mirror of
https://github.com/invoke-ai/InvokeAI.git
synced 2026-04-23 03:00:31 -04:00
adjust non-app modules to use new config system
This commit is contained in:
@@ -44,28 +44,29 @@ from ...frontend.install.widgets import (
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IntTitleSlider,
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set_min_terminal_size,
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)
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from ..args import PRECISION_CHOICES, Args
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from ..globals import Globals, global_cache_dir, global_config_dir, global_config_file
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from .model_install_backend import (
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default_dataset,
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download_from_hf,
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hf_download_with_resume,
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recommended_datasets,
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)
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from invokeai.app.services.config import get_invokeai_config()
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warnings.filterwarnings("ignore")
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transformers.logging.set_verbosity_error()
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# --------------------------globals-----------------------
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config = get_invokeai_config()
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Model_dir = "models"
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Weights_dir = "ldm/stable-diffusion-v1/"
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# the initial "configs" dir is now bundled in the `invokeai.configs` package
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Dataset_path = Path(configs.__path__[0]) / "INITIAL_MODELS.yaml"
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Default_config_file = Path(global_config_dir()) / "models.yaml"
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SD_Configs = Path(global_config_dir()) / "stable-diffusion"
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Default_config_file = config.model_conf_path
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SD_Configs = config.legacy_conf_path
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Datasets = OmegaConf.load(Dataset_path)
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@@ -73,6 +74,8 @@ Datasets = OmegaConf.load(Dataset_path)
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MIN_COLS = 135
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MIN_LINES = 45
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PRECISION_CHOICES = ['auto','float16','float32','autocast']
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INIT_FILE_PREAMBLE = """# InvokeAI initialization file
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# This is the InvokeAI initialization file, which contains command-line default values.
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# Feel free to edit. If anything goes wrong, you can re-initialize this file by deleting
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@@ -103,7 +106,7 @@ Command-line interface:
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invokeai
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If you installed using an installation script, run:
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{Globals.root}/invoke.{"bat" if sys.platform == "win32" else "sh"}
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{config.root}/invoke.{"bat" if sys.platform == "win32" else "sh"}
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Add the '--help' argument to see all of the command-line switches available for use.
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"""
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@@ -216,11 +219,11 @@ def download_realesrgan():
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wdn_model_url = "https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.5.0/realesr-general-wdn-x4v3.pth"
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model_dest = os.path.join(
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Globals.root, "models/realesrgan/realesr-general-x4v3.pth"
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config.root, "models/realesrgan/realesr-general-x4v3.pth"
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)
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wdn_model_dest = os.path.join(
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Globals.root, "models/realesrgan/realesr-general-wdn-x4v3.pth"
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config.root, "models/realesrgan/realesr-general-wdn-x4v3.pth"
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)
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download_with_progress_bar(model_url, model_dest, "RealESRGAN")
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@@ -243,7 +246,7 @@ def download_gfpgan():
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"./models/gfpgan/weights/parsing_parsenet.pth",
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],
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):
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model_url, model_dest = model[0], os.path.join(Globals.root, model[1])
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model_url, model_dest = model[0], os.path.join(config.root, model[1])
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download_with_progress_bar(model_url, model_dest, "GFPGAN weights")
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@@ -253,7 +256,7 @@ def download_codeformer():
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model_url = (
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"https://github.com/sczhou/CodeFormer/releases/download/v0.1.0/codeformer.pth"
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)
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model_dest = os.path.join(Globals.root, "models/codeformer/codeformer.pth")
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model_dest = os.path.join(config.root, "models/codeformer/codeformer.pth")
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download_with_progress_bar(model_url, model_dest, "CodeFormer")
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@@ -306,7 +309,7 @@ def download_vaes():
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if not hf_download_with_resume(
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repo_id=repo_id,
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model_name=model_name,
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model_dir=str(Globals.root / Model_dir / Weights_dir),
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model_dir=str(config.root / Model_dir / Weights_dir),
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):
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raise Exception(f"download of {model_name} failed")
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except Exception as e:
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@@ -321,8 +324,7 @@ def get_root(root: str = None) -> str:
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elif os.environ.get("INVOKEAI_ROOT"):
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return os.environ.get("INVOKEAI_ROOT")
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else:
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return Globals.root
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return config.root
