WandBLogger

class braintools.trainer.WandBLogger(project, name=None, entity=None, config=None, tags=None, notes=None, save_dir=None, offline=False, log_model=False, **kwargs)

Weights & Biases logging backend.

Parameters:

• project (str) – W&B project name.

• name (str | None) – Run name. If None, W&B will auto-generate.

• entity (str | None) – W&B entity (username or team name).

• config (Dict[str, Any] | None) – Hyperparameters to log.

• tags (List[str] | None) – Tags for the run.

• notes (str | None) – Notes for the run.

• save_dir (str | None) – Directory for local W&B files.

• offline (bool) – Whether to run in offline mode.

• log_model (bool) – Whether to log model checkpoints.

Examples

>>> logger = WandBLogger(project='my_project', name='run_1')
>>> trainer = Trainer(logger=logger)

finalize(status='success')

Finalize logging (called at end of training).

Parameters:

status (str) – Final status (‘success’, ‘failed’, ‘interrupted’).

log_artifact(local_path, artifact_path=None)

Log an artifact (file).

Parameters:

• local_path (str) – Path to the local file.

• artifact_path (str | None) – Path in artifact storage.

property log_dir: str | None

Directory for this specific run’s logs.

log_hyperparams(params)

Log hyperparameters.

Parameters:

params (Dict[str, Any]) – Dictionary of hyperparameter names to values.

log_image(key, images, step=None)

Log images.

Parameters:

• key (str) – Image key/tag.

• images (Any) – Images to log (numpy array or list).

• step (int | None) – Global step number.

log_metrics(metrics, step=None)

Log metrics.

Parameters:

• metrics (Dict[str, float]) – Dictionary of metric names to values.

• step (int | None) – Global step number.

log_text(key, text, step=None)

Log text.

Parameters:

• key (str) – Text key/tag.

• text (str) – Text to log.

• step (int | None) – Global step number.

property name: str

Experiment name.

save()

Save/flush any buffered data.

property version: str | None

Experiment version/run ID.