From 539a69860bafe1c922029722a50462f3ef0db5e4 Mon Sep 17 00:00:00 2001 From: hitomi Date: Sat, 25 Mar 2023 13:58:53 -0700 Subject: fix `--realesrgan-models-path` not working --- modules/realesrgan_model.py | 14 ++++++++++++-- 1 file changed, 12 insertions(+), 2 deletions(-) (limited to 'modules/realesrgan_model.py') diff --git a/modules/realesrgan_model.py b/modules/realesrgan_model.py index aad4a629..d6079433 100644 --- a/modules/realesrgan_model.py +++ b/modules/realesrgan_model.py @@ -9,7 +9,7 @@ from realesrgan import RealESRGANer from modules.upscaler import Upscaler, UpscalerData from modules.shared import cmd_opts, opts - +from modules import modelloader class UpscalerRealESRGAN(Upscaler): def __init__(self, path): @@ -23,7 +23,15 @@ class UpscalerRealESRGAN(Upscaler): self.enable = True self.scalers = [] scalers = self.load_models(path) + + local_model_paths = self.find_models(ext_filter=[".pth"]) for scaler in scalers: + if scaler.local_data_path.startswith("http"): + filename = modelloader.friendly_name(scaler.local_data_path) + local = next(iter([local_model for local_model in local_model_paths if local_model.endswith(filename + '.pth')]), None) + if local: + scaler.local_data_path = local + if scaler.name in opts.realesrgan_enabled_models: self.scalers.append(scaler) @@ -64,7 +72,9 @@ class UpscalerRealESRGAN(Upscaler): print(f"Unable to find model info: {path}") return None - info.local_data_path = load_file_from_url(url=info.data_path, model_dir=self.model_path, progress=True) + if info.local_data_path.startswith("http"): + info.local_data_path = load_file_from_url(url=info.data_path, model_dir=self.model_path, progress=True) + return info except Exception as e: print(f"Error making Real-ESRGAN models list: {e}", file=sys.stderr) -- cgit v1.2.3 From 3ba6c3c83c0983a025c7bddc08bb7f49481b3cbb Mon Sep 17 00:00:00 2001 From: Aarni Koskela Date: Tue, 9 May 2023 22:17:58 +0300 Subject: Fix up string formatting/concatenation to f-strings where feasible --- modules/api/api.py | 22 ++++++------ modules/call_queue.py | 5 +-- modules/esrgan_model.py | 11 +++--- modules/esrgan_model_arch.py | 16 ++++----- modules/extra_networks_hypernet.py | 3 +- modules/generation_parameters_copypaste.py | 4 +-- modules/hashes.py | 4 +-- modules/images.py | 8 ++--- modules/interrogate.py | 4 +-- modules/models/diffusion/ddpm_edit.py | 4 +-- modules/models/diffusion/uni_pc/uni_pc.py | 4 +-- modules/ngrok.py | 4 +-- modules/paths.py | 2 +- modules/processing.py | 13 ++++++-- modules/progress.py | 3 +- modules/realesrgan_model.py | 8 ++--- modules/scripts.py | 5 +-- modules/sd_hijack_clip_old.py | 3 +- modules/sd_hijack_unet.py | 2 +- modules/sd_models.py | 4 +-- modules/sd_models_config.py | 2 +- modules/sd_samplers_kdiffusion.py | 2 +- modules/sd_vae.py | 2 +- modules/styles.py | 2 +- modules/textual_inversion/autocrop.py | 6 ++-- modules/textual_inversion/dataset.py | 2 +- modules/textual_inversion/preprocess.py | 6 ++-- modules/textual_inversion/textual_inversion.py | 12 +++---- modules/ui.py | 46 +++++++++++++------------- modules/ui_extensions.py | 3 +- modules/ui_extra_networks.py | 4 ++- scripts/custom_code.py | 2 +- scripts/loopback.py | 2 +- scripts/xyz_grid.py | 2 +- 34 files changed, 121 insertions(+), 101 deletions(-) (limited to 'modules/realesrgan_model.py') diff --git a/modules/api/api.py b/modules/api/api.py index cdbdce32..9bb95dfd 100644 --- a/modules/api/api.py +++ b/modules/api/api.py @@ -570,20 +570,20 @@ class Api: filename = create_embedding(**args) # create empty embedding sd_hijack.model_hijack.embedding_db.load_textual_inversion_embeddings() # reload embeddings so new one can be immediately used shared.state.end() - return CreateResponse(info = "create embedding filename: {filename}".format(filename = filename)) + return CreateResponse(info=f"create embedding filename: {filename}") except AssertionError as e: shared.state.end() - return TrainResponse(info = "create embedding error: {error}".format(error = e)) + return TrainResponse(info=f"create embedding error: {e}") def create_hypernetwork(self, args: dict): try: shared.state.begin() filename = create_hypernetwork(**args) # create empty embedding shared.state.end() - return CreateResponse(info = "create hypernetwork filename: {filename}".format(filename = filename)) + return CreateResponse(info=f"create hypernetwork filename: {filename}") except AssertionError as e: shared.state.end() - return TrainResponse(info = "create hypernetwork error: {error}".format(error = e)) + return TrainResponse(info=f"create hypernetwork error: {e}") def preprocess(self, args: dict): try: @@ -593,13 +593,13 @@ class Api: return PreprocessResponse(info = 'preprocess complete') except KeyError as e: shared.state.end() - return PreprocessResponse(info = "preprocess error: invalid token: {error}".format(error = e)) + return PreprocessResponse(info=f"preprocess error: invalid token: {e}") except AssertionError as e: shared.state.end() - return PreprocessResponse(info = "preprocess error: {error}".format(error = e)) + return PreprocessResponse(info=f"preprocess error: {e}") except FileNotFoundError as e: shared.state.end() - return PreprocessResponse(info = 'preprocess error: {error}'.format(error = e)) + return PreprocessResponse(info=f'preprocess error: {e}') def train_embedding(self, args: dict): try: @@ -617,10 +617,10 @@ class Api: if not apply_optimizations: sd_hijack.apply_optimizations() shared.state.end() - return TrainResponse(info = "train embedding complete: filename: {filename} error: {error}".format(filename = filename, error = error)) + return TrainResponse(info=f"train embedding complete: filename: {filename} error: {error}") except AssertionError as msg: shared.state.end() - return TrainResponse(info = "train embedding error: {msg}".format(msg = msg)) + return TrainResponse(info=f"train embedding error: {msg}") def train_hypernetwork(self, args: dict): try: @@ -641,10 +641,10 @@ class Api: if not apply_optimizations: sd_hijack.apply_optimizations() shared.state.end() - return TrainResponse(info="train embedding complete: filename: {filename} error: {error}".format(filename=filename, error=error)) + return TrainResponse(info=f"train embedding complete: filename: {filename} error: {error}") except AssertionError as msg: shared.state.end() - return TrainResponse(info="train embedding error: {error}".format(error=error)) + return TrainResponse(info=f"train embedding error: {error}") def get_memory(self): try: diff --git a/modules/call_queue.py b/modules/call_queue.py index 1829f3a6..447bb764 100644 --- a/modules/call_queue.py +++ b/modules/call_queue.py @@ -60,7 +60,7 @@ def wrap_gradio_call(func, extra_outputs=None, add_stats=False): max_debug_str_len = 131072 # (1024*1024)/8 print("Error completing request", file=sys.stderr) - argStr = f"Arguments: {str(args)} {str(kwargs)}" + argStr = f"Arguments: {args} {kwargs}" print(argStr[:max_debug_str_len], file=sys.stderr) if len(argStr) > max_debug_str_len: print(f"(Argument list truncated at {max_debug_str_len}/{len(argStr)} characters)", file=sys.stderr) @@ -73,7 +73,8 @@ def wrap_gradio_call(func, extra_outputs=None, add_stats=False): if extra_outputs_array is None: extra_outputs_array = [None, ''] - res = extra_outputs_array + [f"
{html.escape(type(e).__name__+': '+str(e))}
"] + error_message = f'{type(e).__name__}: {e}' + res = extra_outputs_array + [f"
{html.escape(error_message)}
