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fix(install): resolve config-related issues with configurator

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- 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 2024-03-15 16:36:32 +11:00
parent ce9aeeece3
commit cb180909f7
1 changed files with 44 additions and 59 deletions
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103
invokeai/backend/install/invokeai_configure.py
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@ -18,7 +18,7 @@ from argparse import Namespace
from enum import Enum
from pathlib import Path
from shutil import copy, get_terminal_size, move
from typing import Any, Optional, Set, Tuple, Type, get_args, get_type_hints
from typing import Any, Optional, Tuple, Type, get_args, get_type_hints
from urllib import request
import npyscreen
@ -32,9 +32,8 @@ from huggingface_hub import login as hf_hub_login
from tqdm import tqdm
from transformers import AutoFeatureExtractor
import invokeai.configs as configs
import invokeai.configs as model_configs
from invokeai.app.services.config import InvokeAIAppConfig
from invokeai.app.services.config.config_default import get_config
from invokeai.backend.install.install_helper import InstallHelper, InstallSelections
from invokeai.backend.model_manager import ModelType
from invokeai.backend.util import choose_precision, choose_torch_device
@ -64,7 +63,8 @@ def get_literal_fields(field: str) -> Tuple[Any]:
# --------------------------globals-----------------------
config = get_config()
# Start from a fresh config object - we will read the user's config from file later, and update it with their choices
config = InvokeAIAppConfig()
PRECISION_CHOICES = get_literal_fields("precision")
DEVICE_CHOICES = get_literal_fields("device")
@ -98,7 +98,7 @@ class DummyWidgetValue(Enum):
# --------------------------------------------
def postscript(errors: Set[str]) -> None:
def postscript(errors: set[str]) -> None:
if not any(errors):
message = f"""
** INVOKEAI INSTALLATION SUCCESSFUL **
@ -515,7 +515,7 @@ Use cursor arrows to make a checkbox selection, and space to toggle.
self.autoimport_dirs["autoimport_dir"] = self.add_widget_intelligent(
FileBox,
name="Optional folder to scan for new checkpoints, ControlNets, LoRAs and TI models",
value=str(config.autoimport_path) if config.autoimport_dir else "",
value=str(config.autoimport_path),
select_dir=True,
must_exist=False,
use_two_lines=False,
@ -652,7 +652,7 @@ class EditOptApplication(npyscreen.NPSAppManaged):
)
def default_ramcache() -> float:
def get_default_ram_cache_size() -> float:
"""Run a heuristic for the default RAM cache based on installed RAM."""
# Note that on my 64 GB machine, psutil.virtual_memory().total gives 62 GB,
@ -662,11 +662,12 @@ def default_ramcache() -> float:
) # 2.1 is just large enough for sd 1.5 ;-)
def default_startup_options(init_file: Path) -> InvokeAIAppConfig:
opts = get_config()
opts.ram = default_ramcache()
opts.precision = "float32" if FORCE_FULL_PRECISION else choose_precision(torch.device(choose_torch_device()))
return opts
def get_default_config() -> InvokeAIAppConfig:
"""Builds a new config object, setting the ram and precision using the appropriate heuristic."""
config = InvokeAIAppConfig()
config.ram = get_default_ram_cache_size()
config.precision = "float32" if FORCE_FULL_PRECISION else choose_precision(torch.device(choose_torch_device()))
return config
def default_user_selections(program_opts: Namespace, install_helper: InstallHelper) -> InstallSelections:
@ -696,7 +697,7 @@ def initialize_rootdir(root: Path, yes_to_all: bool = False):
for model_type in ModelType:
Path(root, "autoimport", model_type.value).mkdir(parents=True, exist_ok=True)
configs_src = Path(configs.__path__[0])
configs_src = Path(model_configs.__path__[0])
configs_dest = root / "configs"
if not os.path.samefile(configs_src, configs_dest):
shutil.copytree(configs_src, configs_dest, dirs_exist_ok=True)
@ -707,19 +708,19 @@ def initialize_rootdir(root: Path, yes_to_all: bool = False):
# -------------------------------------
def run_console_ui(
program_opts: Namespace, initfile: Path, install_helper: InstallHelper
program_opts: Namespace, install_helper: InstallHelper
) -> Tuple[Optional[Namespace], Optional[InstallSelections]]:
first_time = not (config.root_path / "invokeai.yaml").exists()
invokeai_opts = default_startup_options(initfile) if first_time else config
first_time = not config.init_file_path.exists()
config_opts = get_default_config() if first_time else config
if program_opts.root:
invokeai_opts.set_root(Path(program_opts.root))
config_opts.set_root(Path(program_opts.root))
if not set_min_terminal_size(MIN_COLS, MIN_LINES):
raise WindowTooSmallException(
"Could not increase terminal size. Try running again with a larger window or smaller font size."
