InvokeAI/ldm/invoke/config/model_install.py

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#!/usr/bin/env python
# Copyright (c) 2022 Lincoln D. Stein (https://github.com/lstein)
# Before running stable-diffusion on an internet-isolated machine,
# run this script from one with internet connectivity. The
# two machines must share a common .cache directory.
'''
This is the npyscreen frontend to the model installation application.
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The work is actually done in backend code in model_install_backend.py.
'''
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import argparse
import curses
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import os
import sys
import traceback
from argparse import Namespace
from typing import List
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import npyscreen
import torch
from datetime import datetime
from pathlib import Path
from npyscreen import widget
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from omegaconf import OmegaConf
from ..devices import choose_precision, choose_torch_device
from ..globals import Globals
from .widgets import MultiSelectColumns, TextBox
from .model_install_backend import (Dataset_path, default_config_file,
install_requested_models,
default_dataset, recommended_datasets, get_root
)
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class addModelsForm(npyscreen.FormMultiPage):
def __init__(self, parentApp, name, multipage=False):
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self.initial_models = OmegaConf.load(Dataset_path)
try:
self.existing_models = OmegaConf.load(default_config_file())
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except:
self.existing_models = dict()
self.starter_model_list = [
x for x in list(self.initial_models.keys()) if x not in self.existing_models
]
self.multipage = multipage
self.installed_models=dict()
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super().__init__(parentApp, name)
def create(self):
window_height, window_width = curses.initscr().getmaxyx()
starter_model_labels = self._get_starter_model_labels()
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recommended_models = [
x
for x in self.starter_model_list
if self.initial_models[x].get("recommended", False)
]
self.installed_models = sorted(
[
x for x in list(self.initial_models.keys()) if x in self.existing_models
]
)
self.nextrely -= 1
self.add_widget_intelligent(
npyscreen.FixedText,
value='Use ctrl-N and ctrl-P to move to the <N>ext and <P>revious fields,',
editable=False,
)
self.add_widget_intelligent(
npyscreen.FixedText,
value='cursor arrows to make a selection, and space to toggle checkboxes.',
editable=False,
)
self.nextrely += 1
if len(self.installed_models) > 0:
self.add_widget_intelligent(
npyscreen.TitleFixedText,
name="== INSTALLED STARTER MODELS ==",
value="Currently installed starter models. Uncheck to delete:",
begin_entry_at=2,
editable=False,
color="CONTROL",
)
columns = self._get_columns()
self.previously_installed_models = self.add_widget_intelligent(
MultiSelectColumns,
columns=columns,
values=self.installed_models,
value=[x for x in range(0,len(self.installed_models))],
max_height=1+len(self.installed_models) // columns,
relx = 4,
slow_scroll=True,
scroll_exit = True,
)
self.purge_deleted = self.add_widget_intelligent(
npyscreen.Checkbox,
name='Purge deleted models from disk',
value=False,
scroll_exit=True
)
self.nextrely += 1
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self.add_widget_intelligent(
npyscreen.TitleFixedText,
name="== STARTER MODELS (recommended ones selected) ==",
value="Select from a starter set of Stable Diffusion models from HuggingFace:",
begin_entry_at=2,
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editable=False,
color="CONTROL",
)
self.nextrely -= 1
# if user has already installed some initial models, then don't patronize them
# by showing more recommendations
show_recommended = self.installed_models is None or len(self.installed_models)==0
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self.models_selected = self.add_widget_intelligent(
npyscreen.MultiSelect,
name="Install Starter Models",
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values=starter_model_labels,
value=[
self.starter_model_list.index(x)
for x in self.starter_model_list
if show_recommended and x in recommended_models
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],
max_height=len(starter_model_labels) + 1,
relx = 4,
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scroll_exit=True,
)
for line in [
'== IMPORT LOCAL AND REMOTE MODELS ==',
