tf.contrib.checkpoint.NoDependency
Allows attribute assignment to Trackable
objects with no dependency.
tf.contrib.checkpoint.NoDependency( value )
Example usage:
obj = Trackable() obj.has_dependency = tf.Variable(0., name="dep") obj.no_dependency = NoDependency(tf.Variable(1., name="nodep")) assert obj.no_dependency.name == "nodep:0"
obj
in this example has a dependency on the variable "dep", and both attributes contain un-wrapped Variable
objects.
NoDependency
also works with tf.keras.Model
, but only for checkpoint dependencies: wrapping a Layer
in NoDependency
will assign the (unwrapped) Layer
to the attribute without a checkpoint dependency, but the Model
will still track the Layer
(so it will appear in Model.layers
, and its variables will appear in Model.variables
).
© 2020 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r1.15/api_docs/python/tf/contrib/checkpoint/NoDependency