From 345028099d893f8a66726cfd13627d8cc1bcc724 Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Sat, 3 Sep 2022 12:08:45 +0300 Subject: split codebase into multiple files; to anyone this affects negatively: sorry --- modules/shared.py | 121 ++++++++++++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 121 insertions(+) create mode 100644 modules/shared.py (limited to 'modules/shared.py') diff --git a/modules/shared.py b/modules/shared.py new file mode 100644 index 00000000..33a08559 --- /dev/null +++ b/modules/shared.py @@ -0,0 +1,121 @@ +import argparse +import json +import os +import gradio as gr +import torch + +from modules.paths import script_path, sd_path + +config_filename = "config.json" + +sd_model_file = os.path.join(script_path, 'model.ckpt') +if not os.path.exists(sd_model_file): + sd_model_file = "models/ldm/stable-diffusion-v1/model.ckpt" + +parser = argparse.ArgumentParser() +parser.add_argument("--config", type=str, default=os.path.join(sd_path, "configs/stable-diffusion/v1-inference.yaml"), help="path to config which constructs model",) +parser.add_argument("--ckpt", type=str, default=os.path.join(sd_path, sd_model_file), help="path to checkpoint of model",) +parser.add_argument("--gfpgan-dir", type=str, help="GFPGAN directory", default=('./src/gfpgan' if os.path.exists('./src/gfpgan') else './GFPGAN')) +parser.add_argument("--gfpgan-model", type=str, help="GFPGAN model file name", default='GFPGANv1.3.pth') +parser.add_argument("--no-half", action='store_true', help="do not switch the model to 16-bit floats") +parser.add_argument("--no-progressbar-hiding", action='store_true', help="do not hide progressbar in gradio UI (we hide it because it slows down ML if you have hardware accleration in browser)") +parser.add_argument("--max-batch-count", type=int, default=16, help="maximum batch count value for the UI") +parser.add_argument("--embeddings-dir", type=str, default='embeddings', help="embeddings dirtectory for textual inversion (default: embeddings)") +parser.add_argument("--allow-code", action='store_true', help="allow custom script execution from webui") +parser.add_argument("--medvram", action='store_true', help="enable stable diffusion model optimizations for sacrficing a little speed for low VRM usage") +parser.add_argument("--lowvram", action='store_true', help="enable stable diffusion model optimizations for sacrficing a lot of speed for very low VRM usage") +parser.add_argument("--always-batch-cond-uncond", action='store_true', help="a workaround test; may help with speed in you use --lowvram") +parser.add_argument("--precision", type=str, help="evaluate at this precision", choices=["full", "autocast"], default="autocast") +parser.add_argument("--share", action='store_true', help="use share=True for gradio and make the UI accessible through their site (doesn't work for me but you might have better luck)") +cmd_opts = parser.parse_args() + +cpu = torch.device("cpu") +gpu = torch.device("cuda") +device = gpu if torch.cuda.is_available() else cpu +batch_cond_uncond = cmd_opts.always_batch_cond_uncond or not (cmd_opts.lowvram or cmd_opts.medvram) + +class State: + interrupted = False + job = "" + + def interrupt(self): + self.interrupted = True + +state = State() + + +class Options: + class OptionInfo: + def __init__(self, default=None, label="", component=None, component_args=None): + self.default = default + self.label = label + self.component = component + self.component_args = component_args + + data = None + data_labels = { + "outdir_samples": OptionInfo("", "Output dictectory for images; if empty, defaults to two directories below"), + "outdir_txt2img_samples": OptionInfo("outputs/txt2img-images", 'Output dictectory for txt2img images'), + "outdir_img2img_samples": OptionInfo("outputs/img2img-images", 'Output dictectory for img2img images'), + "outdir_extras_samples": OptionInfo("outputs/extras-images", 'Output dictectory for images from extras tab'), + "outdir_grids": OptionInfo("", "Output dictectory for grids; if empty, defaults to two directories below"), + "outdir_txt2img_grids": OptionInfo("outputs/txt2img-grids", 'Output dictectory for txt2img grids'), + "outdir_img2img_grids": OptionInfo("outputs/img2img-grids", 'Output dictectory for img2img grids'), + "save_to_dirs": OptionInfo(False, "When writing images/grids, create a directory with name derived from the prompt"), + "save_to_dirs_prompt_len": OptionInfo(10, "When using above, how many words from prompt to put into directory name", gr.Slider, {"minimum": 1, "maximum": 32, "step": 1}), + "outdir_save": OptionInfo("log/images", "Directory for saving images using the Save button"), + "samples_save": OptionInfo(True, "Save indiviual samples"), + "samples_format": OptionInfo('png', 'File format for indiviual samples'), + "grid_save": OptionInfo(True, "Save image grids"), + "return_grid": OptionInfo(True, "Show grid in results for web"), + "grid_format": OptionInfo('png', 'File format for grids'), + "grid_extended_filename": OptionInfo(False, "Add extended info (seed, prompt) to filename when saving grid"), + "grid_only_if_multiple": OptionInfo(True, "Do not save grids consisting of one picture"), + "n_rows": OptionInfo(-1, "Grid row count; use -1 for autodetect and 0 for it to be same as batch size", gr.Slider, {"minimum": -1, "maximum": 16, "step": 1}), + "jpeg_quality": OptionInfo(80, "Quality for saved jpeg images", gr.Slider, {"minimum": 1, "maximum": 100, "step": 1}), + "export_for_4chan": OptionInfo(True, "If PNG image is larger than 4MB or any dimension is larger than 4000, downscale and save copy as JPG"), + "enable_pnginfo": OptionInfo(True, "Save text information about generation parameters as chunks to png files"), + "font": OptionInfo("arial.ttf", "Font for image grids that have text"), + "prompt_matrix_add_to_start": OptionInfo(True, "In prompt matrix, add the variable combination of text to the start of the prompt, rather than the end"), + "enable_emphasis": OptionInfo(True, "Use (text) to make model pay more attention to text text and [text] to make it pay less attention"), + "save_txt": OptionInfo(False, "Create a text file next to every image with generation parameters."), + + } + + def __init__(self): + self.data = {k: v.default for k, v in self.data_labels.items()} + + def __setattr__(self, key, value): + if self.data is not None: + if key in self.data: + self.data[key] = value + + return super(Options, self).__setattr__(key, value) + + def __getattr__(self, item): + if self.data is not None: + if item in self.data: + return self.data[item] + + if item in self.data_labels: + return self.data_labels[item].default + + return super(Options, self).__getattribute__(item) + + def save(self, filename): + with open(filename, "w", encoding="utf8") as file: + json.dump(self.data, file) + + def load(self, filename): + with open(filename, "r", encoding="utf8") as file: + self.data = json.load(file) + + +opts = Options() +if os.path.exists(config_filename): + opts.load(config_filename) + + +sd_upscalers = {} + +sd_model = None -- cgit v1.2.1