mirror of
https://github.com/invoke-ai/InvokeAI
synced 2024-08-30 20:32:17 +00:00
fix(install): resolve config-related issues with configurator
- Do not use the singleton app config, this causes a lot of weirdness - Update logic to use new config object - Remove unused code
This commit is contained in:
psychedelicious
parent
ce9aeeece3
commit
cb180909f7
@ -18,7 +18,7 @@ from argparse import Namespace
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from enum import Enum
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from pathlib import Path
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from shutil import copy, get_terminal_size, move
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from typing import Any, Optional, Set, Tuple, Type, get_args, get_type_hints
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from typing import Any, Optional, Tuple, Type, get_args, get_type_hints
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from urllib import request
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import npyscreen
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@ -32,9 +32,8 @@ from huggingface_hub import login as hf_hub_login
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from tqdm import tqdm
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from transformers import AutoFeatureExtractor
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import invokeai.configs as configs
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import invokeai.configs as model_configs
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from invokeai.app.services.config import InvokeAIAppConfig
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from invokeai.app.services.config.config_default import get_config
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from invokeai.backend.install.install_helper import InstallHelper, InstallSelections
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from invokeai.backend.model_manager import ModelType
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from invokeai.backend.util import choose_precision, choose_torch_device
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@ -64,7 +63,8 @@ def get_literal_fields(field: str) -> Tuple[Any]:
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# --------------------------globals-----------------------
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config = get_config()
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# Start from a fresh config object - we will read the user's config from file later, and update it with their choices
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config = InvokeAIAppConfig()
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PRECISION_CHOICES = get_literal_fields("precision")
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DEVICE_CHOICES = get_literal_fields("device")
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@ -98,7 +98,7 @@ class DummyWidgetValue(Enum):
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# --------------------------------------------
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def postscript(errors: Set[str]) -> None:
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def postscript(errors: set[str]) -> None:
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if not any(errors):
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message = f"""
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** INVOKEAI INSTALLATION SUCCESSFUL **
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@ -515,7 +515,7 @@ Use cursor arrows to make a checkbox selection, and space to toggle.
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self.autoimport_dirs["autoimport_dir"] = self.add_widget_intelligent(
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FileBox,
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name="Optional folder to scan for new checkpoints, ControlNets, LoRAs and TI models",
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value=str(config.autoimport_path) if config.autoimport_dir else "",
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value=str(config.autoimport_path),
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select_dir=True,
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must_exist=False,
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use_two_lines=False,
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@ -652,7 +652,7 @@ class EditOptApplication(npyscreen.NPSAppManaged):
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)
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def default_ramcache() -> float:
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def get_default_ram_cache_size() -> float:
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"""Run a heuristic for the default RAM cache based on installed RAM."""
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# Note that on my 64 GB machine, psutil.virtual_memory().total gives 62 GB,
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@ -662,11 +662,12 @@ def default_ramcache() -> float:
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) # 2.1 is just large enough for sd 1.5 ;-)
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def default_startup_options(init_file: Path) -> InvokeAIAppConfig:
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opts = get_config()
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opts.ram = default_ramcache()
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opts.precision = "float32" if FORCE_FULL_PRECISION else choose_precision(torch.device(choose_torch_device()))
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return opts
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def get_default_config() -> InvokeAIAppConfig:
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"""Builds a new config object, setting the ram and precision using the appropriate heuristic."""
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config = InvokeAIAppConfig()
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config.ram = get_default_ram_cache_size()
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config.precision = "float32" if FORCE_FULL_PRECISION else choose_precision(torch.device(choose_torch_device()))
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return config
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def default_user_selections(program_opts: Namespace, install_helper: InstallHelper) -> InstallSelections:
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@ -696,7 +697,7 @@ def initialize_rootdir(root: Path, yes_to_all: bool = False):
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for model_type in ModelType:
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Path(root, "autoimport", model_type.value).mkdir(parents=True, exist_ok=True)
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configs_src = Path(configs.__path__[0])
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configs_src = Path(model_configs.__path__[0])
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configs_dest = root / "configs"
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if not os.path.samefile(configs_src, configs_dest):
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shutil.copytree(configs_src, configs_dest, dirs_exist_ok=True)
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@ -707,19 +708,19 @@ def initialize_rootdir(root: Path, yes_to_all: bool = False):
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# -------------------------------------
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def run_console_ui(
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program_opts: Namespace, initfile: Path, install_helper: InstallHelper
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program_opts: Namespace, install_helper: InstallHelper
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) -> Tuple[Optional[Namespace], Optional[InstallSelections]]:
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first_time = not (config.root_path / "invokeai.yaml").exists()
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invokeai_opts = default_startup_options(initfile) if first_time else config
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first_time = not config.init_file_path.exists()
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config_opts = get_default_config() if first_time else config
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if program_opts.root:
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invokeai_opts.set_root(Path(program_opts.root))
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config_opts.set_root(Path(program_opts.root))
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if not set_min_terminal_size(MIN_COLS, MIN_LINES):
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raise WindowTooSmallException(
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"Could not increase terminal size. Try running again with a larger window or smaller font size."
