Skip to content

Reference for ultralytics/utils/callbacks/wb.py

Note

Full source code for this file is available at https://github.com/ultralytics/ultralytics/blob/main/ultralytics/utils/callbacks/wb.py. Help us fix any issues you see by submitting a Pull Request 🛠️. Thank you 🙏!

ultralytics.utils.callbacks.wb._log_plots(plots, step)

Source code in ultralytics/utils/callbacks/wb.py 
19
20
21
22
23
24
def _log_plots(plots, step):
    for name, params in plots.items():
        timestamp = params['timestamp']
        if _processed_plots.get(name) != timestamp:
            wb.run.log({name.stem: wb.Image(str(name))}, step=step)
            _processed_plots[name] = timestamp



ultralytics.utils.callbacks.wb.on_pretrain_routine_start(trainer)

Initiate and start project if module is present.

Source code in ultralytics/utils/callbacks/wb.py 
27
28
29
def on_pretrain_routine_start(trainer):
    """Initiate and start project if module is present."""
    wb.run or wb.init(project=trainer.args.project or 'YOLOv8', name=trainer.args.name, config=vars(trainer.args))



ultralytics.utils.callbacks.wb.on_fit_epoch_end(trainer)

Logs training metrics and model information at the end of an epoch.

Source code in ultralytics/utils/callbacks/wb.py 
32
33
34
35
36
37
38
def on_fit_epoch_end(trainer):
    """Logs training metrics and model information at the end of an epoch."""
    wb.run.log(trainer.metrics, step=trainer.epoch + 1)
    _log_plots(trainer.plots, step=trainer.epoch + 1)
    _log_plots(trainer.validator.plots, step=trainer.epoch + 1)
    if trainer.epoch == 0:
        wb.run.log(model_info_for_loggers(trainer), step=trainer.epoch + 1)



ultralytics.utils.callbacks.wb.on_train_epoch_end(trainer)

Log metrics and save images at the end of each training epoch.

Source code in ultralytics/utils/callbacks/wb.py 
41
42
43
44
45
46
def on_train_epoch_end(trainer):
    """Log metrics and save images at the end of each training epoch."""
    wb.run.log(trainer.label_loss_items(trainer.tloss, prefix='train'), step=trainer.epoch + 1)
    wb.run.log(trainer.lr, step=trainer.epoch + 1)
    if trainer.epoch == 1:
        _log_plots(trainer.plots, step=trainer.epoch + 1)



ultralytics.utils.callbacks.wb.on_train_end(trainer)

Save the best model as an artifact at end of training.

Source code in ultralytics/utils/callbacks/wb.py 
49
50
51
52
53
54
55
56
def on_train_end(trainer):
    """Save the best model as an artifact at end of training."""
    _log_plots(trainer.validator.plots, step=trainer.epoch + 1)
    _log_plots(trainer.plots, step=trainer.epoch + 1)
    art = wb.Artifact(type='model', name=f'run_{wb.run.id}_model')
    if trainer.best.exists():
        art.add_file(trainer.best)
        wb.run.log_artifact(art, aliases=['best'])




Created 2023-07-16, Updated 2023-08-07
Authors: glenn-jocher (5), Laughing-q (1)