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Experiment Trackers

Experiment trackers let you track your ML experiments.

They log the parameters used and allow you to compare between runs. In the ZenML world, every pipeline run is considered an experiment, and ZenML facilitates the storage of experiment results through ExperimentTracker stack components. This establishes a clear link between pipeline runs and experiments.

BaseExperimentTracker

Bases: StackComponent, ABC

Base class for all ZenML experiment trackers.

Source code in src/zenml/experiment_trackers/base_experiment_tracker.py 
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class BaseExperimentTracker(StackComponent, ABC):
    """Base class for all ZenML experiment trackers."""

    @property
    def config(self) -> BaseExperimentTrackerConfig:
        """Returns the config of the experiment tracker.

        Returns:
            The config of the experiment tracker.
        """
        return cast(BaseExperimentTrackerConfig, self._config)

config property

Returns the config of the experiment tracker.

Returns:

Type Description
BaseExperimentTrackerConfig

The config of the experiment tracker.