Scalar plots are empty, log_scalar values only appear on experiment overview about deepkit-ml HOT 3 OPEN

import deepkit

def train(args, model, device, train_loader, optimizer, epoch):
    # ...
    for batch_idx, (data, target) in enumerate(train_loader):
        data, target = data.to(device), target.to(device)
        optimizer.zero_grad()
        output = model(data)
        loss = F.nll_loss(output, target)
        loss.backward()
        optimizer.step()

        _, predicted = output.max(1)
        total += target.size(0)
        correct += predicted.eq(target).sum().item()

        args.experiment.log_metric('loss/train', loss.item(), x=epoch + (batch_idx / len(train_loader)))

def main():
    # ...
    args = parser.parse_args()
    experiment = deepkit.experiment()
    args.experiment = experiment
    # ...
    for epoch in range(1, args.epochs + 1):
        args.experiment.epoch(epoch, args.epochs)
        train(args, model, device, train_loader, optimizer, epoch)

if __name__ == '__main__':
    main()