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 --- modules/prompt_parser.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) (limited to 'modules/prompt_parser.py') 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() -- cgit v1.2.3 From 96d6ca4199e7c5eee8d451618de5161cea317c40 Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Wed, 10 May 2023 08:25:25 +0300 Subject: manual fixes for ruff --- extensions-builtin/LDSR/ldsr_model_arch.py | 2 +- extensions-builtin/LDSR/scripts/ldsr_model.py | 3 +- extensions-builtin/LDSR/sd_hijack_autoencoder.py | 10 +- extensions-builtin/LDSR/sd_hijack_ddpm_v1.py | 26 ++--- extensions-builtin/ScuNET/scunet_model_arch.py | 9 +- extensions-builtin/SwinIR/scripts/swinir_model.py | 2 +- modules/api/api.py | 129 +++++++++++----------- modules/api/models.py | 5 +- modules/codeformer/codeformer_arch.py | 2 +- modules/esrgan_model_arch.py | 2 + modules/extra_networks_hypernet.py | 2 +- modules/images.py | 4 +- modules/img2img.py | 1 - modules/interrogate.py | 1 - modules/modelloader.py | 6 +- modules/models/diffusion/ddpm_edit.py | 26 ++--- modules/models/diffusion/uni_pc/sampler.py | 3 +- modules/processing.py | 2 +- modules/prompt_parser.py | 11 +- modules/textual_inversion/autocrop.py | 2 +- modules/ui.py | 8 +- modules/upscaler.py | 2 +- 22 files changed, 129 insertions(+), 129 deletions(-) (limited to 'modules/prompt_parser.py') diff --git a/extensions-builtin/LDSR/ldsr_model_arch.py b/extensions-builtin/LDSR/ldsr_model_arch.py index 2339de7f..a5fb8907 100644 --- a/extensions-builtin/LDSR/ldsr_model_arch.py +++ b/extensions-builtin/LDSR/ldsr_model_arch.py @@ -243,7 +243,7 @@ def make_convolutional_sample(batch, model, custom_steps=None, eta=1.0, quantize x_sample_noquant = model.decode_first_stage(sample, force_not_quantize=True) log["sample_noquant"] = x_sample_noquant log["sample_diff"] = torch.abs(x_sample_noquant - x_sample) - except: + except Exception: pass log["sample"] = x_sample diff --git a/extensions-builtin/LDSR/scripts/ldsr_model.py b/extensions-builtin/LDSR/scripts/ldsr_model.py index da19cff1..e8dc083c 100644 --- a/extensions-builtin/LDSR/scripts/ldsr_model.py +++ b/extensions-builtin/LDSR/scripts/ldsr_model.py @@ -7,7 +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, sd_hijack_ddpm_v1 +import sd_hijack_autoencoder +import sd_hijack_ddpm_v1 class UpscalerLDSR(Upscaler): diff --git a/extensions-builtin/LDSR/sd_hijack_autoencoder.py b/extensions-builtin/LDSR/sd_hijack_autoencoder.py index db2231dd..6303fed5 100644 --- a/extensions-builtin/LDSR/sd_hijack_autoencoder.py +++ b/extensions-builtin/LDSR/sd_hijack_autoencoder.py @@ -1,16 +1,21 @@ # The content of this file comes from the ldm/models/autoencoder.py file of the compvis/stable-diffusion repo # The VQModel & VQModelInterface were subsequently removed from ldm/models/autoencoder.py when we moved to the stability-ai/stablediffusion repo # As the LDSR upscaler relies on VQModel & VQModelInterface, the hijack aims to put them back into the ldm.models.autoencoder - +import numpy as np import torch import pytorch_lightning as pl import torch.nn.functional as F from contextlib import contextmanager + +from torch.optim.lr_scheduler import LambdaLR + +from ldm.modules.ema import LitEma from taming.modules.vqvae.quantize import VectorQuantizer2 as VectorQuantizer from ldm.modules.diffusionmodules.model import Encoder, Decoder from ldm.util import instantiate_from_config import ldm.models.autoencoder +from packaging import version class VQModel(pl.LightningModule): def __init__(self, @@ -249,7 +254,8 @@ class VQModel(pl.LightningModule): if plot_ema: with self.ema_scope(): xrec_ema, _ = self(x) - if x.shape[1] > 3: xrec_ema = self.to_rgb(xrec_ema) + if x.shape[1] > 3: + xrec_ema = self.to_rgb(xrec_ema) log["reconstructions_ema"] = xrec_ema return log diff --git a/extensions-builtin/LDSR/sd_hijack_ddpm_v1.py b/extensions-builtin/LDSR/sd_hijack_ddpm_v1.py index 5c0488e5..4d3f6c56 100644 --- a/extensions-builtin/LDSR/sd_hijack_ddpm_v1.py +++ b/extensions-builtin/LDSR/sd_hijack_ddpm_v1.py @@ -450,7 +450,7 @@ class LatentDiffusionV1(DDPMV1): self.cond_stage_key = cond_stage_key try: self.num_downs = len(first_stage_config.params.ddconfig.ch_mult) - 1 - except: + except Exception: self.num_downs = 0 if not scale_by_std: self.scale_factor = scale_factor @@ -877,16 +877,6 @@ class LatentDiffusionV1(DDPMV1): c = self.q_sample(x_start=c, t=tc, noise=torch.randn_like(c.float())) return self.p_losses(x, c, t, *args, **kwargs) - def _rescale_annotations(self, bboxes, crop_coordinates): # TODO: move to dataset - def rescale_bbox(bbox): - x0 = clamp((bbox[0] - crop_coordinates[0]) / crop_coordinates[2]) - y0 = clamp((bbox[1] - crop_coordinates[1]) / crop_coordinates[3]) - w = min(bbox[2] / crop_coordinates[2], 1 - x0) - h = min(bbox[3] / crop_coordinates[3], 1 - y0) - return x0, y0, w, h - - return [rescale_bbox(b) for b in bboxes] - def apply_model(self, x_noisy, t, cond, return_ids=False): if isinstance(cond, dict): @@ -1157,8 +1147,10 @@ class LatentDiffusionV1(DDPMV1): if i % log_every_t == 0 or i == timesteps - 1: intermediates.append(x0_partial) - if callback: callback(i) - if img_callback: img_callback(img, i) + if callback: + callback(i) + if img_callback: + img_callback(img, i) return img, intermediates @torch.no_grad() @@ -1205,8 +1197,10 @@ class LatentDiffusionV1(DDPMV1): if i % log_every_t == 0 or i == timesteps - 1: intermediates.append(img) - if callback: callback(i) - if img_callback: img_callback(img, i) + if callback: + callback(i) + if img_callback: + img_callback(img, i) if return_intermediates: return img, intermediates @@ -1322,7 +1316,7 @@ class LatentDiffusionV1(DDPMV1): if inpaint: # make a simple center square - b, h, w = z.shape[0], z.shape[2], z.shape[3] + h, w = z.shape[2], z.shape[3] mask = torch.ones(N, h, w).to(self.device) # zeros will be filled in mask[:, h // 4:3 * h // 4, w // 4:3 * w // 4] = 0. diff --git a/extensions-builtin/ScuNET/scunet_model_arch.py b/extensions-builtin/ScuNET/scunet_model_arch.py index 43ca8d36..8028918a 100644 --- a/extensions-builtin/ScuNET/scunet_model_arch.py +++ b/extensions-builtin/ScuNET/scunet_model_arch.py @@ -61,7 +61,9 @@ class WMSA(nn.Module): Returns: output: tensor shape [b h w c] """ - if self.type != 'W': x = torch.roll(x, shifts=(-(self.window_size // 2), -(self.window_size // 2)), dims=(1, 2)) + if self.type != 'W': + x = torch.roll(x, shifts=(-(self.window_size // 2), -(self.window_size // 2)), dims=(1, 2)) + x = rearrange(x, 'b (w1 p1) (w2 p2) c -> b w1 w2 p1 p2 c', p1=self.window_size, p2=self.window_size) h_windows = x.size(1) w_windows = x.size(2) @@ -85,8 +87,9 @@ class WMSA(nn.Module): output = self.linear(output) output = rearrange(output, 'b (w1 w2) (p1 p2) c -> b (w1 p1) (w2 p2) c', w1=h_windows, p1=self.window_size) - if self.type != 'W': output = torch.roll(output, shifts=(self.window_size // 2, self.window_size // 2), - dims=(1, 2)) + if self.type != 'W': + output = torch.roll(output, shifts=(self.window_size // 2, self.window_size // 2), dims=(1, 2)) + return output def relative_embedding(self): diff --git a/extensions-builtin/SwinIR/scripts/swinir_model.py b/extensions-builtin/SwinIR/scripts/swinir_model.py index e8783bca..d77c3a92 100644 --- a/extensions-builtin/SwinIR/scripts/swinir_model.py +++ b/extensions-builtin/SwinIR/scripts/swinir_model.py @@ -45,7 +45,7 @@ class UpscalerSwinIR(Upscaler): img = upscale(img, model) try: torch.cuda.empty_cache() - except: + except Exception: pass return img diff --git a/modules/api/api.py b/modules/api/api.py index d47c39fc..f52d371b 100644 --- a/modules/api/api.py +++ b/modules/api/api.py @@ -15,7 +15,8 @@ from secrets import compare_digest import modules.shared as shared from modules import sd_samplers, deepbooru, sd_hijack, images, scripts, ui, postprocessing -from modules.api.models import * +from modules.api import models +from modules.shared import opts from modules.processing import StableDiffusionProcessingTxt2Img, StableDiffusionProcessingImg2Img, process_images from modules.textual_inversion.textual_inversion import create_embedding, train_embedding from modules.textual_inversion.preprocess import preprocess @@ -25,20 +26,21 @@ from modules.sd_models import checkpoints_list, unload_model_weights, reload_mod from modules.sd_models_config import find_checkpoint_config_near_filename from modules.realesrgan_model import get_realesrgan_models from modules import devices -from typing import List +from typing import Dict, List, Any import piexif import piexif.helper + def upscaler_to_index(name: str): try: return [x.name.lower() for x in shared.sd_upscalers].index(name.lower()) - except: - raise HTTPException(status_code=400, detail=f"Invalid upscaler, needs to be one of these: {' , '.join([x.name for x in sd_upscalers])}") + except Exception: + raise HTTPException(status_code=400, detail=f"Invalid upscaler, needs to be one of these: {' , '.join([x.name for x in shared.sd_upscalers])}") def script_name_to_index(name, scripts): try: return [script.title().lower() for script in scripts].index(name.lower()) - except: + except Exception: raise HTTPException(status_code=422, detail=f"Script '{name}' not found") def validate_sampler_name(name): @@ -99,7 +101,7 @@ def api_middleware(app: FastAPI): import starlette # importing just so it can be placed on silent list from rich.console import Console console = Console() - except: + except Exception: import traceback rich_available = False @@ -166,36 +168,36 @@ class Api: self.app = app self.queue_lock = queue_lock