr_scale={hr_scale}|hr_upscaler={hr_upscaler}|hr_force={hr_force}|hr_second_pass_steps={hr_second_pass_steps}|hr_resize_x={hr_resize_x}|hr_resize_y={hr_resize_y}|image_cfg_scale={image_cfg_scale}|diffusers_guidance_rescale={diffusers_guidance_rescale}|refiner_steps={refiner_steps}|refiner_start={refiner_start}|refiner_prompt={refiner_prompt}|refiner_negative={refiner_negative}|override_settings={override_settings_texts}')
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if shared.sd_model is None:
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shared.log.warning('Model not loaded')
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@@ -34,8 +34,8 @@ def txt2img(id_task,
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override_settings = create_override_settings_dict(override_settings_texts)
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if sampler_index is None:
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sampler_index = 0
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if latent_index is None:
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latent_index = 0
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if hr_sampler_index is None:
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hr_sampler_index = 0
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p = processing.StableDiffusionProcessingTxt2Img(
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sd_model=shared.sd_model,
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@@ -51,7 +51,7 @@ def txt2img(id_task,
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seed_resize_from_w=seed_resize_from_w,
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seed_enable_extras=True,
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sampler_name = processing.get_sampler_name(sampler_index),
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latent_sampler = processing.get_sampler_name(latent_index),
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hr_sampler_name = processing.get_sampler_name(hr_sampler_index),
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batch_size=batch_size,
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n_iter=n_iter,
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steps=steps,
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+7
-7
@@ -465,7 +465,7 @@ def create_hires_inputs(tab):
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with FormRow(elem_id=f"{tab}_hires_row1"):
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enable_hr = gr.Checkbox(label='Enable second pass', value=False, elem_id=f"{tab}_enable_hr")
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with FormRow(elem_id=f"{tab}_hires_row2"):
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latent_index = gr.Dropdown(label='Secondary sampler', elem_id=f"{tab}_sampling_alt", choices=[x.name for x in modules.sd_samplers.samplers], value='Default', type="index")
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hr_sampler_index = gr.Dropdown(label='Secondary sampler', elem_id=f"{tab}_sampling_alt", choices=[x.name for x in modules.sd_samplers.samplers], value='Default', type="index")
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denoising_strength = gr.Slider(minimum=0.0, maximum=0.99, step=0.01, label='Denoising strength', value=0.5, elem_id=f"{tab}_denoising_strength")
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with FormRow(elem_id=f"{tab}_hires_finalres", variant="compact"):
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hr_final_resolution = FormHTML(value="", elem_id=f"{tab}_hr_finalres", label="Upscaled resolution", interactive=False)
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@@ -486,7 +486,7 @@ def create_hires_inputs(tab):
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refiner_prompt = gr.Textbox(value='', label='Secondary prompt', elem_id=f"{tab}_refiner_prompt")
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with FormRow(elem_id="txt2img_refiner_row4", variant="compact"):
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refiner_negative = gr.Textbox(value='', label='Secondary negative prompt', elem_id=f"{tab}_refiner_neg_prompt")
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return enable_hr, latent_index, denoising_strength, hr_final_resolution, hr_upscaler, hr_force, hr_second_pass_steps, hr_scale, hr_resize_x, hr_resize_y, refiner_steps, refiner_start, refiner_prompt, refiner_negative
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return enable_hr, hr_sampler_index, denoising_strength, hr_final_resolution, hr_upscaler, hr_force, hr_second_pass_steps, hr_scale, hr_resize_x, hr_resize_y, refiner_steps, refiner_start, refiner_prompt, refiner_negative
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def get_value_for_setting(key):
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@@ -543,7 +543,7 @@ def create_ui(startup_timer = None):
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batch_count, batch_size = create_batch_inputs('txt2img')
