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Module: tf.contrib.checkpoint

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Tools for working with object-based checkpoints.

Visualization and inspection:

Managing dependencies:

Trackable data structures:

Checkpoint management:

Saving and restoring Python state:

Classes

class CheckpointManager: Deletes old checkpoints.

class Checkpointable: Manages dependencies on other objects.

class CheckpointableBase: Base class for Trackable objects without automatic dependencies.

class CheckpointableObjectGraph

class List: An append-only sequence type which is trackable.

class Mapping: An append-only trackable mapping data structure with string keys.

class NoDependency: Allows attribute assignment to Trackable objects with no dependency.

class NumpyState: A trackable object whose NumPy array attributes are saved/restored.

class PythonStateWrapper: A mixin for putting Python state in an object-based checkpoint.

class UniqueNameTracker: Adds dependencies on trackable objects with name hints.

Functions

capture_dependencies(...): Capture variables created within this scope as Template dependencies.

dot_graph_from_checkpoint(...): Visualizes an object-based checkpoint (from tf.train.Checkpoint).

list_objects(...): Traverse the object graph and list all accessible objects.

object_metadata(...): Retrieves information about the objects in a checkpoint.

split_dependency(...): Creates multiple dependencies with a synchronized save/restore.