mlflow.entities

All entities returned by the MLflow REST API.

class mlflow.entities.Experiment(experiment_id, name, artifact_location)

Bases: mlflow.entities._mlflow_object._MLflowObject

Experiment object for python client. Backend stores will hydrate this object in APIs.

DEFAULT_EXPERIMENT_ID = 0

artifact_location

experiment_id

classmethod from_proto(proto)

name

to_proto()

class mlflow.entities.FileInfo(path, is_dir, file_size)

Bases: mlflow.entities._mlflow_object._MLflowObject

file_size

classmethod from_proto(proto)

is_dir

path

to_proto()

class mlflow.entities.Metric(key, value, timestamp)

Bases: mlflow.entities._mlflow_object._MLflowObject

Metric object for python client. Backend stores will hydrate this object in APIs.

classmethod from_proto(proto)

key

timestamp

to_proto()

value

class mlflow.entities.Param(key, value)

Bases: mlflow.entities._mlflow_object._MLflowObject

Param object for python client. Backend stores will hydrate this object in APIs.

classmethod from_proto(proto)

key

to_proto()

value

class mlflow.entities.Run(run_info, run_data)

Bases: mlflow.entities._mlflow_object._MLflowObject

Run object for python client. Backend stores will hydrate this object in APIs.

data

return – mlflow.entities.RunData

classmethod from_dictionary(the_dict)

classmethod from_proto(proto)

info

return – mlflow.entities.RunInfo

to_dictionary()

to_proto()

class mlflow.entities.RunData(metrics=None, params=None)

Bases: mlflow.entities._mlflow_object._MLflowObject

add_metric(metric)

add_param(param)

classmethod from_dictionary(the_dict)

classmethod from_proto(proto)

metrics

params

to_proto()

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, tags, artifact_uri=None)

Bases: mlflow.entities._mlflow_object._MLflowObject

artifact_uri

copy_with_overrides(status, end_time)

Returns a copy the current RunInfo with certain attributes modified

end_time

End time of the run, in number of milliseconds since the UNIX epoch.

entry_point_name

experiment_id

classmethod from_dictionary(the_dict)

classmethod from_proto(proto)

name

run_uuid

source_name

source_type

source_version

start_time

Start time of the run, in number of milliseconds since the UNIX epoch.

status

tags

to_proto()

user_id

class mlflow.entities.RunStatus

Bases: object

FAILED = 4

FINISHED = 3

RUNNING = 1

SCHEDULED = 2

static from_string(status_str)

static is_terminated(status)

static to_string(status)

class mlflow.entities.RunTag(key, value)

Bases: mlflow.entities._mlflow_object._MLflowObject

classmethod from_proto(proto)

key

to_proto()

value

class mlflow.entities.SourceType

Bases: object

JOB = 2

LOCAL = 4

NOTEBOOK = 1

PROJECT = 3

UNKNOWN = 5