api_middleware(self.app) - self.add_api_route("/sdapi/v1/txt2img", self.text2imgapi, methods=["POST"], response_model=TextToImageResponse) - self.add_api_route("/sdapi/v1/img2img", self.img2imgapi, methods=["POST"], response_model=ImageToImageResponse) - self.add_api_route("/sdapi/v1/extra-single-image", self.extras_single_image_api, methods=["POST"], response_model=ExtrasSingleImageResponse) - self.add_api_route("/sdapi/v1/extra-batch-images", self.extras_batch_images_api, methods=["POST"], response_model=ExtrasBatchImagesResponse) - self.add_api_route("/sdapi/v1/png-info", self.pnginfoapi, methods=["POST"], response_model=PNGInfoResponse) - self.add_api_route("/sdapi/v1/progress", self.progressapi, methods=["GET"], response_model=ProgressResponse) + self.add_api_route("/sdapi/v1/txt2img", self.text2imgapi, methods=["POST"], response_model=models.TextToImageResponse) + self.add_api_route("/sdapi/v1/img2img", self.img2imgapi, methods=["POST"], response_model=models.ImageToImageResponse) + self.add_api_route("/sdapi/v1/extra-single-image", self.extras_single_image_api, methods=["POST"], response_model=models.ExtrasSingleImageResponse) + self.add_api_route("/sdapi/v1/extra-batch-images", self.extras_batch_images_api, methods=["POST"], response_model=models.ExtrasBatchImagesResponse) + self.add_api_route("/sdapi/v1/png-info", self.pnginfoapi, methods=["POST"], response_model=models.PNGInfoResponse) + self.add_api_route("/sdapi/v1/progress", self.progressapi, methods=["GET"], response_model=models.ProgressResponse) self.add_api_route("/sdapi/v1/interrogate", self.interrogateapi, methods=["POST"]) self.add_api_route("/sdapi/v1/interrupt", self.interruptapi, methods=["POST"]) self.add_api_route("/sdapi/v1/skip", self.skip, methods=["POST"]) - self.add_api_route("/sdapi/v1/options", self.get_config, methods=["GET"], response_model=OptionsModel) + self.add_api_route("/sdapi/v1/options", self.get_config, methods=["GET"], response_model=models.OptionsModel) self.add_api_route("/sdapi/v1/options", self.set_config, methods=["POST"]) - self.add_api_route("/sdapi/v1/cmd-flags", self.get_cmd_flags, methods=["GET"], response_model=FlagsModel) - self.add_api_route("/sdapi/v1/samplers", self.get_samplers, methods=["GET"], response_model=List[SamplerItem]) - self.add_api_route("/sdapi/v1/upscalers", self.get_upscalers, methods=["GET"], response_model=List[UpscalerItem]) - self.add_api_route("/sdapi/v1/sd-models", self.get_sd_models, methods=["GET"], response_model=List[SDModelItem]) - self.add_api_route("/sdapi/v1/hypernetworks", self.get_hypernetworks, methods=["GET"], response_model=List[HypernetworkItem]) - self.add_api_route("/sdapi/v1/face-restorers", self.get_face_restorers, methods=["GET"], response_model=List[FaceRestorerItem]) - self.add_api_route("/sdapi/v1/realesrgan-models", self.get_realesrgan_models, methods=["GET"], response_model=List[RealesrganItem]) - self.add_api_route("/sdapi/v1/prompt-styles", self.get_prompt_styles, methods=["GET"], response_model=List[PromptStyleItem]) - self.add_api_route("/sdapi/v1/embeddings", self.get_embeddings, methods=["GET"], response_model=EmbeddingsResponse) + self.add_api_route("/sdapi/v1/cmd-flags", self.get_cmd_flags, methods=["GET"], response_model=models.FlagsModel) + self.add_api_route("/sdapi/v1/samplers", self.get_samplers, methods=["GET"], response_model=List[models.SamplerItem]) + self.add_api_route("/sdapi/v1/upscalers", self.get_upscalers, methods=["GET"], response_model=List[models.UpscalerItem]) + self.add_api_route("/sdapi/v1/sd-models", self.get_sd_models, methods=["GET"], response_model=List[models.SDModelItem]) + self.add_api_route("/sdapi/v1/hypernetworks", self.get_hypernetworks, methods=["GET"], response_model=List[models.HypernetworkItem]) + self.add_api_route("/sdapi/v1/face-restorers", self.get_face_restorers, methods=["GET"], response_model=List[models.FaceRestorerItem]) + self.add_api_route("/sdapi/v1/realesrgan-models", self.get_realesrgan_models, methods=["GET"], response_model=List[models.RealesrganItem]) + self.add_api_route("/sdapi/v1/prompt-styles", self.get_prompt_styles, methods=["GET"], response_model=List[models.PromptStyleItem]) + self.add_api_route("/sdapi/v1/embeddings", self.get_embeddings, methods=["GET"], response_model=models.EmbeddingsResponse) self.add_api_route("/sdapi/v1/refresh-checkpoints", self.refresh_checkpoints, methods=["POST"]) - self.add_api_route("/sdapi/v1/create/embedding", self.create_embedding, methods=["POST"], response_model=CreateResponse) - self.add_api_route("/sdapi/v1/create/hypernetwork", self.create_hypernetwork, methods=["POST"], response_model=CreateResponse) - self.add_api_route("/sdapi/v1/preprocess", self.preprocess, methods=["POST"], response_model=PreprocessResponse) - self.add_api_route("/sdapi/v1/train/embedding", self.train_embedding, methods=["POST"], response_model=TrainResponse) - self.add_api_route("/sdapi/v1/train/hypernetwork", self.train_hypernetwork, methods=["POST"], response_model=TrainResponse) - self.add_api_route("/sdapi/v1/memory", self.get_memory, methods=["GET"], response_model=MemoryResponse) + self.add_api_route("/sdapi/v1/create/embedding", self.create_embedding, methods=["POST"], response_model=models.CreateResponse) + self.add_api_route("/sdapi/v1/create/hypernetwork", self.create_hypernetwork, methods=["POST"], response_model=models.CreateResponse) + self.add_api_route("/sdapi/v1/preprocess", self.preprocess, methods=["POST"], response_model=models.PreprocessResponse) + self.add_api_route("/sdapi/v1/train/embedding", self.train_embedding, methods=["POST"], response_model=models.TrainResponse) + self.add_api_route("/sdapi/v1/train/hypernetwork", self.train_hypernetwork, methods=["POST"], response_model=models.TrainResponse) + self.add_api_route("/sdapi/v1/memory", self.get_memory, methods=["GET"], response_model=models.MemoryResponse) self.add_api_route("/sdapi/v1/unload-checkpoint", self.unloadapi, methods=["POST"]) self.add_api_route("/sdapi/v1/reload-checkpoint", self.reloadapi, methods=["POST"]) - self.add_api_route("/sdapi/v1/scripts", self.get_scripts_list, methods=["GET"], response_model=ScriptsList) + self.add_api_route("/sdapi/v1/scripts", self.get_scripts_list, methods=["GET"], response_model=models.ScriptsList) self.default_script_arg_txt2img = [] self.default_script_arg_img2img = [] @@ -224,7 +226,7 @@ class Api: t2ilist = [str(title.lower()) for title in scripts.scripts_txt2img.titles] i2ilist = [str(title.lower()) for title in scripts.scripts_img2img.titles] - return ScriptsList(txt2img = t2ilist, img2img = i2ilist) + return models.ScriptsList(txt2img=t2ilist, img2img=i2ilist) def get_script(self, script_name, script_runner): if script_name is None or script_name == "": @@ -276,7 +278,7 @@ class Api: script_args[alwayson_script.args_from + idx] = request.alwayson_scripts[alwayson_script_name]["args"][idx] return script_args - def text2imgapi(self, txt2imgreq: StableDiffusionTxt2ImgProcessingAPI): + def text2imgapi(self, txt2imgreq: models.StableDiffusionTxt2ImgProcessingAPI): script_runner = scripts.scripts_txt2img if not script_runner.scripts: script_runner.initialize_scripts(False) @@ -320,9 +322,9 @@ class Api: b64images = list(map(encode_pil_to_base64, processed.images)) if send_images else [] - return TextToImageResponse(images=b64images, parameters=vars(txt2imgreq), info=processed.js()) + return models.TextToImageResponse(images=b64images, parameters=vars(txt2imgreq), info=processed.js()) - def img2imgapi(self, img2imgreq: StableDiffusionImg2ImgProcessingAPI): + def img2imgapi(self, img2imgreq: models.StableDiffusionImg2ImgProcessingAPI): init_images = img2imgreq.init_images if init_images is None: raise HTTPException(status_code=404, detail="Init image not found") @@ -381,9 +383,9 @@ class Api: img2imgreq.init_images = None img2imgreq.mask = None - return ImageToImageResponse(images=b64images, parameters=vars(img2imgreq), info=processed.js()) + return models.ImageToImageResponse(images=b64images, parameters=vars(img2imgreq), info=processed.js()) - def extras_single_image_api(self, req: ExtrasSingleImageRequest): + def extras_single_image_api(self, req: models.ExtrasSingleImageRequest): reqDict = setUpscalers(req) reqDict['image'] = decode_base64_to_image(reqDict['image']) @@ -391,9 +393,9 @@ class Api: with self.queue_lock: result = postprocessing.run_extras(extras_mode=0, image_folder="", input_dir="", output_dir="", save_output=False, **reqDict) - return ExtrasSingleImageResponse(image=encode_pil_to_base64(result[0][0]), html_info=result[1]) + return models.ExtrasSingleImageResponse(image=encode_pil_to_base64(result[0][0]), html_info=result[1]) - def extras_batch_images_api(self, req: ExtrasBatchImagesRequest): + def extras_batch_images_api(self, req: models.ExtrasBatchImagesRequest): reqDict = setUpscalers(req) image_list = reqDict.pop('imageList', []) @@ -402,15 +404,15 @@ class Api: with self.queue_lock: result = postprocessing.run_extras(extras_mode=1, image_folder=image_folder, image="", input_dir="", output_dir="", save_output=False, **reqDict) - return ExtrasBatchImagesResponse(images=list(map(encode_pil_to_base64, result[0])), html_info=result[1]) + return models.ExtrasBatchImagesResponse(images=list(map(encode_pil_to_base64, result[0])), html_info=result[1]) - def pnginfoapi(self, req: PNGInfoRequest): + def pnginfoapi(self, req: models.PNGInfoRequest): if(not req.image.strip()): - return PNGInfoResponse(info="") + return models.PNGInfoResponse(info="") image = decode_base64_to_image(req.image.strip()) if image is None: - return PNGInfoResponse(info="") + return