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seed, reuse_seed, subseed, reuse_subseed, subseed_strength, seed_resize_from_h, seed_resize_from_w = create_seed_inputs('txt2img')
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cfg_scale, clip_skip, image_cfg_scale, diffusers_guidance_rescale, full_quality, restore_faces, tiling, hdr_clamp, hdr_boundary, hdr_threshold, hdr_center, hdr_channel_shift, hdr_full_shift, hdr_maximize, hdr_max_center, hdr_max_boundry = create_advanced_inputs('txt2img')
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enable_hr, latent_index, denoising_strength, hr_final_resolution, hr_upscaler, hr_force, hr_second_pass_steps, hr_scale, hr_resize_x, hr_resize_y, refiner_steps, refiner_start, refiner_prompt, refiner_negative = create_hires_inputs('txt2img')
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enable_hr, hr_sampler_index, denoising_strength, hr_final_resolution, hr_upscaler, hr_force, hr_second_pass_steps, hr_scale, hr_resize_x, hr_resize_y, refiner_steps, refiner_start, refiner_prompt, refiner_negative = create_hires_inputs('txt2img')
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override_settings = create_override_inputs('txt2img')
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txt2img_script_inputs = modules.scripts.scripts_txt2img.setup_ui()
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@@ -567,7 +567,7 @@ def create_ui(startup_timer = None):
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txt2img_args = [
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dummy_component,
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txt2img_prompt, txt2img_negative_prompt, txt2img_prompt_styles,
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steps, sampler_index, latent_index,
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steps, sampler_index, hr_sampler_index,
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full_quality, restore_faces, tiling,
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batch_count, batch_size,
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cfg_scale, image_cfg_scale, diffusers_guidance_rescale,
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@@ -623,7 +623,7 @@ def create_ui(startup_timer = None):
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(tiling, "Tiling"),
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# second pass
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(enable_hr, "Second pass"),
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(latent_index, "Latent sampler"),
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(hr_sampler_index, "Hires sampler"),
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(denoising_strength, "Denoising strength"),
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(hr_upscaler, "Hires upscaler"),
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(hr_force, "Hires force"),
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@@ -794,7 +794,7 @@ def create_ui(startup_timer = None):
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init_img_inpaint,
|
||||
init_mask_inpaint,
|
||||
steps,
|
||||
sampler_index, latent_index,
|
||||
sampler_index, hr_sampler_index,
|
||||
mask_blur, mask_alpha,
|
||||
inpainting_fill,
|
||||
full_quality, restore_faces, tiling,
|
||||
@@ -1025,8 +1025,8 @@ def create_ui(startup_timer = None):
|
||||
shared.log.warning("OpenVINO: Setting backend to Diffusers")
|
||||
shared.opts.sd_backend = "diffusers"
|
||||
try:
|
||||
opts.save(shared.config_filename)
|
||||
if len(changed) > 0:
|
||||
opts.save(shared.config_filename)
|
||||
log.info(f'Settings: changed={len(changed)} {changed}')
|
||||
except RuntimeError:
|
||||
log.error(f'Settings failed: change={len(changed)} {changed}')
|
||||
|
||||
@@ -355,7 +355,7 @@ def create_ui(_blocks: gr.Blocks=None):
|
||||
input_mode = gr.Label(value='select', visible=False)
|
||||
input_image = gr.Image(label="Input", show_label=False, type="pil", source="upload", interactive=True, tool="editor", height=gr_height, visible=True, image_mode='RGB', elem_id='control_input_select')
|
||||
input_resize = gr.Image(label="Input", show_label=False, type="pil", source="upload", interactive=True, tool="select", height=gr_height, visible=False, image_mode='RGB', elem_id='control_input_resize')
|
||||
input_inpaint = gr.Image(label="Input", show_label=False, type="pil", source="upload", interactive=True, tool="sketch", height=gr_height, visible=False, image_mode='RGB', elem_id='control_input_inpaint')
|
||||
input_inpaint = gr.Image(label="Input", show_label=False, type="pil", source="upload", interactive=True, tool="sketch", height=gr_height, visible=False, image_mode='RGB', elem_id='control_input_inpaint', brush_radius=64, mask_opacity=0.6)
|
||||
with gr.Row():
|
||||
input_buttons = [gr.Button('Select', visible=True, interactive=False), gr.Button('Inpaint', visible=True, interactive=True), gr.Button('Outpaint', visible=True, interactive=True)]
|
||||
with gr.Tab('Video', id='in-video') as tab_video:
|
||||
|
||||
Reference in New Issue
Block a user