From 2a72d76d6f3d34b1ffccec7736b19e7d52033dad Mon Sep 17 00:00:00 2001 From: dhwz Date: Tue, 8 Aug 2023 19:08:37 +0200 Subject: fix typo --- modules/processing.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) (limited to 'modules/processing.py') diff --git a/modules/processing.py b/modules/processing.py index 31745006..dc6e8ff1 100644 --- a/modules/processing.py +++ b/modules/processing.py @@ -568,7 +568,7 @@ def decode_latent_batch(model, batch, target_device=None, check_for_nans=False): errors.print_error_explanation( "A tensor with all NaNs was produced in VAE.\n" "Web UI will now convert VAE into 32-bit float and retry.\n" - "To disable this behavior, disable the 'Automaticlly revert VAE to 32-bit floats' setting.\n" + "To disable this behavior, disable the 'Automatically revert VAE to 32-bit floats' setting.\n" "To always start with 32-bit VAE, use --no-half-vae commandline flag." ) -- cgit v1.2.1 From d81d3fa8cde83ce1421889ed481a69c950c0c6f6 Mon Sep 17 00:00:00 2001 From: AUTOMATIC1111 <16777216c@gmail.com> Date: Wed, 9 Aug 2023 07:45:06 +0300 Subject: fix styles missing from the prompt in infotext when making a grid of batch of multiplie images --- modules/processing.py | 9 +++++++-- 1 file changed, 7 insertions(+), 2 deletions(-) (limited to 'modules/processing.py') diff --git a/modules/processing.py b/modules/processing.py index d7266307..aa72b132 100644 --- a/modules/processing.py +++ b/modules/processing.py @@ -172,6 +172,8 @@ class StableDiffusionProcessing: self.iteration = 0 self.is_hr_pass = False self.sampler = None + self.main_prompt = None + self.main_negative_prompt = None self.prompts = None self.negative_prompts = None @@ -319,6 +321,9 @@ class StableDiffusionProcessing: self.all_prompts = [shared.prompt_styles.apply_styles_to_prompt(x, self.styles) for x in self.all_prompts] self.all_negative_prompts = [shared.prompt_styles.apply_negative_styles_to_prompt(x, self.styles) for x in self.all_negative_prompts] + self.main_prompt = self.all_prompts[0] + self.main_negative_prompt = self.all_negative_prompts[0] + def cached_params(self, required_prompts, steps, extra_network_data): """Returns parameters that invalidate the cond cache if changed""" @@ -653,8 +658,8 @@ def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments=None, iter 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]) - prompt_text = p.prompt if use_main_prompt else all_prompts[index] - negative_prompt_text = f"\nNegative prompt: {all_negative_prompts[index]}" if all_negative_prompts[index] else "" + prompt_text = p.main_prompt if use_main_prompt else all_prompts[index] + negative_prompt_text = f"\nNegative prompt: {p.main_negative_prompt if use_main_prompt else all_negative_prompts[index]}" if all_negative_prompts[index] else "" return f"{prompt_text}{negative_prompt_text}\n{generation_params_text}".strip() -- cgit v1.2.1 From 0d5dc9a6e7f6362e423a06bf0e75dd5854025394 Mon Sep 17 00:00:00 2001 From: AUTOMATIC1111 <16777216c@gmail.com> Date: Wed, 9 Aug 2023 08:43:31 +0300 Subject: rework RNG to use generators instead of generating noises beforehand --- modules/processing.py | 89 ++++++--------------------------------------------- 1 file changed, 10 insertions(+), 79 deletions(-) (limited to 'modules/processing.py') diff --git a/modules/processing.py b/modules/processing.py index aa72b132..2df5e8c7 100644 --- a/modules/processing.py +++ b/modules/processing.py @@ -14,7 +14,7 @@ from skimage import exposure from typing import Any, Dict, List import modules.sd_hijack -from modules import