def METHOD_NAME(output_predictions, labels, output_tensor):
    logits = output_tensor
    loss_dict = {}
    # Add output predictions.
    if output_predictions:
        assert False
        loss_dict['softmaxes'] = torch.nn.Softmax(dim=-1)(
            logits.float()).data.cpu().numpy().tolist()
        loss_dict['labels'] = labels.data.cpu().numpy().tolist()
        loss_dict['ids'] = batch['uid'].cpu().numpy().tolist()
    # Compute the correct answers.
    predicted = torch.argmax(logits, dim=-1)
    corrects = (predicted == labels)
    # Add to the counters.
    loss_dict['total'] = labels.size(0)
    loss_dict['correct'] = corrects.sum().item()
    return 0, loss_dict