wehub-resource-sync
44 lines
1.6 KiB
Python
44 lines
1.6 KiB
Python
from abc import ABCMeta, abstractmethod
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from mlflow.utils.annotations import developer_stable
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@developer_stable
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class DefaultExperimentProvider:
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"""
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Abstract base class for objects that provide the ID of an MLflow Experiment based on the
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current client context. For example, when the MLflow client is running in a Databricks Job,
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a provider is used to obtain the ID of the MLflow Experiment associated with the Job.
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Usually the experiment_id is set explicitly by the user, but if the experiment is not set,
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MLflow computes a default experiment id based on different contexts.
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When an experiment is created via the fluent ``mlflow.start_run`` method, MLflow iterates
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through the registered ``DefaultExperimentProvider``s until it finds one whose
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``in_context()`` method returns ``True``; MLflow then calls the provider's
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``get_experiment_id()`` method and uses the resulting experiment ID for Tracking operations.
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"""
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__metaclass__ = ABCMeta
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@abstractmethod
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def in_context(self):
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"""Determine if the MLflow client is running in a context where this provider can
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identify an associated MLflow Experiment ID.
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Returns:
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True if the MLflow client is running in a context where the provider
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can identify an associated MLflow Experiment ID. False otherwise.
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"""
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@abstractmethod
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def get_experiment_id(self):
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"""Provide the MLflow Experiment ID for the current MLflow client context.
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Assumes that ``in_context()`` is ``True``.
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Returns:
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The ID of the MLflow Experiment associated with the current context.
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"""
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