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Merge branch 'main' into patch-1

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Lincoln Stein 2023-02-07 22:14:39 -05:00 committed by GitHub
commit 492605ac3e
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3 changed files with 59 additions and 19 deletions
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34
installer/messages.py
View File

@ -9,10 +9,9 @@ from pathlib import Path
from prompt_toolkit import prompt
from prompt_toolkit.completion import PathCompleter
from prompt_toolkit.shortcuts import CompleteStyle
from prompt_toolkit.validation import Validator
from rich import box, print
from rich.console import Console, Group
from rich.console import Console, Group, group
from rich.panel import Panel
from rich.prompt import Confirm
from rich.style import Style
@ -37,17 +36,21 @@ else:
def welcome():
@group()
def text():
if (platform_specific := _platform_specific_help()) != "":
yield platform_specific
yield ""
yield Text.from_markup("Some of the installation steps take a long time to run. Please be patient. If the script appears to hang for more than 10 minutes, please interrupt with [i]Control-C[/] and retry.", justify="center")
console.rule()
print(
Panel(
title="[bold wheat1]Welcome to the InvokeAI Installer",
renderable=Text(
"Some of the installation steps take a long time to run. Please be patient. If the script appears to hang for more than 10 minutes, please interrupt with control-C and retry.",
justify="center",
),
renderable=text(),
box=box.DOUBLE,
width=80,
expand=False,
expand=True,
padding=(1, 2),
style=Style(bgcolor="grey23", color="orange1"),
subtitle=f"[bold grey39]{OS}-{ARCH}",
@ -200,7 +203,7 @@ def graphical_accelerator():
[
f"Detected the [gold1]{OS}-{ARCH}[/] platform",
"",
"See [steel_blue3]https://invoke-ai.github.io/InvokeAI/#system[/] to ensure your system meets the minimum requirements.",
"See [deep_sky_blue1]https://invoke-ai.github.io/InvokeAI/#system[/] to ensure your system meets the minimum requirements.",
"",
"[red3]🠶[/] [b]Your GPU drivers must be correctly installed before using InvokeAI![/] [red3]🠴[/]",
]
@ -294,3 +297,16 @@ def introduction() -> None:
)
)
console.line(2)
def _platform_specific_help()->str:
if OS == "Darwin":
text = Text.from_markup("""[b wheat1]macOS Users![/]\n\nPlease be sure you have the [b wheat1]Xcode command-line tools[/] installed before continuing.\nIf not, cancel with [i]Control-C[/] and follow the Xcode install instructions at [deep_sky_blue1]https://www.freecodecamp.org/news/install-xcode-command-line-tools/[/].""")
elif OS == "Windows":
text = Text.from_markup("""[b wheat1]Windows Users![/]\n\nBefore you start, please do the following:
1. Double-click on the file [b wheat1]WinLongPathsEnabled.reg[/] in order to
enable long path support on your system.
2. Make sure you have the [b wheat1]Visual C++ core libraries[/] installed. If not, install from
[deep_sky_blue1]https://learn.microsoft.com/en-US/cpp/windows/latest-supported-vc-redist?view=msvc-170[/]""")
else:
text = ""
return text

2
ldm/invoke/_version.py
View File

@ -1 +1 @@
__version__='2.3.0-rc5'
__version__='2.3.0-rc6'

42
ldm/invoke/config/invokeai_configure.py
View File

@ -10,6 +10,7 @@ print("Loading Python libraries...\n")
import argparse
import io
import os
import re
import shutil
import sys
import traceback
@ -320,7 +321,7 @@ You may re-run the configuration script again in the future if you do not wish t
while again:
try:
access_token = getpass_asterisk.getpass_asterisk(prompt="HF Token ❯ ")
if access_token is None or len(access_token)==0:
if access_token is None or len(access_token) == 0:
raise EOFError
HfLogin(access_token)
access_token = HfFolder.get_token()
@ -379,7 +380,7 @@ def download_weight_datasets(
migrate_models_ckpt()
successful = dict()
for mod in models.keys():
print(f"{mod}...", file=sys.stderr, end="")
print(f"Downloading {mod}:")
successful[mod] = _download_repo_or_file(
Datasets[mod], access_token, precision=precision
)
@ -532,7 +533,7 @@ def update_config_file(successfully_downloaded: dict, opt: dict):
configs_dest = Default_config_file.parent
shutil.copytree(configs_src, configs_dest, dirs_exist_ok=True)
yaml = new_config_file_contents(successfully_downloaded, config_file)
yaml = new_config_file_contents(successfully_downloaded, config_file, opt)
try:
backup = None
@ -568,7 +569,7 @@ def update_config_file(successfully_downloaded: dict, opt: dict):
# ---------------------------------------------
def new_config_file_contents(successfully_downloaded: dict, config_file: Path) -> str:
def new_config_file_contents(successfully_downloaded: dict, config_file: Path, opt: dict) -> str:
if config_file.exists():
conf = OmegaConf.load(str(config_file.expanduser().resolve()))
else:
@ -576,7 +577,14 @@ def new_config_file_contents(successfully_downloaded: dict, config_file: Path) -
default_selected = None
for model in successfully_downloaded:
stanza = conf[model] if model in conf else {}
# a bit hacky - what we are doing here is seeing whether a checkpoint
# version of the model was previously defined, and whether the current
# model is a diffusers (indicated with a path)
if conf.get(model) and Path(successfully_downloaded[model]).is_dir():
offer_to_delete_weights(model, conf[model], opt.yes_to_all)
stanza = {}
mod = Datasets[model]
stanza["description"] = mod["description"]
stanza["repo_id"] = mod["repo_id"]
@ -599,8 +607,8 @@ def new_config_file_contents(successfully_downloaded: dict, config_file: Path) -
)
else:
stanza["vae"] = mod["vae"]
if mod.get('default',False):
stanza['default'] = True
if mod.get("default", False):
stanza["default"] = True
default_selected = True
conf[model] = stanza
@ -612,7 +620,22 @@ def new_config_file_contents(successfully_downloaded: dict, config_file: Path) -
return OmegaConf.to_yaml(conf)
# ---------------------------------------------
def offer_to_delete_weights(model_name: str, conf_stanza: dict, yes_to_all: bool):
if not (weights := conf_stanza.get('weights')):
return
if re.match('/VAE/',conf_stanza.get('config')):
return
if yes_to_all or \
yes_or_no(f'\n** The checkpoint version of {model_name} is superseded by the diffusers version. Delete the original file {weights}?', default_yes=False):
weights = Path(weights)
if not weights.is_absolute():
weights = Path(Globals.root) / weights
try:
weights.unlink()
except OSError as e:
print(str(e))
# ---------------------------------------------
# this will preload the Bert tokenizer fles
def download_bert():
@ -641,7 +664,8 @@ def download_from_hf(
resume_download=True,
**kwargs,
)
return path if model else None
model_name = '--'.join(('models',*model_name.split('/')))
return path / model_name if model else None
# ---------------------------------------------