devices, prompt_parser, masking, sd_samplers, lowvram, generation_parameters_copypaste, extra_networks, sd_vae_approx, scripts, sd_samplers_common, sd_unet, errors +from modules import devices, prompt_parser, masking, sd_samplers, lowvram, generation_parameters_copypaste, extra_networks, sd_vae_approx, scripts, sd_samplers_common, sd_unet, errors, rng from modules.sd_hijack import model_hijack from modules.sd_samplers_common import images_tensor_to_samples, decode_first_stage, approximation_indexes from modules.shared import opts, cmd_opts, state @@ -186,6 +186,7 @@ class StableDiffusionProcessing: self.cached_c = StableDiffusionProcessing.cached_c self.uc = None self.c = None + self.rng: rng.ImageRNG = None self.user = None @@ -475,82 +476,9 @@ class Processed: return self.token_merging_ratio_hr if for_hr else self.token_merging_ratio -# from https://discuss.pytorch.org/t/help-regarding-slerp-function-for-generative-model-sampling/32475/3 -def slerp(val, low, high): - low_norm = low/torch.norm(low, dim=1, keepdim=True) - high_norm = high/torch.norm(high, dim=1, keepdim=True) - dot = (low_norm*high_norm).sum(1) - - if dot.mean() > 0.9995: - return low * val + high * (1 - val) - - omega = torch.acos(dot) - so = torch.sin(omega) - res = (torch.sin((1.0-val)*omega)/so).unsqueeze(1)*low + (torch.sin(val*omega)/so).unsqueeze(1) * high - return res - - def create_random_tensors(shape, seeds, subseeds=None, subseed_strength=0.0, seed_resize_from_h=0, seed_resize_from_w=0, p=None): - eta_noise_seed_delta = opts.eta_noise_seed_delta or 0 - xs = [] - - # if we have multiple seeds, this means we are working with batch size>1; this then - # enables the generation of additional tensors with noise that the sampler will use during its processing. - # Using those pre-generated tensors instead of simple torch.randn allows a batch with seeds [100, 101] to - # produce the same images as with two batches [100], [101]. - if p is not None and p.sampler is not None and (len(seeds) > 1 and opts.enable_batch_seeds or eta_noise_seed_delta > 0): - sampler_noises = [[] for _ in range(p.sampler.number_of_needed_noises(p))] - else: - sampler_noises = None - - for i, seed in enumerate(seeds): - noise_shape = shape if seed_resize_from_h <= 0 or seed_resize_from_w <= 0 else (shape[0], seed_resize_from_h//8, seed_resize_from_w//8) - - subnoise = None - if subseeds is not None and subseed_strength != 0: - subseed = 0 if i >= len(subseeds) else subseeds[i] - - subnoise = devices.randn(subseed, noise_shape) - - # randn results depend on device; gpu and cpu get different results for same seed; - # the way I see it, it's better to do this on CPU, so that everyone gets same result; - # but the original script had it like this, so I do not dare change it for now because - # it will break everyone's seeds. - noise = devices.randn(seed, noise_shape) - - if subnoise is not None: - noise = slerp(subseed_strength, noise, subnoise) - - if noise_shape != shape: - x = devices.randn(seed, shape) - dx = (shape[2] - noise_shape[2]) // 2 - dy = (shape[1] - noise_shape[1]) // 2 - w = noise_shape[2] if dx >= 0 else noise_shape[2] + 2 * dx - h = noise_shape[1] if dy >= 0 else noise_shape[1] + 2 * dy - tx = 0 if dx < 0 else dx - ty = 0 if dy < 0 else dy - dx = max(-dx, 0) - dy = max(-dy, 0) - - x[:, ty:ty+h, tx:tx+w] = noise[:, dy:dy+h, dx:dx+w] - noise = x - - if sampler_noises is not None: - cnt = p.sampler.number_of_needed_noises(p) - - if eta_noise_seed_delta > 0: - devices.manual_seed(seed + eta_noise_seed_delta) - - for j in range(cnt): - sampler_noises[j].append(devices.randn_without_seed(tuple(noise_shape))) - - xs.append(noise) - - if