Skip to content

Show the moving average loss #189

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
merged 2 commits into from
Feb 16, 2023
Merged

Show the moving average loss #189

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
2 commits
Select commit Hold shift + click to select a range
21f5b61
Show the moving average loss
shirayu Feb 14, 2023
8aed512
Removed call of sum()
shirayu Feb 14, 2023
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
12 changes: 9 additions & 3 deletions train_db.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -206,6 +206,8 @@ def train(args):
if accelerator.is_main_process:
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)
Expand All @@ -216,7 +218,6 @@ def train(args):
if args.gradient_checkpointing or global_step < args.stop_text_encoder_training:
text_encoder.train()

loss_total = 0
for step, batch in enumerate(train_dataloader):
# 指定したステップ数でText Encoderの学習を止める
if global_step == args.stop_text_encoder_training:
Expand Down Expand Up @@ -291,16 +292,21 @@ def train(args):
logs = {"loss": current_loss, "lr": lr_scheduler.get_last_lr()[0]}
accelerator.log(logs, step=global_step)

if epoch == 0:
loss_list.append(current_loss)
else:
loss_total -= loss_list[step]
loss_list[step] = current_loss
loss_total += current_loss
avr_loss = loss_total / (step+1)
avr_loss = loss_total / len(loss_list)
logs = {"loss": avr_loss} # , "lr": lr_scheduler.get_last_lr()[0]}
progress_bar.set_postfix(**logs)

if global_step >= args.max_train_steps:
break

if args.logging_dir is not None:
logs = {"epoch_loss": loss_total / len(train_dataloader)}
logs = {"epoch_loss": loss_total / len(loss_list)}
accelerator.log(logs, step=epoch+1)

accelerator.wait_for_everyone()
Expand Down
12 changes: 9 additions & 3 deletions train_network.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -378,6 +378,8 @@ def train(args):
if accelerator.is_main_process:
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)
Expand All @@ -386,7 +388,6 @@ def train(args):

network.on_epoch_start(text_encoder, unet)

loss_total = 0
for step, batch in enumerate(train_dataloader):
with accelerator.accumulate(network):
with torch.no_grad():
Expand Down Expand Up @@ -446,8 +447,13 @@ def train(args):
global_step += 1

current_loss = loss.detach().item()
if epoch == 0:
loss_list.append(current_loss)
else:
loss_total -= loss_list[step]
loss_list[step] = current_loss
loss_total += current_loss
avr_loss = loss_total / (step+1)
avr_loss = loss_total / len(loss_list)
logs = {"loss": avr_loss} # , "lr": lr_scheduler.get_last_lr()[0]}
progress_bar.set_postfix(**logs)

Expand All @@ -459,7 +465,7 @@ def train(args):
break

if args.logging_dir is not None:
logs = {"loss/epoch": loss_total / len(train_dataloader)}
logs = {"loss/epoch": loss_total / len(loss_list)}
accelerator.log(logs, step=epoch+1)

accelerator.wait_for_everyone()
Expand Down