def get_save_model_task_and_dataset(self):
if not self._pending_save_model_task:
return None, None
task = self._pending_save_model_task
self._pending_save_model_task = None
return task, create_dataset_from_tasks([task], self.data_reader)
def get_validation_dataset(self, eval_task):
"""
If an evaluation task exists, this creates a `tf.data.Dataset`
object as well as its corresponding model version and task_id.
Otherwise, this returns `None`.
"""
if not eval_task:
return None
return (
create_dataset_from_tasks([eval_task], self.data_reader),
eval_task.model_version,
eval_task.task_id,
)
def get_evaluation_dataset(self):
"""
If there are _pending_eval_tasks, return a RecordIO dataset for
an evaluation task and its corresponding model version, task_id.
Return None if no _pending_eval_tasks.
"""
if not self._pending_eval_tasks:
return None
shards = []
task = None
with self._lock:
if self._pending_eval_tasks:
task = self._pending_eval_tasks.pop(0)
shards.append(task)
if shards and task:
return (
create_dataset_from_tasks(shards, self.data_reader),
task.model_version,
task.task_id,
)
else:
return None