VictorMylle/Kohya-ss-sd-scripts
1
0
Fork 1
mirror of https://github.com/kohya-ss/sd-scripts.git synced 2026-04-08 22:35:09 +00:00
Code Issues Packages Projects Releases Wiki Activity

enable full bf16 trainint in train_network

Browse Source
This commit is contained in:
Kohya S
2023-07-19 08:41:42 +09:00
parent 7875ca8fb5
commit 225e871819
3 changed files with 11 additions and 3 deletions
Download Patch File Download Diff File Expand all files Collapse all files

4
library/train_util.py
View File

@@ -2687,7 +2687,9 @@ def add_training_arguments(parser: argparse.ArgumentParser, support_dreambooth:
"--mixed_precision", type=str, default="no", choices=["no", "fp16", "bf16"], help="use mixed precision / 混合精度を使う場合、その精度"
)
parser.add_argument("--full_fp16", action="store_true", help="fp16 training including gradients / 勾配も含めてfp16で学習する")
parser.add_argument("--full_bf16", action="store_true", help="bf16 training including gradients / 勾配も含めてbf16で学習する")
parser.add_argument(
"--full_bf16", action="store_true", help="bf16 training including gradients / 勾配も含めてbf16で学習する"
) # TODO move to SDXL training, because it is not supported by SD1/2
parser.add_argument(
"--clip_skip",
type=int,

2
sdxl_train.py
View File

@@ -273,7 +273,7 @@ def train(args):
# lr schedulerを用意する
lr_scheduler = train_util.get_scheduler_fix(args, optimizer, accelerator.num_processes)
# 実験的機能：勾配も含めたfp16/bf16学習を行う　モデル全体をfp16にする
# 実験的機能：勾配も含めたfp16/bf16学習を行う　モデル全体をfp16/bf16にする
if args.full_fp16:
assert (
args.mixed_precision == "fp16"

8
train_network.py
View File

@@ -350,13 +350,19 @@ class NetworkTrainer:
# lr schedulerを用意する
lr_scheduler = train_util.get_scheduler_fix(args, optimizer, accelerator.num_processes)
# 実験的機能：勾配も含めたfp16学習を行う　モデル全体をfp16にする
# 実験的機能：勾配も含めたfp16/bf16学習を行う　モデル全体をfp16/bf16にする
if args.full_fp16:
assert (
args.mixed_precision == "fp16"
), "full_fp16 requires mixed precision='fp16' / full_fp16を使う場合はmixed_precision='fp16'を指定してください。"
accelerator.print("enable full fp16 training.")
network.to(weight_dtype)
elif args.full_bf16:
assert (
args.mixed_precision == "bf16"
), "full_bf16 requires mixed precision='bf16' / full_bf16を使う場合はmixed_precision='bf16'を指定してください。"
accelerator.print("enable full bf16 training.")
network.to(weight_dtype)
unet.requires_grad_(False)
unet.to(dtype=weight_dtype)