From 5fbb13e0da8eb2e26bd2c45ec8ffbb2de669ef47 Mon Sep 17 00:00:00 2001 From: Aarni Koskela Date: Sat, 30 Dec 2023 20:46:44 +0200 Subject: [PATCH] Remove `cleanup_models` code --- modules/initialize.py | 3 --- modules/modelloader.py | 50 ------------------------------------------ 2 files changed, 53 deletions(-) diff --git a/modules/initialize.py b/modules/initialize.py index ac95fc6f0..4a3cd98cf 100644 --- a/modules/initialize.py +++ b/modules/initialize.py @@ -54,9 +54,6 @@ def initialize(): initialize_util.configure_sigint_handler() initialize_util.configure_opts_onchange() - from modules import modelloader - modelloader.cleanup_models() - from modules import sd_models sd_models.setup_model() startup_timer.record("setup SD model") diff --git a/modules/modelloader.py b/modules/modelloader.py index f4182559e..5f7aec3e4 100644 --- a/modules/modelloader.py +++ b/modules/modelloader.py @@ -2,7 +2,6 @@ from __future__ import annotations import logging import os -import shutil import importlib from urllib.parse import urlparse @@ -10,7 +9,6 @@ import torch from modules import shared from modules.upscaler import Upscaler, UpscalerLanczos, UpscalerNearest, UpscalerNone -from modules.paths import script_path, models_path logger = logging.getLogger(__name__) @@ -96,54 +94,6 @@ def friendly_name(file: str): return model_name -def cleanup_models(): - # This code could probably be more efficient if we used a tuple list or something to store the src/destinations - # and then enumerate that, but this works for now. In the future, it'd be nice to just have every "model" scaler - # somehow auto-register and just do these things... - root_path = script_path - src_path = models_path - dest_path = os.path.join(models_path, "Stable-diffusion") - move_files(src_path, dest_path, ".ckpt") - move_files(src_path, dest_path, ".safetensors") - src_path = os.path.join(root_path, "ESRGAN") - dest_path = os.path.join(models_path, "ESRGAN") - move_files(src_path, dest_path) - src_path = os.path.join(models_path, "BSRGAN") - dest_path = os.path.join(models_path, "ESRGAN") - move_files(src_path, dest_path, ".pth") - src_path = os.path.join(root_path, "gfpgan") - dest_path = os.path.join(models_path, "GFPGAN") - move_files(src_path, dest_path) - src_path = os.path.join(root_path, "SwinIR") - dest_path = os.path.join(models_path, "SwinIR") - move_files(src_path, dest_path) - src_path = os.path.join(root_path, "repositories/latent-diffusion/experiments/pretrained_models/") - dest_path = os.path.join(models_path, "LDSR") - move_files(src_path, dest_path) - - -def move_files(src_path: str, dest_path: str, ext_filter: str = None): - try: - os.makedirs(dest_path, exist_ok=True) - if os.path.exists(src_path): - for file in os.listdir(src_path): - fullpath = os.path.join(src_path, file) - if os.path.isfile(fullpath): - if ext_filter is not None: - if ext_filter not in file: - continue - print(f"Moving {file} from {src_path} to {dest_path}.") - try: - shutil.move(fullpath, dest_path) - except Exception: - pass - if len(os.listdir(src_path)) == 0: - print(f"Removing empty folder: {src_path}") - shutil.rmtree(src_path, True) - except Exception: - pass - - def load_upscalers(): # We can only do this 'magic' method to dynamically load upscalers if they are referenced, # so we'll try to import any _model.py files before looking in __subclasses__