sampler_noises is not None: - p.sampler.sampler_noises = [torch.stack(n).to(shared.device) for n in sampler_noises] - - x = torch.stack(xs).to(shared.device) - return x + g = rng.ImageRNG(shape, seeds, subseeds=subseeds, subseed_strength=subseed_strength, seed_resize_from_h=seed_resize_from_h, seed_resize_from_w=seed_resize_from_w) + return g.next() class DecodedSamples(list): @@ -769,6 +697,8 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed: p.seeds = p.all_seeds[n * p.batch_size:(n + 1) * p.batch_size] p.subseeds = p.all_subseeds[n * p.batch_size:(n + 1) * p.batch_size] + p.rng = rng.ImageRNG((opt_C, p.height // opt_f, p.width // opt_f), p.seeds, subseeds=p.subseeds, subseed_strength=p.subseed_strength, seed_resize_from_h=p.seed_resize_from_h, seed_resize_from_w=p.seed_resize_from_w) + if p.scripts is not None: p.scripts.before_process_batch(p, batch_number=n, prompts=p.prompts, seeds=p.seeds, subseeds=p.subseeds) @@ -1072,7 +1002,7 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing): def sample(self, conditioning, unconditional_conditioning, seeds, subseeds, subseed_strength, prompts): self.sampler = sd_samplers.create_sampler(self.sampler_name, self.sd_model) - x = create_random_tensors([opt_C, self.height // opt_f, self.width // opt_f], seeds=seeds, subseeds=subseeds, subseed_strength=self.subseed_strength, seed_resize_from_h=self.seed_resize_from_h, seed_resize_from_w=self.seed_resize_from_w, p=self) + x = self.rng.next() samples = self.sampler.sample(self, x, conditioning, unconditional_conditioning, image_conditioning=self.txt2img_image_conditioning(x)) del x @@ -1160,7 +1090,8 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing): 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] - noise = create_random_tensors(samples.shape[1:], seeds=seeds, subseeds=subseeds, subseed_strength=subseed_strength, p=self) + self.rng = rng.ImageRNG(samples.shape[1:], self.seeds, subseeds=self.subseeds, subseed_strength=self.subseed_strength, seed_resize_from_h=self.seed_resize_from_h, seed_resize_from_w=self.seed_resize_from_w) + noise = self.rng.next() # GC now before running the next img2img to prevent running out of memory devices.torch_gc() @@ -1418,7 +1349,7 @@ class StableDiffusionProcessingImg2Img(StableDiffusionProcessing): self.image_conditioning = self.img2img_image_conditioning(image, self.init_latent, image_mask) def sample(self, conditioning, unconditional_conditioning, seeds, subseeds, subseed_strength, prompts): - x = create_random_tensors([opt_C, self.height // opt_f, self.width // opt_f], seeds=seeds, subseeds=subseeds, subseed_strength=self.subseed_strength, seed_resize_from_h=self.seed_resize_from_h, seed_resize_from_w=self.seed_resize_from_w, p=self) + x = self.rng.next() if self.initial_noise_multiplier != 1.0: self.extra_generation_params["Noise multiplier"] = self.initial_noise_multiplier -- cgit v1.2.1 From 259805947e4e567abcf6a4be20fe520d456c251f Mon Sep 17 00:00:00 2001 From: catboxanon <122327233+catboxanon@users.noreply.github.com> Date: Wed, 9 Aug 2023 14:24:16 -0400 Subject: Add slerp import for extension backwards compat --- modules/processing.py | 1 + 1 file changed, 1 insertion(+) (limited to 'modules/processing.py') diff --git a/modules/processing.py b/modules/processing.py index 2df5e8c7..6961b7b1 100644 --- a/modules/processing.py +++ b/modules/processing.py @@ -15,6 +15,7 @@ from typing import Any, Dict, List import modules.sd_hijack from modules import devices, prompt_parser, masking, sd_samplers, lowvram, generation_parameters_copypaste, extra_networks, sd_vae_approx, scripts, sd_samplers_common, sd_unet, errors, rng +from modules.rng import slerp # noqa: F401 from modules.sd_hijack import model_hijack from modules.sd_samplers_common import images_tensor_to_samples, decode_first_stage, approximation_indexes from modules.shared import opts, cmd_opts, state -- cgit v1.2.1 From 9199b6b7ebe96cdf09571ba874a103e8ed8c90ef Mon Sep 17 00:00:00 2001 From: AUTOMATIC1111 <16777216c@gmail.com> Date: Thu, 10 Aug 2023 11:20:46 +0300 Subject: add a custom UI element that combines accordion and checkbox rework hires fix UI to use accordion prevent bogus progress output in console when calculating hires fix dimensions --- modules/processing.py | 77 ++++++++++++++++++++++++++------------------------- 1 file changed, 40 insertions(+), 37 deletions(-) (limited to 'modules/processing.py') diff --git a/modules/processing.py b/modules/processing.py index 6961b7b1..7819644c 100644 --- a/modules/processing.py +++ b/modules/processing.py @@ -924,6 +924,45 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing): self.hr_c = None self.hr_uc = None + def calculate_target_resolution(self): + if opts.use_old_hires_fix_width_height and self.applied_old_hires_behavior_to != (self.width, self.height): + self.hr_resize_x = self.width + self.hr_resize_y = self.height + self.hr_upscale_to_x = self.width + self.hr_upscale_to_y = self.height + + self.width, self.height = old_hires_fix_first_pass_dimensions(self.width, self.height) + self.applied_old_hires_behavior_to = (self.width, self.height) + + if self.hr_resize_x == 0 and self.hr_resize_y == 0: + self.extra_generation_params["Hires upscale"] = self.hr_scale + self.hr_upscale_to_x = int(self.width * self.hr_scale) + self.hr_upscale_to_y = int(self.height * self.hr_scale) + else: + self.extra_generation_params["Hires resize"] = f"{self.hr_resize_x}x{self.hr_resize_y}" + + if self.hr_resize_y == 0: + self.hr_upscale_to_x = self.hr_resize_x + self.hr_upscale_to_y = self.hr_resize_x * self.height // self.width + elif self.hr_resize_x == 0: + self.hr_upscale_to_x = self.hr_resize_y * self.width // self.height + self.hr_upscale_to_y = self.hr_resize_y + else: + target_w = self.hr_resize_x + target_h = self.hr_resize_y + src_ratio = self.width / self.height + dst_ratio = self.hr_resize_x / self.hr_resize_y + + if src_ratio < dst_ratio: + self.hr_upscale_to_x = self.hr_resize_x + self.hr_upscale_to_y = self.hr_resize_x * self.height // self.width + else: + self.hr_upscale_to_x = self.hr_resize_y * self.width // self.height + self.hr_upscale_to_y = self.hr_resize_y + + self.truncate_x = (self.hr_upscale_to_x - target_w) // opt_f + self.truncate_y = (self.hr_upscale_to_y - target_h) // opt_f + def init(self, all_prompts, all_seeds, all_subseeds): if self.enable_hr: if self.hr_checkpoint_name: @@ -948,43 +987,7 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing): if not any(x.name == self.hr_upscaler for x in shared.sd_upscalers): raise Exception(f"could not find upscaler named {self.hr_upscaler}") - if opts.use_old_hires_fix_width_height and self.applied_old_hires_behavior_to != (self.width, self.height): - self.hr_resize_x = self.width - self.hr_resize_y = self.height - self.hr_upscale_to_x = self.width - self.hr_upscale_to_y = self.height - - self.width, self.height = old_hires_fix_first_pass_dimensions(self.width, self.height) - self.applied_old_hires_behavior_to = (self.width, self.height) - - if self.hr_resize_x == 0 and self.hr_resize_y == 0: - self.extra_generation_params["Hires upscale"] = self.hr_scale - self.hr_upscale_to_x = int(self.width * self.hr_scale) - self.hr_upscale_to_y = int(self.height * self.hr_scale) - else: - self.extra_generation_params["Hires resize"] = f"{self.hr_resize_x}x{self.hr_resize_y}" - - if self.hr_resize_y == 0: - self.hr_upscale_to_x = self.hr_resize_x - self.hr_upscale_to_y = self.hr_resize_x * self.height // self.width - elif self.hr_resize_x == 0: - self.hr_upscale_to_x = self.hr_resize_y * self.width // self.height - self.hr_upscale_to_y = self.hr_resize_y - else: - target_w = self.hr_resize_x - target_h = self.hr_resize_y - src_ratio = self.width / self.height - dst_ratio = self.hr_resize_x / self.hr_resize_y - - if src_ratio < dst_ratio: - self.hr_upscale_to_x = self.hr_resize_x - self.hr_upscale_to_y = self.hr_resize_x * self.height // self.width - else: - self.hr_upscale_to_x = self.hr_resize_y * self.width // self.height - self.hr_upscale_to_y = self.hr_resize_y - - self.truncate_x = (self.hr_upscale_to_x - target_w) // opt_f - self.truncate_y = (self.hr_upscale_to_y - target_h) // opt_f + self.calculate_target_resolution() if not state.processing_has_refined_job_count: if state.job_count == -1: -- cgit v1.2.1 From 33446acf47a8c3e0c0964782189562df3c4bcf4f Mon Sep 17 00:00:00 2001 From: AUTOMATIC1111 <16777216c@gmail.com> Date: Thu, 10 Aug 2023 12:41:41 +0300 Subject: face restoration and tiling moved to settings - use "Options in main UI" setting if you want them back --- modules/processing.py | 11 +++++++++-- 1 file changed, 9 insertions(+), 2 deletions(-) (limited to 'modules/processing.py') diff --git a/modules/processing.py b/modules/processing.py index 7819644c..68a8f1c6 100644 --- a/modules/processing.py +++ b/modules/processing.py @@ -111,7 +111,7 @@ class StableDiffusionProcessing: cached_uc = [None, None] cached_c = [None, None] - 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, batch_size: int = 1, n_iter: int = 1, steps: int = 50, cfg_scale: float = 7.0, width: int = 512, height: int = 512, 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, ddim_discretize: str = None, s_min_uncond: float = 0.0, s_churn: float = 0.0, s_tmax: float = None, s_tmin: float = 0.0, s_noise: float = None, override_settings: Dict[str, Any] = None, override_settings_restore_afterwards: bool = True, sampler_index: int = None, script_args: list = None): + 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, batch_size: int = 1, n_iter: int = 1, steps: int = 50, cfg_scale: float = 7.0, width: int = 512, height: int = 512, restore_faces: bool = None, tiling: bool = None, 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, ddim_discretize: str = None, s_min_uncond: float = 0.0, s_churn: float = 0.0, s_tmax: float = None, s_tmin: float = 0.0, s_noise: float = None, override_settings: Dict[str, Any] = None, override_settings_restore_afterwards: bool = True, sampler_index: int = None, script_args: list = None): if sampler_index is not None: print("sampler_index argument for StableDiffusionProcessing does not do anything; use sampler_name", file=sys.stderr) @@ -564,7 +564,7 @@ def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments=None, iter "CFG scale": p.cfg_scale, "Image CFG scale": getattr(p, 'image_cfg_scale', None), "Seed": p.all_seeds[0] if use_main_prompt else all_seeds[index], - "Face restoration": (opts.face_restoration_model if p.restore_faces else None), + "Face restoration": opts.face_restoration_model if p.restore_faces else None, "Size": f"{p.width}x{p.height}", "Model hash": getattr(p, 'sd_model_hash', None if not opts.add_model_hash_to_info or not shared.sd_model.sd_model_hash else