"] shared.state.skipped = False shared.state.interrupted = False diff --git a/modules/esrgan_model.py b/modules/esrgan_model.py index 9a9c38f1..f4369257 100644 --- a/modules/esrgan_model.py +++ b/modules/esrgan_model.py @@ -156,13 +156,16 @@ class UpscalerESRGAN(Upscaler): def load_model(self, path: str): if "http" in path: - filename = load_file_from_url(url=self.model_url, model_dir=self.model_path, - file_name="%s.pth" % self.model_name, - progress=True) + filename = load_file_from_url( + url=self.model_url, + model_dir=self.model_path, + file_name=f"{self.model_name}.pth", + progress=True, + ) else: filename = path if not os.path.exists(filename) or filename is None: - print("Unable to load %s from %s" % (self.model_path, filename)) + print(f"Unable to load {self.model_path} from {filename}") return None state_dict = torch.load(filename, map_location='cpu' if devices.device_esrgan.type == 'mps' else None) diff --git a/modules/esrgan_model_arch.py b/modules/esrgan_model_arch.py index 1b52b0f5..6071fea7 100644 --- a/modules/esrgan_model_arch.py +++ b/modules/esrgan_model_arch.py @@ -38,7 +38,7 @@ class RRDBNet(nn.Module): elif upsample_mode == 'pixelshuffle': upsample_block = pixelshuffle_block else: - raise NotImplementedError('upsample mode [{:s}] is not found'.format(upsample_mode)) + raise NotImplementedError(f'upsample mode [{upsample_mode}] is not found') if upscale == 3: upsampler = upsample_block(nf, nf, 3, act_type=act_type, convtype=convtype) else: @@ -261,10 +261,10 @@ class Upsample(nn.Module): def extra_repr(self): if self.scale_factor is not None: - info = 'scale_factor=' + str(self.scale_factor) + info = f'scale_factor={self.scale_factor}' else: - info = 'size=' + str(self.size) - info += ', mode=' + self.mode + info = f'size={self.size}' + info += f', mode={self.mode}' return info @@ -350,7 +350,7 @@ def act(act_type, inplace=True, neg_slope=0.2, n_prelu=1, beta=1.0): elif act_type == 'sigmoid': # [0, 1] range output layer = nn.Sigmoid() else: - raise NotImplementedError('activation layer [{:s}] is not found'.format(act_type)) + raise NotImplementedError(f'activation layer [{act_type}] is not found') return layer @@ -372,7 +372,7 @@ def norm(norm_type, nc): elif norm_type == 'none': def norm_layer(x): return Identity() else: - raise NotImplementedError('normalization layer [{:s}] is not found'.format(norm_type)) + raise NotImplementedError(f'normalization layer [{norm_type}] is not found') return layer @@ -388,7 +388,7 @@ def pad(pad_type, padding): elif pad_type == 'zero': layer = nn.ZeroPad2d(padding) else: - raise NotImplementedError('padding layer [{:s}] is not implemented'.format(pad_type)) + raise NotImplementedError(f'padding layer [{pad_type}] is not implemented') return layer @@ -432,7 +432,7 @@ def conv_block(in_nc, out_nc, kernel_size, stride=1, dilation=1, groups=1, bias= pad_type='zero', norm_type=None, act_type='relu', mode='CNA', convtype='Conv2D', spectral_norm=False): """ Conv layer with padding, normalization, activation """ - assert mode in ['CNA', 'NAC', 'CNAC'], 'Wrong conv mode [{:s}]'.format(mode) + assert mode in ['CNA', 'NAC', 'CNAC'], f'Wrong conv mode [{mode}]' padding = get_valid_padding(kernel_size, dilation) p = pad(pad_type, padding) if pad_type and pad_type != 'zero' else None padding = padding if pad_type == 'zero' else 0 diff --git a/modules/extra_networks_hypernet.py b/modules/extra_networks_hypernet.py index 33d100dd..04f27c9f 100644 --- a/modules/extra_networks_hypernet.py +++ b/modules/extra_networks_hypernet.py @@ -10,7 +10,8 @@ class ExtraNetworkHypernet(extra_networks.ExtraNetwork): additional = shared.opts.sd_hypernetwork if additional != "None" and additional in shared.hypernetworks and len([x for x in params_list if x.items[0] == additional]) == 0: - p.all_prompts = [x + f"" for x in p.all_prompts] + hypernet_prompt_text = f"" + p.all_prompts = [f"{prompt}{hypernet_prompt_text}" for prompt in p.all_prompts] params_list.append(extra_networks.ExtraNetworkParams(items=[additional, shared.opts.extra_networks_default_multiplier])) names = [] diff --git a/modules/generation_parameters_copypaste.py b/modules/generation_parameters_copypaste.py index 78248ed2..fe8b18b2 100644 --- a/modules/generation_parameters_copypaste.py +++ b/modules/generation_parameters_copypaste.py @@ -269,8 +269,8 @@ Steps: 20, Sampler: Euler a, CFG scale: 7, Seed: 965400086, Size: 512x512, Model v = v[1:-1] if v[0] == '"' and v[-1] == '"' else v m = re_imagesize.match(v) if m is not None: - res[k+"-1"] = m.group(1) - res[k+"-2"] = m.group(2) + res[f"{k}-1"] = m.group(1) + res[f"{k}-2"] = m.group(2) else: res[k] = v diff --git a/modules/hashes.py b/modules/hashes.py index 83272a07..032120f4 100644 --- a/modules/hashes.py +++ b/modules/hashes.py @@ -13,7 +13,7 @@ cache_data = None def dump_cache(): - with filelock.FileLock(cache_filename+".lock"): + with filelock.FileLock(f"{cache_filename}.lock"): with open(cache_filename, "w", encoding="utf8") as file: json.dump(cache_data, file, indent=4) @@ -22,7 +22,7 @@ def cache(subsection): global cache_data if cache_data is None: - with filelock.FileLock(cache_filename+".lock"): + with filelock.FileLock(f"{cache_filename}.lock"): if not os.path.isfile(cache_filename): cache_data = {} else: diff --git a/modules/images.py b/modules/images.py index 6ceb7c7c..a41965ab 100644 --- a/modules/images.py +++ b/modules/images.py @@ -467,7 +467,7 @@ def get_next_sequence_number(path, basename): """ result = -1 if basename != '': - basename = basename + "-" + basename = f"{basename}-" prefix_length = len(basename) for p in os.listdir(path): @@ -536,7 +536,7 @@ def save_image(image, path, basename, seed=None, prompt=None, extension='png', i add_number = opts.save_images_add_number or file_decoration == '' if file_decoration != "" and add_number: - file_decoration = "-" + file_decoration + file_decoration = f"-{file_decoration}" file_decoration = namegen.apply(file_decoration) + suffix @@ -566,7 +566,7 @@ def save_image(image, path, basename, seed=None, prompt=None, extension='png', i def _atomically_save_image(image_to_save, filename_without_extension, extension): # save image with .tmp extension to avoid race condition when another process detects new image in the directory - temp_file_path = filename_without_extension + ".tmp" + temp_file_path = f"{filename_without_extension}.tmp" image_format = Image.registered_extensions()[extension] if extension.lower() == '.png': @@ -626,7 +626,7 @@ def save_image(image, path, basename, seed=None, prompt=None, extension='png', i if opts.save_txt and info is not None: txt_fullfn = f"{fullfn_without_extension}.txt" with open(txt_fullfn, "w", encoding="utf8") as file: - file.write(info + "\n") + file.write(f"{info}\n") else: txt_fullfn = None diff --git a/modules/interrogate.py b/modules/interrogate.py index e1665708..9f7d657f 100644 --- a/modules/interrogate.py +++ b/modules/interrogate.py @@ -28,7 +28,7 @@ def category_types(): def download_default_clip_interrogate_categories(content_dir): print("Downloading CLIP categories...") - tmpdir = content_dir + "_tmp" + tmpdir = f"{content_dir}_tmp" category_types = ["artists", "flavors", "mediums", "movements"] try: @@ -214,7 +214,7 @@ class InterrogateModels: if shared.opts.interrogate_return_ranks: res += f", ({match}:{score/100:.3f})" else: - res += ", " + match + res += f", {match}" except Exception: print("Error interrogating", file=sys.stderr) diff --git a/modules/models/diffusion/ddpm_edit.py b/modules/models/diffusion/ddpm_edit.py index f3d49c44..f880bc3c 100644 --- a/modules/models/diffusion/ddpm_edit.py +++ b/modules/models/diffusion/ddpm_edit.py @@ -223,7 +223,7 @@ class DDPM(pl.LightningModule): for k in keys: for ik in ignore_keys: if k.startswith(ik): - print("Deleting key {} from state_dict.".format(k)) + print(f"Deleting key {k} from state_dict.") del sd[k] missing, unexpected = self.load_state_dict(sd, strict=False) if not only_model else self.model.load_state_dict( sd, strict=False) @@ -386,7 +386,7 @@ class DDPM(pl.LightningModule): _, loss_dict_no_ema = self.shared_step(batch) with self.ema_scope(): _, loss_dict_ema = self.shared_step(batch) - loss_dict_ema = {key + '_ema': loss_dict_ema[key] for key in loss_dict_ema} + loss_dict_ema = {f"{key}_ema": loss_dict_ema[key] for key in loss_dict_ema} self.log_dict(loss_dict_no_ema, prog_bar=False, logger=True, on_step=False, on_epoch=True) self.log_dict(loss_dict_ema, prog_bar=False, logger=True, on_step=False, on_epoch=True) diff --git a/modules/models/diffusion/uni_pc/uni_pc.py b/modules/models/diffusion/uni_pc/uni_pc.py index eb5f4e76..11b330bc 100644 --- a/modules/models/diffusion/uni_pc/uni_pc.py +++ b/modules/models/diffusion/uni_pc/uni_pc.py @@ -94,7 +94,7 @@ class NoiseScheduleVP: """ if schedule not in ['discrete', 'linear', 'cosine']: - raise ValueError("Unsupported noise schedule {}. The schedule needs to be 'discrete' or 'linear' or 'cosine'".format(schedule)) + raise ValueError(f"Unsupported noise schedule {schedule}. The schedule needs to be 'discrete' or 'linear' or 'cosine'") self.schedule = schedule if schedule == 'discrete': @@ -469,7 +469,7 @@ class UniPC: t = torch.linspace(t_T**(1. / t_order), t_0**(1. / t_order), N + 1).pow(t_order).to(device) return t else: - raise ValueError("Unsupported skip_type {}, need to be 'logSNR' or 'time_uniform' or 'time_quadratic'".format(skip_type)) + raise ValueError(f"Unsupported skip_type {skip_type}, need to be 'logSNR' or 'time_uniform' or 'time_quadratic'") def get_orders_and_timesteps_for_singlestep_solver(self, steps, order, skip_type, t_T, t_0, device): """ diff --git a/modules/ngrok.py b/modules/ngrok.py index 1ad7989b..7a7b4b26 100644 --- a/modules/ngrok.py +++ b/modules/ngrok.py @@ -7,8 +7,8 @@ def connect(token, port, region): else: if ':' in token: # token = authtoken:username:password - account = token.split(':')[1] + ':' + token.split(':')[-1] - token = token.split(':')[0] + token, username, password = token.split(':', 2) + account = f"{username}:{password}" config = conf.PyngrokConfig( auth_token=token, region=region diff --git a/modules/paths.py b/modules/paths.py index 0e1e00e7..acf1894b 100644 --- a/modules/paths.py +++ b/modules/paths.py @@ -16,7 +16,7 @@ for possible_sd_path in possible_sd_paths: sd_path = os.path.abspath(possible_sd_path) break -assert sd_path is not None, "Couldn't find Stable Diffusion in any of: " + str(possible_sd_paths) +assert sd_path is not None, f"Couldn't find Stable Diffusion in any of: {possible_sd_paths}" path_dirs = [ (sd_path, 'ldm', 'Stable Diffusion', []), diff --git a/modules/processing.py b/modules/processing.py index e786791a..1a76e552 100644 --- a/modules/processing.py +++ b/modules/processing.py @@ -500,7 +500,7 @@ 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]) - negative_prompt_text = "\nNegative prompt: " + p.all_negative_prompts[index] if p.all_negative_prompts[index] else "" + negative_prompt_text = f"\nNegative prompt: {p.all_negative_prompts[index]}" if p.all_negative_prompts[index] else "" return f"{all_prompts[index]}{negative_prompt_text}\n{generation_params_text}".strip() @@ -780,7 +780,16 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed: devices.torch_gc() - res = Processed(p, output_images, p.all_seeds[0], infotext(), comments="".join(["\n\n" + x for x in comments]), subseed=p.all_subseeds[0], index_of_first_image=index_of_first_image, infotexts=infotexts) + res = Processed( + p, + images_list=output_images, + seed=p.all_seeds[0], + info=infotext(), + comments="".join(f"\n\n{comment}" for comment in comments), + subseed=p.all_subseeds[0], + index_of_first_image=index_of_first_image, + infotexts=infotexts, + ) if p.scripts is not None: p.scripts.postprocess(p, res) diff --git a/modules/progress.py b/modules/progress.py index 5655346b..948e6f00 100644 --- a/modules/progress.py +++ b/modules/progress.py @@ -96,7 +96,8 @@ def progressapi(req: ProgressRequest): if image is not None: buffered = io.BytesIO() image.save(buffered, format="png") - live_preview = 'data:image/png;base64,' + base64.b64encode(buffered.getvalue()).decode("ascii") + base64_image = base64.b64encode(buffered.getvalue()).decode('ascii') + live_preview = f"data:image/png;base64,{base64_image}" id_live_preview = shared.state.id_live_preview else: live_preview = None diff --git a/modules/realesrgan_model.py b/modules/realesrgan_model.py index d6079433..efd7fca5 100644 --- a/modules/realesrgan_model.py +++ b/modules/realesrgan_model.py @@ -28,9 +28,9 @@ class UpscalerRealESRGAN(Upscaler): for scaler in scalers: if scaler.local_data_path.startswith("http"): filename = modelloader.friendly_name(scaler.local_data_path) - local = next(iter([local_model for local_model in local_model_paths if local_model.endswith(filename + '.pth')]), None) - if local: - scaler.local_data_path = local + local_model_candidates = [local_model for local_model in local_model_paths if local_model.endswith(f"{filename}.pth")] + if local_model_candidates: + scaler.local_data_path = local_model_candidates[0] if scaler.name in opts.realesrgan_enabled_models: self.scalers.append(scaler) @@ -47,7 +47,7 @@ class UpscalerRealESRGAN(Upscaler): info = self.load_model(path) if not os.path.exists(info.local_data_path): - print("Unable to load RealESRGAN model: %s" % info.name) + print(f"Unable to load RealESRGAN model: {info.name}") return img upsampler = RealESRGANer( diff --git a/modules/scripts.py b/modules/scripts.py index 4d0bbd66..d945b89f 100644 --- a/modules/scripts.py +++ b/modules/scripts.py @@ -163,7 +163,8 @@ class Script: """helper function to generate id for a HTML element, constructs final id out of script name, tab and user-supplied item_id""" need_tabname = self.show(True) == self.show(False) - tabname = ('img2img' if self.is_img2img else 'txt2txt') + "_" if need_tabname else "" + tabkind = 'img2img' if self.is_img2img else 'txt2txt' + tabname = f"{tabkind}_" if need_tabname else "" title = re.sub(r'[^a-z_0-9]', '', re.sub(r'\s', '_', self.title().lower())) return f'script_{tabname}{title}_{item_id}' @@ -526,7 +527,7 @@ def add_classes_to_gradio_component(comp): this adds gradio-* to the component for css styling (ie gradio-button to gr.Button), as well as some others """ - comp.elem_classes = ["gradio-" + comp.get_block_name(), *(comp.elem_classes or [])] + comp.elem_classes = [f"gradio-{comp.get_block_name()}", *(comp.elem_classes or [])] if getattr(comp, 'multiselect', False): comp.elem_classes.append('multiselect') diff --git a/modules/sd_hijack_clip_old.py b/modules/sd_hijack_clip_old.py index 6d9fbbe6..a3476e95 100644 --- a/modules/sd_hijack_clip_old.py +++ b/modules/sd_hijack_clip_old.py @@ -75,7 +75,8 @@ def forward_old(self: sd_hijack_clip.FrozenCLIPEmbedderWithCustomWordsBase, text self.hijack.comments += hijack_comments if len(used_custom_terms) > 0: - self.hijack.comments.append("Used embeddings: " + ", ".join([f'{word} [{checksum}]' for word, checksum in used_custom_terms])) + embedding_names = ", ".join(f"{word} [{checksum}]" for word, checksum in used_custom_terms) + self.hijack.comments.append(f"Used embeddings: {embedding_names}") self.hijack.fixes = hijack_fixes return self.process_tokens(remade_batch_tokens, batch_multipliers) diff --git a/modules/sd_hijack_unet.py b/modules/sd_hijack_unet.py index 15858263..ca1daf45 100644 --- a/modules/sd_hijack_unet.py +++ b/modules/sd_hijack_unet.py @@ -18,7 +18,7 @@ class TorchHijackForUnet: if hasattr(torch, item): return getattr(torch, item) - raise AttributeError("'{}' object has no attribute '{}'".format(type(self).__name__, item)) + raise AttributeError(f"'{type(self).__name__}' object has no attribute '{item}'") def cat(self, tensors, *args, **kwargs): if len(tensors) == 2: diff --git a/modules/sd_models.py b/modules/sd_models.py index 59adc7cc..36f643e1 100644 --- a/modules/sd_models.py +++ b/modules/sd_models.py @@ -47,7 +47,7 @@ class CheckpointInfo: self.model_name = os.path.splitext(name.replace("/", "_").replace("\\", "_"))[0] self.hash = model_hash(filename) - self.sha256 = hashes.sha256_from_cache(self.filename, "checkpoint/" + name) + self.sha256 = hashes.sha256_from_cache(self.filename, f"checkpoint/{name}") self.shorthash = self.sha256[0:10] if self.sha256 else None self.title = name if self.shorthash is None else f'{name} [{self.shorthash}]' @@ -69,7 +69,7 @@ class CheckpointInfo: checkpoint_alisases[id] = self def calculate_shorthash(self): - self.sha256 = hashes.sha256(self.filename, "checkpoint/" + self.name) + self.sha256 = hashes.sha256(self.filename, f"checkpoint/{self.name}") if self.sha256 is None: return diff --git a/modules/sd_models_config.py b/modules/sd_models_config.py index 9398f528..7a79925a 100644 --- a/modules/sd_models_config.py +++ b/modules/sd_models_config.py @@ -111,7 +111,7 @@ def find_checkpoint_config_near_filename(info): if info is None: return None - config = os.path.splitext(info.filename)[0] + ".yaml" + config = f"{os.path.splitext(info.filename)[0]}.yaml" if os.path.exists(config): return config diff --git a/modules/sd_samplers_kdiffusion.py b/modules/sd_samplers_kdiffusion.py index eb98e599..0fc9f456 100644 --- a/modules/sd_samplers_kdiffusion.py +++ b/modules/sd_samplers_kdiffusion.py @@ -198,7 +198,7 @@ class TorchHijack: if hasattr(torch, item): return getattr(torch, item) - raise AttributeError("'{}' object has no attribute '{}'".format(type(self).__name__, item)) + raise AttributeError(f"'{type(self).