diff options
Diffstat (limited to 'modules/modelloader.py')
| -rw-r--r-- | modules/modelloader.py | 92 |
1 files changed, 41 insertions, 51 deletions
diff --git a/modules/modelloader.py b/modules/modelloader.py index 098bcb79..e100bb24 100644 --- a/modules/modelloader.py +++ b/modules/modelloader.py @@ -1,13 +1,20 @@ from __future__ import annotations -import os -import shutil import importlib +import logging +import os +from typing import TYPE_CHECKING from urllib.parse import urlparse +import torch + from modules import shared from modules.upscaler import Upscaler, UpscalerLanczos, UpscalerNearest, UpscalerNone -from modules.paths import script_path, models_path + +if TYPE_CHECKING: + import spandrel + +logger = logging.getLogger(__name__) def load_file_from_url( @@ -90,54 +97,6 @@ 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__ @@ -177,3 +136,34 @@ def load_upscalers(): # Special case for UpscalerNone keeps it at the beginning of the list. key=lambda x: x.name.lower() if not isinstance(x.scaler, (UpscalerNone, UpscalerLanczos, UpscalerNearest)) else "" ) + + +def load_spandrel_model( + path: str | os.PathLike, + *, + device: str | torch.device | None, + prefer_half: bool = False, + dtype: str | torch.dtype | None = None, + expected_architecture: str | None = None, +) -> spandrel.ModelDescriptor: + import spandrel + model_descriptor = spandrel.ModelLoader(device=device).load_from_file(str(path)) + if expected_architecture and model_descriptor.architecture != expected_architecture: + logger.warning( + f"Model {path!r} is not a {expected_architecture!r} model (got {model_descriptor.architecture!r})", + ) + half = False + if prefer_half: + if model_descriptor.supports_half: + model_descriptor.model.half() + half = True + else: + logger.info("Model %s does not support half precision, ignoring --half", path) + if dtype: + model_descriptor.model.to(dtype=dtype) + model_descriptor.model.eval() + logger.debug( + "Loaded %s from %s (device=%s, half=%s, dtype=%s)", + model_descriptor, path, device, half, dtype, + ) + return model_descriptor |