Gathers and serializes a trackable view.
tf.train.TrackableView(
root
)
Example usage:
class SimpleModule(tf.Module):
def __init__(self, name=None):
super().__init__(name=name)
self.a_var = tf.Variable(5.0)
self.b_var = tf.Variable(4.0)
self.vars = [tf.Variable(1.0), tf.Variable(2.0)]
root = SimpleModule(name="root")
root.leaf = SimpleModule(name="leaf")
trackable_view = tf.train.TrackableView(root)
Pass root to tf.train.TrackableView.children() to get the dictionary of all children directly linked to root by name.
>>> trackable_view_children = trackable_view.children(root)
>>> for item in trackable_view_children.items():
... print(item)
('a_var', <tf.Variable 'Variable:0' shape=() dtype=float32, numpy=5.0>)
('b_var', <tf.Variable 'Variable:0' shape=() dtype=float32, numpy=4.0>)
('vars', ListWrapper([<tf.Variable 'Variable:0' shape=() dtype=float32,
numpy=1.0>, <tf.Variable 'Variable:0' shape=() dtype=float32, numpy=2.0>]))
('leaf', ...)
Args | |
---|---|
root
|
A Trackable object whose variables (including the variables of
dependencies, recursively) should be saved. May be a weak reference.
|
Methods
children
@classmethod
children( obj, save_type=base.SaveType.CHECKPOINT, **kwargs )
Returns all child trackables attached to obj.
Args | |
---|---|
obj
|
A Trackable object.
|
save_type
|
A string, can be 'savedmodel' or 'checkpoint'. |
**kwargs
|
kwargs to use when retrieving the object's children. |
Returns | |
---|---|
Dictionary of all children attached to the object with name to trackable. |
descendants
descendants()
Returns a list of all nodes from self.root using a breadth first traversal.