models.PNGInfoResponse(info="") geninfo, items = images.read_info_from_image(image) if geninfo is None: @@ -418,13 +420,13 @@ class Api: items = {**{'parameters': geninfo}, **items} - return PNGInfoResponse(info=geninfo, items=items) + return models.PNGInfoResponse(info=geninfo, items=items) - def progressapi(self, req: ProgressRequest = Depends()): + def progressapi(self, req: models.ProgressRequest = Depends()): # copy from check_progress_call of ui.py if shared.state.job_count == 0: - return ProgressResponse(progress=0, eta_relative=0, state=shared.state.dict(), textinfo=shared.state.textinfo) + return models.ProgressResponse(progress=0, eta_relative=0, state=shared.state.dict(), textinfo=shared.state.textinfo) # avoid dividing zero progress = 0.01 @@ -446,9 +448,9 @@ class Api: if shared.state.current_image and not req.skip_current_image: current_image = encode_pil_to_base64(shared.state.current_image) - return ProgressResponse(progress=progress, eta_relative=eta_relative, state=shared.state.dict(), current_image=current_image, textinfo=shared.state.textinfo) + return models.ProgressResponse(progress=progress, eta_relative=eta_relative, state=shared.state.dict(), current_image=current_image, textinfo=shared.state.textinfo) - def interrogateapi(self, interrogatereq: InterrogateRequest): + def interrogateapi(self, interrogatereq: models.InterrogateRequest): image_b64 = interrogatereq.image if image_b64 is None: raise HTTPException(status_code=404, detail="Image not found") @@ -465,7 +467,7 @@ class Api: else: raise HTTPException(status_code=404, detail="Model not found") - return InterrogateResponse(caption=processed) + return models.InterrogateResponse(caption=processed) def interruptapi(self): shared.state.interrupt() @@ -570,36 +572,36 @@ 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=f"create embedding filename: {filename}") + return models.CreateResponse(info=f"create embedding filename: {filename}") except AssertionError as e: shared.state.end() - return TrainResponse(info=f"create embedding error: {e}") + return models.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=f"create hypernetwork filename: {filename}") + return models.CreateResponse(info=f"create hypernetwork filename: {filename}") except AssertionError as e: shared.state.end() - return TrainResponse(info=f"create hypernetwork error: {e}") + return models.TrainResponse(info=f"create hypernetwork error: {e}") def preprocess(self, args: dict): try: shared.state.begin() preprocess(**args) # quick operation unless blip/booru interrogation is enabled shared.state.end() - return PreprocessResponse(info = 'preprocess complete') + return models.PreprocessResponse(info = 'preprocess complete') except KeyError as e: shared.state.end() - return PreprocessResponse(info=f"preprocess error: invalid token: {e}") + return models.PreprocessResponse(info=f"preprocess error: invalid token: {e}") except AssertionError as e: shared.state.end() - return PreprocessResponse(info=f"preprocess error: {e}") + return models.PreprocessResponse(info=f"preprocess error: {e}") except FileNotFoundError as e: shared.state.end() - return PreprocessResponse(info=f'preprocess error: {e}') + return models.PreprocessResponse(info=f'preprocess error: {e}') def train_embedding(self, args: dict): try: @@ -617,10 +619,10 @@ class Api: if not apply_optimizations: sd_hijack.apply_optimizations() shared.state.end() - return TrainResponse(info=f"train embedding complete: filename: {filename} error: {error}") + return models.TrainResponse(info=f"train embedding complete: filename: {filename} error: {error}") except AssertionError as msg: shared.state.end() - return TrainResponse(info=f"train embedding error: {msg}") + return models.TrainResponse(info=f"train embedding error: {msg}") def train_hypernetwork(self, args: dict): try: @@ -641,14 +643,15 @@ class Api: if not apply_optimizations: sd_hijack.apply_optimizations() shared.state.end() - return TrainResponse(info=f"train embedding complete: filename: {filename} error: {error}") + return models.TrainResponse(info=f"train embedding complete: filename: {filename} error: {error}") except AssertionError: shared.state.end() - return TrainResponse(info=f"train embedding error: {error}") + return models.TrainResponse(info=f"train embedding error: {error}") def get_memory(self): try: - import os, psutil + import os + import psutil process = psutil.Process(os.getpid()) res = process.memory_info() # only rss is cross-platform guaranteed so we dont rely on other values ram_total = 100 * res.rss / process.memory_percent() # and total memory is calculated as actual value is not cross-platform safe @@ -675,10 +678,10 @@ class Api: 'events': warnings, } else: - cuda = { 'error': 'unavailable' } + cuda = {'error': 'unavailable'} except Exception as err: - cuda = { 'error': f'{err}' } - return MemoryResponse(ram = ram, cuda = cuda) + cuda = {'error': f'{err}'} + return models.MemoryResponse(ram=ram, cuda=cuda) def launch(self, server_name, port): self.app.include_router(self.router) diff --git a/modules/api/models.py b/modules/api/models.py index 4a70f440..4d291076 100644 --- a/modules/api/models.py +++ b/modules/api/models.py @@ -223,8 +223,9 @@ for key in _options: if(_options[key].dest != 'help'): flag = _options[key] _type = str - if _options[key].default is not None: _type = type(_options[key].default) - flags.update({flag.dest: (_type,Field(default=flag.default, description=flag.help))}) + if _options[key].default is not None: + _type = type(_options[key].default) + flags.update({flag.dest: (_type, Field(default=flag.default, description=flag.help))}) FlagsModel = create_model("Flags", **flags) diff --git a/modules/codeformer/codeformer_arch.py b/modules/codeformer/codeformer_arch.py index 11dcc3ee..f1a7cf09 100644 --- a/modules/codeformer/codeformer_arch.py +++ b/modules/codeformer/codeformer_arch.py @@ -7,7 +7,7 @@ from torch import nn, Tensor import torch.nn.functional as F from typing import Optional, List -from modules.codeformer.vqgan_arch import * +from modules.codeformer.vqgan_arch import VQAutoEncoder, ResBlock from basicsr.utils import get_root_logger from basicsr.utils.registry import ARCH_REGISTRY diff --git a/modules/esrgan_model_arch.py b/modules/esrgan_model_arch.py index 6071fea7..7f8bc7c0 100644 --- a/modules/esrgan_model_arch.py +++ b/modules/esrgan_model_arch.py @@ -438,9 +438,11 @@ def conv_block(in_nc, out_nc, kernel_size, stride=1, dilation=1, groups=1, bias= padding = padding if pad_type == 'zero' else 0 if convtype=='PartialConv2D': + from torchvision.ops import PartialConv2d # this is definitely not going to work, but PartialConv2d doesn't work anyway and this shuts up static analyzer c = PartialConv2d(in_nc, out_nc, kernel_size=kernel_size, stride=stride, padding=padding, dilation=dilation, bias=bias, groups=groups) elif convtype=='DeformConv2D': + from torchvision.ops import DeformConv2d # not tested c = DeformConv2d(in_nc, out_nc, kernel_size=kernel_size, stride=stride, padding=padding, dilation=dilation, bias=bias, groups=groups) elif convtype=='Conv3D': diff --git a/modules/extra_networks_hypernet.py b/modules/extra_networks_hypernet.py index 04f27c9f..aa2a14ef 100644 --- a/modules/extra_networks_hypernet.py +++ b/modules/extra_networks_hypernet.py @@ -1,4 +1,4 @@ -from modules import extra_networks, shared, extra_networks +from modules import extra_networks, shared from modules.hypernetworks import hypernetwork diff --git a/modules/images.py b/modules/images.py index 3d5d76cc..5eb6d855 100644 --- a/modules/images.py +++ b/modules/images.py @@ -472,9 +472,9 @@ def get_next_sequence_number(path, basename): prefix_length = len(basename) for p in os.listdir(path): if p.startswith(basename): - l = os.path.splitext(p[prefix_length:])[0].split('-') # splits the filename (removing the basename first if one is defined, so the sequence number is always the first element) + parts = os.path.splitext(p[prefix_length:])[0].split('-') # splits the filename (removing the basename first if one is defined, so the sequence number is always the first element) try: - result = max(int(l[0]), result) + result = max(int(parts[0]), result) except ValueError: pass diff --git a/modules/img2img.py b/modules/img2img.py index cdae301a..32b1ecd6 100644 --- a/modules/img2img.py +++ b/modules/img2img.py @@ -13,7 +13,6 @@ from modules.shared import opts, state import modules.shared as shared import modules.processing as processing from modules.ui import plaintext_to_html -import modules.images as images import modules.scripts diff --git a/modules/interrogate.py b/modules/interrogate.py index 9f7d657f..22df9216 100644 --- a/modules/interrogate.py +++ b/modules/interrogate.py @@ -11,7 +11,6 @@ import torch.hub from torchvision import transforms from torchvision.transforms.functional import InterpolationMode -import modules.shared as shared from modules import devices, paths, shared, lowvram, modelloader, errors blip_image_eval_size = 384 diff --git a/modules/modelloader.py b/modules/modelloader.py index cb85ac4f..cf685000 100644 --- a/modules/modelloader.py +++ b/modules/modelloader.py @@ -108,12 +108,12 @@ def move_files(src_path: str, dest_path: str, ext_filter: str = None): print(f"Moving {file} from {src_path} to {dest_path}.") try: shutil.move(fullpath, dest_path) - except: + except Exception: pass if len(os.listdir(src_path)) == 0: print(f"Removing empty folder: {src_path}") shutil.rmtree(src_path, True) - except: + except Exception: pass @@ -141,7 +141,7 @@ def load_upscalers(): full_model = f"modules.