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# -------------------------------------
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class editOptsForm(npyscreen.FormMultiPage):
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@@ -332,7 +334,7 @@ class editOptsForm(npyscreen.FormMultiPage):
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def create(self):
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program_opts = self.parentApp.program_opts
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old_opts = self.parentApp.invokeai_opts
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first_time = not (Globals.root / Globals.initfile).exists()
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first_time = not (config.root / 'invokeai.init').exists()
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access_token = HfFolder.get_token()
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window_width, window_height = get_terminal_size()
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for i in [
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@@ -384,7 +386,7 @@ class editOptsForm(npyscreen.FormMultiPage):
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self.safety_checker = self.add_widget_intelligent(
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npyscreen.Checkbox,
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name="NSFW checker",
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value=old_opts.safety_checker,
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value=old_opts.nsfw_checker,
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relx=5,
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scroll_exit=True,
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)
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@@ -438,14 +440,7 @@ class editOptsForm(npyscreen.FormMultiPage):
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self.xformers = self.add_widget_intelligent(
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npyscreen.Checkbox,
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name="Enable xformers support if available",
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value=old_opts.xformers,
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relx=5,
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scroll_exit=True,
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)
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self.ckpt_convert = self.add_widget_intelligent(
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npyscreen.Checkbox,
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name="Load legacy checkpoint models into memory as diffusers models",
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value=old_opts.ckpt_convert,
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value=old_opts.xformers_enabled,
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relx=5,
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scroll_exit=True,
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)
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@@ -583,7 +578,6 @@ class editOptsForm(npyscreen.FormMultiPage):
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"xformers",
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"always_use_cpu",
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"embedding_path",
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"ckpt_convert",
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]:
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setattr(new_opts, attr, getattr(self, attr).value)
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@@ -628,15 +622,14 @@ def edit_opts(program_opts: Namespace, invokeai_opts: Namespace) -> argparse.Nam
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def default_startup_options(init_file: Path) -> Namespace:
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opts = Args().parse_args([])
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opts = InvokeAIAppConfig(argv=[])
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outdir = Path(opts.outdir)
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if not outdir.is_absolute():
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opts.outdir = str(Globals.root / opts.outdir)
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opts.outdir = str(config.root / opts.outdir)
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if not init_file.exists():
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opts.safety_checker = True
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opts.nsfw_checker = True
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return opts
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def default_user_selections(program_opts: Namespace) -> Namespace:
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return Namespace(
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starter_models=default_dataset()
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@@ -724,7 +717,6 @@ def write_opts(opts: Namespace, init_file: Path):
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--max_loaded_models={int(opts.max_loaded_models)}
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--{'no-' if not opts.safety_checker else ''}nsfw_checker
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--{'no-' if not opts.xformers else ''}xformers
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--{'no-' if not opts.ckpt_convert else ''}ckpt_convert
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{'--free_gpu_mem' if opts.free_gpu_mem else ''}
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{'--always_use_cpu' if opts.always_use_cpu else ''}
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"""
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@@ -740,13 +732,11 @@ def write_opts(opts: Namespace, init_file: Path):
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# -------------------------------------
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def default_output_dir() -> Path:
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return Globals.root / "outputs"
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return config.root / "outputs"
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# -------------------------------------
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def default_embedding_dir() -> Path:
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return Globals.root / "embeddings"
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return config.root / "embeddings"
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# -------------------------------------
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def write_default_options(program_opts: Namespace, initfile: Path):
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@@ -810,7 +800,7 @@ def main():
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opt = parser.parse_args()
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# setting a global here
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Globals.root = Path(os.path.expanduser(get_root(opt.root) or ""))
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config.root = Path(os.path.expanduser(get_root(opt.root) or ""))
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errors = set()
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@@ -818,9 +808,10 @@ def main():
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models_to_download = default_user_selections(opt)
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# We check for to see if the runtime directory is correctly initialized.