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)
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editApp = EditOptApplication(program_opts, invokeai_opts, install_helper)
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editApp = EditOptApplication(program_opts, config_opts, install_helper)
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editApp.run()
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if editApp.user_cancelled:
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return (None, None)
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@ -727,34 +728,11 @@ def run_console_ui(
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return (editApp.new_opts, editApp.install_selections)
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# -------------------------------------
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def write_opts(opts: InvokeAIAppConfig, init_file: Path) -> None:
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"""
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Update the invokeai.yaml file with values from current settings.
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"""
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new_config = get_config()
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new_config.set_root(config.root_path)
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# Remove any fields that are not in the model_fields list, like `hf_token`
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cleaned_opts = {k: v for k, v in vars(opts).items() if k in new_config.model_fields}
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new_config.update_config(cleaned_opts)
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new_config.write_file(init_file)
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if hasattr(opts, "hf_token") and opts.hf_token:
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HfLogin(opts.hf_token)
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# -------------------------------------
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def default_output_dir() -> Path:
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return config.root_path / "outputs"
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# -------------------------------------
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def write_default_options(program_opts: Namespace, initfile: Path) -> None:
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opt = default_startup_options(initfile)
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write_opts(opt, initfile)
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def is_v2_install(root: Path) -> bool:
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# We check for to see if the runtime directory is correctly initialized.
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old_init_file = root / "invokeai.init"
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@ -802,14 +780,6 @@ def main() -> None:
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action="store_true",
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help="when --yes specified, only install the default model",
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)
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parser.add_argument(
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"--config_file",
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"-c",
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dest="config_file",
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type=str,
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default=None,
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help="path to configuration file to create",
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)
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parser.add_argument(
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"--root_dir",
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dest="root",
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@ -823,13 +793,22 @@ def main() -> None:
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config.set_root(Path(opt.root))
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if opt.full_precision:
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updates["precision"] = "float32"
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try:
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# Attempt to read the config file into the config object
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config.merge_from_file()
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except FileNotFoundError:
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# No config file, first time running the app
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pass
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config.update_config(updates)
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logger = InvokeAILogger().get_logger(config=config)
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errors = set()
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errors: set[str] = set()
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FORCE_FULL_PRECISION = opt.full_precision # FIXME global
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new_init_file = config.root_path / "invokeai.yaml"
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# Before we write anything else, make a backup of the existing init file
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new_init_file = config.init_file_path
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backup_init_file = new_init_file.with_suffix(".bak")
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if new_init_file.exists():
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copy(new_init_file, backup_init_file)
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@ -849,13 +828,20 @@ def main() -> None:
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models_to_download = default_user_selections(opt, install_helper)
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if opt.yes_to_all:
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write_default_options(opt, new_init_file)
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init_options = Namespace(precision="float32" if opt.full_precision else "float16")
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# We will not show the UI - just write the default config to the file and move on to installing models.
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get_default_config().write_file(new_init_file)
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else:
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init_options, models_to_download = run_console_ui(opt, new_init_file, install_helper)
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if init_options:
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write_opts(init_options, new_init_file)
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# Run the UI to get the user's options & model choices
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user_opts, models_to_download = run_console_ui(opt, install_helper)
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if user_opts:
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# Create a dict of the user's opts, omitting any fields that are not config settings (like `hf_token`)
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user_opts_dict = {k: v for k, v in vars(user_opts).items() if k in config.model_fields}
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# Merge the user's opts back into the config object & write it
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config.update_config(user_opts_dict)
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config.write_file(config.init_file_path)
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if hasattr(user_opts, "hf_token") and user_opts.hf_token:
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HfLogin(user_opts.hf_token)
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else:
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logger.info('\n** CANCELLED AT USER\'S REQUEST. USE THE "invoke.sh" LAUNCHER TO RUN LATER **\n')
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sys.exit(0)
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@ -868,7 +854,6 @@ def main() -> None:
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if opt.skip_sd_weights:
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logger.warning("Skipping diffusion weights download per user request")
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elif models_to_download:
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install_helper.add_or_delete(models_to_download)
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