mirror of
https://github.com/invoke-ai/InvokeAI
synced 2024-08-30 20:32:17 +00:00
remove errant def that was crashing invokeai-configure
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5278a64301
commit
b06d63fb34
@ -84,6 +84,8 @@ _, MAX_VRAM = torch.cuda.mem_get_info() if HAS_CUDA else (0.0, 0.0)
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MAX_VRAM /= GB
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MAX_VRAM /= GB
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MAX_RAM = psutil.virtual_memory().total / GB
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MAX_RAM = psutil.virtual_memory().total / GB
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FORCE_FULL_PRECISION = False
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INIT_FILE_PREAMBLE = """# InvokeAI initialization file
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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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# 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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# Feel free to edit. If anything goes wrong, you can re-initialize this file by deleting
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@ -112,9 +114,6 @@ then run one of the following commands to start InvokeAI.
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Web UI:
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Web UI:
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invokeai-web
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invokeai-web
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Command-line client:
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invokeai
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If you installed using an installation script, run:
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If you installed using an installation script, run:
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{config.root_path}/invoke.{"bat" if sys.platform == "win32" else "sh"}
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{config.root_path}/invoke.{"bat" if sys.platform == "win32" else "sh"}
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@ -408,7 +407,7 @@ Use cursor arrows to make a checkbox selection, and space to toggle.
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begin_entry_at=3,
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begin_entry_at=3,
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max_height=2,
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max_height=2,
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relx=30,
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relx=30,
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max_width=56,
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max_width=80,
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scroll_exit=True,
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scroll_exit=True,
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)
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)
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self.add_widget_intelligent(
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self.add_widget_intelligent(
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@ -664,7 +663,6 @@ https://huggingface.co/stabilityai/stable-diffusion-xl-base-1.0/blob/main/LICENS
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generation_options = [GENERATION_OPT_CHOICES[x] for x in self.generation_options.value]
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generation_options = [GENERATION_OPT_CHOICES[x] for x in self.generation_options.value]
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for v in GENERATION_OPT_CHOICES:
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for v in GENERATION_OPT_CHOICES:
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setattr(new_opts, v, v in generation_options)
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setattr(new_opts, v, v in generation_options)
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return new_opts
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return new_opts
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@ -695,9 +693,6 @@ class EditOptApplication(npyscreen.NPSAppManaged):
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cycle_widgets=False,
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cycle_widgets=False,
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)
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)
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def new_opts(self) -> Namespace:
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return self.options.marshall_arguments()
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def default_ramcache() -> float:
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def default_ramcache() -> float:
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"""Run a heuristic for the default RAM cache based on installed RAM."""
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"""Run a heuristic for the default RAM cache based on installed RAM."""
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@ -712,6 +707,7 @@ def default_ramcache() -> float:
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def default_startup_options(init_file: Path) -> InvokeAIAppConfig:
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def default_startup_options(init_file: Path) -> InvokeAIAppConfig:
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opts = InvokeAIAppConfig.get_config()
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opts = InvokeAIAppConfig.get_config()
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opts.ram = default_ramcache()
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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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return opts
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@ -760,7 +756,8 @@ def initialize_rootdir(root: Path, yes_to_all: bool = False):
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def run_console_ui(
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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, initfile: Path, install_helper: InstallHelper
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) -> Tuple[Optional[Namespace], Optional[InstallSelections]]:
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) -> Tuple[Optional[Namespace], Optional[InstallSelections]]:
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invokeai_opts = default_startup_options(initfile)
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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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invokeai_opts.root = program_opts.root
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invokeai_opts.root = program_opts.root
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if not set_min_terminal_size(MIN_COLS, MIN_LINES):
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if not set_min_terminal_size(MIN_COLS, MIN_LINES):
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@ -773,7 +770,7 @@ def run_console_ui(
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if editApp.user_cancelled:
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if editApp.user_cancelled:
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return (None, None)
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return (None, None)
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else:
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else:
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return (editApp.new_opts(), editApp.install_selections)
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return (editApp.new_opts, editApp.install_selections)
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# -------------------------------------
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# -------------------------------------
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@ -785,7 +782,7 @@ def write_opts(opts: InvokeAIAppConfig, init_file: Path) -> None:
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new_config = InvokeAIAppConfig.get_config()
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new_config = InvokeAIAppConfig.get_config()
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new_config.root = config.root
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new_config.root = config.root
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for key, value in opts.model_dump().items():
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for key, value in vars(opts).items():
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if hasattr(new_config, key):
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if hasattr(new_config, key):
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setattr(new_config, key, value)
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setattr(new_config, key, value)
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@ -869,7 +866,8 @@ def migrate_if_needed(opt: Namespace, root: Path) -> bool:
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# -------------------------------------
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# -------------------------------------
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def main():
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def main() -> None:
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global FORCE_FULL_PRECISION # FIXME
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parser = argparse.ArgumentParser(description="InvokeAI model downloader")
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parser = argparse.ArgumentParser(description="InvokeAI model downloader")
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parser.add_argument(
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parser.add_argument(
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"--skip-sd-weights",
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"--skip-sd-weights",
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@ -921,17 +919,16 @@ def main():
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help="path to root of install directory",
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help="path to root of install directory",
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)
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)
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opt = parser.parse_args()
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opt = parser.parse_args()
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invoke_args = []
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invoke_args = []
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if opt.root:
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if opt.root:
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invoke_args.extend(["--root", opt.root])
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invoke_args.extend(["--root", opt.root])
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if opt.full_precision:
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if opt.full_precision:
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invoke_args.extend(["--precision", "float32"])
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invoke_args.extend(["--precision", "float32"])
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config.parse_args(invoke_args)
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config.parse_args(invoke_args)
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config.precision = "float32" if opt.full_precision else choose_precision(torch.device(choose_torch_device()))
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logger = InvokeAILogger().get_logger(config=config)
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logger = InvokeAILogger().get_logger(config=config)
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errors = set()
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errors = set()
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FORCE_FULL_PRECISION = opt.full_precision # FIXME global
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try:
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try:
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# if we do a root migration/upgrade, then we are keeping previous
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# if we do a root migration/upgrade, then we are keeping previous
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@ -43,7 +43,7 @@ from invokeai.frontend.install.widgets import (
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warnings.filterwarnings("ignore", category=UserWarning) # noqa: E402
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warnings.filterwarnings("ignore", category=UserWarning) # noqa: E402
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config = InvokeAIAppConfig.get_config()
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config = InvokeAIAppConfig.get_config()
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logger = InvokeAILogger.get_logger("ModelInstallService")
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logger = InvokeAILogger.get_logger("ModelInstallService")
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logger.setLevel("WARNING")
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# logger.setLevel("WARNING")
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# logger.setLevel('DEBUG')
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# logger.setLevel('DEBUG')
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# build a table mapping all non-printable characters to None
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# build a table mapping all non-printable characters to None
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