rdf2vecgpu.logger package

Submodules

rdf2vecgpu.logger.mlflow_logger module

class MlflowTracker(experiment, tracking_uri, registry_uri=None)[source]

Bases: BaseTracker

Parameters:

  • experiment (str)

  • tracking_uri (str)

  • registry_uri (str | None)

close()[source]
enabled()[source]
Return type:

bool

log_artifact(path, artifact_path=None)[source]
log_data(sample_data, data_name, artifact_path, tags)[source]
Parameters:

tags (Dict[str, str] | None)

log_figure(figure, artifact_file, artifact_path)[source]
log_metrics(metrics, step=None)[source]
Parameters:

  • metrics (Dict[str, float])

  • step (int | None)

log_model_pytorch(model, artifact_path)[source]
Parameters:

artifact_path (str)

log_params(params)[source]
Parameters:

params (Dict[str, Any])

log_pytorch()[source]
set_tags(tags)[source]
Parameters:

tags (Dict[str, str])

stage(name)[source]
Parameters:

name (str)

start_pipeline(run_name=None, tags=None)[source]
Parameters:

  • run_name (str | None)

  • tags (Dict[str, str] | None)

Return type:

MlflowTracker

rdf2vecgpu.logger.wandb_logger module

class WandbTracker(project, entity=None, run_name=None, config=None)[source]

Bases: BaseTracker

Parameters:

  • project (str)

  • entity (str | None)

  • run_name (str | None)

  • config (dict | None)

close()[source]
enabled()[source]
Return type:

bool

log_artifact(path, artifact_path=None)[source]
log_data(sample_data, data_name, artifact_path, tags=None)[source]
log_dict(d, artifact_file, artifact_path=None)[source]
log_figure(figure, artifact_file, artifact_path)
Parameters:

  • figure (Any)

  • artifact_file (str)

  • artifact_path (str)

log_metrics(metrics, step=None)[source]
log_model_pytorch(model, artifact_path)[source]
Parameters:

artifact_path (str)

log_params(params)[source]
log_pytorch()[source]
log_text(text, artifact_file, artifact_path=None)[source]
set_tags(tags)[source]
stage(name)[source]
start_pipeline(run_name, tags=None, resume_run_id=None)[source]

Module contents

build_tracker(spec, kwargs=None)[source]

spec: “none”, “mlflow”, “wandb” kwargs: {“mlflow”: {…}, “wandb”: {…}}

Parameters:

  • spec (str | None)

  • kwargs (dict | None)

Return type:

BaseTracker