tf.contrib.checkpoint.Checkpointable
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Manages dependencies on other objects.
Inherits From: CheckpointableBase
View aliases
Main aliases
`tf.contrib.eager.Checkpointable`
Trackable objects may have dependencies: other Trackable objects
which should be saved if the object declaring the dependency is saved. A
correctly saveable program has a dependency graph such that if changing a
global variable affects an object (e.g. changes the behavior of any of its
methods) then there is a chain of dependencies from the influenced object to
the variable.
Dependency edges have names, and are created implicitly when a
Trackable object is assigned to an attribute of another
Trackable object. For example:
obj = Trackable()
obj.v = ResourceVariable(0.)
The Trackable object obj now has a dependency named "v" on a
variable.
Trackable objects may specify Tensors to be saved and restored
directly (e.g. a Variable indicating how to save itself) rather than through
dependencies on other objects. See
Trackable._gather_saveables_for_checkpoint for details.
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Last updated 2020-10-01 UTC.
[null,null,["Last updated 2020-10-01 UTC."],[],[],null,["# tf.contrib.checkpoint.Checkpointable\n\n\u003cbr /\u003e\n\n|-----------------------------------------------------------------------------------------------------------------------------------------|\n| [View source on GitHub](https://github.com/tensorflow/tensorflow/blob/v1.15.0/tensorflow/python/training/tracking/tracking.py#L48-L112) |\n\nManages dependencies on other objects.\n\nInherits From: [`CheckpointableBase`](../../../tf/contrib/checkpoint/CheckpointableBase)\n\n#### View aliases\n\n\n**Main aliases**\n\n\\`tf.contrib.eager.Checkpointable\\`\n\n\u003cbr /\u003e\n\n`Trackable` objects may have dependencies: other `Trackable` objects\nwhich should be saved if the object declaring the dependency is saved. A\ncorrectly saveable program has a dependency graph such that if changing a\nglobal variable affects an object (e.g. changes the behavior of any of its\nmethods) then there is a chain of dependencies from the influenced object to\nthe variable.\n\nDependency edges have names, and are created implicitly when a\n`Trackable` object is assigned to an attribute of another\n`Trackable` object. For example: \n\n obj = Trackable()\n obj.v = ResourceVariable(0.)\n\nThe `Trackable` object `obj` now has a dependency named \"v\" on a\nvariable.\n\n`Trackable` objects may specify `Tensor`s to be saved and restored\ndirectly (e.g. a `Variable` indicating how to save itself) rather than through\ndependencies on other objects. See\n`Trackable._gather_saveables_for_checkpoint` for details."]]
View source on GitHub