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