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# Copyright (C) 2022 Lopho <contact@lopho.org>
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU Affero General Public License as published
# by the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU Affero General Public License for more details.
#
# You should have received a copy of the GNU Affero General Public License
# along with this program. If not, see <https://www.gnu.org/licenses/>.
def prune(
checkpoint,
fp16 = False,
ema = False,
clip = True,
vae = True,
depth = True,
unet = True,
):
sd = checkpoint
nested_sd = False
if 'state_dict' in sd:
sd = sd['state_dict']
nested_sd = True
sd_pruned = dict()
for k in sd:
cp = unet and k.startswith('model.diffusion_model.')
cp = cp or (depth and k.startswith('depth_model.'))
cp = cp or (vae and k.startswith('first_stage_model.'))
cp = cp or (clip and k.startswith('cond_stage_model.'))
if cp:
k_in = k
if ema:
k_ema = 'model_ema.' + k[6:].replace('.', '')
if k_ema in sd:
k_in = k_ema
sd_pruned[k] = sd[k_in].half() if fp16 else sd[k_in]
if nested_sd:
return { 'state_dict': sd_pruned }
else:
return sd_pruned
def main(args):
import os
from argparse import ArgumentParser
from functools import partial
parser = ArgumentParser(
description = "Prune a stable diffusion checkpoint",
epilog = "Copyright (C) 2022 Lopho <contact@lopho.org> | \
Licensed under the AGPLv3 <https://www.gnu.org/licenses/>"
)
parser.add_argument(
'input',
type = str,
help = "input checkpoint"
)
parser.add_argument(
'output',
type = str,
help = "output checkpoint"
)
parser.add_argument(
'-p', '--fp16',
action = 'store_true',
help = "convert to float16"
)
parser.add_argument(
'-e', '--ema',
action = 'store_true',
help = "use EMA for weights"
)
parser.add_argument(
'-c', '--no-clip',
action = 'store_true',
help = "strip CLIP weights"
)
parser.add_argument(
'-a', '--no-vae',
action = 'store_true',
help = "strip VAE weights"
)
parser.add_argument(
'-d', '--no-depth',
action = 'store_true',
help = "strip depth model weights"
)
parser.add_argument(
'-u', '--no-unet',
action = 'store_true',
help = "strip UNet weights"
)
def error(self, message):
import sys
sys.stderr.write(f"error: {message}\n")
self.print_help()
self.exit()
parser.error = partial(error, parser) # type: ignore
args = parser.parse_args(args)
is_safetensors = os.path.splitext(args.input)[1].lower() == '.safetensors'
if is_safetensors:
from safetensors.torch import load_file, save_file
input_sd = load_file(args.input)
else:
from torch import load, save
import pickle as python_pickle
class torch_pickle:
class Unpickler(python_pickle.Unpickler):
def find_class(self, module, name):
try:
return super().find_class(module, name)
except:
return None
input_sd = load(args.input, pickle_module = torch_pickle) # type: ignore
pruned = prune(
input_sd,
fp16 = args.fp16,
ema = args.ema,
clip = not args.no_clip,
vae = not args.no_vae,
depth = not args.no_depth,
unet = not args.no_unet
)
if is_safetensors:
save_file(pruned, args.output)
else:
save(pruned, args.output)
if __name__ == '__main__':
import sys
main(sys.argv[1:])
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