{model_name}_model" try: importlib.import_module(full_model) - except: + except Exception: pass datas = [] diff --git a/modules/models/diffusion/ddpm_edit.py b/modules/models/diffusion/ddpm_edit.py index f880bc3c..611c2b69 100644 --- a/modules/models/diffusion/ddpm_edit.py +++ b/modules/models/diffusion/ddpm_edit.py @@ -479,7 +479,7 @@ class LatentDiffusion(DDPM): self.cond_stage_key = cond_stage_key try: self.num_downs = len(first_stage_config.params.ddconfig.ch_mult) - 1 - except: + except Exception: self.num_downs = 0 if not scale_by_std: self.scale_factor = scale_factor @@ -891,16 +891,6 @@ class LatentDiffusion(DDPM): c = self.q_sample(x_start=c, t=tc, noise=torch.randn_like(c.float())) return self.p_losses(x, c, t, *args, **kwargs) - def _rescale_annotations(self, bboxes, crop_coordinates): # TODO: move to dataset - def rescale_bbox(bbox): - x0 = clamp((bbox[0] - crop_coordinates[0]) / crop_coordinates[2]) - y0 = clamp((bbox[1] - crop_coordinates[1]) / crop_coordinates[3]) - w = min(bbox[2] / crop_coordinates[2], 1 - x0) - h = min(bbox[3] / crop_coordinates[3], 1 - y0) - return x0, y0, w, h - - return [rescale_bbox(b) for b in bboxes] - def apply_model(self, x_noisy, t, cond, return_ids=False): if isinstance(cond, dict): @@ -1171,8 +1161,10 @@ class LatentDiffusion(DDPM): if i % log_every_t == 0 or i == timesteps - 1: intermediates.append(x0_partial) - if callback: callback(i) - if img_callback: img_callback(img, i) + if callback: + callback(i) + if img_callback: + img_callback(img, i) return img, intermediates @torch.no_grad() @@ -1219,8 +1211,10 @@ class LatentDiffusion(DDPM): if i % log_every_t == 0 or i == timesteps - 1: intermediates.append(img) - if callback: callback(i) - if img_callback: img_callback(img, i) + if callback: + callback(i) + if img_callback: + img_callback(img, i) if return_intermediates: return img, intermediates @@ -1337,7 +1331,7 @@ class LatentDiffusion(DDPM): if inpaint: # make a simple center square - b, h, w = z.shape[0], z.shape[2], z.shape[3] + h, w = z.shape[2], z.shape[3] mask = torch.ones(N, h, w).to(self.device) # zeros will be filled in mask[:, h // 4:3 * h // 4, w // 4:3 * w // 4] = 0. diff --git a/modules/models/diffusion/uni_pc/sampler.py b/modules/models/diffusion/uni_pc/sampler.py index a241c8a7..0a9defa1 100644 --- a/modules/models/diffusion/uni_pc/sampler.py +++ b/modules/models/diffusion/uni_pc/sampler.py @@ -54,7 +54,8 @@ class UniPCSampler(object): if conditioning is not None: if isinstance(conditioning, dict): ctmp = conditioning[list(conditioning.keys())[0]] - while isinstance(ctmp, list): ctmp = ctmp[0] + while isinstance(ctmp, list): + ctmp = ctmp[0] cbs = ctmp.shape[0] if cbs != batch_size: print(f"Warning: Got {cbs} conditionings but batch-size is {batch_size}") diff --git a/modules/processing.py b/modules/processing.py index 1a76e552..6f5233c1 100644 --- a/modules/processing.py +++ b/modules/processing.py @@ -664,7 +664,7 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed: if not shared.opts.dont_fix_second_order_samplers_schedule: try: step_multiplier = 2 if sd_samplers.all_samplers_map.get(p.sampler_name).aliases[0] in ['k_dpmpp_2s_a', 'k_dpmpp_2s_a_ka', 'k_dpmpp_sde', 'k_dpmpp_sde_ka', 'k_dpm_2', 'k_dpm_2_a', 'k_heun'] else 1 - except: + except Exception: pass uc = get_conds_with_caching(prompt_parser.get_learned_conditioning, negative_prompts, p.steps * step_multiplier, cached_uc) c = get_conds_with_caching(prompt_parser.get_multicond_learned_conditioning, prompts, p.steps * step_multiplier, cached_c) diff --git a/modules/prompt_parser.py b/modules/prompt_parser.py index e084e948..3a720721 100644 --- a/modules/prompt_parser.py +++ b/modules/prompt_parser.py @@ -54,18 +54,21 @@ def get_learned_conditioning_prompt_schedules(prompts, steps): """ def collect_steps(steps, tree): - l = [steps] + res = [steps] + class CollectSteps(lark.Visitor): def scheduled(self, tree): tree.children[-1] = float(tree.children[-1]) if tree.children[-1] < 1: tree.children[-1] *= steps tree.children[-1] = min(steps, int(tree.children[-1])) - l.append(tree.children[-1]) + res.append(tree.children[-1]) + def alternate(self, tree): - l.extend(range(1, steps+1)) + res.extend(range(1, steps+1)) + CollectSteps().visit(tree) - return sorted(set(l)) + return sorted(set(res)) def at_step(step, tree): class AtStep(lark.Transformer): diff --git a/modules/textual_inversion/autocrop.py b/modules/textual_inversion/autocrop.py index ba1bdcd4..d7d8d2e3 100644 --- a/modules/textual_inversion/autocrop.py +++ b/modules/textual_inversion/autocrop.py @@ -185,7 +185,7 @@ def image_face_points(im, settings): try: faces = classifier.detectMultiScale(gray, scaleFactor=1.1, minNeighbors=7, minSize=(minsize, minsize), flags=cv2.CASCADE_SCALE_IMAGE) - except: + except Exception: continue if len(faces) > 0: diff --git a/modules/ui.py b/modules/ui.py index 2171f3aa..6beda76f 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1,15 +1,9 @@ -import html import json -import math import mimetypes import os -import platform -import random import sys -import tempfile -import time import traceback -from functools import partial, reduce +from functools import reduce import warnings import gradio as gr diff --git a/modules/upscaler.py b/modules/upscaler.py index e2eaa730..0ad4fe99 100644 --- a/modules/upscaler.py +++ b/modules/upscaler.py @@ -45,7 +45,7 @@ class Upscaler: try: import cv2 self.can_tile = True - except: + except Exception: pass @abstractmethod -- cgit v1.2.3 From a5121e7a0623db328a9462d340d389ed6737374a Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Wed, 10 May 2023 11:37:18 +0300 Subject: fixes for B007 --- extensions-builtin/LDSR/ldsr_model_arch.py | 2 +- extensions-builtin/Lora/lora.py | 2 +- extensions-builtin/ScuNET/scripts/scunet_model.py | 2 +- extensions-builtin/SwinIR/swinir_model_arch.py | 2 +- extensions-builtin/SwinIR/swinir_model_arch_v2.py | 2 +- modules/codeformer_model.py | 2 +- modules/esrgan_model.py | 8 ++------ modules/extra_networks.py | 2 +- modules/generation_parameters_copypaste.py | 2 +- modules/hypernetworks/hypernetwork.py | 12 ++++++------ modules/images.py | 2 +- modules/interrogate.py | 4 ++-- modules/prompt_parser.py | 14 +++++++------- modules/safe.py | 4 ++-- modules/scripts.py | 10 +++++----- modules/scripts_postprocessing.py | 8 ++++---- modules/sd_hijack_clip.py | 2 +- modules/shared.py | 6 +++--- modules/textual_inversion/learn_schedule.py | 2 +- modules/textual_inversion/textual_inversion.py | 10 +++++----- modules/ui.py | 6 +++--- modules/ui_extra_networks.py | 2 +- modules/ui_tempdir.py | 2 +- modules/upscaler.py | 2 +- pyproject.toml | 1 - scripts/prompts_from_file.py | 2 +- scripts/sd_upscale.py | 4 ++-- scripts/xyz_grid.py | 2 +- 28 files changed, 57 insertions(+), 62 deletions(-) (limited to 'modules/prompt_parser.py') diff --git a/extensions-builtin/LDSR/ldsr_model_arch.py b/extensions-builtin/LDSR/ldsr_model_arch.py index a5fb8907..27e38549 100644 --- a/extensions-builtin/LDSR/ldsr_model_arch.py +++ b/extensions-builtin/LDSR/ldsr_model_arch.py @@ -88,7 +88,7 @@ class LDSR: x_t = None logs = None - for n in range(n_runs): + for _ in range(n_runs): if custom_shape is not None: x_t = torch.randn(1, custom_shape[1], custom_shape[2], custom_shape[3]).to(model.device) x_t = repeat(x_t, '1 c h w -> b c h w', b=custom_shape[0]) diff --git a/extensions-builtin/Lora/lora.py b/extensions-builtin/Lora/lora.py index 9795540f..7b56136f 100644 --- a/extensions-builtin/Lora/lora.py +++ b/extensions-builtin/Lora/lora.py @@ -418,7 +418,7 @@ def infotext_pasted(infotext, params): added = [] - for k, v in params.items(): + for k in params: if not k.startswith("AddNet Model "): continue diff --git a/extensions-builtin/ScuNET/scripts/scunet_model.py b/extensions-builtin/ScuNET/scripts/scunet_model.py index aa2fdb3a..1f5ea0d3 100644 --- a/extensions-builtin/ScuNET/scripts/scunet_model.py +++ b/extensions-builtin/ScuNET/scripts/scunet_model.py @@ -132,7 +132,7 @@ class UpscalerScuNET(modules.upscaler.Upscaler): model = net(in_nc=3, config=[4, 4, 4, 4, 4, 4, 4], dim=64) model.load_state_dict(torch.load(filename), strict=True) model.eval() - for k, v in model.named_parameters(): + for _, v in model.named_parameters(): v.requires_grad = False model = model.to(device) diff --git a/extensions-builtin/SwinIR/swinir_model_arch.py b/extensions-builtin/SwinIR/swinir_model_arch.py index 75f7bedc..de195d9b 100644 --- a/extensions-builtin/SwinIR/swinir_model_arch.py +++ b/extensions-builtin/SwinIR/swinir_model_arch.py @@ -848,7 +848,7 @@ class SwinIR(nn.Module): H, W = self.patches_resolution flops += H * W * 3 * self.embed_dim * 9 flops += self.patch_embed.flops() - for i, layer in enumerate(self.layers): + for layer in self.layers: flops += layer.flops() flops += H * W * 3 * self.embed_dim * self.embed_dim flops += self.upsample.flops() diff --git a/extensions-builtin/SwinIR/swinir_model_arch_v2.py b/extensions-builtin/SwinIR/swinir_model_arch_v2.py index d4c0b0da..15777af9 100644 --- a/extensions-builtin/SwinIR/swinir_model_arch_v2.py +++ b/extensions-builtin/SwinIR/swinir_model_arch_v2.py @@ -1001,7 +1001,7 @@ class Swin2SR(nn.Module): H, W = self.patches_resolution flops += H * W * 3 * self.embed_dim * 9 flops += self.patch_embed.flops() - for i, layer in enumerate(self.layers): + for layer in self.layers: flops += layer.flops() flops += H * W * 3 * self.embed_dim * self.embed_dim flops += self.upsample.flops() diff --git a/modules/codeformer_model.py b/modules/codeformer_model.py index 8e56cb89..ececdbae 100644 --- a/modules/codeformer_model.py +++ b/modules/codeformer_model.py @@ -94,7 +94,7 @@ def setup_model(dirname): self.face_helper.get_face_landmarks_5(only_center_face=False, resize=640, eye_dist_threshold=5) self.face_helper.align_warp_face() - for idx, cropped_face in enumerate(self.face_helper.cropped_faces): + for cropped_face in self.face_helper.cropped_faces: cropped_face_t = img2tensor(cropped_face / 255., bgr2rgb=True, float32=True) normalize(cropped_face_t, (0.5, 0.5, 0.5), (0.5, 0.5, 0.5), inplace=True) cropped_face_t = cropped_face_t.unsqueeze(0).to(devices.device_codeformer) diff --git a/modules/esrgan_model.py b/modules/esrgan_model.py index 85aa6934..a009eb42 100644 --- a/modules/esrgan_model.py +++ b/modules/esrgan_model.py @@ -16,9 +16,7 @@ def mod2normal(state_dict): # this code is copied from https://github.com/victorca25/iNNfer if 'conv_first.weight' in state_dict: crt_net = {} - items = [] - for k, v in state_dict.items(): - items.append(k) + items = list(state_dict) crt_net['model.0.weight'] = state_dict['conv_first.weight'] crt_net['model.0.bias'] = state_dict['conv_first.bias'] @@ -52,9 +50,7 @@ def resrgan2normal(state_dict, nb=23): if "conv_first.weight" in state_dict and "body.0.rdb1.conv1.weight" in state_dict: re8x = 0 crt_net = {} - items = [] - for k, v in state_dict.items(): - items.append(k) + items = list(state_dict) crt_net['model.0.weight'] = state_dict['conv_first.weight'] crt_net['model.0.bias'] = state_dict['conv_first.bias'] diff --git a/modules/extra_networks.py b/modules/extra_networks.py index 1978673d..f9db41bc 100644 --- a/modules/extra_networks.py +++ b/modules/extra_networks.py @@ -91,7 +91,7 @@ def deactivate(p, extra_network_data): """call deactivate for extra networks in extra_network_data in specified order, then call deactivate for all remaining registered networks""" - for extra_network_name, extra_network_args in extra_network_data.items(): + for extra_network_name in extra_network_data: extra_network = extra_network_registry.get(extra_network_name, None) if extra_network is None: continue diff --git a/modules/generation_parameters_copypaste.py b/modules/generation_parameters_copypaste.py index 7fbbe707..b0e945a1 100644 --- a/modules/generation_parameters_copypaste.py +++ b/modules/generation_parameters_copypaste.py @@ -247,7 +247,7 @@ Steps: 20, Sampler: Euler a, CFG scale: 7, Seed: 965400086, Size: 512x512, Model lines.append(lastline) lastline = '' - for i, line in enumerate(lines): + for line in lines: line = line.strip() if line.startswith("Negative prompt:"): done_with_prompt = True diff --git a/modules/hypernetworks/hypernetwork.py b/modules/hypernetworks/hypernetwork.py index 6ef0bfdf..38ef074f 100644 --- a/modules/hypernetworks/hypernetwork.py +++ b/modules/hypernetworks/hypernetwork.py @@ -177,34 +177,34 @@ class Hypernetwork: def weights(self): res = [] - for k, layers in self.layers.items(): + for layers in self.layers.values(): for layer in layers: res += layer.parameters() return res def train(self, mode=True): - for k, layers in self.layers.items(): + for layers in self.layers.values(): for layer in layers: layer.train(mode=mode) for param in layer.parameters(): param.requires_grad = mode def to(self, device): - for k, layers in self.layers.items(): + for layers in self.layers.values(): for layer in layers: layer.to(device) return self def set_multiplier(self, multiplier): - for k, layers in self.layers.items(): + for layers in self.layers.values(): for layer in layers: layer.multiplier = multiplier return self def eval(self): - for k, layers in self.layers.items(): + for layers in self.layers.values(): for layer in layers: layer.eval() for param in layer.parameters(): @@ -619,7 +619,7 @@ def train_hypernetwork(id_task, hypernetwork_name, learn_rate, batch_size, gradi try: sd_hijack_checkpoint.add() - for i in range((steps-initial_step) * gradient_step): + for _ in range((steps-initial_step) * gradient_step): if scheduler.finished: break if shared.state.interrupted: diff --git a/modules/images.py b/modules/images.py index 7392cb8b..c4e98c75 100644 --- a/modules/images.py +++ b/modules/images.py @@ -149,7 +149,7 @@ def draw_grid_annotations(im, width, height, hor_texts, ver_texts, margin=0): return ImageFont.truetype(Roboto, fontsize) def draw_texts(drawing, draw_x, draw_y, lines, initial_fnt, initial_fontsize): - for i, line in enumerate(lines): + for line in lines: fnt = initial_fnt fontsize = initial_fontsize while drawing.multiline_textsize(line.text, font=fnt)[0] > line.allowed_width and fontsize > 0: diff --git a/modules/interrogate.py b/modules/interrogate.py index a1c8e537..111b1322 100644 --- a/modules/interrogate.py +++ b/modules/interrogate.py @@ -207,8 +207,8 @@ class InterrogateModels: image_features /= image_features.norm(dim=-1, keepdim=True) - for name, topn, items in self.categories(): - matches = self.rank(image_features, items, top_count=topn) + for cat in self.categories(): + matches = self.rank(image_features, cat.items, top_count=cat.topn) for match, score in matches: if shared.opts.interrogate_return_ranks: res += f", ({match}:{score/100:.3f})" diff --git a/modules/prompt_parser.py b/modules/prompt_parser.py index 3a720721..b4aff704 100644 --- a/modules/prompt_parser.py +++ b/modules/prompt_parser.py @@ -143,7 +143,7 @@ def get_learned_conditioning(model, prompts, steps): conds = model.get_learned_conditioning(texts) cond_schedule = [] - for i, (end_at_step, text) in enumerate(prompt_schedule): + for i, (end_at_step, _) in enumerate(prompt_schedule): cond_schedule.append(ScheduledPromptConditioning(end_at_step, conds[i])) cache[prompt] = cond_schedule @@ -219,8 +219,8 @@ def reconstruct_cond_batch(c: List[List[ScheduledPromptConditioning]], current_s res = torch.zeros((len(c),) + param.shape, device=param.device, dtype=param.dtype) for i, cond_schedule in enumerate(c): target_index = 0 - for current, (end_at, cond) in enumerate(cond_schedule): - if current_step <= end_at: + for current, entry in enumerate(cond_schedule): + if current_step <= entry.end_at_step: target_index = current break res[i] = cond_schedule[target_index].cond @@ -234,13 +234,13 @@ def reconstruct_multicond_batch(c: MulticondLearnedConditioning, current_step): tensors = [] conds_list = [] - for batch_no, composable_prompts in enumerate(c.batch): + for composable_prompts in c.batch: conds_for_batch = [] - for cond_index, composable_prompt in enumerate(composable_prompts): + for composable_prompt in composable_prompts: target_index = 0 - for current, (end_at, cond) in enumerate(composable_prompt.schedules): - if current_step <= end_at: + for current, entry in enumerate(composable_prompt.schedules): + if current_step <= entry.end_at_step: target_index = current break diff --git a/modules/safe.py b/modules/safe.py index 2d5b972f..1e791c5b 100644 --- a/modules/safe.py +++ b/modules/safe.py @@ -95,11 +95,11 @@ def check_pt(filename, extra_handler): except zipfile.BadZipfile: - # if it's not a zip file, it's an olf pytorch format, with five objects written to pickle + # if it's not a zip file, it's an old pytorch format, with five objects written to pickle with open(filename, "rb") as file: unpickler = RestrictedUnpickler(file) unpickler.extra_handler = extra_handler - for i in range(5): + for _ in range(5): unpickler.load() diff --git a/modules/scripts.py b/modules/scripts.py index d945b89f..0c12ebd5 100644 --- a/modules/scripts.py +++ b/modules/scripts.py @@ -231,7 +231,7 @@ def load_scripts(): syspath = sys.path def register_scripts_from_module(module): - for key, script_class in module.__dict__.items(): + for script_class in module.__dict__.values(): if type(script_class) != type: continue @@ -295,9 +295,9 @@ class ScriptRunner: auto_processing_scripts = scripts_auto_postprocessing.create_auto_preprocessing_script_data() - for script_class, path, basedir, script_module in auto_processing_scripts + scripts_data: - script = script_class() - script.filename = path + for script_data in auto_processing_scripts + scripts_data: + script = script_data.script_class() + script.filename = script_data.path script.is_txt2img = not is_img2img script.is_img2img = is_img2img @@ -492,7 +492,7 @@ class ScriptRunner: module = script_loading.load_module(script.filename) cache[filename] = module - for key, script_class in module.__dict__.items(): + for script_class in module.