From 9cc29a75ce8131db67b48e92dac3c16a255b92ed Mon Sep 17 00:00:00 2001 From: Alexandre Passos Date: Wed, 18 Jul 2018 10:16:16 -0700 Subject: Allows constructing resource variables from tf.Variable. Also adds arguments to control distributed aggregation to the tf.Variable constructor. Removes tfe.Variable from examples as it's now unnecessary. PiperOrigin-RevId: 205096552 --- third_party/examples/eager/spinn/spinn.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) (limited to 'third_party/examples/eager') diff --git a/third_party/examples/eager/spinn/spinn.py b/third_party/examples/eager/spinn/spinn.py index 67456a5bdf..c242ef3fdd 100644 --- a/third_party/examples/eager/spinn/spinn.py +++ b/third_party/examples/eager/spinn/spinn.py @@ -419,7 +419,7 @@ class SNLIClassifierTrainer(tfe.Checkpointable): # Create a custom learning rate Variable for the RMSProp optimizer, because # the learning rate needs to be manually decayed later (see # decay_learning_rate()). - self._learning_rate = tfe.Variable(lr, name="learning_rate") + self._learning_rate = tf.Variable(lr, name="learning_rate") self._optimizer = tf.train.RMSPropOptimizer(self._learning_rate, epsilon=1e-6) -- cgit v1.2.3