2d34259281a6251cbdc67103ce8a1310010b8ceb,orbit/controller.py,Controller,__init__,#Controller#,39
Before Change
checkpoint_interval = self.checkpoint_manager.checkpoint_interval
restored_path = self.restore_checkpoint()
if restored_path:
logging.info("Restored from checkpoint: %s", restored_path)
def train(self, steps: int, checkpoint_at_completion: bool = True):
Runs training.
After Change
if self.checkpoint_manager is not None:
restored_path = self.restore_checkpoint()
if restored_path:
_log(f"restored from checkpoint: {restored_path}")
def train(self, steps: int, checkpoint_at_completion: bool = True):
Runs training until the specified global step count has been reached.
In pattern: SUPERPATTERN
Frequency: 3
Non-data size: 3
Instances Project Name: tensorflow/models
Commit Name: 2d34259281a6251cbdc67103ce8a1310010b8ceb
Time: 2020-10-05
Author: dhr@google.com
File Name: orbit/controller.py
Class Name: Controller
Method Name: __init__
Project Name: tensorflow/models
Commit Name: 2d34259281a6251cbdc67103ce8a1310010b8ceb
Time: 2020-10-05
Author: dhr@google.com
File Name: orbit/controller.py
Class Name: Controller
Method Name: _maybe_save_checkpoint
Project Name: tensorflow/models
Commit Name: 2d34259281a6251cbdc67103ce8a1310010b8ceb
Time: 2020-10-05
Author: dhr@google.com
File Name: orbit/controller.py
Class Name: Controller
Method Name: train