Skip to content

Mlflow

Initialization for the ZenML MLflow integration.

The MLflow integrations currently enables you to use MLflow tracking as a convenient way to visualize your experiment runs within the MLflow UI.

MlflowIntegration

Bases: Integration

Definition of MLflow integration for ZenML.

Source code in src/zenml/integrations/mlflow/__init__.py 
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
class MlflowIntegration(Integration):
    """Definition of MLflow integration for ZenML."""

    NAME = MLFLOW

    REQUIREMENTS_IGNORED_ON_UNINSTALL = [
        "python-rapidjson",
        "pydantic",
        "numpy",
        "pandas",
    ]

    @classmethod
    def get_requirements(
        cls, target_os: Optional[str] = None, python_version: Optional[str] = None
    ) -> List[str]:
        """Method to get the requirements for the integration.

        Args:
            target_os: The target operating system to get the requirements for.
            python_version: The Python version to use for the requirements.

        Returns:
            A list of requirements.
        """
        from zenml.integrations.numpy import NumpyIntegration
        from zenml.integrations.pandas import PandasIntegration

        reqs = [
            "mlflow>=2.1.1,<3",
            # TODO: remove this requirement once rapidjson is fixed
            "python-rapidjson<1.15",
        ]

        reqs.extend(NumpyIntegration.get_requirements(target_os=target_os, python_version=python_version))
        reqs.extend(PandasIntegration.get_requirements(target_os=target_os, python_version=python_version))
        return reqs

    @classmethod
    def activate(cls) -> None:
        """Activate the MLflow integration."""
        from zenml.integrations.mlflow import services  # noqa

    @classmethod
    def flavors(cls) -> List[Type[Flavor]]:
        """Declare the stack component flavors for the MLflow integration.

        Returns:
            List of stack component flavors for this integration.
        """
        from zenml.integrations.mlflow.flavors import (
            MLFlowExperimentTrackerFlavor,
            MLFlowModelDeployerFlavor,
            MLFlowModelRegistryFlavor,
        )

        return [
            MLFlowModelDeployerFlavor,
            MLFlowExperimentTrackerFlavor,
            MLFlowModelRegistryFlavor,
        ]

activate() classmethod

Activate the MLflow integration.

Source code in src/zenml/integrations/mlflow/__init__.py 
74
75
76
77
@classmethod
def activate(cls) -> None:
    """Activate the MLflow integration."""
    from zenml.integrations.mlflow import services  # noqa

flavors() classmethod

Declare the stack component flavors for the MLflow integration.

Returns:

Type Description
List[Type[Flavor]]

List of stack component flavors for this integration.
Source code in src/zenml/integrations/mlflow/__init__.py 
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
@classmethod
def flavors(cls) -> List[Type[Flavor]]:
    """Declare the stack component flavors for the MLflow integration.

    Returns:
        List of stack component flavors for this integration.
    """
    from zenml.integrations.mlflow.flavors import (
        MLFlowExperimentTrackerFlavor,
        MLFlowModelDeployerFlavor,
        MLFlowModelRegistryFlavor,
    )

    return [
        MLFlowModelDeployerFlavor,
        MLFlowExperimentTrackerFlavor,
        MLFlowModelRegistryFlavor,
    ]

get_requirements(target_os=None, python_version=None) classmethod

Method to get the requirements for the integration.

Parameters:

Name Type Description Default
target_os Optional[str]

The target operating system to get the requirements for.

 None
python_version Optional[str]

The Python version to use for the requirements.

 None

Returns:

Type Description
List[str]

A list of requirements.
Source code in src/zenml/integrations/mlflow/__init__.py 
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
@classmethod
def get_requirements(
    cls, target_os: Optional[str] = None, python_version: Optional[str] = None
) -> List[str]:
    """Method to get the requirements for the integration.

    Args:
        target_os: The target operating system to get the requirements for.
        python_version: The Python version to use for the requirements.

    Returns:
        A list of requirements.
    """
    from zenml.integrations.numpy import NumpyIntegration
    from zenml.integrations.pandas import PandasIntegration

    reqs = [
        "mlflow>=2.1.1,<3",
        # TODO: remove this requirement once rapidjson is fixed
        "python-rapidjson<1.15",
    ]

    reqs.extend(NumpyIntegration.get_requirements(target_os=target_os, python_version=python_version))
    reqs.extend(PandasIntegration.get_requirements(target_os=target_os, python_version=python_version))
    return reqs