tf.contrib.checkpoint.UniqueNameTracker

Adds dependencies on trackable objects with name hints.

tf.contrib.checkpoint.UniqueNameTracker()

Useful for creating dependencies with locally unique names.

Example usage:

class SlotManager(tf.contrib.checkpoint.Checkpointable):

  def __init__(self):
    # Create a dependency named "slotdeps" on the container.
    self.slotdeps = tf.contrib.checkpoint.UniqueNameTracker()
    slotdeps = self.slotdeps
    slots = []
    slots.append(slotdeps.track(tf.Variable(3.), "x"))  # Named "x"
    slots.append(slotdeps.track(tf.Variable(4.), "y"))
    slots.append(slotdeps.track(tf.Variable(5.), "x"))  # Named "x_1"

Attributes
layers
losses	Aggregate losses from any Layer instances.
non_trainable_variables
non_trainable_weights
trainable
trainable_variables
trainable_weights
updates	Aggregate updates from any Layer instances.
variables
weights

Methods

track

View source

track(
    trackable, base_name
)

Add a dependency on trackable.

Args
trackable	An object to add a checkpoint dependency on.
base_name	A name hint, which is uniquified to determine the dependency name.

Returns
trackable, for chaining.

Raises
ValueError	If trackable is not a trackable object.

__eq__

View source

__eq__(
    other
)

Return self==value.