from mlflow.entities._mlflow_object import _MlflowObject
from mlflow.entities.lifecycle_stage import LifecycleStage
from mlflow.entities.run_status import RunStatus
from mlflow.exceptions import MlflowException
from mlflow.protos.databricks_pb2 import INVALID_PARAMETER_VALUE
from mlflow.protos.service_pb2 import RunInfo as ProtoRunInfo
def check_run_is_active(run_info):
if run_info.lifecycle_stage != LifecycleStage.ACTIVE:
raise MlflowException(
f"The run {run_info.run_id} must be in 'active' lifecycle_stage.",
error_code=INVALID_PARAMETER_VALUE,
)
class searchable_attribute(property):
# Wrapper class over property to designate some of the properties as searchable
# run attributes
pass
class orderable_attribute(property):
# Wrapper class over property to designate some of the properties as orderable
# run attributes
pass
[docs]class RunInfo(_MlflowObject):
"""
Metadata about a run.
"""
def __init__(
self,
run_id,
experiment_id,
user_id,
status,
start_time,
end_time,
lifecycle_stage,
artifact_uri=None,
run_name=None,
):
if experiment_id is None:
raise Exception("experiment_id cannot be None")
if user_id is None:
raise Exception("user_id cannot be None")
if status is None:
raise Exception("status cannot be None")
if start_time is None:
raise Exception("start_time cannot be None")
self._run_id = run_id
self._experiment_id = experiment_id
self._user_id = user_id
self._status = status
self._start_time = start_time
self._end_time = end_time
self._lifecycle_stage = lifecycle_stage
self._artifact_uri = artifact_uri
self._run_name = run_name
def __eq__(self, other):
if type(other) is type(self):
# TODO deep equality here?
return self.__dict__ == other.__dict__
return False
def _copy_with_overrides(self, status=None, end_time=None, lifecycle_stage=None, run_name=None):
"""A copy of the RunInfo with certain attributes modified."""
proto = self.to_proto()
if status:
proto.status = status
if end_time:
proto.end_time = end_time
if lifecycle_stage:
proto.lifecycle_stage = lifecycle_stage
if run_name:
proto.run_name = run_name
return RunInfo.from_proto(proto)
[docs] @searchable_attribute
def run_id(self):
"""String containing run id."""
return self._run_id
@property
def experiment_id(self):
"""String ID of the experiment for the current run."""
return self._experiment_id
[docs] @searchable_attribute
def run_name(self):
"""String containing run name."""
return self._run_name
def _set_run_name(self, new_name):
self._run_name = new_name
[docs] @searchable_attribute
def user_id(self):
"""String ID of the user who initiated this run."""
return self._user_id
[docs] @searchable_attribute
def status(self):
"""
One of the values in :py:class:`mlflow.entities.RunStatus`
describing the status of the run.
"""
return self._status
[docs] @searchable_attribute
def start_time(self):
"""Start time of the run, in number of milliseconds since the UNIX epoch."""
return self._start_time
[docs] @searchable_attribute
def end_time(self):
"""End time of the run, in number of milliseconds since the UNIX epoch."""
return self._end_time
[docs] @searchable_attribute
def artifact_uri(self):
"""String root artifact URI of the run."""
return self._artifact_uri
@property
def lifecycle_stage(self):
"""
One of the values in :py:class:`mlflow.entities.lifecycle_stage.LifecycleStage`
describing the lifecycle stage of the run.
"""
return self._lifecycle_stage
[docs] def to_proto(self):
proto = ProtoRunInfo()
proto.run_uuid = self.run_id
proto.run_id = self.run_id
if self.run_name is not None:
proto.run_name = self.run_name
proto.experiment_id = self.experiment_id
proto.user_id = self.user_id
proto.status = RunStatus.from_string(self.status)
proto.start_time = self.start_time
if self.end_time:
proto.end_time = self.end_time
if self.artifact_uri:
proto.artifact_uri = self.artifact_uri
proto.lifecycle_stage = self.lifecycle_stage
return proto
[docs] @classmethod
def from_proto(cls, proto):
end_time = proto.end_time
# The proto2 default scalar value of zero indicates that the run's end time is absent.
# An absent end time is represented with a NoneType in the `RunInfo` class
if end_time == 0:
end_time = None
return cls(
run_id=proto.run_id,
run_name=proto.run_name,
experiment_id=proto.experiment_id,
user_id=proto.user_id,
status=RunStatus.to_string(proto.status),
start_time=proto.start_time,
end_time=end_time,
lifecycle_stage=proto.lifecycle_stage,
artifact_uri=proto.artifact_uri,
)
[docs] @classmethod
def get_searchable_attributes(cls):
return sorted(
[p for p in cls.__dict__ if isinstance(getattr(cls, p), searchable_attribute)]
)
[docs] @classmethod
def get_orderable_attributes(cls):
# Note that all searchable attributes are also orderable.
return sorted(
[
p
for p in cls.__dict__
if isinstance(getattr(cls, p), (searchable_attribute, orderable_attribute))
]
)
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