# Ultralytics YOLO 🚀, AGPL-3.0 license

from ultralytics.utils import LOGGER, TESTS_RUNNING, colorstr

try:
    from torch.utils.tensorboard import SummaryWriter

    assert not TESTS_RUNNING  # do not log pytest

# TypeError for handling 'Descriptors cannot not be created directly.' protobuf errors in Windows
except (ImportError, AssertionError, TypeError):
    SummaryWriter = None

writer = None  # TensorBoard SummaryWriter instance


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)


callbacks = {
    'on_pretrain_routine_start': on_pretrain_routine_start,
    'on_fit_epoch_end': on_fit_epoch_end,
    'on_batch_end': on_batch_end}