ALTeGraD-2023 Data Challenge

Battre_Sacha_et_Wan

Syntax for the use of loss functions: loss = LossFunctions.Contrastive_Loss

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loss = LossFunctions.InfoNCE

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loss = LossFunctions.NTXent('cpu', batch_size, 0.1, True)

Puis train_val_test.train(nb_epochs, optimizer, loss, model, train_loader, val_loader, save_path, device, hyper_param, print_every=1)

To use the learning rate scheduler (LROnPlateau):

optimizer = optim.AdamW(model.parameters(), lr=learning_rate, betas=(0.9, 0.999), weight_decay=0.01) scheduler = optim.lr_scheduler.ReduceLROnPlateau(optimizer, 'min', patience=2, factor=0.1, threshold=0.1, threshold_mode='rel', verbose=True)

and when calling the training: train(nb_epochs, optimizer, loss, model, train_loader, val_loader, save_path, device, hyper_param, save_id=1000, scheduler=scheduler, print_every=1) (the default value of the scheduler is None, so that it works even when not given)