VictorMylle/Kohya-ss-sd-scripts
1
0
Fork 1
mirror of https://github.com/kohya-ss/sd-scripts.git synced 2026-04-09 06:45:09 +00:00
Code Issues Packages Projects Releases Wiki Activity

Merge branch 'dev' of https://github.com/kohya-ss/sd-scripts into dev

Browse Source
This commit is contained in:
Kohya S
2023-01-21 12:46:20 +09:00
parent 9ff26af68b 7ee808d5d7
commit 17089b1287
2 changed files with 18 additions and 5 deletions
Download Patch File Download Diff File Expand all files Collapse all files

12
library/train_util.py
View File

@@ -1423,5 +1423,17 @@ def save_state_on_train_end(args: argparse.Namespace, accelerator):
model_name = DEFAULT_LAST_OUTPUT_NAME if args.output_name is None else args.output_name model_name = DEFAULT_LAST_OUTPUT_NAME if args.output_name is None else args.output_name
accelerator.save_state(os.path.join(args.output_dir, LAST_STATE_NAME.format(model_name))) accelerator.save_state(os.path.join(args.output_dir, LAST_STATE_NAME.format(model_name)))
def generate_step_logs(args: argparse.Namespace, current_loss, avr_loss, lr_scheduler):
logs = {"loss/current": current_loss, "loss/average": avr_loss}
if args.network_train_unet_only:
logs["lr/unet"] = lr_scheduler.get_last_lr()[0]
elif args.network_train_text_encoder_only:
logs["lr/textencoder"] = lr_scheduler.get_last_lr()[0]
else:
logs["lr/textencoder"] = lr_scheduler.get_last_lr()[0]
logs["lr/unet"] = lr_scheduler.get_last_lr()[-1]
return logs
# endregion # endregion

11
train_network.py
View File

@@ -347,20 +347,21 @@ def train(args):
global_step += 1 global_step += 1
current_loss = loss.detach().item() current_loss = loss.detach().item()
if args.logging_dir is not None:
logs = {"loss": current_loss, "lr": lr_scheduler.get_last_lr()[0]}
accelerator.log(logs, step=global_step)
loss_total += current_loss loss_total += current_loss
avr_loss = loss_total / (step+1) avr_loss = loss_total / (step+1)
logs = {"loss": avr_loss} # , "lr": lr_scheduler.get_last_lr()[0]} logs = {"loss": avr_loss} # , "lr": lr_scheduler.get_last_lr()[0]}
progress_bar.set_postfix(**logs) progress_bar.set_postfix(**logs)
if args.logging_dir is not None:
logs = train_util.generate_step_logs(args, current_loss, avr_loss, lr_scheduler)
accelerator.log(logs, step=global_step)
if global_step >= args.max_train_steps: if global_step >= args.max_train_steps:
break break
if args.logging_dir is not None: if args.logging_dir is not None:
logs = {"epoch_loss": loss_total / len(train_dataloader)} logs = {"loss/epoch": loss_total / len(train_dataloader)}
accelerator.log(logs, step=epoch+1) accelerator.log(logs, step=epoch+1)
accelerator.wait_for_everyone() accelerator.wait_for_everyone()