__dict__.values(): if type(script_class) == type and issubclass(script_class, Script): self.scripts[si] = script_class() self.scripts[si].filename = filename diff --git a/modules/scripts_postprocessing.py b/modules/scripts_postprocessing.py index b11568c0..6751406c 100644 --- a/modules/scripts_postprocessing.py +++ b/modules/scripts_postprocessing.py @@ -66,9 +66,9 @@ class ScriptPostprocessingRunner: def initialize_scripts(self, scripts_data): self.scripts = [] - for script_class, path, basedir, script_module in scripts_data: - script: ScriptPostprocessing = script_class() - script.filename = path + for script_data in scripts_data: + script: ScriptPostprocessing = script_data.script_class() + script.filename = script_data.path if script.name == "Simple Upscale": continue @@ -124,7 +124,7 @@ class ScriptPostprocessingRunner: script_args = args[script.args_from:script.args_to] process_args = {} - for (name, component), value in zip(script.controls.items(), script_args): + for (name, component), value in zip(script.controls.items(), script_args): # noqa B007 process_args[name] = value script.process(pp, **process_args) diff --git a/modules/sd_hijack_clip.py b/modules/sd_hijack_clip.py index 9fa5c5c5..c0c350f6 100644 --- a/modules/sd_hijack_clip.py +++ b/modules/sd_hijack_clip.py @@ -223,7 +223,7 @@ class FrozenCLIPEmbedderWithCustomWordsBase(torch.nn.Module): self.hijack.fixes = [x.fixes for x in batch_chunk] for fixes in self.hijack.fixes: - for position, embedding in fixes: + for position, embedding in fixes: # noqa: B007 used_embeddings[embedding.name] = embedding z = self.process_tokens(tokens, multipliers) diff --git a/modules/shared.py b/modules/shared.py index e2691585..913c9e63 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -211,7 +211,7 @@ class OptionInfo: def options_section(section_identifier, options_dict): - for k, v in options_dict.items(): + for v in options_dict.values(): v.section = section_identifier return options_dict @@ -579,7 +579,7 @@ class Options: section_ids = {} settings_items = self.data_labels.items() - for k, item in settings_items: + for _, item in settings_items: if item.section not in section_ids: section_ids[item.section] = len(section_ids) @@ -740,7 +740,7 @@ def walk_files(path, allowed_extensions=None): if allowed_extensions is not None: allowed_extensions = set(allowed_extensions) - for root, dirs, files in os.walk(path): + for root, _, files in os.walk(path): for filename in files: if allowed_extensions is not None: _, ext = os.path.splitext(filename) diff --git a/modules/textual_inversion/learn_schedule.py b/modules/textual_inversion/learn_schedule.py index fda58898..c56bea45 100644 --- a/modules/textual_inversion/learn_schedule.py +++ b/modules/textual_inversion/learn_schedule.py @@ -12,7 +12,7 @@ class LearnScheduleIterator: self.it = 0 self.maxit = 0 try: - for i, pair in enumerate(pairs): + for pair in pairs: if not pair.strip(): continue tmp = pair.split(':') diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py index c37bb2ad..47035332 100644 --- a/modules/textual_inversion/textual_inversion.py +++ b/modules/textual_inversion/textual_inversion.py @@ -29,7 +29,7 @@ textual_inversion_templates = {} def list_textual_inversion_templates(): textual_inversion_templates.clear() - for root, dirs, fns in os.walk(shared.cmd_opts.textual_inversion_templates_dir): + for root, _, fns in os.walk(shared.cmd_opts.textual_inversion_templates_dir): for fn in fns: path = os.path.join(root, fn) @@ -198,7 +198,7 @@ class EmbeddingDatabase: if not os.path.isdir(embdir.path): return - for root, dirs, fns in os.walk(embdir.path, followlinks=True): + for root, _, fns in os.walk(embdir.path, followlinks=True): for fn in fns: try: fullfn = os.path.join(root, fn) @@ -215,7 +215,7 @@ class EmbeddingDatabase: def load_textual_inversion_embeddings(self, force_reload=False): if not force_reload: need_reload = False - for path, embdir in self.embedding_dirs.items(): + for embdir in self.embedding_dirs.values(): if embdir.has_changed(): need_reload = True break @@ -228,7 +228,7 @@ class EmbeddingDatabase: self.skipped_embeddings.clear() self.expected_shape = self.get_expected_shape() - for path, embdir in self.embedding_dirs.items(): + for embdir in self.embedding_dirs.values(): self.load_from_dir(embdir) embdir.update() @@ -469,7 +469,7 @@ def train_embedding(id_task, embedding_name, learn_rate, batch_size, gradient_st try: sd_hijack_checkpoint.add() - for i in range((steps-initial_step) * gradient_step): + for _ in range((steps-initial_step) * gradient_step): if scheduler.finished: break if shared.state.interrupted: diff --git a/modules/ui.py b/modules/ui.py index 84d661b2..83bfb7d8 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -416,7 +416,7 @@ def create_sampler_and_steps_selection(choices, tabname): def ordered_ui_categories(): user_order = {x.strip(): i * 2 + 1 for i, x in enumerate(shared.opts.ui_reorder.split(","))} - for i, category in sorted(enumerate(shared.ui_reorder_categories), key=lambda x: user_order.get(x[1], x[0] * 2 + 0)): + for _, category in sorted(enumerate(shared.ui_reorder_categories), key=lambda x: user_order.get(x[1], x[0] * 2 + 0)): yield category @@ -1646,7 +1646,7 @@ def create_ui(): with gr.Blocks(theme=shared.gradio_theme, analytics_enabled=False, title="Stable Diffusion") as demo: with gr.Row(elem_id="quicksettings", variant="compact"): - for i, k, item in sorted(quicksettings_list, key=lambda x: quicksettings_names.get(x[1], x[0])): + for _i, k, _item in sorted(quicksettings_list, key=lambda x: quicksettings_names.get(x[1], x[0])): component = create_setting_component(k, is_quicksettings=True) component_dict[k] = component @@ -1673,7 +1673,7 @@ def create_ui(): outputs=[text_settings, result], ) - for i, k, item in quicksettings_list: + for _i, k, _item in quicksettings_list: component = component_dict[k] info = opts.data_labels[k] diff --git a/modules/ui_extra_networks.py b/modules/ui_extra_networks.py index ab585917..2fd82e8e 100644 --- a/modules/ui_extra_networks.py +++ b/modules/ui_extra_networks.py @@ -90,7 +90,7 @@ class ExtraNetworksPage: subdirs = {} for parentdir in [os.path.abspath(x) for x in self.allowed_directories_for_previews()]: - for root, dirs, files in os.walk(parentdir): + for root, dirs, _ in os.walk(parentdir): for dirname in dirs: x = os.path.join(root, dirname) diff --git a/modules/ui_tempdir.py b/modules/ui_tempdir.py index cac73c51..f05049e1 100644 --- a/modules/ui_tempdir.py +++ b/modules/ui_tempdir.py @@ -72,7 +72,7 @@ def cleanup_tmpdr(): if temp_dir == "" or not os.path.isdir(temp_dir): return - for root, dirs, files in os.walk(temp_dir, topdown=False): + for root, _, files in os.walk(temp_dir, topdown=False): for name in files: _, extension = os.path.splitext(name) if extension != ".png": diff --git a/modules/upscaler.py b/modules/upscaler.py index e145be30..8acb6e96 100644 --- a/modules/upscaler.py +++ b/modules/upscaler.py @@ -55,7 +55,7 @@ class Upscaler: dest_w = int(img.width * scale) dest_h = int(img.height * scale) - for i in range(3): + for _ in range(3): shape = (img.width, img.height) img = self.do_upscale(img, selected_model) diff --git a/pyproject.toml b/pyproject.toml index 346a0cde..c88907be 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -20,7 +20,6 @@ ignore = [ "I001", # Import block is un-sorted or un-formatted "C901", # Function is too complex "C408", # Rewrite as a literal - "B007", # Loop control variable not used within loop body ] diff --git a/scripts/prompts_from_file.py b/scripts/prompts_from_file.py index 149bc85f..27af5ff6 100644 --- a/scripts/prompts_from_file.py +++ b/scripts/prompts_from_file.py @@ -156,7 +156,7 @@ class Script(scripts.Script): images = [] all_prompts = [] infotexts = [] - for n, args in enumerate(jobs): + for args in jobs: state.job = f"{state.job_no + 1} out of {state.job_count}" copy_p = copy.copy(p) diff --git a/scripts/sd_upscale.py b/scripts/sd_upscale.py index d873a09c..0b1d3096 100644 --- a/scripts/sd_upscale.py +++ b/scripts/sd_upscale.py @@ -56,7 +56,7 @@ class Script(scripts.Script): work = [] - for y, h, row in grid.tiles: + for _y, _h, row in grid.tiles: for tiledata in row: work.append(tiledata[2]) @@ -85,7 +85,7 @@ class Script(scripts.Script): work_results += processed.images image_index = 0 - for y, h, row in grid.tiles: + for _y, _h, row in grid.tiles: for tiledata in row: tiledata[2] = work_results[image_index] if image_index < len(work_results) else Image.new("RGB", (p.width, p.height)) image_index += 1 diff --git a/scripts/xyz_grid.py b/scripts/xyz_grid.py index 332e0ecd..38a20381 100644 --- a/scripts/xyz_grid.py +++ b/scripts/xyz_grid.py @@ -704,7 +704,7 @@ class Script(scripts.Script): if not include_sub_grids: # Done with sub-grids, drop all related information: - for sg in range(z_count): + for _ in range(z_count): del processed.images[1] del processed.all_prompts[1] del processed.all_seeds[1] -- cgit v1.2.3 From 51864790fd72386fbbbb015d24a43ce501ecaa4b Mon Sep 17 00:00:00 2001 From: Aarni Koskela Date: Fri, 2 Jun 2023 14:58:10 +0300 Subject: Simplify a bunch of `len(x) > 0`/`len(x) == 0` style expressions --- extensions-builtin/LDSR/sd_hijack_autoencoder.py | 3 ++- extensions-builtin/LDSR/sd_hijack_ddpm_v1.py | 4 ++-- extensions-builtin/Lora/extra_networks_lora.py | 4 ++-- extensions-builtin/Lora/lora.py | 4 ++-- .../extra-options-section/scripts/extra_options_section.py | 2 +- modules/api/api.py | 2 +- modules/call_queue.py | 2 +- modules/extra_networks_hypernet.py | 4 ++-- modules/generation_parameters_copypaste.py | 6 ++---- modules/images.py | 6 +++--- modules/img2img.py | 3 +-- modules/models/diffusion/ddpm_edit.py | 4 ++-- modules/processing.py | 3 ++- modules/prompt_parser.py | 6 +++--- modules/script_callbacks.py | 4 ++-- modules/sd_hijack_clip.py | 2 +- modules/sd_hijack_clip_old.py | 2 +- modules/textual_inversion/autocrop.py | 14 +++++++------- modules/textual_inversion/dataset.py | 2 +- modules/textual_inversion/preprocess.py | 4 ++-- modules/textual_inversion/textual_inversion.py | 2 +- modules/ui.py | 2 +- modules/ui_extensions.py | 5 +++-- modules/ui_settings.py | 2 +- scripts/prompts_from_file.py | 3 +-- 25 files changed, 47 insertions(+), 48 deletions(-) (limited to 'modules/prompt_parser.py') diff --git a/extensions-builtin/LDSR/sd_hijack_autoencoder.py b/extensions-builtin/LDSR/sd_hijack_autoencoder.py index 27a86e13..c29d274d 100644 --- a/extensions-builtin/LDSR/sd_hijack_autoencoder.py +++ b/extensions-builtin/LDSR/sd_hijack_autoencoder.py @@ -91,8 +91,9 @@ class VQModel(pl.LightningModule): del sd[k] missing, unexpected = self.load_state_dict(sd, strict=False) print(f"Restored from {path} with {len(missing)} missing and {len(unexpected)} unexpected keys") - if len(missing) > 0: + if missing: print(f"Missing Keys: {missing}") + if unexpected: print(f"Unexpected Keys: {unexpected}") def