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improve ability to bulk import .ckpt and .safetensors

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This commit cleans up the code that did bulk imports of legacy model
files. The code has been refactored, and the user is now offered the
option of importing all the model files found in the directory, or
selecting which ones to import.
This commit is contained in:
Lincoln Stein 2023-02-11 17:59:12 -05:00
parent 4f7af55bc3
commit c660dcdfcd
2 changed files with 97 additions and 38 deletions
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46
docs/installation/050_INSTALLING_MODELS.md
View File

@ -95,7 +95,7 @@ There are multiple ways to install and manage models:
models files.
3. The web interface (WebUI) has a GUI for importing and managing
models.
models.
### Installation via `invokeai-configure`
@ -111,7 +111,7 @@ confirm that the files are complete.
You can install a new model, including any of the community-supported ones, via
the command-line client's `!import_model` command.
#### Installing `.ckpt` and `.safetensors` models
#### Installing individual `.ckpt` and `.safetensors` models
If the model is already downloaded to your local disk, use
`!import_model /path/to/file.ckpt` to load it. For example:
@ -136,15 +136,39 @@ invoke> !import_model https://example.org/sd_models/martians.safetensors
For this to work, the URL must not be password-protected. Otherwise
you will receive a 404 error.
When you import a legacy model, the CLI will ask you a few questions
about the model, including what size image it was trained on (usually
512x512), what name and description you wish to use for it, what
configuration file to use for it (usually the default
`v1-inference.yaml`), whether you'd like to make this model the
default at startup time, and whether you would like to install a
custom VAE (variable autoencoder) file for the model. For recent
models, the answer to the VAE question is usually "no," but it won't
hurt to answer "yes".
When you import a legacy model, the CLI will first ask you what type
of model this is. You can indicate whether it is a model based on
Stable Diffusion 1.x (1.4 or 1.5), one based on Stable Diffusion 2.x,
or a 1.x inpainting model. Be careful to indicate the correct model
type, or it will not load correctly. You can correct the model type
after the fact using the `!edit_model` command.
The system will then ask you a few other questions about the model,
including what size image it was trained on (usually 512x512), what
name and description you wish to use for it, and whether you would
like to install a custom VAE (variable autoencoder) file for the
model. For recent models, the answer to the VAE question is usually
"no," but it won't hurt to answer "yes".
After importing, the model will load. If this is successful, you will
be asked if you want to keep the model loaded in memory to start
generating immediately. You'll also be asked if you wish to make this
the default model on startup. You can change this later using
`!edit_model`.
#### Importing a batch of `.ckpt` and `.safetensors` models from a directory
You may also point `!import_model` to a directory containing a set of
`.ckpt` or `.safetensors` files. They will be imported _en masse_.
Example:
```console
invoke> !import_model C:/Users/fred/Downloads/civitai_models/
```
You will be given the option to import all models found in the
directory, or select which ones to import. If there are subfolders
within the directory, they will be searched for models to import.
#### Installing `diffusers` models

