mlflow.entities
The mlflow.entities module defines entities returned by the MLflow
REST API.
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class
mlflow.entities.Experiment(experiment_id, name, artifact_location, lifecycle_stage)
Bases: mlflow.entities._mlflow_object._MLflowObject
Experiment object.
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ACTIVE_LIFECYCLE = 'active'
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DEFAULT_EXPERIMENT_ID = 0
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DELETED_LIFECYCLE = 'deleted'
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artifact_location
String corresponding to the root artifact URI for the experiment.
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experiment_id
Integer ID of the experiment.
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classmethod
from_proto(proto)
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lifecycle_stage
Lifecycle stage of the experiment. Can either be ‘active’ or ‘deleted’.
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name
String name of the experiment.
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to_proto()
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class
mlflow.entities.FileInfo(path, is_dir, file_size)
Bases: mlflow.entities._mlflow_object._MLflowObject
Metadata about a file or directory.
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file_size
Size of the file or directory. If the FileInfo is a directory, returns None.
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classmethod
from_proto(proto)
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is_dir
Whether the FileInfo corresponds to a directory.
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path
String path of the file or directory.
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to_proto()
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class
mlflow.entities.Metric(key, value, timestamp)
Bases: mlflow.entities._mlflow_object._MLflowObject
Metric object.
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classmethod
from_proto(proto)
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key
String key corresponding to the metric name.
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timestamp
Metric timestamp as an integer (milliseconds since the Unix epoch).
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to_proto()
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value
Float value of the metric.
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class
mlflow.entities.Param(key, value)
Bases: mlflow.entities._mlflow_object._MLflowObject
Parameter object.
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classmethod
from_proto(proto)
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key
String key corresponding to the parameter name.
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to_proto()
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value
String value of the parameter.
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class
mlflow.entities.Run(run_info, run_data)
Bases: mlflow.entities._mlflow_object._MLflowObject
Run object.
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data
The run data, including metrics, parameters, and tags.
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classmethod
from_dictionary(the_dict)
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classmethod
from_proto(proto)
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info
The run metadata, such as the run id, start time, and status.
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to_dictionary()
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to_proto()
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class
mlflow.entities.RunData(metrics=None, params=None, tags=None)
Bases: mlflow.entities._mlflow_object._MLflowObject
Run data (metrics and parameters).
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classmethod
from_dictionary(the_dict)
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classmethod
from_proto(proto)
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metrics
List of mlflow.entities.Metric for the current run.
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params
List of mlflow.entities.Param for the current run.
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tags
List of mlflow.entities.RunTag for the current run.
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to_proto()
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class
mlflow.entities.RunInfo(run_uuid, experiment_id, name, source_type, source_name, entry_point_name, user_id, status, start_time, end_time, source_version, lifecycle_stage, artifact_uri=None)
Bases: mlflow.entities._mlflow_object._MLflowObject
Metadata about a run.
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ACTIVE_LIFECYCLE = 'active'
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DELETED_LIFECYCLE = 'deleted'
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artifact_uri
String root artifact URI of the run.
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end_time
End time of the run, in number of milliseconds since the UNIX epoch.
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entry_point_name
String name of the entry point for the run.
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experiment_id
Integer ID of the experiment for the current run.
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classmethod
from_proto(proto)
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lifecycle_stage
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name
String name of the run.
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run_uuid
String containing run UUID.
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source_name
String name of the source of the run (GitHub URI of the project corresponding to the run,
etc).
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source_type
mlflow.entities.SourceType describing the source of the run.
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source_version
String Git commit hash of the code used for the run, if available.
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start_time
Start time of the run, in number of milliseconds since the UNIX epoch.
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status
One of the values in mlflow.entities.RunStatus
describing the status of the run.
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to_proto()
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user_id
String ID of the user who initiated this run.
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class
mlflow.entities.RunStatus
Bases: object
Enum for status of an mlflow.entities.Run.
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FAILED = 4
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FINISHED = 3
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RUNNING = 1
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SCHEDULED = 2
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static
from_string(status_str)
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static
is_terminated(status)
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static
to_string(status)
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class
mlflow.entities.RunTag(key, value)
Bases: mlflow.entities._mlflow_object._MLflowObject
Tag object associated with a run.
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classmethod
from_proto(proto)
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key
String name of the tag.
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to_proto()
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value
String value of the tag.
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class
mlflow.entities.SourceType
Bases: object
Enum for originating source of a mlflow.entities.Run.
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JOB = 2
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LOCAL = 4
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NOTEBOOK = 1
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PROJECT = 3
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UNKNOWN = 5
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class
mlflow.entities.ViewType
Bases: object
Enum to filter requested experiment types.
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ACTIVE_ONLY = 1
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ALL = 3
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DELETED_ONLY = 2
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classmethod
from_proto(proto_view_type)
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classmethod
from_string(view_str)
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classmethod
to_proto(view_type)
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classmethod
to_string(view_type)