Loading zoo/monochrome/train_.py +2 −2 Original line number Diff line number Diff line Loading @@ -121,8 +121,8 @@ def train(dataset_dir: str, session_name: Optional[str] = None, from_ckpt: Optio #if torch.cuda.is_available(): # model = model.cuda() #loss_fn = nn.CrossEntropyLoss() loss_fn = lambda inputs, targets: sigmoid_focal_loss(inputs, targets, reduction='mean') loss_fn = nn.CrossEntropyLoss() #loss_fn = lambda inputs, targets: sigmoid_focal_loss(inputs, targets, reduction='mean') optimizer = torch.optim.AdamW(model.parameters(), lr=learning_rate, weight_decay=weight_decay) scheduler = lr_scheduler.OneCycleLR( optimizer, max_lr=learning_rate, Loading Loading
zoo/monochrome/train_.py +2 −2 Original line number Diff line number Diff line Loading @@ -121,8 +121,8 @@ def train(dataset_dir: str, session_name: Optional[str] = None, from_ckpt: Optio #if torch.cuda.is_available(): # model = model.cuda() #loss_fn = nn.CrossEntropyLoss() loss_fn = lambda inputs, targets: sigmoid_focal_loss(inputs, targets, reduction='mean') loss_fn = nn.CrossEntropyLoss() #loss_fn = lambda inputs, targets: sigmoid_focal_loss(inputs, targets, reduction='mean') optimizer = torch.optim.AdamW(model.parameters(), lr=learning_rate, weight_decay=weight_decay) scheduler = lr_scheduler.OneCycleLR( optimizer, max_lr=learning_rate, Loading