mirror of
https://github.com/brycedrennan/imaginAIry
synced 2024-11-17 09:25:47 +00:00
40 lines
1.0 KiB
Python
40 lines
1.0 KiB
Python
import logging
|
|
import os
|
|
|
|
import torch
|
|
|
|
logger = logging.getLogger(__name__)
|
|
|
|
|
|
def prune_diffusion_ckpt(ckpt_path, dst_path=None):
|
|
if dst_path is None:
|
|
dst_path = f"{os.path.splitext(ckpt_path)[0]}-pruned.ckpt"
|
|
|
|
data = torch.load(ckpt_path, map_location="cpu")
|
|
|
|
new_data = prune_model_data(data)
|
|
|
|
torch.save(new_data, dst_path)
|
|
|
|
size_initial = os.path.getsize(ckpt_path)
|
|
newsize = os.path.getsize(dst_path)
|
|
msg = (
|
|
f"New ckpt size: {newsize * 1e-9:.2f} GB. "
|
|
f"Saved {(size_initial - newsize) * 1e-9:.2f} GB by removing optimizer states"
|
|
)
|
|
logger.info(msg)
|
|
|
|
|
|
def prune_model_data(data, only_keep_ema=True):
|
|
data.pop("optimizer_states", None)
|
|
if only_keep_ema:
|
|
state_dict = data["state_dict"]
|
|
model_keys = [k for k in state_dict.keys() if k.startswith("model.")]
|
|
|
|
for model_key in model_keys:
|
|
ema_key = "model_ema." + model_key[6:].replace(".", "")
|
|
state_dict[model_key] = state_dict[ema_key]
|
|
del state_dict[ema_key]
|
|
|
|
return data
|