__name__}' object has no attribute '{item}'") def randn_like(self, x): if self.sampler_noises: diff --git a/modules/sd_vae.py b/modules/sd_vae.py index 9b00f76e..521e485a 100644 --- a/modules/sd_vae.py +++ b/modules/sd_vae.py @@ -89,7 +89,7 @@ def refresh_vae_list(): def find_vae_near_checkpoint(checkpoint_file): checkpoint_path = os.path.splitext(checkpoint_file)[0] - for vae_location in [checkpoint_path + ".vae.pt", checkpoint_path + ".vae.ckpt", checkpoint_path + ".vae.safetensors"]: + for vae_location in [f"{checkpoint_path}.vae.pt", f"{checkpoint_path}.vae.ckpt", f"{checkpoint_path}.vae.safetensors"]: if os.path.isfile(vae_location): return vae_location diff --git a/modules/styles.py b/modules/styles.py index 9ed85991..11642075 100644 --- a/modules/styles.py +++ b/modules/styles.py @@ -74,7 +74,7 @@ class StyleDatabase: def save_styles(self, path: str) -> None: # Always keep a backup file around if os.path.exists(path): - shutil.copy(path, path + ".bak") + shutil.copy(path, f"{path}.bak") fd = os.open(path, os.O_RDWR|os.O_CREAT) with os.fdopen(fd, "w", encoding="utf-8-sig", newline='') as file: diff --git a/modules/textual_inversion/autocrop.py b/modules/textual_inversion/autocrop.py index 68e1103c..ba1bdcd4 100644 --- a/modules/textual_inversion/autocrop.py +++ b/modules/textual_inversion/autocrop.py @@ -111,7 +111,7 @@ def focal_point(im, settings): if corner_centroid is not None: color = BLUE box = corner_centroid.bounding(max_size * corner_centroid.weight) - d.text((box[0], box[1]-15), "Edge: %.02f" % corner_centroid.weight, fill=color) + d.text((box[0], box[1]-15), f"Edge: {corner_centroid.weight:.02f}", fill=color) d.ellipse(box, outline=color) if len(corner_points) > 1: for f in corner_points: @@ -119,7 +119,7 @@ def focal_point(im, settings): if entropy_centroid is not None: color = "#ff0" box = entropy_centroid.bounding(max_size * entropy_centroid.weight) - d.text((box[0], box[1]-15), "Entropy: %.02f" % entropy_centroid.weight, fill=color) + d.text((box[0], box[1]-15), f"Entropy: {entropy_centroid.weight:.02f}", fill=color) d.ellipse(box, outline=color) if len(entropy_points) > 1: for f in entropy_points: @@ -127,7 +127,7 @@ def focal_point(im, settings): if face_centroid is not None: color = RED box = face_centroid.bounding(max_size * face_centroid.weight) - d.text((box[0], box[1]-15), "Face: %.02f" % face_centroid.weight, fill=color) + d.text((box[0], box[1]-15), f"Face: {face_centroid.weight:.02f}", fill=color) d.ellipse(box, outline=color) if len(face_points) > 1: for f in face_points: diff --git a/modules/textual_inversion/dataset.py b/modules/textual_inversion/dataset.py index af9fbcf2..41610e03 100644 --- a/modules/textual_inversion/dataset.py +++ b/modules/textual_inversion/dataset.py @@ -72,7 +72,7 @@ class PersonalizedBase(Dataset): except Exception: continue - text_filename = os.path.splitext(path)[0] + ".txt" + text_filename = f"{os.path.splitext(path)[0]}.txt" filename = os.path.basename(path) if os.path.exists(text_filename): diff --git a/modules/textual_inversion/preprocess.py b/modules/textual_inversion/preprocess.py index 4a29151d..da0bcb26 100644 --- a/modules/textual_inversion/preprocess.py +++ b/modules/textual_inversion/preprocess.py @@ -63,9 +63,9 @@ def save_pic_with_caption(image, index, params: PreprocessParams, existing_capti image.save(os.path.join(params.dstdir, f"{basename}.png")) if params.preprocess_txt_action == 'prepend' and existing_caption: - caption = existing_caption + ' ' + caption + caption = f"{existing_caption} {caption}" elif params.preprocess_txt_action == 'append' and existing_caption: - caption = caption + ' ' + existing_caption + caption = f"{caption} {existing_caption}" elif params.preprocess_txt_action == 'copy' and existing_caption: caption = existing_caption @@ -174,7 +174,7 @@ def preprocess_work(process_src, process_dst, process_width, process_height, pre params.src = filename existing_caption = None - existing_caption_filename = os.path.splitext(filename)[0] + '.txt' + existing_caption_filename = f"{os.path.splitext(filename)[0]}.txt" if os.path.exists(existing_caption_filename): with open(existing_caption_filename, 'r', encoding="utf8") as file: existing_caption = file.read() diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py index 379df243..4368eb63 100644 --- a/modules/textual_inversion/textual_inversion.py +++ b/modules/textual_inversion/textual_inversion.py @@ -69,7 +69,7 @@ class Embedding: 'hash': self.checksum(), 'optimizer_state_dict': self.optimizer_state_dict, } - torch.save(optimizer_saved_dict, filename + '.optim') + torch.save(optimizer_saved_dict, f"{filename}.optim") def checksum(self): if self.cached_checksum is not None: @@ -437,8 +437,8 @@ def train_embedding(id_task, embedding_name, learn_rate, batch_size, gradient_st optimizer = torch.optim.AdamW([embedding.vec], lr=scheduler.learn_rate, weight_decay=0.0) if shared.opts.save_optimizer_state: optimizer_state_dict = None - if os.path.exists(filename + '.optim'): - optimizer_saved_dict = torch.load(filename + '.optim', map_location='cpu') + if os.path.exists(f"{filename}.optim"): + optimizer_saved_dict = torch.load(f"{filename}.optim", map_location='cpu') if embedding.checksum() == optimizer_saved_dict.get('hash', None): optimizer_state_dict = optimizer_saved_dict.get('optimizer_state_dict', None) @@ -599,7 +599,7 @@ def train_embedding(id_task, embedding_name, learn_rate, batch_size, gradient_st data = torch.load(last_saved_file) info.add_text("sd-ti-embedding", embedding_to_b64(data)) - title = "<{}>".format(data.get('name', '???')) + title = f"<{data.get('name', '???')}>" try: vectorSize = list(data['string_to_param'].values())[0].shape[0] @@ -608,8 +608,8 @@ def train_embedding(id_task, embedding_name, learn_rate, batch_size, gradient_st checkpoint = sd_models.select_checkpoint() footer_left = checkpoint.model_name - footer_mid = '[{}]'.format(checkpoint.shorthash) - footer_right = '{}v {}s'.format(vectorSize, steps_done) + footer_mid = f'[{checkpoint.shorthash}]' + footer_right = f'{vectorSize}v {steps_done}s' captioned_image = caption_image_overlay(image, title, footer_left, footer_mid, footer_right) captioned_image = insert_image_data_embed(captioned_image, data) diff --git a/modules/ui.py b/modules/ui.py index 34b2aaff..d02f6e82 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -101,7 +101,7 @@ def visit(x, func, path=""): for c in x.children: visit(c, func, path) elif x.label is not None: - func(path + "/" + str(x.label), x) + func(f"{path}/{x.label}", x) def add_style(name: str, prompt: str, negative_prompt: str): @@ -166,7 +166,7 @@ def process_interrogate(interrogation_function, mode, ii_input_dir, ii_output_di img = Image.open(image) filename = os.path.basename(image) left, _ = os.path.splitext(filename) - print(interrogation_function(img), file=open(os.path.join(ii_output_dir, left + ".txt"), 'a')) + print(interrogation_function(img), file=open(os.path.join(ii_output_dir, f"{left}.txt"), 'a')) return [gr.update(), None] @@ -182,29 +182,29 @@ def interrogate_deepbooru(image): def create_seed_inputs(target_interface): - with FormRow(elem_id=target_interface + '_seed_row', variant="compact"): - seed = (gr.Textbox if cmd_opts.use_textbox_seed else gr.Number)(label='Seed', value=-1, elem_id=target_interface + '_seed') + with FormRow(elem_id=f"{target_interface}_seed_row", variant="compact"): + seed = (gr.Textbox if cmd_opts.use_textbox_seed else gr.Number)(label='Seed', value=-1, elem_id=f"{target_interface}_seed") seed.style(container=False) - random_seed = ToolButton(random_symbol, elem_id=target_interface + '_random_seed', label='Random seed') - reuse_seed = ToolButton(reuse_symbol, elem_id=target_interface + '_reuse_seed', label='Reuse seed') + random_seed = ToolButton(random_symbol, elem_id=f"{target_interface}_random_seed", label='Random seed') + reuse_seed = ToolButton(reuse_symbol, elem_id=f"{target_interface}_reuse_seed", label='Reuse seed') - seed_checkbox = gr.Checkbox(label='Extra', elem_id=target_interface + '_subseed_show', value=False) + seed_checkbox = gr.Checkbox(label='Extra', elem_id=f"{target_interface}_subseed_show", value=False) # Components to show/hide based on the 'Extra' checkbox seed_extras = [] - with FormRow(visible=False, elem_id=target_interface + '_subseed_row') as seed_extra_row_1: + with FormRow(visible=False, elem_id=f"{target_interface}_subseed_row") as seed_extra_row_1: seed_extras.append(seed_extra_row_1) - subseed = gr.Number(label='Variation seed', value=-1, elem_id=target_interface + '_subseed') + subseed = gr.Number(label='Variation seed', value=-1, elem_id=f"{target_interface}_subseed") subseed.style(container=False) - random_subseed = ToolButton(random_symbol, elem_id=target_interface + '_random_subseed') - reuse_subseed = ToolButton(reuse_symbol, elem_id=target_interface + '_reuse_subseed') - subseed_strength = gr.Slider(label='Variation strength', value=0.0, minimum=0, maximum=1, step=0.01, elem_id=target_interface + '_subseed_strength') + random_subseed = ToolButton(random_symbol, elem_id=f"{target_interface}_random_subseed") + reuse_subseed = ToolButton(reuse_symbol, elem_id=f"{target_interface}_reuse_subseed") + subseed_strength = gr.Slider(label='Variation strength', value=0.0, minimum=0, maximum=1, step=0.01, elem_id=f"{target_interface}_subseed_strength") with FormRow(visible=False) as seed_extra_row_2: seed_extras.append(seed_extra_row_2) - seed_resize_from_w = gr.Slider(minimum=0, maximum=2048, step=8, label="Resize seed from width", value=0, elem_id=target_interface + '_seed_resize_from_w') - seed_resize_from_h = gr.Slider(minimum=0, maximum=2048, step=8, label="Resize seed from height", value=0, elem_id=target_interface + '_seed_resize_from_h') + seed_resize_from_w = gr.Slider(minimum=0, maximum=2048, step=8, label="Resize seed from width", value=0, elem_id=f"{target_interface}_seed_resize_from_w") + seed_resize_from_h = gr.Slider(minimum=0, maximum=2048, step=8, label="Resize seed from height", value=0, elem_id=f"{target_interface}_seed_resize_from_h") random_seed.click(fn=lambda: -1, show_progress=False, inputs=[], outputs=[seed]) random_subseed.click(fn=lambda: -1, show_progress=False, inputs=[], outputs=[subseed]) @@ -765,7 +765,7 @@ def create_ui(): ) button.click( fn=lambda: None, - _js="switch_to_"+name.replace(" ", "_"), + _js=f"switch_to_{name.replace(' ', '_')}", inputs=[], outputs=[], ) @@ -1462,18 +1462,18 @@ def create_ui(): elif t == bool: comp = gr.Checkbox else: - raise Exception(f'bad options item type: {str(t)} for key {key}') + raise Exception(f'bad options item type: {t} for key {key}') - elem_id = "setting_"+key + elem_id = f"setting_{key}" if info.refresh is not None: if is_quicksettings: res = comp(label=info.label, value=fun(), elem_id=elem_id, **(args or {})) - create_refresh_button(res, info.refresh, info.component_args, "refresh_" + key) + create_refresh_button(res, info.refresh, info.component_args, f"refresh_{key}") else: with FormRow(): res = comp(label=info.label, value=fun(), elem_id=elem_id, **(args or {})) - create_refresh_button(res, info.refresh, info.component_args, "refresh_" + key) + create_refresh_button(res, info.refresh, info.component_args, f"refresh_{key}") else: res = comp(label=info.label, value=fun(), elem_id=elem_id, **(args or {})) @@ -1545,7 +1545,7 @@ def create_ui(): current_tab.__exit__() gr.Group() - current_tab = gr.TabItem(elem_id="settings_{}".format(elem_id), label=text) + current_tab = gr.TabItem(elem_id=f"settings_{elem_id}", label=text) current_tab.__enter__() current_row = gr.Column(variant='compact') current_row.__enter__() @@ -1664,7 +1664,7 @@ def create_ui(): for interface, label, ifid in interfaces: if label in shared.opts.hidden_tabs: continue - with gr.TabItem(label, id=ifid, elem_id='tab_' + ifid): + with gr.TabItem(label, id=ifid, elem_id=f"tab_{ifid}"): interface.render() if os.path.exists(os.path.join(script_path, "notification.mp3")): @@ -1771,10 +1771,10 @@ def create_ui(): def loadsave(path, x): def apply_field(obj, field, condition=None, init_field=None): - key = path + "/" + field + key = f"{path}/{field}" if getattr(obj, 'custom_script_source', None) is not None: - key = 'customscript/' + obj.custom_script_source + '/' + key + key = f"customscript/{obj.custom_script_source}/{key}" if getattr(obj, 'do_not_save_to_config', False): return diff --git a/modules/ui_extensions.py b/modules/ui_extensions.py index 99ac8756..d9faf85a 100644 --- a/modules/ui_extensions.py +++ b/modules/ui_extensions.py @@ -61,7 +61,8 @@ def save_config_state(name): if not name: name = "Config" current_config_state["name"] = name - filename = os.path.join(config_states_dir, datetime.now().strftime("%Y_%m_%d-%H_%M_%S") + "_" + name + ".json") + timestamp = datetime.now().strftime('%Y_%m_%d-%H_%M_%S') + filename = os.path.join(config_states_dir, f"{timestamp}_{name}.json") print(f"Saving backup of webui/extension state to {filename}.") with open(filename, "w", encoding="utf-8") as f: json.dump(current_config_state, f) diff --git a/modules/ui_extra_networks.py b/modules/ui_extra_networks.py index 86c05a55..8c3dea56 100644 --- a/modules/ui_extra_networks.py +++ b/modules/ui_extra_networks.py @@ -69,7 +69,9 @@ class ExtraNetworksPage: pass def link_preview(self, filename): - return "./sd_extra_networks/thumb?filename=" + urllib.parse.quote(filename.replace('\\', '/')) + "&mtime=" + str(os.path.getmtime(filename)) + quoted_filename = urllib.parse.quote(filename.replace('\\', '/')) + mtime = os.path.getmtime(filename) + return f"./sd_extra_networks/thumb?filename={quoted_filename}&mtime={mtime}" def search_terms_from_path(self, filename, possible_directories=None): abspath = os.path.abspath(filename) diff --git a/scripts/custom_code.py b/scripts/custom_code.py index 4071d86d..f36a3675 100644 --- a/scripts/custom_code.py +++ b/scripts/custom_code.py @@ -77,7 +77,7 @@ return process_images(p) module.display = display indent = " " * indent_level - indented = code.replace('\n', '\n' + indent) + indented = code.replace('\n', f"\n{indent}") body = f"""def __webuitemp__(): {indent}{indented} __webuitemp__()""" diff --git a/scripts/loopback.py b/scripts/loopback.py index d3065fe6..ad6609be 100644 --- a/scripts/loopback.py +++ b/scripts/loopback.py @@ -84,7 +84,7 @@ class Script(scripts.Script): p.color_corrections = initial_color_corrections if append_interrogation != "None": - p.prompt = original_prompt + ", " if original_prompt != "" else "" + p.prompt = f"{original_prompt}, " if original_prompt else "" if append_interrogation == "CLIP": p.prompt += shared.interrogator.interrogate(p.init_images[0]) elif append_interrogation == "DeepBooru": diff --git a/scripts/xyz_grid.py b/scripts/xyz_grid.py index 01d97791..a725d74a 100644 --- a/scripts/xyz_grid.py +++ b/scripts/xyz_grid.py @@ -439,7 +439,7 @@ class Script(scripts.Script): z_type.change(fn=select_axis, inputs=[z_type,z_values_dropdown], outputs=[fill_z_button,z_values,z_values_dropdown]) def get_dropdown_update_from_params(axis,params): - val_key = axis + " Values" + val_key = f"{axis} Values" vals = params.get(val_key,"") valslist = [x.strip() for x in chain.from_iterable(csv.reader(StringIO(vals))) if x] return gr.update(value = valslist) -- cgit v1.2.3 From 762265eab58cdb8f2d6398769bab43d8b8db0075 Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Wed, 10 May 2023 07:52:45 +0300 Subject: autofixes from ruff --- extensions-builtin/LDSR/ldsr_model_arch.py | 1 - extensions-builtin/LDSR/sd_hijack_autoencoder.py | 2 +- modules/api/api.py | 14 +++++++------- modules/extras.py | 4 ++-- modules/images.py | 4 ++-- modules/img2img.py | 2 +- modules/prompt_parser.py | 2 +- modules/realesrgan_model.py | 2 +- modules/sd_disable_initialization.py | 2 +- modules/sd_hijack.py | 4 ++-- modules/sd_hijack_ip2p.py | 2 +- modules/sd_hijack_optimizations.py | 1 - modules/sd_models.py | 6 +++--- modules/textual_inversion/textual_inversion.py | 2 +- modules/ui.py | 13 ++++++------- modules/ui_extensions.py | 2 +- modules/ui_extra_networks.py | 2 +- pyproject.toml | 4 +++- scripts/outpainting_mk_2.py | 2 +- scripts/postprocessing_upscale.py | 6 +++--- scripts/xyz_grid.py | 2 +- webui.py | 2 +- 22 files changed, 40 insertions(+), 41 deletions(-) (limited to 'modules/realesrgan_model.py') diff --git a/extensions-builtin/LDSR/ldsr_model_arch.py b/extensions-builtin/LDSR/ldsr_model_arch.py index bc11cc6e..2339de7f 100644 --- a/extensions-builtin/LDSR/ldsr_model_arch.py +++ b/extensions-builtin/LDSR/ldsr_model_arch.py @@ -110,7 +110,6 @@ class LDSR: diffusion_steps = int(steps) eta = 1.0 - down_sample_method = 'Lanczos' gc.collect() if torch.cuda.is_available: diff --git a/extensions-builtin/LDSR/sd_hijack_autoencoder.py b/extensions-builtin/LDSR/sd_hijack_autoencoder.py index 8e03c7f8..db2231dd 100644 --- a/extensions-builtin/LDSR/sd_hijack_autoencoder.py +++ b/extensions-builtin/LDSR/sd_hijack_autoencoder.py @@ -165,7 +165,7 @@ class VQModel(pl.LightningModule): def validation_step(self, batch, batch_idx): log_dict = self._validation_step(batch, batch_idx) with self.ema_scope(): - log_dict_ema = self._validation_step(batch, batch_idx, suffix="_ema") + self._validation_step(batch, batch_idx, suffix="_ema") return log_dict def _validation_step(self, batch, batch_idx, suffix=""): diff --git a/modules/api/api.py b/modules/api/api.py index 9bb95dfd..d47c39fc 100644 --- a/modules/api/api.py +++ b/modules/api/api.py @@ -60,7 +60,7 @@ def decode_base64_to_image(encoding): try: image = Image.open(BytesIO(base64.b64decode(encoding))) return image - except Exception as err: + except Exception: raise HTTPException(status_code=500, detail="Invalid encoded image") def encode_pil_to_base64(image): @@ -264,11 +264,11 @@ class Api: if request.alwayson_scripts and (len(request.alwayson_scripts) > 0): for alwayson_script_name in request.alwayson_scripts.keys(): alwayson_script = self.get_script(alwayson_script_name, script_runner) - if alwayson_script == None: + if alwayson_script is None: raise HTTPException(status_code=422, detail=f"always on script {alwayson_script_name} not found") # Selectable script in always on script param check - if alwayson_script.alwayson == False: - raise HTTPException(status_code=422, detail=f"Cannot