from mlflow.entities._mlflow_object import _MLflowObject
from mlflow.entities.run_data import RunData
from mlflow.entities.run_info import RunInfo
from mlflow.exceptions import MlflowException
from mlflow.protos.service_pb2 import Run as ProtoRun
[docs]class Run(_MLflowObject):
"""
Run object.
"""
def __init__(self, run_info, run_data):
if run_info is None:
raise MlflowException("run_info cannot be None")
self._info = run_info
self._data = run_data
@property
def info(self):
"""
The run metadata, such as the run id, start time, and status.
:rtype: :py:class:`mlflow.entities.RunInfo`
"""
return self._info
@property
def data(self):
"""
The run data, including metrics, parameters, and tags.
:rtype: :py:class:`mlflow.entities.RunData`
"""
return self._data
[docs] def to_proto(self):
run = ProtoRun()
run.info.MergeFrom(self.info.to_proto())
if self.data:
run.data.MergeFrom(self.data.to_proto())
return run
[docs] @classmethod
def from_proto(cls, proto):
return cls(RunInfo.from_proto(proto.info), RunData.from_proto(proto.data))
[docs] def to_dictionary(self):
run_dict = {
"info": dict(self.info),
}
if self.data:
run_dict["data"] = self.data.to_dictionary()
return run_dict