)
editApp = EditOptApplication(program_opts, invokeai_opts, install_helper)
editApp = EditOptApplication(program_opts, config_opts, install_helper)
editApp.run()
if editApp.user_cancelled:
return (None, None)
@ -727,34 +728,11 @@ def run_console_ui(
return (editApp.new_opts, editApp.install_selections)
# -------------------------------------
def write_opts(opts: InvokeAIAppConfig, init_file: Path) -> None:
"""
Update the invokeai.yaml file with values from current settings.
"""
new_config = get_config()
new_config.set_root(config.root_path)
# Remove any fields that are not in the model_fields list, like `hf_token`
cleaned_opts = {k: v for k, v in vars(opts).items() if k in new_config.model_fields}
new_config.update_config(cleaned_opts)
new_config.write_file(init_file)
if hasattr(opts, "hf_token") and opts.hf_token:
HfLogin(opts.hf_token)
# -------------------------------------
def default_output_dir() -> Path:
return config.root_path / "outputs"
# -------------------------------------
def write_default_options(program_opts: Namespace, initfile: Path) -> None:
opt = default_startup_options(initfile)
write_opts(opt, initfile)
def is_v2_install(root: Path) -> bool:
# We check for to see if the runtime directory is correctly initialized.
old_init_file = root / "invokeai.init"
@ -802,14 +780,6 @@ def main() -> None:
action="store_true",
help="when --yes specified, only install the default model",
)
parser.add_argument(
"--config_file",
"-c",
dest="config_file",
type=str,
default=None,
help="path to configuration file to create",
)
parser.add_argument(
"--root_dir",
dest="root",
@ -823,13 +793,22 @@ def main() -> None:
config.set_root(Path(opt.root))
if opt.full_precision:
updates["precision"] = "float32"
config.merge_from_file()
try:
# Attempt to read the config file into the config object
config.merge_from_file()
except FileNotFoundError:
# No config file, first time running the app
pass
config.update_config(updates)
logger = InvokeAILogger().get_logger(config=config)
errors = set()
errors: set[str] = set()
FORCE_FULL_PRECISION = opt.full_precision # FIXME global
new_init_file = config.root_path / "invokeai.yaml"
# Before we write anything else, make a backup of the existing init file
new_init_file = config.init_file_path
backup_init_file = new_init_file.with_suffix(".bak")
if new_init_file.exists():
copy(new_init_file, backup_init_file)
@ -849,13 +828,20 @@ def main() -> None:
models_to_download = default_user_selections(opt, install_helper)
if opt.yes_to_all:
write_default_options(opt, new_init_file)
init_options = Namespace(precision="float32" if opt.full_precision else "float16")
# We will not show the UI - just write the default config to the file and move on to installing models.
get_default_config().write_file(new_init_file)
else:
init_options, models_to_download = run_console_ui(opt, new_init_file, install_helper)
if init_options:
write_opts(init_options, new_init_file)
# Run the UI to get the user's options & model choices
user_opts, models_to_download = run_console_ui(opt, install_helper)
if user_opts:
# Create a dict of the user's opts, omitting any fields that are not config settings (like `hf_token`)
user_opts_dict = {k: v for k, v in vars(user_opts).items() if k in config.model_fields}
# Merge the user's opts back into the config object & write it
config.update_config(user_opts_dict)
config.write_file(config.init_file_path)
if hasattr(user_opts, "hf_token") and user_opts.hf_token:
HfLogin(user_opts.hf_token)
else:
logger.info('\n** CANCELLED AT USER\'S REQUEST. USE THE "invoke.sh" LAUNCHER TO RUN LATER **\n')
sys.exit(0)
@ -868,7 +854,6 @@ def main() -> None:
if opt.skip_sd_weights:
logger.warning("Skipping diffusion weights download per user request")
elif models_to_download:
install_helper.add_or_delete(models_to_download)