mirror of
https://github.com/invoke-ai/InvokeAI
synced 2024-08-30 20:32:17 +00:00
use diffusers 0.14 cache layout, upgrade transformers, safetensors, accelerate (#2913)
This PR ports the `main` PR #2871 to the v2.3 branch. This adjusts the global diffusers model cache to work with the 0.14 diffusers layout of placing models in HF_HOME/hub rather than HF_HOME/diffusers. It also implements the one-time migration action to the new layout.
This commit is contained in:
commit
9c2f3259ca
@ -960,7 +960,6 @@ def prepare_image_metadata(
|
||||
wildcards["seed"] = seed
|
||||
wildcards["model_id"] = model_id
|
||||
try:
|
||||
print(f'DEBUG: fnformat={opt.fnformat}')
|
||||
filename = opt.fnformat.format(**wildcards)
|
||||
except KeyError as e:
|
||||
print(
|
||||
|
@ -1 +1 @@
|
||||
__version__='2.3.1.post2'
|
||||
__version__='2.3.2'
|
||||
|
@ -290,7 +290,7 @@ def download_vaes():
|
||||
# first the diffusers version
|
||||
repo_id = "stabilityai/sd-vae-ft-mse"
|
||||
args = dict(
|
||||
cache_dir=global_cache_dir("diffusers"),
|
||||
cache_dir=global_cache_dir("hub"),
|
||||
)
|
||||
if not AutoencoderKL.from_pretrained(repo_id, **args):
|
||||
raise Exception(f"download of {repo_id} failed")
|
||||
|
@ -262,7 +262,6 @@ def _download_diffusion_weights(
|
||||
path = download_from_hf(
|
||||
model_class,
|
||||
repo_id,
|
||||
cache_subdir="diffusers",
|
||||
safety_checker=None,
|
||||
**extra_args,
|
||||
)
|
||||
|
@ -88,16 +88,13 @@ def global_cache_dir(subdir:Union[str,Path]='')->Path:
|
||||
'''
|
||||
Returns Path to the model cache directory. If a subdirectory
|
||||
is provided, it will be appended to the end of the path, allowing
|
||||
for huggingface-style conventions:
|
||||
global_cache_dir('diffusers')
|
||||
for Hugging Face-style conventions. Currently, Hugging Face has
|
||||
moved all models into the "hub" subfolder, so for any pretrained
|
||||
HF model, use:
|
||||
global_cache_dir('hub')
|
||||
Current HuggingFace documentation (mid-Jan 2023) indicates that
|
||||
transformers models will be cached into a "transformers" subdirectory,
|
||||
but in practice they seem to go into "hub". But if needed:
|
||||
global_cache_dir('transformers')
|
||||
One other caveat is that HuggingFace is moving some diffusers models
|
||||
into the "hub" subdirectory as well, so this will need to be revisited
|
||||
from time to time.
|
||||
|
||||
The legacy location for transformers used to be global_cache_dir('transformers')
|
||||
and global_cache_dir('diffusers') for diffusers.
|
||||
'''
|
||||
home: str = os.getenv('HF_HOME')
|
||||
|
||||
|
@ -437,10 +437,10 @@ def main():
|
||||
args = _parse_args()
|
||||
global_set_root(args.root_dir)
|
||||
|
||||
cache_dir = str(global_cache_dir("diffusers"))
|
||||
cache_dir = str(global_cache_dir("hub"))
|
||||
os.environ[
|
||||
"HF_HOME"
|
||||
] = cache_dir # because not clear the merge pipeline is honoring cache_dir
|
||||
] = str(global_cache_dir()) # because not clear the merge pipeline is honoring cache_dir
|
||||
args.cache_dir = cache_dir
|
||||
|
||||
try:
|
||||
|
@ -507,7 +507,7 @@ class ModelManager(object):
|
||||
if vae := self._load_vae(mconfig["vae"]):
|
||||
pipeline_args.update(vae=vae)
|
||||
if not isinstance(name_or_path, Path):
|
||||
pipeline_args.update(cache_dir=global_cache_dir("diffusers"))
|
||||
pipeline_args.update(cache_dir=global_cache_dir("hub"))
|
||||
if using_fp16:
|
||||
pipeline_args.update(torch_dtype=torch.float16)
|
||||
fp_args_list = [{"revision": "fp16"}, {}]
|
||||
@ -1093,9 +1093,12 @@ class ModelManager(object):
|
||||
to the 2.3.0 "diffusers" version. This should be a one-time operation, called at
|
||||
script startup time.
|
||||
"""
|
||||
# Three transformer models to check: bert, clip and safety checker
|
||||
# Three transformer models to check: bert, clip and safety checker, and
|
||||
# the diffusers as well
|
||||
models_dir = Path(Globals.root, "models")
|
||||
legacy_locations = [
|
||||
Path(
|
||||
models_dir,
|
||||
"CompVis/stable-diffusion-safety-checker/models--CompVis--stable-diffusion-safety-checker"
|
||||
),
|
||||
Path("bert-base-uncased/models--bert-base-uncased"),
|
||||
@ -1103,17 +1106,26 @@ class ModelManager(object):
|
||||
"openai/clip-vit-large-patch14/models--openai--clip-vit-large-patch14"
|
||||
),
|
||||
]
|
||||
models_dir = Path(Globals.root, "models")
|
||||
legacy_locations.extend(list(global_cache_dir("diffusers").glob('*')))
|
||||
legacy_layout = False
|
||||
for model in legacy_locations:
|
||||
legacy_layout = legacy_layout or Path(models_dir, model).exists()
|
||||
legacy_layout = legacy_layout or model.exists()
|
||||
if not legacy_layout:
|
||||
return
|
||||
|
||||
print(
|
||||
"** Legacy version <= 2.2.5 model directory layout detected. Reorganizing."
