LostTech.TensorFlow : API Documentation

Type CheckpointSaverListener

Namespace tensorflow.train

Parent PythonObjectContainer

Interfaces ICheckpointSaverListener

Interface for listeners that take action before or after checkpoint save.

`CheckpointSaverListener` triggers only in steps when `CheckpointSaverHook` is triggered, and provides callbacks at the following points: - before using the session - before each call to `Saver.save()` - after each call to `Saver.save()` - at the end of session

To use a listener, implement a class and pass the listener to a `CheckpointSaverHook`, as in this example: A `CheckpointSaverListener` may simply take some action after every checkpoint save. It is also possible for the listener to use its own schedule to act less frequently, e.g. based on global_step_value. In this case, implementors should implement the `end()` method to handle actions related to the last checkpoint save. But the listener should not act twice if `after_save()` already handled this last checkpoint save.

A `CheckpointSaverListener` can request training to be stopped, by returning True in `after_save`. Please note that, in replicated distributed training setting, only `chief` should use this behavior. Otherwise each worker will do their own evaluation, which may be wasteful of resources.
Show Example
class ExampleCheckpointSaverListener(CheckpointSaverListener):
              def begin(self):
                # You can add ops to the graph here.
                print('Starting the session.')
                self.your_tensor =... 

def before_save(self, session, global_step_value): print('About to write a checkpoint')

def after_save(self, session, global_step_value): print('Done writing checkpoint.') if decided_to_stop_training(): return True

def end(self, session, global_step_value): print('Done with the session.')

... listener = ExampleCheckpointSaverListener() saver_hook = tf.estimator.CheckpointSaverHook( checkpoint_dir, listeners=[listener]) with tf.compat.v1.train.MonitoredTrainingSession(chief_only_hooks=[saver_hook]): ...


Public properties

object PythonObject get;