weigt and bias

weigt_and_bias.py

import wandb

    model_profile_str = f'{args.model}_{args.wider_factor}Xwider_{args.dataset}'
    wandb_proiject_name = "model folding" 
    experiment_name = f"train_{model_profile_str}"
    run = wandb.init(project=wandb_proiject_name, name=experiment_name, entity="naguoyu", 
               config={"dataset":args.dataset},
               )


    for epoch in range(epochs):
        train_acc, train_loss = train(train_loader, model, criterion, optimizer, epoch, device=device)
        scheduler.step()
        test_acc, test_loss = test(test_loader, model, criterion, epoch, device=device)
        run.log({"train/acc": train_acc, "train/loss": train_loss, "test/acc": test_acc, "test/loss": test_loss})

    test_acc = test(test_loader, model, criterion, epoch, device=device)

    print(f'Test accuracy: {test_acc}')
    print('\n')



if __name__ == '__main__':
    main()