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tf.distribute.experimental.coordinator.RemoteValue

An asynchronously available value of a scheduled function.

This class is used as the return value of tf.distribute.experimental.coordinator.ClusterCoordinator.schedule where the underlying value becomes available at a later time once the function has been executed.

Using tf.distribute.experimental.coordinator.RemoteValue as an input to a subsequent function scheduled with tf.distribute.experimental.coordinator.ClusterCoordinator.schedule is currently not supported.

Example:

strategy = tf.distribute.experimental.ParameterServerStrategy(
    cluster_resolver=...)
coordinator = (
    tf.distribute.experimental.coordinator.ClusterCoordinator(strategy))

with strategy.scope():
  v1 = tf.Variable(initial_value=0.0)
  v2 = tf.Variable(initial_value=1.0)

@tf.function
def worker_fn():
  v1.assign_add(0.1)
  v2.assign_sub(0.2)
  return v1.read_value() / v2.read_value()

result = coordinator.schedule(worker_fn)
# Note that `fetch()` gives the actual result instead of a `tf.Tensor`.
assert result.fetch() == 0.125

for _ in range(10):
  # `worker_fn` will be run on arbitrary workers that are available. The
  # `result` value will be available later.
  result = coordinator.schedule(worker_fn)

Methods

fetch

View source

Wait for the result of RemoteValue to be ready and return the result.

This makes the value concrete by copying the remote value to local.

Returns
The actual output of the tf.function associated with this RemoteValue, previously by a tf.distribute.experimental.coordinator.ClusterCoordinator.schedule call. This can be a single value, or a structure of values, depending on the output of the tf.function.

Raises
tf.errors.CancelledError If the function that produces this RemoteValue is aborted or cancelled due to failure.