on_train_batch_end(self, *args, **kwargs): diff --git a/extensions-builtin/LDSR/sd_hijack_ddpm_v1.py b/extensions-builtin/LDSR/sd_hijack_ddpm_v1.py index 631a08ef..04adc5eb 100644 --- a/extensions-builtin/LDSR/sd_hijack_ddpm_v1.py +++ b/extensions-builtin/LDSR/sd_hijack_ddpm_v1.py @@ -195,9 +195,9 @@ class DDPMV1(pl.LightningModule): missing, unexpected = self.load_state_dict(sd, strict=False) if not only_model else self.model.load_state_dict( sd, strict=False) print(f"Restored from {path} with {len(missing)} missing and {len(unexpected)} unexpected keys") - if len(missing) > 0: + if missing: print(f"Missing Keys: {missing}") - if len(unexpected) > 0: + if unexpected: print(f"Unexpected Keys: {unexpected}") def q_mean_variance(self, x_start, t): diff --git a/extensions-builtin/Lora/extra_networks_lora.py b/extensions-builtin/Lora/extra_networks_lora.py index b5fea4d2..66ee9c85 100644 --- a/extensions-builtin/Lora/extra_networks_lora.py +++ b/extensions-builtin/Lora/extra_networks_lora.py @@ -9,14 +9,14 @@ class ExtraNetworkLora(extra_networks.ExtraNetwork): def activate(self, p, params_list): additional = shared.opts.sd_lora - if additional != "None" and additional in lora.available_loras and len([x for x in params_list if x.items[0] == additional]) == 0: + if additional != "None" and additional in lora.available_loras and not any(x for x in params_list if x.items[0] == additional): p.all_prompts = [x + f"" for x in p.all_prompts] params_list.append(extra_networks.ExtraNetworkParams(items=[additional, shared.opts.extra_networks_default_multiplier])) names = [] multipliers = [] for params in params_list: - assert len(params.items) > 0 + assert params.items names.append(params.items[0]) multipliers.append(float(params.items[1]) if len(params.items) > 1 else 1.0) diff --git a/extensions-builtin/Lora/lora.py b/extensions-builtin/Lora/lora.py index eec14712..af93991c 100644 --- a/extensions-builtin/Lora/lora.py +++ b/extensions-builtin/Lora/lora.py @@ -219,7 +219,7 @@ def load_lora(name, lora_on_disk): else: raise AssertionError(f"Bad Lora layer name: {key_diffusers} - must end in lora_up.weight, lora_down.weight or alpha") - if len(keys_failed_to_match) > 0: + if keys_failed_to_match: print(f"Failed to match keys when loading Lora {lora_on_disk.filename}: {keys_failed_to_match}") return lora @@ -267,7 +267,7 @@ def load_loras(names, multipliers=None): lora.multiplier = multipliers[i] if multipliers else 1.0 loaded_loras.append(lora) - if len(failed_to_load_loras) > 0: + if failed_to_load_loras: sd_hijack.model_hijack.comments.append("Failed to find Loras: " + ", ".join(failed_to_load_loras)) diff --git a/extensions-builtin/extra-options-section/scripts/extra_options_section.py b/extensions-builtin/extra-options-section/scripts/extra_options_section.py index 17f84184..a05e10d8 100644 --- a/extensions-builtin/extra-options-section/scripts/extra_options_section.py +++ b/extensions-builtin/extra-options-section/scripts/extra_options_section.py @@ -21,7 +21,7 @@ class ExtraOptionsSection(scripts.Script): self.setting_names = [] with gr.Blocks() as interface: - with gr.Accordion("Options", open=False) if shared.opts.extra_options_accordion and len(shared.opts.extra_options) > 0 else gr.Group(), gr.Row(): + with gr.Accordion("Options", open=False) if shared.opts.extra_options_accordion and shared.opts.extra_options else gr.Group(), gr.Row(): for setting_name in shared.opts.extra_options: with FormColumn(): comp = ui_settings.create_setting_component(setting_name) diff --git a/modules/api/api.py b/modules/api/api.py index d34ab422..555eefdb 100644 --- a/modules/api/api.py +++ b/modules/api/api.py @@ -280,7 +280,7 @@ class Api: script_args[0] = selectable_idx + 1 # Now check for always on scripts - if request.alwayson_scripts and (len(request.alwayson_scripts) > 0): + if request.alwayson_scripts: for alwayson_script_name in request.alwayson_scripts.keys(): alwayson_script = self.get_script(alwayson_script_name, script_runner) if alwayson_script is None: diff --git a/modules/call_queue.py b/modules/call_queue.py index 53af6d70..1b5e5273 100644 --- a/modules/call_queue.py +++ b/modules/call_queue.py @@ -21,7 +21,7 @@ def wrap_gradio_gpu_call(func, extra_outputs=None): def f(*args, **kwargs): # if the first argument is a string that says "task(...)", it is treated as a job id - if len(args) > 0 and type(args[0]) == str and args[0][0:5] == "task(" and args[0][-1] == ")": + if args and type(args[0]) == str and args[0].startswith("task(") and args[0].endswith(")"): id_task = args[0] progress.add_task_to_queue(id_task) else: diff --git a/modules/extra_networks_hypernet.py b/modules/extra_networks_hypernet.py index aa2a14ef..b6a6dc0e 100644 --- a/modules/extra_networks_hypernet.py +++ b/modules/extra_networks_hypernet.py @@ -9,7 +9,7 @@ class ExtraNetworkHypernet(extra_networks.ExtraNetwork): def activate(self, p, params_list): 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: + if additional != "None" and additional in shared.hypernetworks and not any(x for x in params_list if x.items[0] == additional): 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])) @@ -17,7 +17,7 @@ class ExtraNetworkHypernet(extra_networks.ExtraNetwork): names = [] multipliers = [] for params in params_list: - assert len(params.items) > 0 + assert params.items names.append(params.items[0]) multipliers.append(float(params.items[1]) if len(params.items) > 1 else 1.0) diff --git a/modules/generation_parameters_copypaste.py b/modules/generation_parameters_copypaste.py index 071bd9ea..237401a1 100644 --- a/modules/generation_parameters_copypaste.py +++ b/modules/generation_parameters_copypaste.py @@ -55,7 +55,7 @@ def image_from_url_text(filedata): if filedata is None: return None - if type(filedata) == list and len(filedata) > 0 and type(filedata[0]) == dict and filedata[0].get("is_file", False): + if type(filedata) == list and filedata and type(filedata[0]) == dict and filedata[0].get("is_file", False): filedata = filedata[0] if type(filedata) == dict and filedata.get("is_file", False): @@ -437,7 +437,7 @@ def connect_paste(button, paste_fields, input_comp, override_settings_component, vals_pairs = [f"{k}: {v}" for k, v in vals.items()] - return gr.Dropdown.update(value=vals_pairs, choices=vals_pairs, visible=len(vals_pairs) > 0) + return gr.Dropdown.update(value=vals_pairs, choices=vals_pairs, visible=bool(vals_pairs)) paste_fields = paste_fields + [(override_settings_component, paste_settings)] @@ -454,5 +454,3 @@ def connect_paste(button, paste_fields, input_comp, override_settings_component, outputs=[], show_progress=False, ) - - diff --git a/modules/images.py b/modules/images.py index a12d252b..7bbfc3e0 100644 --- a/modules/images.py +++ b/modules/images.py @@ -406,7 +406,7 @@ class FilenameGenerator: prompt_no_style = self.prompt for style in shared.prompt_styles.get_style_prompts(self.p.styles): - if len(style) > 0: + if style: for part in style.split("{prompt}"): prompt_no_style = prompt_no_style.replace(part, "").replace(", ,", ",").strip().strip(',') @@ -415,7 +415,7 @@ class FilenameGenerator: return sanitize_filename_part(prompt_no_style, replace_spaces=False) def prompt_words(self): - words = [x for x in re_nonletters.split(self.prompt or "") if len(x) > 0] + words = [x for x in re_nonletters.split(self.prompt or "") if x] if len(words) == 0: words = ["empty"] return sanitize_filename_part(" ".join(words[0:opts.directories_max_prompt_words]), replace_spaces=False) @@ -423,7 +423,7 @@ class FilenameGenerator: def datetime(self, *args): time_datetime = datetime.datetime.now() - time_format = args[0] if len(args) > 0 and args[0] != "" else self.default_time_format + time_format = args[0] if (args 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: diff --git a/modules/img2img.py b/modules/img2img.py index 4c12c2c5..35c4facc 100644 --- a/modules/img2img.py +++ b/modules/img2img.py @@ -21,8 +21,7 @@ def process_batch(p, input_dir, output_dir, inpaint_mask_dir, args): is_inpaint_batch = False if inpaint_mask_dir: inpaint_masks = shared.listfiles(inpaint_mask_dir) - is_inpaint_batch = len(inpaint_masks) > 0 - if is_inpaint_batch: + is_inpaint_batch = bool(inpaint_masks) print(f"\nInpaint batch is enabled. {len(inpaint_masks)} masks found.") print(f"Will process {len(images)} images, creating {p.n_iter * p.batch_size} new images for each.") diff --git a/modules/models/diffusion/ddpm_edit.py b/modules/models/diffusion/ddpm_edit.py index 3fb76b65..b892d5fc 100644 --- a/modules/models/diffusion/ddpm_edit.py +++ b/modules/models/diffusion/ddpm_edit.py @@ -230,9 +230,9 @@ class DDPM(pl.LightningModule): missing, unexpected = self.load_state_dict(sd, strict=False) if not only_model else self.model.load_state_dict( sd, strict=False) print(f"Restored from {path} with {len(missing)} missing and {len(unexpected)} unexpected keys") - if len(missing) > 0: + if missing: print(f"Missing Keys: {missing}") - if len(unexpected) > 0: + if unexpected: print(f"Unexpected Keys: {unexpected}") def q_mean_variance(self, x_start, t): diff --git a/modules/processing.py b/modules/processing.py index 362ab4c2..9ebdb549 100644 --- a/modules/processing.py +++ b/modules/processing.py @@ -975,7 +975,8 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing): latent_scale_mode = shared.latent_upscale_modes.get(self.hr_upscaler, None) if self.hr_upscaler is not None else shared.latent_upscale_modes.get(shared.latent_upscale_default_mode, "nearest") if self.enable_hr and latent_scale_mode is None: - assert len([x for x in shared.sd_upscalers if x.name == self.hr_upscaler]) > 0, f"could not find upscaler named {self.hr_upscaler}" + 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}") 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) samples = self.sampler.sample(self, x, conditioning, unconditional_conditioning, image_conditioning=self.txt2img_image_conditioning(x)) diff --git a/modules/prompt_parser.py b/modules/prompt_parser.py index b4aff704..0069d8b0 100644 --- a/modules/prompt_parser.py +++ b/modules/prompt_parser.py @@ -336,11 +336,11 @@ def parse_prompt_attention(text): round_brackets.append(len(res)) elif text == '[': square_brackets.append(len(res)) - elif weight is not None and len(round_brackets) > 0: + elif weight is not None and round_brackets: multiply_range(round_brackets.pop(), float(weight)) - elif text == ')' and len(round_brackets) > 0: + elif text == ')' and round_brackets: multiply_range(round_brackets.pop(), round_bracket_multiplier) - elif text == ']' and len(square_brackets) > 0: + elif text == ']' and square_brackets: multiply_range(square_brackets.pop(), square_bracket_multiplier) else: parts = re.split(re_break, text) diff --git a/modules/script_callbacks.py b/modules/script_callbacks.py index f755283c..77ee55ee 100644 --- a/modules/script_callbacks.py +++ b/modules/script_callbacks.py @@ -287,14 +287,14 @@ def list_unets_callback(): def add_callback(callbacks, fun): stack = [x for x in inspect.stack() if x.filename != __file__] - filename = stack[0].filename if len(stack) > 0 else 'unknown file' + filename = stack[0].filename if stack else 'unknown file' callbacks.append(ScriptCallback(filename, fun)) def remove_current_script_callbacks(): stack = [x for x in inspect.stack() if x.filename != __file__] - filename = stack[0].filename if len(stack) > 0 else 'unknown file' + filename = stack[0].filename if stack else 'unknown file' if filename == 'unknown file': return for callback_list in callback_map.values(): diff --git a/modules/sd_hijack_clip.py b/modules/sd_hijack_clip.py index cc6e8c21..3b5a7666 100644 --- a/modules/sd_hijack_clip.py +++ b/modules/sd_hijack_clip.py @@ -167,7 +167,7 @@ class FrozenCLIPEmbedderWithCustomWordsBase(torch.nn.Module): chunk.multipliers += [weight] * emb_len position += embedding_length_in_tokens - if len(chunk.tokens) > 0 or len(chunks) == 0: + if chunk.tokens or not chunks: next_chunk(is_last=True) return chunks, token_count diff --git a/modules/sd_hijack_clip_old.py b/modules/sd_hijack_clip_old.py index a3476e95..c5c6270b 100644 --- a/modules/sd_hijack_clip_old.py +++ b/modules/sd_hijack_clip_old.py @@ -74,7 +74,7 @@ def forward_old(self: sd_hijack_clip.FrozenCLIPEmbedderWithCustomWordsBase, text self.hijack.comments += hijack_comments - if len(used_custom_terms) > 0: + if 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}") diff --git a/modules/textual_inversion/autocrop.py b/modules/textual_inversion/autocrop.py index 8e667a4d..75705459 100644 --- a/modules/textual_inversion/autocrop.py +++ b/modules/textual_inversion/autocrop.py @@ -77,27 +77,27 @@ def focal_point(im, settings): pois = [] weight_pref_total = 0 - if len(corner_points) > 0: + if corner_points: weight_pref_total += settings.corner_points_weight - if len(entropy_points) > 0: + if entropy_points: weight_pref_total += settings.entropy_points_weight - if len(face_points) > 0: + if face_points: weight_pref_total += settings.face_points_weight corner_centroid = None - if len(corner_points) > 0: + if corner_points: corner_centroid = centroid(corner_points) corner_centroid.weight = settings.corner_points_weight / weight_pref_total pois.append(corner_centroid) entropy_centroid = None - if len(entropy_points) > 0: + if entropy_points: entropy_centroid = centroid(entropy_points) entropy_centroid.weight = settings.entropy_points_weight / weight_pref_total pois.append(entropy_centroid) face_centroid = None - if len(face_points) > 0: + if face_points: face_centroid = centroid(face_points) face_centroid.weight = settings.face_points_weight / weight_pref_total pois.append(face_centroid) @@ -187,7 +187,7 @@ def image_face_points(im, settings): except Exception: continue - if len(faces) > 0: + if faces: rects = [[f[0], f[1], f[0] + f[2], f[1] + f[3]] for f in faces] return [PointOfInterest((r[0] +r[2]) // 2, (r[1] + r[3]) // 2, size=abs(r[0]-r[2]), weight=1/len(rects)) for r in rects] return [] diff --git a/modules/textual_inversion/dataset.py b/modules/textual_inversion/dataset.py index b9621fc9..7ee05061 100644 --- a/modules/textual_inversion/dataset.py +++ b/modules/textual_inversion/dataset.py @@ -32,7 +32,7 @@ class DatasetEntry: class PersonalizedBase(Dataset): def __init__(self, data_root, width, height, repeats, flip_p=0.5, placeholder_token="*", model=None, cond_model=None, device=None, template_file=None, include_cond=False, batch_size=1, gradient_step=1, shuffle_tags=False, tag_drop_out=0, latent_sampling_method='once', varsize=False, use_weight=False): - re_word = re.compile(shared.opts.dataset_filename_word_regex) if len(shared.opts.dataset_filename_word_regex) > 0 else None + re_word = re.compile(shared.opts.dataset_filename_word_regex) if shared.opts.dataset_filename_word_regex else None self.placeholder_token = placeholder_token diff --git a/modules/textual_inversion/preprocess.py b/modules/textual_inversion/preprocess.py index a009d8e8..0d4c3f84 100644 --- a/modules/textual_inversion/preprocess.py +++ b/modules/textual_inversion/preprocess.py @@ -47,7 +47,7 @@ def save_pic_with_caption(image, index, params: PreprocessParams, existing_capti caption += shared.interrogator.generate_caption(image) if params.process_caption_deepbooru: - if len(caption) > 0: + if caption: caption += ", " caption += deepbooru.model.tag_multi(image) @@ -67,7 +67,7 @@ def save_pic_with_caption(image, index, params: PreprocessParams, existing_capti caption = caption.strip() - if len(caption) > 0: + if caption: with open(os.path.join(params.dstdir, f"{basename}.txt"), "w", encoding="utf8") as file: file.write(caption) diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py index 8da050ca..bb6f211c 100644 --- a/modules/textual_inversion/textual_inversion.py +++ b/modules/textual_inversion/textual_inversion.py @@ -251,7 +251,7 @@ class EmbeddingDatabase: if self.previously_displayed_embeddings != displayed_embeddings: self.previously_displayed_embeddings = displayed_embeddings print(f"Textual inversion embeddings loaded({len(self.word_embeddings)}): {', '.join(self.word_embeddings.keys())}") - if len(self.skipped_embeddings) > 0: + if self.skipped_embeddings: print(f"Textual inversion embeddings skipped({len(self.skipped_embeddings)}): {', '.join(self.skipped_embeddings.keys())}") def find_embedding_at_position(self, tokens, offset): diff --git a/modules/ui.py b/modules/ui.py index b7459f08..9a025cca 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -398,7 +398,7 @@ def create_override_settings_dropdown(tabname, row): dropdown = gr.Dropdown([], label="Override settings", visible=False, elem_id=f"{tabname}_override_settings", multiselect=True) dropdown.change( - fn=lambda x: gr.Dropdown.update(visible=len(x) > 0), + fn=lambda x: gr.Dropdown.update(visible=bool(x)), inputs=[dropdown], outputs=[dropdown], ) diff --git a/modules/ui_extensions.py b/modules/ui_extensions.py index 3140ed64..65173e06 100644 --- a/modules/ui_extensions.py +++ b/modules/ui_extensions.py @@ -333,7 +333,8 @@ def install_extension_from_url(dirname, url, branch_name=None): assert not os.path.exists(target_dir), f'Extension directory already exists: {target_dir}' normalized_url = normalize_git_url(url) - assert len([x for x in extensions.extensions if normalize_git_url(x.remote) == normalized_url]) == 0, 'Extension with this URL is already installed' + if any(x for x in extensions.extensions if normalize_git_url(x.remote) == normalized_url): + raise Exception(f'Extension with this URL is already installed: {url}') tmpdir = os.path.join(paths.data_path, "tmp", dirname) @@ -449,7 +450,7 @@ def refresh_available_extensions_from_data(hide_tags, sort_column, filter_text=" existing = installed_extension_urls.get(normalize_git_url(url), None) extension_tags = extension_tags + ["installed"] if existing else extension_tags - if len([x for x in extension_tags if x in tags_to_hide]) > 0: + if any(x for x in extension_tags if x in tags_to_hide): hidden += 1 continue diff --git a/modules/ui_settings.py b/modules/ui_settings.py index 7874298e..2688d8c2 100644 --- a/modules/ui_settings.py +++ b/modules/ui_settings.py @@ -81,7 +81,7 @@ class UiSettings: opts.save(shared.config_filename) except RuntimeError: return opts.dumpjson(), f'{len(changed)} settings changed without save: {", ".join(changed)}.' - return opts.dumpjson(), f'{len(changed)} settings changed{": " if len(changed) > 0 else ""}{", ".join(changed)}.' + return opts.dumpjson(), f'{len(changed)} settings changed{": " if changed else ""}{", ".join(changed)}.' def run_settings_single(self, value, key): if not opts.same_type(value, opts.data_labels[key].default): diff --git a/scripts/prompts_from_file.py b/scripts/prompts_from_file.py index 83a2f220..50320d55 100644 --- a/scripts/prompts_from_file.py +++ b/scripts/prompts_from_file.py @@ -121,8 +121,7 @@ class Script(scripts.Script): return [checkbox_iterate, checkbox_iterate_batch, prompt_txt] def run(self, p, checkbox_iterate, checkbox_iterate_batch, prompt_txt: str): - lines = [x.strip() for x in prompt_txt.splitlines()] - lines = [x for x in lines if len(x) > 0] + lines = [x for x in (x.strip() for x in prompt_txt.splitlines()) if x] p.do_not_save_grid = True -- cgit v1.2.3