VictorMylle/Kohya-ss-sd-scripts
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Use LossRecorder

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This commit is contained in:
Yuta Hayashibe
2023-10-27 18:31:36 +09:00
parent 0d21925bdf
commit 9d00c8eea2
3 changed files with 15 additions and 33 deletions
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16
sdxl_train_control_net_lllite.py
View File

@@ -350,8 +350,7 @@ def train(args):
"lllite_control_net_train" if args.log_tracker_name is None else args.log_tracker_name, init_kwargs=init_kwargs "lllite_control_net_train" if args.log_tracker_name is None else args.log_tracker_name, init_kwargs=init_kwargs
) )
loss_list = [] loss_recorder = train_util.LossRecorder()
loss_total = 0.0
del train_dataset_group del train_dataset_group
# function for saving/removing # function for saving/removing
@@ -500,14 +499,9 @@ def train(args):
remove_model(remove_ckpt_name) remove_model(remove_ckpt_name)
current_loss = loss.detach().item() current_loss = loss.detach().item()
if epoch == 0: loss_recorder.add(epoch=epoch, step=step, loss=current_loss)
loss_list.append(current_loss) avr_loss: float = loss_recorder.moving_average
else: logs = {"avr_loss": avr_loss} # , "lr": lr_scheduler.get_last_lr()[0]}
loss_total -= loss_list[step]
loss_list[step] = current_loss
loss_total += current_loss
avr_loss = loss_total / len(loss_list)
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: if args.logging_dir is not None:
@@ -518,7 +512,7 @@ def train(args):
break break
if args.logging_dir is not None: if args.logging_dir is not None:
logs = {"loss/epoch": loss_total / len(loss_list)} logs = {"loss/epoch": loss_recorder.moving_average}
accelerator.log(logs, step=epoch + 1) accelerator.log(logs, step=epoch + 1)
accelerator.wait_for_everyone() accelerator.wait_for_everyone()

16
sdxl_train_control_net_lllite_old.py
View File

@@ -323,8 +323,7 @@ def train(args):
"lllite_control_net_train" if args.log_tracker_name is None else args.log_tracker_name, init_kwargs=init_kwargs "lllite_control_net_train" if args.log_tracker_name is None else args.log_tracker_name, init_kwargs=init_kwargs
) )
loss_list = [] loss_recorder = train_util.LossRecorder()
loss_total = 0.0
del train_dataset_group del train_dataset_group
# function for saving/removing # function for saving/removing
@@ -470,14 +469,9 @@ def train(args):
remove_model(remove_ckpt_name) remove_model(remove_ckpt_name)
current_loss = loss.detach().item() current_loss = loss.detach().item()
if epoch == 0: loss_recorder.add(epoch=epoch, step=step, loss=current_loss)
loss_list.append(current_loss) avr_loss: float = loss_recorder.moving_average
else: logs = {"avr_loss": avr_loss} # , "lr": lr_scheduler.get_last_lr()[0]}
loss_total -= loss_list[step]
loss_list[step] = current_loss
loss_total += current_loss
avr_loss = loss_total / len(loss_list)
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: if args.logging_dir is not None:
@@ -488,7 +482,7 @@ def train(args):
break break
if args.logging_dir is not None: if args.logging_dir is not None:
logs = {"loss/epoch": loss_total / len(loss_list)} logs = {"loss/epoch": loss_recorder.moving_average}
accelerator.log(logs, step=epoch + 1) accelerator.log(logs, step=epoch + 1)
accelerator.wait_for_everyone() accelerator.wait_for_everyone()

16
train_controlnet.py
View File

@@ -337,8 +337,7 @@ def train(args):
init_kwargs = toml.load(args.log_tracker_config) init_kwargs = toml.load(args.log_tracker_config)
accelerator.init_trackers("controlnet_train" if args.log_tracker_name is None else args.log_tracker_name, init_kwargs=init_kwargs) accelerator.init_trackers("controlnet_train" if args.log_tracker_name is None else args.log_tracker_name, init_kwargs=init_kwargs)
loss_list = [] loss_recorder = train_util.LossRecorder()
loss_total = 0.0
del train_dataset_group del train_dataset_group
# function for saving/removing # function for saving/removing
@@ -500,14 +499,9 @@ def train(args):
remove_model(remove_ckpt_name) remove_model(remove_ckpt_name)
current_loss = loss.detach().item() current_loss = loss.detach().item()
if epoch == 0: loss_recorder.add(epoch=epoch, step=step, loss=current_loss)
loss_list.append(current_loss) avr_loss: float = loss_recorder.moving_average
else: logs = {"avr_loss": avr_loss} # , "lr": lr_scheduler.get_last_lr()[0]}
loss_total -= loss_list[step]
loss_list[step] = current_loss
loss_total += current_loss
avr_loss = loss_total / len(loss_list)
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: if args.logging_dir is not None:
@@ -518,7 +512,7 @@ def train(args):
break break
if args.logging_dir is not None: if args.logging_dir is not None:
logs = {"loss/epoch": loss_total / len(loss_list)} logs = {"loss/epoch": loss_recorder.moving_average}
accelerator.log(logs, step=epoch + 1) accelerator.log(logs, step=epoch + 1)
accelerator.wait_for_everyone() accelerator.wait_for_everyone()