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Experiment Trackers

zenml.experiment_trackers special

Experiment Trackers

Experiment trackers let you track your ML experiments by logging the parameters and allowing 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.

base_experiment_tracker

BaseExperimentTracker (StackComponent, ABC) pydantic-model

Base class for all ZenML experiment trackers.

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

    # Class configuration
    TYPE: ClassVar[StackComponentType] = StackComponentType.EXPERIMENT_TRACKER
    FLAVOR: ClassVar[str]