mirror of
https://github.com/kohya-ss/sd-scripts.git
synced 2026-04-15 08:36:41 +00:00
Removed call of sum()
This commit is contained in:
@@ -207,6 +207,7 @@ def train(args):
|
||||
accelerator.init_trackers("dreambooth")
|
||||
|
||||
loss_list = []
|
||||
loss_total = 0.0
|
||||
for epoch in range(num_train_epochs):
|
||||
print(f"epoch {epoch+1}/{num_train_epochs}")
|
||||
train_dataset.set_current_epoch(epoch + 1)
|
||||
@@ -294,8 +295,10 @@ def train(args):
|
||||
if epoch == 0:
|
||||
loss_list.append(current_loss)
|
||||
else:
|
||||
loss_total -= loss_list[step]
|
||||
loss_list[step] = current_loss
|
||||
avr_loss = sum(loss_list) / len(loss_list)
|
||||
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)
|
||||
|
||||
@@ -303,7 +306,7 @@ def train(args):
|
||||
break
|
||||
|
||||
if args.logging_dir is not None:
|
||||
logs = {"epoch_loss": sum(loss_list) / len(loss_list)}
|
||||
logs = {"epoch_loss": loss_total / len(loss_list)}
|
||||
accelerator.log(logs, step=epoch+1)
|
||||
|
||||
accelerator.wait_for_everyone()
|
||||
|
||||
@@ -379,6 +379,7 @@ def train(args):
|
||||
accelerator.init_trackers("network_train")
|
||||
|
||||
loss_list = []
|
||||
loss_total = 0.0
|
||||
for epoch in range(num_train_epochs):
|
||||
print(f"epoch {epoch+1}/{num_train_epochs}")
|
||||
train_dataset.set_current_epoch(epoch + 1)
|
||||
@@ -449,8 +450,10 @@ def train(args):
|
||||
if epoch == 0:
|
||||
loss_list.append(current_loss)
|
||||
else:
|
||||
loss_total -= loss_list[step]
|
||||
loss_list[step] = current_loss
|
||||
avr_loss = sum(loss_list) / len(loss_list)
|
||||
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)
|
||||
|
||||
@@ -462,7 +465,7 @@ def train(args):
|
||||
break
|
||||
|
||||
if args.logging_dir is not None:
|
||||
logs = {"loss/epoch": sum(loss_list) / len(loss_list)}
|
||||
logs = {"loss/epoch": loss_total / len(loss_list)}
|
||||
accelerator.log(logs, step=epoch+1)
|
||||
|
||||
accelerator.wait_for_everyone()
|
||||
|
||||
Reference in New Issue
Block a user