106 lines
3.2 KiB
Python
106 lines
3.2 KiB
Python
#
|
|
# From: https://raw.githubusercontent.com/KohakuBlueleaf/LoCon/main/extract_locon.py
|
|
#
|
|
|
|
import argparse
|
|
|
|
def get_args():
|
|
parser = argparse.ArgumentParser()
|
|
parser.add_argument(
|
|
"base_model", help="The model which use it to train the dreambooth model",
|
|
default='', type=str
|
|
)
|
|
parser.add_argument(
|
|
"db_model", help="the dreambooth model you want to extract the locon",
|
|
default='', type=str
|
|
)
|
|
parser.add_argument(
|
|
"output_name", help="the output model",
|
|
default='./out.pt', type=str
|
|
)
|
|
parser.add_argument(
|
|
"--is_v2", help="Your base/db model is sd v2 or not",
|
|
default=False, action="store_true"
|
|
)
|
|
parser.add_argument(
|
|
"--device", help="Which device you want to use to extract the locon",
|
|
default='cpu', type=str
|
|
)
|
|
parser.add_argument(
|
|
"--mode",
|
|
help=(
|
|
'extraction mode, can be "fixed", "threshold", "ratio", "percentile". '
|
|
'If not "fixed", network_dim and conv_dim will be ignored'
|
|
),
|
|
default='fixed', type=str
|
|
)
|
|
parser.add_argument(
|
|
"--linear_dim", help="network dim for linear layer in fixed mode",
|
|
default=1, type=int
|
|
)
|
|
parser.add_argument(
|
|
"--conv_dim", help="network dim for conv layer in fixed mode",
|
|
default=1, type=int
|
|
)
|
|
parser.add_argument(
|
|
"--linear_threshold", help="singular value threshold for linear layer in threshold mode",
|
|
default=0., type=float
|
|
)
|
|
parser.add_argument(
|
|
"--conv_threshold", help="singular value threshold for conv layer in threshold mode",
|
|
default=0., type=float
|
|
)
|
|
parser.add_argument(
|
|
"--linear_ratio", help="singular ratio for linear layer in ratio mode",
|
|
default=0., type=float
|
|
)
|
|
parser.add_argument(
|
|
"--conv_ratio", help="singular ratio for conv layer in ratio mode",
|
|
default=0., type=float
|
|
)
|
|
parser.add_argument(
|
|
"--linear_percentile", help="singular value percentile for linear layer percentile mode",
|
|
default=1., type=float
|
|
)
|
|
parser.add_argument(
|
|
"--conv_percentile", help="singular value percentile for conv layer percentile mode",
|
|
default=1., type=float
|
|
)
|
|
return parser.parse_args()
|
|
ARGS = get_args()
|
|
|
|
from locon.utils import extract_diff
|
|
from locon.kohya_model_utils import load_models_from_stable_diffusion_checkpoint
|
|
|
|
import torch
|
|
|
|
|
|
def main():
|
|
args = ARGS
|
|
base = load_models_from_stable_diffusion_checkpoint(args.is_v2, args.base_model)
|
|
db = load_models_from_stable_diffusion_checkpoint(args.is_v2, args.db_model)
|
|
|
|
linear_mode_param = {
|
|
'fixed': args.linear_dim,
|
|
'threshold': args.linear_threshold,
|
|
'ratio': args.linear_ratio,
|
|
'percentile': args.linear_percentile,
|
|
}[args.mode]
|
|
conv_mode_param = {
|
|
'fixed': args.conv_dim,
|
|
'threshold': args.conv_threshold,
|
|
'ratio': args.conv_ratio,
|
|
'percentile': args.conv_percentile,
|
|
}[args.mode]
|
|
|
|
state_dict = extract_diff(
|
|
base, db,
|
|
args.mode,
|
|
linear_mode_param, conv_mode_param,
|
|
args.device
|
|
)
|
|
torch.save(state_dict, args.output_name)
|
|
|
|
|
|
if __name__ == '__main__':
|
|
main() |