have a selectable script in the always on scripts params") + if alwayson_script.alwayson is False: + raise HTTPException(status_code=422, detail="Cannot have a selectable script in the always on scripts params") # always on script with no arg should always run so you don't really need to add them to the requests if "args" in request.alwayson_scripts[alwayson_script_name]: # min between arg length in scriptrunner and arg length in the request @@ -310,7 +310,7 @@ class Api: p.outpath_samples = opts.outdir_txt2img_samples shared.state.begin() - if selectable_scripts != None: + if selectable_scripts is not None: p.script_args = script_args processed = scripts.scripts_txt2img.run(p, *p.script_args) # Need to pass args as list here else: @@ -367,7 +367,7 @@ class Api: p.outpath_samples = opts.outdir_img2img_samples shared.state.begin() - if selectable_scripts != None: + if selectable_scripts is not None: p.script_args = script_args processed = scripts.scripts_img2img.run(p, *p.script_args) # Need to pass args as list here else: @@ -642,7 +642,7 @@ class Api: sd_hijack.apply_optimizations() shared.state.end() return TrainResponse(info=f"train embedding complete: filename: {filename} error: {error}") - except AssertionError as msg: + except AssertionError: shared.state.end() return TrainResponse(info=f"train embedding error: {error}") diff --git a/modules/extras.py b/modules/extras.py index ff4e9c4e..eb4f0b42 100644 --- a/modules/extras.py +++ b/modules/extras.py @@ -136,14 +136,14 @@ def run_modelmerger(id_task, primary_model_name, secondary_model_name, tertiary_ result_is_instruct_pix2pix_model = False if theta_func2: - shared.state.textinfo = f"Loading B" + shared.state.textinfo = "Loading B" print(f"Loading {secondary_model_info.filename}...") theta_1 = sd_models.read_state_dict(secondary_model_info.filename, map_location='cpu') else: theta_1 = None if theta_func1: - shared.state.textinfo = f"Loading C" + shared.state.textinfo = "Loading C" print(f"Loading {tertiary_model_info.filename}...") theta_2 = sd_models.read_state_dict(tertiary_model_info.filename, map_location='cpu') diff --git a/modules/images.py b/modules/images.py index a41965ab..3d5d76cc 100644 --- a/modules/images.py +++ b/modules/images.py @@ -409,13 +409,13 @@ class FilenameGenerator: time_format = args[0] if len(args) > 0 and args[0] != "" else self.default_time_format try: time_zone = pytz.timezone(args[1]) if len(args) > 1 else None - except pytz.exceptions.UnknownTimeZoneError as _: + except pytz.exceptions.UnknownTimeZoneError: time_zone = None time_zone_time = time_datetime.astimezone(time_zone) try: formatted_time = time_zone_time.strftime(time_format) - except (ValueError, TypeError) as _: + except (ValueError, TypeError): formatted_time = time_zone_time.strftime(self.default_time_format) return sanitize_filename_part(formatted_time, replace_spaces=False) diff --git a/modules/img2img.py b/modules/img2img.py index 9fc3a698..cdae301a 100644 --- a/modules/img2img.py +++ b/modules/img2img.py @@ -59,7 +59,7 @@ def process_batch(p, input_dir, output_dir, inpaint_mask_dir, args): # try to find corresponding mask for an image using simple filename matching mask_image_path = os.path.join(inpaint_mask_dir, os.path.basename(image)) # if not found use first one ("same mask for all images" use-case) - if not mask_image_path in inpaint_masks: + if mask_image_path not in inpaint_masks: mask_image_path = inpaint_masks[0] mask_image = Image.open(mask_image_path) p.image_mask = mask_image diff --git a/modules/prompt_parser.py b/modules/prompt_parser.py index 69665372..e084e948 100644 --- a/modules/prompt_parser.py +++ b/modules/prompt_parser.py @@ -92,7 +92,7 @@ def get_learned_conditioning_prompt_schedules(prompts, steps): def get_schedule(prompt): try: tree = schedule_parser.parse(prompt) - except lark.exceptions.LarkError as e: + except lark.exceptions.LarkError: if 0: import traceback traceback.print_exc() diff --git a/modules/realesrgan_model.py b/modules/realesrgan_model.py index efd7fca5..9ec1adf2 100644 --- a/modules/realesrgan_model.py +++ b/modules/realesrgan_model.py @@ -134,6 +134,6 @@ def get_realesrgan_models(scaler): ), ] return models - except Exception as e: + except Exception: print("Error making Real-ESRGAN models list:", file=sys.stderr) print(traceback.format_exc(), file=sys.stderr) diff --git a/modules/sd_disable_initialization.py b/modules/sd_disable_initialization.py index c4a09d15..9fc89dc6 100644 --- a/modules/sd_disable_initialization.py +++ b/modules/sd_disable_initialization.py @@ -61,7 +61,7 @@ class DisableInitialization: if res is None: res = original(url, *args, local_files_only=False, **kwargs) return res - except Exception as e: + except Exception: return original(url, *args, local_files_only=False, **kwargs) def transformers_utils_hub_get_from_cache(url, *args, local_files_only=False, **kwargs): diff --git a/modules/sd_hijack.py b/modules/sd_hijack.py index f4bb0266..d8135211 100644 --- a/modules/sd_hijack.py +++ b/modules/sd_hijack.py @@ -118,7 +118,7 @@ def weighted_forward(sd_model, x, c, w, *args, **kwargs): try: #Delete temporary weights if appended del sd_model._custom_loss_weight - except AttributeError as e: + except AttributeError: pass #If we have an old loss function, reset the loss function to the original one @@ -133,7 +133,7 @@ def apply_weighted_forward(sd_model): def undo_weighted_forward(sd_model): try: del sd_model.weighted_forward - except AttributeError as e: + except AttributeError: pass diff --git a/modules/sd_hijack_ip2p.py b/modules/sd_hijack_ip2p.py index 3c727d3b..41ed54a2 100644 --- a/modules/sd_hijack_ip2p.py +++ b/modules/sd_hijack_ip2p.py @@ -10,4 +10,4 @@ def should_hijack_ip2p(checkpoint_info): ckpt_basename = os.path.basename(checkpoint_info.filename).lower() cfg_basename = os.path.basename(sd_models_config.find_checkpoint_config_near_filename(checkpoint_info)).lower() - return "pix2pix" in ckpt_basename and not "pix2pix" in cfg_basename + return "pix2pix" in ckpt_basename and "pix2pix" not in cfg_basename diff --git a/modules/sd_hijack_optimizations.py b/modules/sd_hijack_optimizations.py index f10865cd..b623d53d 100644 --- a/modules/sd_hijack_optimizations.py +++ b/modules/sd_hijack_optimizations.py @@ -296,7 +296,6 @@ def sub_quad_attention(q, k, v, q_chunk_size=1024, kv_chunk_size=None, kv_chunk_ if chunk_threshold_bytes is not None and qk_matmul_size_bytes <= chunk_threshold_bytes: # the big matmul fits into our memory limit; do everything in 1 chunk, # i.e. send it down the unchunked fast-path - query_chunk_size = q_tokens kv_chunk_size = k_tokens with devices.without_autocast(disable=q.dtype == v.dtype): diff --git a/modules/sd_models.py b/modules/sd_models.py index 36f643e1..11c1a344 100644 --- a/modules/sd_models.py +++ b/modules/sd_models.py @@ -239,7 +239,7 @@ def read_metadata_from_safetensors(filename): if isinstance(v, str) and v[0:1] == '{': try: res[k] = json.loads(v) - except Exception as e: + except Exception: pass return res @@ -467,7 +467,7 @@ def load_model(checkpoint_info=None, already_loaded_state_dict=None): try: with sd_disable_initialization.DisableInitialization(disable_clip=clip_is_included_into_sd): sd_model = instantiate_from_config(sd_config.model) - except Exception as e: + except Exception: pass if sd_model is None: @@ -544,7 +544,7 @@ def reload_model_weights(sd_model=None, info=None): try: load_model_weights(sd_model, checkpoint_info, state_dict, timer) - except Exception as e: + except Exception: print("Failed to load checkpoint, restoring previous") load_model_weights(sd_model, current_checkpoint_info, None, timer) raise diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py index 4368eb63..f753b75f 100644 --- a/modules/textual_inversion/textual_inversion.py +++ b/modules/textual_inversion/textual_inversion.py @@ -603,7 +603,7 @@ def train_embedding(id_task, embedding_name, learn_rate, batch_size, gradient_st try: vectorSize = list(data['string_to_param'].values())[0].shape[0] - except Exception as e: + except Exception: vectorSize = '?' checkpoint = sd_models.select_checkpoint() diff --git a/modules/ui.py b/modules/ui.py index d02f6e82..2171f3aa 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -246,7 +246,7 @@ def connect_reuse_seed(seed: gr.Number, reuse_seed: gr.Button, generation_info: all_seeds = gen_info.get('all_seeds', [-1]) res = all_seeds[index if 0 <= index < len(all_seeds) else 0] - except json.decoder.JSONDecodeError as e: + except json.decoder.JSONDecodeError: if gen_info_string != '': print("Error parsing JSON generation info:", file=sys.stderr) print(gen_info_string, file=sys.stderr) @@ -736,8 +736,8 @@ def create_ui(): with gr.TabItem('Batch', id='batch', elem_id="img2img_batch_tab") as tab_batch: hidden = '
