The latest release 1.1.0 removed the latest training metrics from the result produced by Trainer.test method. Why?
For some reason Trainer.test methods doesn't return train metrics starting with v.1.1.0 PTL.
Was that done on purpose? If yes, then how can I get the latest values of training metrics?
v1.1.0:
DATALOADER:0 TEST RESULTS
{'test_acc': tensor(0.6441, device='cuda:0'),
'test_acc_epoch': tensor(0.8204, device='cuda:0'),
'test_f1': tensor(0.6441, device='cuda:0'),
'test_f1_epoch': tensor(0.8204, device='cuda:0'),
'test_loss': tensor(1.4021, device='cuda:0'),
'test_loss_epoch': tensor(0.6918, device='cuda:0'),
'test_prec': tensor(0.6441, device='cuda:0'),
'test_prec_epoch': tensor(0.8204, device='cuda:0'),
'test_rec': tensor(0.6441, device='cuda:0'),
'test_rec_epoch': tensor(0.8204, device='cuda:0'),
'val_acc': tensor(0.6441, device='cuda:0'),
'val_acc_epoch': tensor(0.8204, device='cuda:0'),
'val_f1': tensor(0.6441, device='cuda:0'),
'val_f1_epoch': tensor(0.8204, device='cuda:0'),
'val_loss': tensor(1.4021, device='cuda:0'),
'val_loss_epoch': tensor(0.6918, device='cuda:0'),
'val_prec': tensor(0.6441, device='cuda:0'),
'val_prec_epoch': tensor(0.8204, device='cuda:0'),
'val_rec': tensor(0.6441, device='cuda:0'),
'val_rec_epoch': tensor(0.8204, device='cuda:0')
}
Before v1.1.0:
DATALOADER:0 TEST RESULTS
{'test_acc': tensor(0.6441, device='cuda:0'),
'test_acc_epoch': tensor(0.8204, device='cuda:0'),
'test_f1': tensor(0.6441, device='cuda:0'),
'test_f1_epoch': tensor(0.8204, device='cuda:0'),
'test_loss': tensor(1.4021, device='cuda:0'),
'test_loss_epoch': tensor(0.6918, device='cuda:0'),
'test_prec': tensor(0.6441, device='cuda:0'),
'test_prec_epoch': tensor(0.8204, device='cuda:0'),
'test_rec': tensor(0.6441, device='cuda:0'),
'test_rec_epoch': tensor(0.8204, device='cuda:0'),
'val_acc': tensor(0.6441, device='cuda:0'),
'val_acc_epoch': tensor(0.8204, device='cuda:0'),
'val_f1': tensor(0.6441, device='cuda:0'),
'val_f1_epoch': tensor(0.8204, device='cuda:0'),
'val_loss': tensor(1.4021, device='cuda:0'),
'val_loss_epoch': tensor(0.6918, device='cuda:0'),
'val_prec': tensor(0.6441, device='cuda:0'),
'val_prec_epoch': tensor(0.8204, device='cuda:0'),
'val_rec': tensor(0.6441, device='cuda:0'),
'val_rec_epoch': tensor(0.8204, device='cuda:0'),
'train_acc':
'train_acc_epoch':
'train_f1':
'train_f1_epoch':
'train_loss':
'train_loss_epoch':
'train_prec':
'train_prec_epoch':
'train_rec':
'train_rec_epoch': }