89
ldm/invoke/CLI.py
View File

@ -1,3 +1,4 @@
import click
import os
import re
import sys
@ -6,7 +7,7 @@ import traceback
from argparse import Namespace
from pathlib import Path
from typing import Optional, Union
from typing import Optional, Union, List
if sys.platform == "darwin":
os.environ["PYTORCH_ENABLE_MPS_FALLBACK"] = "1"
@ -21,7 +22,6 @@ from ldm.invoke.image_util import make_grid
from ldm.invoke.log import write_log
from ldm.invoke.model_manager import ModelManager
import click # type: ignore
import ldm.invoke
import pyparsing # type: ignore
@ -592,12 +592,8 @@ def import_model(model_path: str, gen, opt, completer):
models = list(Path(model_path).rglob('*.ckpt')) + list(Path(model_path).rglob('*.safetensors'))
if models:
# Only the last model name will be used below.
for model in sorted(models):
if click.confirm(f'Import {model.stem} ?', default=True):
model_name = import_ckpt_model(model, gen, opt, completer)
print()
models = import_checkpoint_list(models, gen, opt, completer)
model_name = models[0] if len(models) == 1 else None
else:
model_name = import_diffuser_model(Path(model_path), gen, opt, completer)
@ -614,13 +610,49 @@ def import_model(model_path: str, gen, opt, completer):
print('** model failed to load. Discarding configuration entry')
gen.model_manager.del_model(model_name)
return
if input('Make this the default model? [n] ').strip() in ('y','Y'):
if click.confirm('Make this the default model?', default=False):
gen.model_manager.set_default_model(model_name)
gen.model_manager.commit(opt.conf)
completer.update_models(gen.model_manager.list_models())
print(f'>> {model_name} successfully installed')
def import_checkpoint_list(models: List[Path], gen, opt, completer)->List[str]:
'''
Does a mass import of all the checkpoint/safetensors on a path list
'''
model_names = list()
choice = input('** Directory of checkpoint/safetensors models detected. Install <a>ll or <s>elected models? [a] ') or 'a'
do_all = choice.startswith('a')
if do_all:
config_file = _ask_for_config_file(models[0], completer, plural=True)
manager = gen.model_manager
for model in sorted(models):
model_name = f'{model.stem}'
model_description = f'Imported model {model_name}'
if model_name in manager.model_names():
print(f'** {model_name} is already imported. Skipping.')
elif manager.import_ckpt_model(
model,
config = config_file,
model_name = model_name,
model_description = model_description,
commit_to_conf = opt.conf):
model_names.append(model_name)
print(f'>> Model {model_name} imported successfully')
else:
print(f'** Model {model} failed to import')
else:
for model in sorted(models):
if click.confirm(f'Import {model.stem} ?', default=True):
if model_name := import_ckpt_model(model, gen, opt, completer):
print(f'>> Model {model.stem} imported successfully')
model_names.append(model_name)
else:
printf('** Model {model} failed to import')
print()
return model_names
def import_diffuser_model(path_or_repo: Union[Path, str], gen, _, completer) -> Optional[str]:
manager = gen.model_manager
default_name = Path(path_or_repo).stem
@ -632,7 +664,7 @@ def import_diffuser_model(path_or_repo: Union[Path, str], gen, _, completer) ->
model_description=default_description
)
vae = None
if input('Replace this model\'s VAE with "stabilityai/sd-vae-ft-mse"? [n] ').strip() in ('y','Y'):
if click.confirm('Replace this model\'s VAE with "stabilityai/sd-vae-ft-mse"?', default=False):
vae = dict(repo_id='stabilityai/sd-vae-ft-mse')
if not manager.import_diffuser_model(
@ -696,8 +728,7 @@ def _verify_load(model_name:str, gen)->bool:
print('** note that importing 2.X checkpoints is not supported. Please use !convert_model instead.')
return False
do_switch = input('Keep model loaded? [y] ')
if len(do_switch)==0 or do_switch[0] in ('y','Y'):
if click.confirm('Keep model loaded?', default=True):
gen.set_model(model_name)
else:
print('>> Restoring previous model')
@ -710,20 +741,26 @@ def _get_model_name_and_desc(model_manager,completer,model_name:str='',model_des
model_description = input(f'Description for this model [{model_description}]: ').strip() or model_description
return model_name, model_description
def _ask_for_config_file(model_path: Union[str,Path], completer)->Path:
default = 1
def _ask_for_config_file(model_path: Union[str,Path], completer, plural: bool=False)->Path:
default = '1'
if re.search('inpaint',str(model_path),flags=re.IGNORECASE):
default = 3
default = '3'
choices={
'1': 'v1-inference.yaml',
'2': 'v2-inference-v.yaml',
'3': 'v1-inpainting-inference.yaml',
}
print('''What type of model is this?:
prompt = '''What type of models are these?:
[1] Models based on Stable Diffusion 1.X
[2] Models based on Stable Diffusion 2.X
[3] Inpainting models based on Stable Diffusion 1.X
[4] Something else''' if plural else '''What type of model is this?:
[1] A model based on Stable Diffusion 1.X
[2] A model based on Stable Diffusion 2.X
[3] An inpainting model based on Stable Diffusion 1.X
[4] Something else''')
[3] An inpainting models based on Stable Diffusion 1.X
[4] Something else'''
print(prompt)
choice = input(f'Your choice: [{default}] ')
choice = choice.strip() or default
if config_file := choices.get(choice,None):
@ -782,7 +819,7 @@ def optimize_model(model_name_or_path:str, gen, opt, completer, original_config_
return
vae = None
if input('Replace this model\'s VAE with "stabilityai/sd-vae-ft-mse"? [n] ').strip() in ('y','Y'):
if click.confirm('Replace this model\'s VAE with "stabilityai/sd-vae-ft-mse"?', default=False):
vae = dict(repo_id='stabilityai/sd-vae-ft-mse')
new_config = gen.model_manager.convert_and_import(
@ -798,11 +835,10 @@ def optimize_model(model_name_or_path:str, gen, opt, completer, original_config_
return
completer.update_models(gen.model_manager.list_models())
if input(f'Load optimized model {model_name}? [y] ').strip() not in ('n','N'):
if click.confirm(f'Load optimized model {model_name}?', default=True):
gen.set_model(model_name)
response = input(f'Delete the original .ckpt file at ({ckpt_path} ? [n] ')
if response.startswith(('y','Y')):
if click.confirm(f'Delete the original .ckpt file at {ckpt_path}?',default=False):
ckpt_path.unlink(missing_ok=True)
print(f'{ckpt_path} deleted')
@ -815,10 +851,10 @@ def del_config(model_name:str, gen, opt, completer):
print(f"** Unknown model {model_name}")
return
if input(f'Remove {model_name} from the list of models known to InvokeAI? [y] ').strip().startswith(('n','N')):
if not click.confirm(f'Remove {model_name} from the list of models known to InvokeAI?',default=True):
return
delete_completely = input('Completely remove the model file or directory from disk? [n] ').startswith(('y','Y'))
delete_completely = click.confirm('Completely remove the model file or directory from disk?',default=False)
gen.model_manager.del_model(model_name,delete_files=delete_completely)
gen.model_manager.commit(opt.conf)
print(f'** {model_name} deleted')
@ -847,7 +883,7 @@ def edit_model(model_name:str, gen, opt, completer):
# this does the update
manager.add_model(new_name, info, True)
if input('Make this the default model? [n] ').startswith(('y','Y')):
if click.confirm('Make this the default model?',default=False):
manager.set_default_model(new_name)
manager.commit(opt.conf)
completer.update_models(manager.list_models())
@ -1179,8 +1215,7 @@ def report_model_error(opt:Namespace, e:Exception):
if yes_to_all:
print('** Reconfiguration is being forced by environment variable INVOKE_MODEL_RECONFIGURE')
else:
response = input('Do you want to run invokeai-configure script to select and/or reinstall models? [y] ')
if response.startswith(('n', 'N')):
if click.confirm('Do you want to run invokeai-configure script to select and/or reinstall models?', default=True):
return
print('invokeai-configure is launching....\n')