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Sklearn

zenml.integrations.sklearn special

Initialization of the sklearn integration.

SklearnIntegration (Integration)

Definition of sklearn integration for ZenML.

Source code in zenml/integrations/sklearn/__init__.py
class SklearnIntegration(Integration):
    """Definition of sklearn integration for ZenML."""

    NAME = SKLEARN
    REQUIREMENTS = ["scikit-learn"]

    @classmethod
    def activate(cls) -> None:
        """Activates the integration."""
        from zenml.integrations.sklearn import materializers  # noqa

activate() classmethod

Activates the integration.

Source code in zenml/integrations/sklearn/__init__.py
@classmethod
def activate(cls) -> None:
    """Activates the integration."""
    from zenml.integrations.sklearn import materializers  # noqa

materializers special

Initialization of the sklearn materializer.

sklearn_materializer

Implementation of the sklearn materializer.

SklearnMaterializer (BaseMaterializer)

Materializer to read data to and from sklearn.

Source code in zenml/integrations/sklearn/materializers/sklearn_materializer.py
class SklearnMaterializer(BaseMaterializer):
    """Materializer to read data to and from sklearn."""

    ASSOCIATED_TYPES = (
        BaseEstimator,
        ClassifierMixin,
        ClusterMixin,
        BiclusterMixin,
        OutlierMixin,
        RegressorMixin,
        MetaEstimatorMixin,
        MultiOutputMixin,
        DensityMixin,
        TransformerMixin,
    )
    ASSOCIATED_ARTIFACT_TYPE = ArtifactType.MODEL

    def load(
        self, data_type: Type[Any]
    ) -> Union[
        BaseEstimator,
        ClassifierMixin,
        ClusterMixin,
        BiclusterMixin,
        OutlierMixin,
        RegressorMixin,
        MetaEstimatorMixin,
        MultiOutputMixin,
        DensityMixin,
        TransformerMixin,
    ]:
        """Reads a base sklearn model from a pickle file.

        Args:
            data_type: The type of the model.

        Returns:
            The model.
        """
        super().load(data_type)
        filepath = os.path.join(self.uri, DEFAULT_FILENAME)
        with fileio.open(filepath, "rb") as fid:
            clf = pickle.load(fid)
        return clf

    def save(
        self,
        clf: Union[
            BaseEstimator,
            ClassifierMixin,
            ClusterMixin,
            BiclusterMixin,
            OutlierMixin,
            RegressorMixin,
            MetaEstimatorMixin,
            MultiOutputMixin,
            DensityMixin,
            TransformerMixin,
        ],
    ) -> None:
        """Creates a pickle for a sklearn model.

        Args:
            clf: A sklearn model.
        """
        super().save(clf)
        filepath = os.path.join(self.uri, DEFAULT_FILENAME)
        with fileio.open(filepath, "wb") as fid:
            pickle.dump(clf, fid)
load(self, data_type)

Reads a base sklearn model from a pickle file.

Parameters:

Name Type Description Default
data_type Type[Any]

The type of the model.

required

Returns:

Type Description
Union[sklearn.base.BaseEstimator, sklearn.base.ClassifierMixin, sklearn.base.ClusterMixin, sklearn.base.BiclusterMixin, sklearn.base.OutlierMixin, sklearn.base.RegressorMixin, sklearn.base.MetaEstimatorMixin, sklearn.base.MultiOutputMixin, sklearn.base.DensityMixin, sklearn.base.TransformerMixin]

The model.

Source code in zenml/integrations/sklearn/materializers/sklearn_materializer.py
def load(
    self, data_type: Type[Any]
) -> Union[
    BaseEstimator,
    ClassifierMixin,
    ClusterMixin,
    BiclusterMixin,
    OutlierMixin,
    RegressorMixin,
    MetaEstimatorMixin,
    MultiOutputMixin,
    DensityMixin,
    TransformerMixin,
]:
    """Reads a base sklearn model from a pickle file.

    Args:
        data_type: The type of the model.

    Returns:
        The model.
    """
    super().load(data_type)
    filepath = os.path.join(self.uri, DEFAULT_FILENAME)
    with fileio.open(filepath, "rb") as fid:
        clf = pickle.load(fid)
    return clf
save(self, clf)

Creates a pickle for a sklearn model.

Parameters:

Name Type Description Default
clf Union[sklearn.base.BaseEstimator, sklearn.base.ClassifierMixin, sklearn.base.ClusterMixin, sklearn.base.BiclusterMixin, sklearn.base.OutlierMixin, sklearn.base.RegressorMixin, sklearn.base.MetaEstimatorMixin, sklearn.base.MultiOutputMixin, sklearn.base.DensityMixin, sklearn.base.TransformerMixin]

A sklearn model.

required
Source code in zenml/integrations/sklearn/materializers/sklearn_materializer.py
def save(
    self,
    clf: Union[
        BaseEstimator,
        ClassifierMixin,
        ClusterMixin,
        BiclusterMixin,
        OutlierMixin,
        RegressorMixin,
        MetaEstimatorMixin,
        MultiOutputMixin,
        DensityMixin,
        TransformerMixin,
    ],
) -> None:
    """Creates a pickle for a sklearn model.

    Args:
        clf: A sklearn model.
    """
    super().save(clf)
    filepath = os.path.join(self.uri, DEFAULT_FILENAME)
    with fileio.open(filepath, "wb") as fid:
        pickle.dump(clf, fid)