def __init__(self, train_id, data_manager, tag=None):
Validation.check_param_empty(train_id=train_id)
super(GraphProcessor, self).__init__(data_manager)
train_job = self._data_manager.get_train_job_by_plugin(
train_id, PluginNameEnum.GRAPH.value)
if train_job is None:
raise exceptions.TrainJobNotExistError()
if not train_job['tags'] or (tag is not None
and tag not in train_job['tags']):
raise exceptions.GraphNotExistError()
if tag is None:
tag = train_job['tags'][0]
tensors = self._data_manager.list_tensors(train_id, tag=tag)
self._graph = tensors[0].value
def get_single_train_task(self, plugin_name, train_id):
"""
get single train task.
Args:
plugin_name (str): Plugin name, refer `PluginNameEnum`.
train_id (str): Specify a training job to query.
Returns:
{'train_jobs': list[TrainJob]}, refer to restful api.
"""
Validation.check_param_empty(plugin_name=plugin_name, train_id=train_id)
Validation.check_plugin_name(plugin_name=plugin_name)
train_job = self._data_manager.get_train_job_by_plugin(train_id=train_id, plugin_name=plugin_name)
if train_job is None:
raise exceptions.TrainJobNotExistError()
return dict(train_jobs=[train_job])