'Enter URLs, file paths, or HuggingFace diffusers repository IDs separated by spaces.',
'Use control-V or shift-control-V to paste:'
]:
self.add_widget_intelligent(
npyscreen.TitleText,
name=line,
editable=False,
color="CONTROL",
)
self.nextrely -= 1
self.import_model_paths = self.add_widget_intelligent(
TextBox,
max_height=8,
scroll_exit=True,
editable=True,
relx=4
)
self.nextrely += 1
self.show_directory_fields= self.add_widget_intelligent(
npyscreen.FormControlCheckbox,
name='Select a directory for models to import',
value=False,
)
self.autoload_directory = self.add_widget_intelligent(
npyscreen.TitleFilename,
name='Directory (<tab> autocompletes):',
select_dir=True,
must_exist=True,
use_two_lines=False,
labelColor='DANGER',
begin_entry_at=34,
scroll_exit=True,
)
self.autoscan_on_startup = self.add_widget_intelligent(
npyscreen.Checkbox,
name='Scan this directory each time InvokeAI starts for new models to import',
value=False,
relx = 4,
scroll_exit=True,
)
self.convert_models = self.add_widget_intelligent(
npyscreen.TitleSelectOne,
name='== CONVERT IMPORTED MODELS INTO DIFFUSERS==',
values=['Keep original format','Convert to diffusers'],
value=0,
begin_entry_at=4,
max_height=4,
scroll_exit=True,
)
self.cancel = self.add_widget_intelligent(
npyscreen.ButtonPress,
name='CANCEL',
rely = -3,
when_pressed_function=self.on_cancel,
)
done_label = 'DONE'
back_label = 'BACK'
button_length = len(done_label)
button_offset = 0
if self.multipage:
button_length += len(back_label)+1
button_offset += len(back_label)+1
self.back_button = self.add_widget_intelligent(
npyscreen.ButtonPress,
name=back_label,
relx= (window_width-button_length)//2,
rely= -3,
when_pressed_function=self.on_back
)
self.ok_button = self.add_widget_intelligent(
npyscreen.ButtonPress,
name=done_label,
relx= button_offset + 1 + (window_width-button_length)//2,
rely= -3,
when_pressed_function=self.on_ok
)
for i in [self.autoload_directory,self.autoscan_on_startup]:
self.show_directory_fields.addVisibleWhenSelected(i)
def resize(self):
super().resize()
self.models_selected.values = self._get_starter_model_labels()
def _get_starter_model_labels(self)->List[str]:
window_height, window_width = curses.initscr().getmaxyx()
label_width = 25
checkbox_width = 4
spacing_width = 2
description_width = window_width - label_width - checkbox_width - spacing_width
im = self.initial_models
names = self.starter_model_list
descriptions = [im[x].description [0:description_width-3]+'...'
if len(im[x].description) > description_width
else im[x].description
for x in names]
return [
f"%-{label_width}s %s" % (names[x], descriptions[x]) for x in range(0,len(names))
]
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def _get_columns(self)->int:
window_height, window_width = curses.initscr().getmaxyx()
return 4 if window_width > 240 else 3 if window_width>160 else 2 if window_width>80 else 1
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def on_ok(self):
self.parentApp.setNextForm(None)
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self.editing = False
self.parentApp.user_cancelled = False
self.marshall_arguments()
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def on_back(self):
self.parentApp.switchFormPrevious()
self.editing = False
def on_cancel(self):
if npyscreen.notify_yes_no(
'Are you sure you want to cancel?\nYou may re-run this script later using the invoke.sh or invoke.bat command.\n'
):
self.parentApp.setNextForm(None)
self.parentApp.user_cancelled = True
self.editing = False
def marshall_arguments(self):
'''
Assemble arguments and store as attributes of the application:
.starter_models: dict of model names to install from INITIAL_CONFIGURE.yaml
True => Install
False => Remove
.scan_directory: Path to a directory of models to scan and import
.autoscan_on_startup: True if invokeai should scan and import at startup time
.import_model_paths: list of URLs, repo_ids and file paths to import
.convert_to_diffusers: if True, convert legacy checkpoints into diffusers
'''
# we're using a global here rather than storing the result in the parentapp
# due to some bug in npyscreen that is causing attributes to be lost
selections = self.parentApp.user_selections
# starter models to install/remove
starter_models = dict(map(lambda x: (self.starter_model_list[x], True), self.models_selected.value))
selections.purge_deleted_models=False
if hasattr(self,'previously_installed_models'):
unchecked = [
self.previously_installed_models.values[x]
for x in range(0,len(self.previously_installed_models.values))
if x not in self.previously_installed_models.value
]
starter_models.update(