Disabled when launched with --hide-ui-dir-config.' if shared.cmd_opts.hide_ui_dir_config else '' gr.HTML( - f"

Process images in a directory on the same machine where the server is running." + - f"
Use an empty output directory to save pictures normally instead of writing to the output directory." + + "

Process images in a directory on the same machine where the server is running." + + "
Use an empty output directory to save pictures normally instead of writing to the output directory." + f"
Add inpaint batch mask directory to enable inpaint batch processing." f"{hidden}

" ) @@ -746,7 +746,6 @@ def create_ui(): img2img_batch_inpaint_mask_dir = gr.Textbox(label="Inpaint batch mask directory (required for inpaint batch processing only)", **shared.hide_dirs, elem_id="img2img_batch_inpaint_mask_dir") img2img_tabs = [tab_img2img, tab_sketch, tab_inpaint, tab_inpaint_color, tab_inpaint_upload, tab_batch] - img2img_image_inputs = [init_img, sketch, init_img_with_mask, inpaint_color_sketch] for i, tab in enumerate(img2img_tabs): tab.select(fn=lambda tabnum=i: tabnum, inputs=[], outputs=[img2img_selected_tab]) @@ -1290,8 +1289,8 @@ def create_ui(): with gr.Column(elem_id='ti_gallery_container'): ti_output = gr.Text(elem_id="ti_output", value="", show_label=False) - ti_gallery = gr.Gallery(label='Output', show_label=False, elem_id='ti_gallery').style(columns=4) - ti_progress = gr.HTML(elem_id="ti_progress", value="") + gr.Gallery(label='Output', show_label=False, elem_id='ti_gallery').style(columns=4) + gr.HTML(elem_id="ti_progress", value="") ti_outcome = gr.HTML(elem_id="ti_error", value="") create_embedding.click( @@ -1668,7 +1667,7 @@ def create_ui(): interface.render() if os.path.exists(os.path.join(script_path, "notification.mp3")): - audio_notification = gr.Audio(interactive=False, value=os.path.join(script_path, "notification.mp3"), elem_id="audio_notification", visible=False) + gr.Audio(interactive=False, value=os.path.join(script_path, "notification.mp3"), elem_id="audio_notification", visible=False) footer = shared.html("footer.html") footer = footer.format(versions=versions_html()) diff --git a/modules/ui_extensions.py b/modules/ui_extensions.py index d9faf85a..ed70abe5 100644 --- a/modules/ui_extensions.py +++ b/modules/ui_extensions.py @@ -490,7 +490,7 @@ def create_ui(): config_states.list_config_states() with gr.Blocks(analytics_enabled=False) as ui: - with gr.Tabs(elem_id="tabs_extensions") as tabs: + with gr.Tabs(elem_id="tabs_extensions"): with gr.TabItem("Installed", id="installed"): with gr.Row(elem_id="extensions_installed_top"): diff --git a/modules/ui_extra_networks.py b/modules/ui_extra_networks.py index 8c3dea56..49e06289 100644 --- a/modules/ui_extra_networks.py +++ b/modules/ui_extra_networks.py @@ -263,7 +263,7 @@ def create_ui(container, button, tabname): ui.stored_extra_pages = pages_in_preferred_order(extra_pages.copy()) ui.tabname = tabname - with gr.Tabs(elem_id=tabname+"_extra_tabs") as tabs: + with gr.Tabs(elem_id=tabname+"_extra_tabs"): for page in ui.stored_extra_pages: page_id = page.title.lower().replace(" ", "_") diff --git a/pyproject.toml b/pyproject.toml index 9e9662ad..1e164abc 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -2,7 +2,9 @@ ignore = [ "E501", - "E731" + "E731", + "E402", # Module level import not at top of file + "F401" # Module imported but unused ] exclude = ["extensions"] diff --git a/scripts/outpainting_mk_2.py b/scripts/outpainting_mk_2.py index 670bb8ac..b10fed6c 100644 --- a/scripts/outpainting_mk_2.py +++ b/scripts/outpainting_mk_2.py @@ -72,7 +72,7 @@ def get_matched_noise(_np_src_image, np_mask_rgb, noise_q=1, color_variation=0.0 height = _np_src_image.shape[1] num_channels = _np_src_image.shape[2] - np_src_image = _np_src_image[:] * (1. - np_mask_rgb) + _np_src_image[:] * (1. - np_mask_rgb) np_mask_grey = (np.sum(np_mask_rgb, axis=2) / 3.) img_mask = np_mask_grey > 1e-6 ref_mask = np_mask_grey < 1e-3 diff --git a/scripts/postprocessing_upscale.py b/scripts/postprocessing_upscale.py index ef1186ac..edb70ac0 100644 --- a/scripts/postprocessing_upscale.py +++ b/scripts/postprocessing_upscale.py @@ -98,13 +98,13 @@ class ScriptPostprocessingUpscale(scripts_postprocessing.ScriptPostprocessing): assert upscaler2 or (upscaler_2_name is None), f'could not find upscaler named {upscaler_2_name}' upscaled_image = self.upscale(pp.image, pp.info, upscaler1, upscale_mode, upscale_by, upscale_to_width, upscale_to_height, upscale_crop) - pp.info[f"Postprocess upscaler"] = upscaler1.name + pp.info["Postprocess upscaler"] = upscaler1.name if upscaler2 and upscaler_2_visibility > 0: second_upscale = self.upscale(pp.image, pp.info, upscaler2, upscale_mode, upscale_by, upscale_to_width, upscale_to_height, upscale_crop) upscaled_image = Image.blend(upscaled_image, second_upscale, upscaler_2_visibility) - pp.info[f"Postprocess upscaler 2"] = upscaler2.name + pp.info["Postprocess upscaler 2"] = upscaler2.name pp.image = upscaled_image @@ -134,4 +134,4 @@ class ScriptPostprocessingUpscaleSimple(ScriptPostprocessingUpscale): assert upscaler1, f'could not find upscaler named {upscaler_name}' pp.image = self.upscale(pp.image, pp.info, upscaler1, 0, upscale_by, 0, 0, False) - pp.info[f"Postprocess upscaler"] = upscaler1.name + pp.info["Postprocess upscaler"] = upscaler1.name diff --git a/scripts/xyz_grid.py b/scripts/xyz_grid.py index a725d74a..2ff42ef8 100644 --- a/scripts/xyz_grid.py +++ b/scripts/xyz_grid.py @@ -316,7 +316,7 @@ def draw_xyz_grid(p, xs, ys, zs, x_labels, y_labels, z_labels, cell, draw_legend return Processed(p, []) z_count = len(zs) - sub_grids = [None] * z_count + for i in range(z_count): start_index = (i * len(xs) * len(ys)) + i end_index = start_index + len(xs) * len(ys) diff --git a/webui.py b/webui.py index 727ebd31..ec3d2aba 100644 --- a/webui.py +++ b/webui.py @@ -360,7 +360,7 @@ def webui(): if cmd_opts.subpath: redirector = FastAPI() redirector.get("/") - mounted_app = gradio.mount_gradio_app(redirector, shared.demo, path=f"/{cmd_opts.subpath}") + gradio.mount_gradio_app(redirector, shared.demo, path=f"/{cmd_opts.subpath}") wait_on_server(shared.demo) print('Restarting UI...') -- cgit v1.2.3 From 4b854806d98cf5ccd48e5cd99c172613da7937f0 Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Wed, 10 May 2023 09:02:23 +0300 Subject: F401 fixes for ruff --- extensions-builtin/LDSR/scripts/ldsr_model.py | 4 ++-- modules/cmd_args.py | 2 +- modules/deepbooru.py | 1 - modules/extensions.py | 2 +- modules/gfpgan_model.py | 2 +- modules/models/diffusion/uni_pc/__init__.py | 2 +- modules/paths.py | 4 ++-- modules/realesrgan_model.py | 6 +++--- modules/script_loading.py | 1 - modules/sd_hijack_inpainting.py | 2 +- modules/sd_models.py | 4 +--- modules/sd_samplers.py | 2 +- modules/shared.py | 2 +- modules/ui.py | 4 ++-- modules/upscaler.py | 2 +- pyproject.toml | 9 +++++---- webui.py | 8 ++++---- 17 files changed, 27 insertions(+), 30 deletions(-) (limited to 'modules/realesrgan_model.py') diff --git a/extensions-builtin/LDSR/scripts/ldsr_model.py b/extensions-builtin/LDSR/scripts/ldsr_model.py index e8dc083c..fbbe9005 100644 --- a/extensions-builtin/LDSR/scripts/ldsr_model.py +++ b/extensions-builtin/LDSR/scripts/ldsr_model.py @@ -7,8 +7,8 @@ from basicsr.utils.download_util import load_file_from_url from modules.upscaler import Upscaler, UpscalerData from ldsr_model_arch import LDSR from modules import shared, script_callbacks -import sd_hijack_autoencoder -import sd_hijack_ddpm_v1 +import sd_hijack_autoencoder # noqa: F401 +import sd_hijack_ddpm_v1 # noqa: F401 class UpscalerLDSR(Upscaler): diff --git a/modules/cmd_args.py b/modules/cmd_args.py index d906a571..e01ca655 100644 --- a/modules/cmd_args.py +++ b/modules/cmd_args.py @@ -1,6 +1,6 @@ import argparse import os -from modules.paths_internal import models_path, script_path, data_path, extensions_dir, extensions_builtin_dir, sd_default_config, sd_model_file +from modules.paths_internal import models_path, script_path, data_path, extensions_dir, extensions_builtin_dir, sd_default_config, sd_model_file # noqa: F401 parser = argparse.ArgumentParser() diff --git a/modules/deepbooru.py b/modules/deepbooru.py index 122fce7f..1c4554a2 100644 --- a/modules/deepbooru.py +++ b/modules/deepbooru.py @@ -2,7 +2,6 @@ import os import re import torch -from PIL import Image import numpy as np from modules import modelloader, paths, deepbooru_model, devices, images, shared diff --git