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init_file = Path(Globals.root, Globals.initfile)
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if not init_file.exists() or not global_config_file().exists():
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initialize_rootdir(Globals.root, opt.yes_to_all)
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print('** invokeai.init init file is no longer supported. Migrate this code to invokeai.yaml **')
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init_file = Path(config.root, 'invokeai.init')
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if not init_file.exists() or not config.model_conf_path.exists():
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initialize_rootdir(config.root, opt.yes_to_all)
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if opt.yes_to_all:
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write_default_options(opt, init_file)
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@@ -19,13 +19,15 @@ from tqdm import tqdm
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import invokeai.configs as configs
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from ..globals import Globals, global_cache_dir, global_config_dir
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from invokeai.app.services.config import get_invokeai_config()
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from ..model_management import ModelManager
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from ..stable_diffusion import StableDiffusionGeneratorPipeline
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warnings.filterwarnings("ignore")
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# --------------------------globals-----------------------
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config = get_invokeai_config()
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Model_dir = "models"
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Weights_dir = "ldm/stable-diffusion-v1/"
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@@ -47,12 +49,11 @@ Config_preamble = """
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def default_config_file():
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return Path(global_config_dir()) / "models.yaml"
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return config.model_conf_path
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def sd_configs():
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return Path(global_config_dir()) / "stable-diffusion"
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return config.legacy_conf_path
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def initial_models():
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global Datasets
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@@ -121,8 +122,9 @@ def install_requested_models(
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if scan_at_startup and scan_directory.is_dir():
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argument = "--autoconvert"
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initfile = Path(Globals.root, Globals.initfile)
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replacement = Path(Globals.root, f"{Globals.initfile}.new")
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print('** The global initfile is no longer supported; rewrite to support new yaml format **')
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initfile = Path(config.root, 'invokeai.init')
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replacement = Path(config.root, f"invokeai.init.new")
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directory = str(scan_directory).replace("\\", "/")
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with open(initfile, "r") as input:
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with open(replacement, "w") as output:
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@@ -150,7 +152,7 @@ def get_root(root: str = None) -> str:
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elif os.environ.get("INVOKEAI_ROOT"):
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return os.environ.get("INVOKEAI_ROOT")
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else:
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return Globals.root
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return config.root
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# ---------------------------------------------
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@@ -183,7 +185,7 @@ def all_datasets() -> dict:
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# look for legacy model.ckpt in models directory and offer to
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# normalize its name
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def migrate_models_ckpt():
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model_path = os.path.join(Globals.root, Model_dir, Weights_dir)
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model_path = os.path.join(config.root, Model_dir, Weights_dir)
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if not os.path.exists(os.path.join(model_path, "model.ckpt")):
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return
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new_name = initial_models()["stable-diffusion-1.4"]["file"]
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@@ -228,7 +230,7 @@ def _download_repo_or_file(
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def _download_ckpt_weights(mconfig: DictConfig, access_token: str) -> Path:
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repo_id = mconfig["repo_id"]
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filename = mconfig["file"]
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cache_dir = os.path.join(Globals.root, Model_dir, Weights_dir)
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cache_dir = os.path.join(config.root, Model_dir, Weights_dir)
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return hf_download_with_resume(
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repo_id=repo_id,
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model_dir=cache_dir,
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@@ -239,9 +241,9 @@ def _download_ckpt_weights(mconfig: DictConfig, access_token: str) -> Path:
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# ---------------------------------------------
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def download_from_hf(
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model_class: object, model_name: str, cache_subdir: Path = Path("hub"), **kwargs
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model_class: object, model_name: str, **kwargs
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):
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path = global_cache_dir(cache_subdir)
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path = config.cache_dir
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model = model_class.from_pretrained(
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model_name,
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cache_dir=path,
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@@ -417,7 +419,7 @@ def new_config_file_contents(
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stanza["height"] = mod["height"]
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if "file" in mod:
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stanza["weights"] = os.path.relpath(
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successfully_downloaded[model], start=Globals.root
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successfully_downloaded[model], start=config.root
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)
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stanza["config"] = os.path.normpath(
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os.path.join(sd_configs(), mod["config"])
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@@ -456,7 +458,7 @@ def delete_weights(model_name: str, conf_stanza: dict):
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weights = Path(weights)
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if not weights.is_absolute():
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weights = Path(Globals.root) / weights
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weights = Path(config.root) / weights
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try:
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weights.unlink()
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except OSError as e:
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