|
||||
"""
|
||||
>> ALERT:
|
||||
>> The location of your previously-installed diffusers models needs to move from
|
||||
>> invokeai/models/diffusers to invokeai/models/hub due to a change introduced by
|
||||
>> diffusers version 0.14. InvokeAI will now move all models from the "diffusers" directory
|
||||
>> into "hub" and then remove the diffusers directory. This is a quick, safe, one-time
|
||||
>> operation. However if you have customized either of these directories and need to
|
||||
>> make adjustments, please press ctrl-C now to abort and relaunch InvokeAI when you are ready.
|
||||
>> Otherwise press <enter> to continue."""
|
||||
)
|
||||
print("** This is a quick one-time operation.")
|
||||
input("continue> ")
|
||||
|
||||
# transformer files get moved into the hub directory
|
||||
if cls._is_huggingface_hub_directory_present():
|
||||
@ -1125,33 +1137,20 @@ class ModelManager(object):
|
||||
for model in legacy_locations:
|
||||
source = models_dir / model
|
||||
dest = hub / model.stem
|
||||
if dest.exists() and not source.exists():
|
||||
continue
|
||||
print(f"** {source} => {dest}")
|
||||
if source.exists():
|
||||
if dest.exists():
|
||||
rmtree(source)
|
||||
if dest.is_symlink():
|
||||
print(f"** Found symlink at {dest.name}. Not migrating.")
|
||||
elif dest.exists():
|
||||
if source.is_dir():
|
||||
rmtree(source)
|
||||
else:
|
||||
source.unlink()
|
||||
else:
|
||||
move(source, dest)
|
||||
|
||||
# anything else gets moved into the diffusers directory
|
||||
if cls._is_huggingface_hub_directory_present():
|
||||
diffusers = global_cache_dir("diffusers")
|
||||
else:
|
||||
diffusers = models_dir / "diffusers"
|
||||
|
||||
os.makedirs(diffusers, exist_ok=True)
|
||||
for root, dirs, _ in os.walk(models_dir, topdown=False):
|
||||
for dir in dirs:
|
||||
full_path = Path(root, dir)
|
||||
if full_path.is_relative_to(hub) or full_path.is_relative_to(diffusers):
|
||||
continue
|
||||
if Path(dir).match("models--*--*"):
|
||||
dest = diffusers / dir
|
||||
print(f"** {full_path} => {dest}")
|
||||
if dest.exists():
|
||||
rmtree(full_path)
|
||||
else:
|
||||
move(full_path, dest)
|
||||
|
||||
|
||||
# now clean up by removing any empty directories
|
||||
empty = [
|
||||
root
|
||||
@ -1249,7 +1248,7 @@ class ModelManager(object):
|
||||
path = name_or_path
|
||||
else:
|
||||
owner, repo = name_or_path.split("/")
|
||||
path = Path(global_cache_dir("diffusers") / f"models--{owner}--{repo}")
|
||||
path = Path(global_cache_dir("hub") / f"models--{owner}--{repo}")
|
||||
if not path.exists():
|
||||
return None
|
||||
hashpath = path / "checksum.sha256"
|
||||
@ -1310,7 +1309,7 @@ class ModelManager(object):
|
||||
using_fp16 = self.precision == "float16"
|
||||
|
||||
vae_args.update(
|
||||
cache_dir=global_cache_dir("diffusers"),
|
||||
cache_dir=global_cache_dir("hug"),
|
||||
local_files_only=not Globals.internet_available,
|
||||
)
|
||||
|
||||
|
@ -634,7 +634,7 @@ def do_textual_inversion_training(
|
||||
assert (
|
||||
pretrained_model_name_or_path
|
||||
), f"models.yaml error: neither 'repo_id' nor 'path' is defined for {model}"
|
||||
pipeline_args = dict(cache_dir=global_cache_dir("diffusers"))
|
||||
pipeline_args = dict(cache_dir=global_cache_dir("hub"))
|
||||
|
||||
# Load tokenizer
|
||||
if tokenizer_name:
|
||||
|
@ -28,13 +28,13 @@ classifiers = [
|
||||
"Topic :: Scientific/Engineering :: Image Processing",
|
||||
]
|
||||
dependencies = [
|
||||
"accelerate",
|
||||
"accelerate~=0.16",
|
||||
"albumentations",
|
||||
"click",
|
||||
"clip_anytorch",
|
||||
"compel==0.1.7",
|
||||
"datasets",
|
||||
"diffusers[torch]~=0.13",
|
||||
"diffusers[torch]~=0.14",
|
||||
"dnspython==2.2.1",
|
||||
"einops",
|
||||
"eventlet",
|
||||
@ -63,7 +63,7 @@ dependencies = [
|
||||
"pytorch-lightning==1.7.7",
|
||||
"realesrgan",
|
||||
"requests==2.28.2",
|
||||
"safetensors",
|
||||
"safetensors~=0.3.0",
|
||||
"scikit-image>=0.19",
|
||||
"send2trash",
|
||||
"streamlit",
|
||||
@ -73,7 +73,7 @@ dependencies = [
|
||||
"torch>=1.13.1",
|
||||
"torchmetrics",
|
||||
"torchvision>=0.14.1",
|
||||
"transformers~=4.25",
|
||||
"transformers~=4.26",
|
||||
"windows-curses; sys_platform=='win32'",
|
||||
]
|
||||
description = "An implementation of Stable Diffusion which provides various new features and options to aid the image generation process"
|
||||
|
Loading…
Reference in New Issue
Block a user