a/modules/extensions.py b/modules/extensions.py index 829f8cd9..bc2c0450 100644 --- a/modules/extensions.py +++ b/modules/extensions.py @@ -6,7 +6,7 @@ import time import git from modules import shared -from modules.paths_internal import extensions_dir, extensions_builtin_dir, script_path +from modules.paths_internal import extensions_dir, extensions_builtin_dir, script_path # noqa: F401 extensions = [] diff --git a/modules/gfpgan_model.py b/modules/gfpgan_model.py index fbe6215a..0131dea4 100644 --- a/modules/gfpgan_model.py +++ b/modules/gfpgan_model.py @@ -78,7 +78,7 @@ def setup_model(dirname): try: from gfpgan import GFPGANer - from facexlib import detection, parsing + from facexlib import detection, parsing # noqa: F401 global user_path global have_gfpgan global gfpgan_constructor diff --git a/modules/models/diffusion/uni_pc/__init__.py b/modules/models/diffusion/uni_pc/__init__.py index e1265e3f..dbb35964 100644 --- a/modules/models/diffusion/uni_pc/__init__.py +++ b/modules/models/diffusion/uni_pc/__init__.py @@ -1 +1 @@ -from .sampler import UniPCSampler +from .sampler import UniPCSampler # noqa: F401 diff --git a/modules/paths.py b/modules/paths.py index acf1894b..5f6474c0 100644 --- a/modules/paths.py +++ b/modules/paths.py @@ -1,8 +1,8 @@ import os import sys -from modules.paths_internal import models_path, script_path, data_path, extensions_dir, extensions_builtin_dir +from modules.paths_internal import models_path, script_path, data_path, extensions_dir, extensions_builtin_dir # noqa: F401 -import modules.safe +import modules.safe # noqa: F401 # data_path = cmd_opts_pre.data diff --git a/modules/realesrgan_model.py b/modules/realesrgan_model.py index 9ec1adf2..c24d8dbb 100644 --- a/modules/realesrgan_model.py +++ b/modules/realesrgan_model.py @@ -17,9 +17,9 @@ class UpscalerRealESRGAN(Upscaler): self.user_path = path super().__init__() try: - from basicsr.archs.rrdbnet_arch import RRDBNet - from realesrgan import RealESRGANer - from realesrgan.archs.srvgg_arch import SRVGGNetCompact + from basicsr.archs.rrdbnet_arch import RRDBNet # noqa: F401 + from realesrgan import RealESRGANer # noqa: F401 + from realesrgan.archs.srvgg_arch import SRVGGNetCompact # noqa: F401 self.enable = True self.scalers = [] scalers = self.load_models(path) diff --git a/modules/script_loading.py b/modules/script_loading.py index a7d2203f..57b15862 100644 --- a/modules/script_loading.py +++ b/modules/script_loading.py @@ -2,7 +2,6 @@ import os import sys import traceback import importlib.util -from types import ModuleType def load_module(path): diff --git a/modules/sd_hijack_inpainting.py b/modules/sd_hijack_inpainting.py index 344d75c8..058575b7 100644 --- a/modules/sd_hijack_inpainting.py +++ b/modules/sd_hijack_inpainting.py @@ -4,7 +4,7 @@ import ldm.models.diffusion.ddpm import ldm.models.diffusion.ddim import ldm.models.diffusion.plms -from ldm.models.diffusion.ddim import DDIMSampler, noise_like +from ldm.models.diffusion.ddim import noise_like from ldm.models.diffusion.sampling_util import norm_thresholding diff --git a/modules/sd_models.py b/modules/sd_models.py index 1c09c709..d1e946a5 100644 --- a/modules/sd_models.py +++ b/modules/sd_models.py @@ -15,7 +15,6 @@ import ldm.modules.midas as midas from ldm.util import instantiate_from_config from modules import paths, shared, modelloader, devices, script_callbacks, sd_vae, sd_disable_initialization, errors, hashes, sd_models_config -from modules.paths import models_path from modules.sd_hijack_inpainting import do_inpainting_hijack from modules.timer import Timer @@ -87,8 +86,7 @@ class CheckpointInfo: try: # this silences the annoying "Some weights of the model checkpoint were not used when initializing..." message at start. - - from transformers import logging, CLIPModel + from transformers import logging, CLIPModel # noqa: F401 logging.set_verbosity_error() except Exception: diff --git a/modules/sd_samplers.py b/modules/sd_samplers.py index ff361f22..4f1bf21d 100644 --- a/modules/sd_samplers.py +++ b/modules/sd_samplers.py @@ -1,7 +1,7 @@ from modules import sd_samplers_compvis, sd_samplers_kdiffusion, shared # imports for functions that previously were here and are used by other modules -from modules.sd_samplers_common import samples_to_image_grid, sample_to_image +from modules.sd_samplers_common import samples_to_image_grid, sample_to_image # noqa: F401 all_samplers = [ *sd_samplers_kdiffusion.samplers_data_k_diffusion, diff --git a/modules/shared.py b/modules/shared.py index 44cd2c0c..7d70f041 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -12,7 +12,7 @@ import modules.memmon import modules.styles import modules.devices as devices from modules import localization, script_loading, errors, ui_components, shared_items, cmd_args -from modules.paths_internal import models_path, script_path, data_path, sd_configs_path, sd_default_config, sd_model_file, default_sd_model_file, extensions_dir, extensions_builtin_dir +from modules.paths_internal import models_path, script_path, data_path, sd_configs_path, sd_default_config, sd_model_file, default_sd_model_file, extensions_dir, extensions_builtin_dir # noqa: F401 from ldm.models.diffusion.ddpm import LatentDiffusion demo = None diff --git a/modules/ui.py b/modules/ui.py index f7e57593..782b569d 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -10,10 +10,10 @@ import gradio as gr import gradio.routes import gradio.utils import numpy as np -from PIL import Image, PngImagePlugin +from PIL import Image, PngImagePlugin # noqa: F401 from modules.call_queue import wrap_gradio_gpu_call, wrap_queued_call, wrap_gradio_call -from modules import sd_hijack, sd_models, localization, script_callbacks, ui_extensions, deepbooru, sd_vae, extra_networks, postprocessing, ui_components, ui_common, ui_postprocessing, progress +from modules import sd_hijack, sd_models, localization, script_callbacks, ui_extensions, deepbooru, sd_vae, extra_networks, ui_common, ui_postprocessing, progress from modules.ui_components import FormRow, FormGroup, ToolButton, FormHTML from modules.paths import script_path, data_path diff --git a/modules/upscaler.py b/modules/upscaler.py index 777593b0..e145be30 100644 --- a/modules/upscaler.py +++ b/modules/upscaler.py @@ -41,7 +41,7 @@ class Upscaler: os.makedirs(self.model_path, exist_ok=True) try: - import cv2 + import cv2 # noqa: F401 self.can_tile = True except Exception: pass diff --git a/pyproject.toml b/pyproject.toml index 9caa9ba2..0883c127 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -1,13 +1,14 @@ [tool.ruff] +target-version = "py310" + exclude = ["extensions"] ignore = [ - "E501", - - "F401", # Module imported but unused + "E501", # Line too long + "E731", # Do not assign a `lambda` expression, use a `def` ] [tool.ruff.per-file-ignores] -"webui.py" = ["E402"] # Module level import not at top of file \ No newline at end of file +"webui.py" = ["E402"] # Module level import not at top of file diff --git a/webui.py b/webui.py index 48277075..5d5e80b5 100644 --- a/webui.py +++ b/webui.py @@ -16,12 +16,12 @@ from packaging import version import logging logging.getLogger("xformers").addFilter(lambda record: 'A matching Triton is not available' not in record.getMessage()) -from modules import paths, timer, import_hook, errors +from modules import paths, timer, import_hook, errors # noqa: F401 startup_timer = timer.Timer() import torch -import pytorch_lightning # pytorch_lightning should be imported after torch, but it re-enables warnings on import so import once to disable them +import pytorch_lightning # noqa: F401 # pytorch_lightning should be imported after torch, but it re-enables warnings on import so import once to disable them warnings.filterwarnings(action="ignore", category=DeprecationWarning, module="pytorch_lightning") warnings.filterwarnings(action="ignore", category=UserWarning, module="torchvision") @@ -31,12 +31,12 @@ startup_timer.record("import torch") import gradio startup_timer.record("import gradio") -import ldm.modules.encoders.modules +import ldm.modules.encoders.modules # noqa: F401 startup_timer.record("import ldm") from modules import extra_networks, ui_extra_networks_checkpoints from modules import extra_networks_hypernet, ui_extra_networks_hypernets, ui_extra_networks_textual_inversion -from modules.call_queue import wrap_queued_call, queue_lock, wrap_gradio_gpu_call +from modules.call_queue import wrap_queued_call, queue_lock # Truncate version number of nightly/local build of PyTorch to not cause exceptions with CodeFormer or Safetensors if ".dev" in torch.__version__ or "+git" in torch.__version__: -- cgit v1.2.3