def _log_scalars(scalars, step=0):
    """Logs scalar values to TensorBoard."""
    if writer:
        for k, v in scalars.items():
            writer.add_scalar(k, v, step)

def on_pretrain_routine_start(trainer):
    """Initialize TensorBoard logging with SummaryWriter."""
    if SummaryWriter:
        try:
            global writer
            writer = SummaryWriter(str(trainer.save_dir))
            prefix = colorstr('TensorBoard: ')
            LOGGER.info(f"{prefix}Start with 'tensorboard --logdir {trainer.save_dir}', view at http://localhost:6006/")
        except Exception as e:
            LOGGER.warning(f'WARNING ⚠️ TensorBoard not initialized correctly, not logging this run. {e}')

def on_batch_end(trainer):
    """Logs scalar statistics at the end of a training batch."""
    _log_scalars(trainer.label_loss_items(trainer.tloss, prefix='train'), trainer.epoch + 1)

def on_fit_epoch_end(trainer):
    """Logs epoch metrics at end of training epoch."""
    _log_scalars(trainer.metrics, trainer.epoch + 1)