def create_run(self, experiment_id, user_id, start_time, tags):
"""
Creates a run with the specified attributes.
"""
experiment_id = FileStore.DEFAULT_EXPERIMENT_ID if experiment_id is None else experiment_id
experiment = self.get_experiment(experiment_id)
if experiment is None:
raise MlflowException(
"Could not create run under experiment with ID %s - no such experiment "
"exists." % experiment_id,
databricks_pb2.RESOURCE_DOES_NOT_EXIST)
if experiment.lifecycle_stage != LifecycleStage.ACTIVE:
raise MlflowException(
"Could not create run under non-active experiment with ID "
"%s." % experiment_id, databricks_pb2.INVALID_STATE)
run_uuid = uuid.uuid4().hex
artifact_uri = self._get_artifact_dir(experiment_id, run_uuid)
run_info = RunInfo(run_uuid=run_uuid,
run_id=run_uuid,
experiment_id=experiment_id,
artifact_uri=artifact_uri,
user_id=user_id,
status=RunStatus.to_string(RunStatus.RUNNING),
start_time=start_time,
end_time=None,
lifecycle_stage=LifecycleStage.ACTIVE)
# Persist run metadata and create directories for logging metrics, parameters, artifacts
run_dir = self._get_run_dir(run_info.experiment_id, run_info.run_id)
mkdir(run_dir)
run_info_dict = _make_persisted_run_info_dict(run_info)
write_yaml(run_dir, FileStore.META_DATA_FILE_NAME, run_info_dict)
mkdir(run_dir, FileStore.METRICS_FOLDER_NAME)
mkdir(run_dir, FileStore.PARAMS_FOLDER_NAME)
mkdir(run_dir, FileStore.ARTIFACTS_FOLDER_NAME)
for tag in tags:
self.set_tag(run_uuid, tag)
return self.get_run(run_id=run_uuid)
def create_run(self, experiment_id, user_id, run_name, source_type,
source_name, entry_point_name, start_time, source_version,
tags):
"""
Creates a run with the specified attributes.
"""
if self.get_experiment(experiment_id) is None:
raise Exception(
"Could not create run under experiment with ID %s - no such experiment "
"exists." % experiment_id)
run_uuid = uuid.uuid4().hex
artifact_uri = self._get_artifact_dir(experiment_id, run_uuid)
run_info = RunInfo(run_uuid=run_uuid,
experiment_id=experiment_id,
name="",
artifact_uri=artifact_uri,
source_type=source_type,
source_name=source_name,
entry_point_name=entry_point_name,
user_id=user_id,
status=RunStatus.RUNNING,
start_time=start_time,
end_time=None,
source_version=source_version)
# Persist run metadata and create directories for logging metrics, parameters, artifacts
run_dir = self._get_run_dir(run_info.experiment_id, run_info.run_uuid)
mkdir(run_dir)
write_yaml(run_dir, FileStore.META_DATA_FILE_NAME,
self._make_run_info_dict(run_info))
mkdir(run_dir, FileStore.METRICS_FOLDER_NAME)
mkdir(run_dir, FileStore.PARAMS_FOLDER_NAME)
mkdir(run_dir, FileStore.ARTIFACTS_FOLDER_NAME)
for tag in tags:
self.set_tag(run_uuid, tag)
if run_name:
self.set_tag(run_uuid, RunTag(key=MLFLOW_RUN_NAME, value=run_name))
return Run(run_info=run_info, run_data=None)
def _create_experiment_with_id(self, name, experiment_id):
self._check_root_dir()
location = mkdir(self.root_directory, str(experiment_id))
experiment = Experiment(experiment_id, name, location)
write_yaml(location, FileStore.META_DATA_FILE_NAME, dict(experiment))
return experiment_id
def log_artifacts(self, local_dir, artifact_path):
artifact_dir = build_path(self.artifact_uri, artifact_path) \
if artifact_path else self.artifact_uri
if not exists(artifact_dir):
mkdir(artifact_dir)
dir_util.copy_tree(src=local_dir, dst=artifact_dir)
def log_artifact(self, local_file, artifact_path):
artifact_dir = build_path(self.artifact_uri, artifact_path) \
if artifact_path else self.artifact_uri
if not exists(artifact_dir):
mkdir(artifact_dir)
shutil.copy(local_file, artifact_dir)