map(lambda x: (x, False), unchecked)
)
selections.purge_deleted_models = self.purge_deleted.value
selections.starter_models=starter_models
# load directory and whether to scan on startup
if self.show_directory_fields.value:
selections.scan_directory = self.autoload_directory.value
selections.autoscan_on_startup = self.autoscan_on_startup.value
else:
selections.scan_directory = None
selections.autoscan_on_startup = False
# URLs and the like
selections.import_model_paths = self.import_model_paths.value.split()
selections.convert_to_diffusers = self.convert_models.value[0] == 1
class AddModelApplication(npyscreen.NPSAppManaged):
def __init__(self):
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super().__init__()
self.user_cancelled = False
self.user_selections = Namespace(
starter_models = None,
purge_deleted_models = False,
scan_directory = None,
autoscan_on_startup = None,
import_model_paths = None,
convert_to_diffusers = None
)
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def onStart(self):
npyscreen.setTheme(npyscreen.Themes.DefaultTheme)
self.main_form = self.addForm(
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"MAIN",
addModelsForm,
name="Add/Remove Models"
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)
# --------------------------------------------------------
def process_and_execute(opt: Namespace, selections: Namespace):
models_to_remove = [x for x in selections.starter_models if not selections.starter_models[x]]
models_to_install = [x for x in selections.starter_models if selections.starter_models[x]]
directory_to_scan = selections.scan_directory
scan_at_startup = selections.autoscan_on_startup
potential_models_to_install = selections.import_model_paths
convert_to_diffusers = selections.convert_to_diffusers
install_requested_models(
install_initial_models = models_to_install,
remove_models = models_to_remove,
scan_directory = Path(directory_to_scan) if directory_to_scan else None,
external_models = potential_models_to_install,
scan_at_startup = scan_at_startup,
convert_to_diffusers = convert_to_diffusers,
precision = 'float32' if opt.full_precision else choose_precision(torch.device(choose_torch_device())),
purge_deleted = selections.purge_deleted_models,
config_file_path = Path(opt.config_file) if opt.config_file else None,
)
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# --------------------------------------------------------
def select_and_download_models(opt: Namespace):
precision= 'float32' if opt.full_precision else choose_precision(torch.device(choose_torch_device())),
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if opt.default_only:
install_requested_models(
install_initial_models = default_dataset(),
precision = precision,
)
elif opt.yes_to_all:
install_requested_models(
install_initial_models = recommended_datasets(),
precision = precision,
)
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else:
installApp = AddModelApplication()
installApp.run()
if not installApp.user_cancelled:
process_and_execute(opt, installApp.user_selections)
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# -------------------------------------
def main():
parser = argparse.ArgumentParser(description="InvokeAI model downloader")
parser.add_argument(
"--full-precision",
dest="full_precision",
action=argparse.BooleanOptionalAction,
type=bool,
default=False,
help="use 32-bit weights instead of faster 16-bit weights",
)
parser.add_argument(
"--yes",
"-y",
dest="yes_to_all",
action="store_true",
help='answer "yes" to all prompts',
)
parser.add_argument(
"--default_only",
action="store_true",
help="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",
type=str,
default=None,
help="path to root of install directory",
)
opt = parser.parse_args()
# setting a global here
Globals.root = os.path.expanduser(get_root(opt.root) or "")
try:
select_and_download_models(opt)
except AssertionError as e:
print(str(e))
sys.exit(-1)
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except KeyboardInterrupt:
print("\nGoodbye! Come back soon.")
except (widget.NotEnoughSpaceForWidget, Exception) as e:
if str(e).startswith("Height of 1 allocated"):
print(
"** Insufficient vertical space for the interface. Please make your window taller and try again"
)
elif str(e).startswith('addwstr'):
print(
'** Insufficient horizontal space for the interface. Please make your window wider and try again.'
)
else:
print(f"** An error has occurred: {str(e)}")
traceback.print_exc()
sys.exit(-1)
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# -------------------------------------
if __name__ == "__main__":
main()