# Codeblock 8
def class_loss_test():
    target = torch.zeros(BATCH_SIZE, S, S, (C+5))
    prediction = torch.zeros(BATCH_SIZE, S, S, (C+B*5))
    
    target[0, 3, 3, 21:25] = torch.tensor([0.4, 0.5, 2.4, 3.2])
    target[0, 3, 3, 20] = 1.0
    target[0, 3, 3, 7] = 1.0
    
    prediction[0, 3, 3, 21:25] = torch.tensor([0.4, 0.5, 2.4, 3.2])
    
    prediction[0, 3, 3, 7] = 1.0    #(1)
    #prediction[0, 3, 3, 7:9] = torch.tensor([0.9, 0.1])    #(2)
    #prediction[0, 3, 3, 7:9] = torch.tensor([0.2, 0.8])    #(3)
    
    target = target.reshape(BATCH_SIZE, S*S*(C+5))
    prediction = prediction.reshape(BATCH_SIZE, S*S*(C+B*5))

    class_loss = loss(target, prediction)[3]
    
    return class_loss

class_loss_test()