shared.sd_model.sd_model_hash), "Model": (None if not opts.add_model_name_to_info else shared.sd_model.sd_checkpoint_info.name_for_extra), @@ -580,6 +580,7 @@ def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments=None, iter "Init image hash": getattr(p, 'init_img_hash', None), "RNG": opts.randn_source if opts.randn_source != "GPU" and opts.randn_source != "NV" else None, "NGMS": None if p.s_min_uncond == 0 else p.s_min_uncond, + "Tiling": "True" if p.tiling else None, **p.extra_generation_params, "Version": program_version() if opts.add_version_to_infotext else None, "User": p.user if opts.add_user_name_to_info else None, @@ -645,6 +646,12 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed: seed = get_fixed_seed(p.seed) subseed = get_fixed_seed(p.subseed) + if p.restore_faces is None: + p.restore_faces = opts.face_restoration + + if p.tiling is None: + p.tiling = opts.tiling + modules.sd_hijack.model_hijack.apply_circular(p.tiling) modules.sd_hijack.model_hijack.clear_comments() -- cgit v1.2.1 From 1b3093fe3aedb20aa8d505ceeea7900ac592e6fe Mon Sep 17 00:00:00 2001 From: AUTOMATIC1111 <16777216c@gmail.com> Date: Thu, 10 Aug 2023 15:58:53 +0300 Subject: fix --use-textbox-seed --- modules/processing.py | 12 ++++++++++-- 1 file changed, 10 insertions(+), 2 deletions(-) (limited to 'modules/processing.py') diff --git a/modules/processing.py b/modules/processing.py index 68a8f1c6..f06c374a 100644 --- a/modules/processing.py +++ b/modules/processing.py @@ -521,7 +521,15 @@ def decode_latent_batch(model, batch, target_device=None, check_for_nans=False): def get_fixed_seed(seed): - if seed is None or seed == '' or seed == -1: + if seed == '' or seed is None: + seed = -1 + elif isinstance(seed, str): + try: + seed = int(seed) + except Exception: + seed = -1 + + if seed == -1: return int(random.randrange(4294967294)) return seed @@ -728,7 +736,7 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed: # strength, which is saved as "Model Strength: 1.0" in the infotext if n == 0: with open(os.path.join(paths.data_path, "params.txt"), "w", encoding="utf8") as file: - processed = Processed(p, [], p.seed, "") + processed = Processed(p, []) file.write(processed.infotext(p, 0)) p.setup_conds() -- cgit v1.2.1 From 9d78d317ae492db59ebf8b31fda9a049f6c9bd14 Mon Sep 17 00:00:00 2001 From: AUTOMATIC1111 <16777216c@gmail.com> Date: Thu, 10 Aug 2023 16:22:10 +0300 Subject: add VAE to infotext --- modules/processing.py | 2 ++ 1 file changed, 2 insertions(+) (limited to 'modules/processing.py') diff --git a/modules/processing.py b/modules/processing.py index f06c374a..44d47e8c 100644 --- a/modules/processing.py +++ b/modules/processing.py @@ -576,6 +576,8 @@ def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments=None, iter "Size": f"{p.width}x{p.height}", "Model hash": getattr(p, 'sd_model_hash', None if not opts.add_model_hash_to_info or not shared.sd_model.sd_model_hash else shared.sd_model.sd_model_hash), "Model": (None if not opts.add_model_name_to_info else shared.sd_model.sd_checkpoint_info.name_for_extra), + "VAE hash": sd_vae.get_loaded_vae_hash() if opts.add_model_hash_to_info else None, + "VAE": sd_vae.get_loaded_vae_name() if opts.add_model_name_to_info else None, "Variation seed": (None if p.subseed_strength == 0 else (p.all_subseeds[0] if use_main_prompt else all_subseeds[index])), "Variation seed strength": (None if p.subseed_strength == 0 else p.subseed_strength), "Seed resize from": (None if p.seed_resize_from_w <= 0 or p.seed_resize_from_h <= 0 else f"{p.seed_resize_from_w}x{p.seed_resize_from_h}"), -- cgit v1.2.1