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Log lr for param groups (#159)

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Ayush Chaurasia 2023-01-09 04:57:14 +05:30 committed by GitHub
parent e79ea1666c
commit 9a2f67b3b4
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2 changed files with 4 additions and 2 deletions
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5
ultralytics/yolo/engine/trainer.py
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@ -317,7 +317,8 @@ class BaseTrainer:
self.run_callbacks("on_train_batch_end")
lr = {f"lr{ir}": x['lr'] for ir, x in enumerate(self.optimizer.param_groups)} # for loggers
self.lr = {f"lr/pg{ir}": x['lr'] for ir, x in enumerate(self.optimizer.param_groups)} # for loggers
self.scheduler.step()
self.run_callbacks("on_train_epoch_end")
@ -328,7 +329,7 @@ class BaseTrainer:
final_epoch = (epoch + 1 == self.epochs)
if self.args.val or final_epoch:
self.metrics, self.fitness = self.validate()
self.save_metrics(metrics={**self.label_loss_items(self.tloss), **self.metrics, **lr})
self.save_metrics(metrics={**self.label_loss_items(self.tloss), **self.metrics, **self.lr})
# Save model
if self.args.save or (epoch + 1 == self.epochs):

1
ultralytics/yolo/utils/callbacks/wb.py
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@ -25,6 +25,7 @@ def on_fit_epoch_end(trainer):
def on_train_epoch_end(trainer):
wandb.run.log(trainer.label_loss_items(trainer.tloss, prefix="train"), step=trainer.epoch + 1)
wandb.run.log(trainer.lr, step=trainer.epoch + 1)
if trainer.epoch == 1:
wandb.run.log({f.stem: wandb.Image(str(f))
for f in trainer.save_dir.glob('train_batch*.jpg')},