diff options
| author |  A. Unique TensorFlower <gardener@tensorflow.org> | 2018-07-06 18:02:00 -0700 |
|---|---|---|
| committer | TensorFlower Gardener <gardener@tensorflow.org> | 2018-07-07 21:21:42 -0700 |
| commit | d7416d53ef09052a3dc10ec54ee5bd19e883cf86 (patch) | |
| tree | 7bf2b5cbee0ce8ad768da5116fdce07979b26982 /tensorflow/contrib/opt | |
| parent | 1caaea99e0156523e7d65f7e54cc2ac7117a8f90 (diff) | |
[TF:XLA] Add implementation of ResourceApplyPowerSign and ResourceApplyAddSign.
PiperOrigin-RevId: 203547001
Diffstat (limited to 'tensorflow/contrib/opt')
| -rw-r--r-- | tensorflow/contrib/opt/python/training/addsign_test.py | 6 | ||||
| -rw-r--r-- | tensorflow/contrib/opt/python/training/powersign_test.py | 2 |
2 files changed, 4 insertions, 4 deletions
diff --git a/tensorflow/contrib/opt/python/training/addsign_test.py b/tensorflow/contrib/opt/python/training/addsign_test.py index 08d45ed73f..628a735e72 100644 --- a/tensorflow/contrib/opt/python/training/addsign_test.py +++ b/tensorflow/contrib/opt/python/training/addsign_test.py @@ -214,7 +214,7 @@ class AddSignTest(test.TestCase): # Run 7 steps of AddSign # first 4 steps with positive gradient # last 3 steps with negative gradient (sign(gm) should be -1) - for t in range(1, 4): + for t in range(1, 8): if t < 5: update.run() else: @@ -222,7 +222,7 @@ class AddSignTest(test.TestCase): var0_np, m0 = addsign_update_numpy( var0_np, - grads0_np, + grads0_np if t < 5 else -grads0_np, m0, learning_rate, alpha=alpha, @@ -232,7 +232,7 @@ class AddSignTest(test.TestCase): ) var1_np, m1 = addsign_update_numpy( var1_np, - grads1_np, + grads1_np if t < 5 else -grads1_np, m1, learning_rate, alpha=alpha, diff --git a/tensorflow/contrib/opt/python/training/powersign_test.py b/tensorflow/contrib/opt/python/training/powersign_test.py index 5214082dd6..0bcf5d230a 100644 --- a/tensorflow/contrib/opt/python/training/powersign_test.py +++ b/tensorflow/contrib/opt/python/training/powersign_test.py @@ -216,7 +216,7 @@ class PowerSignTest(test.TestCase): self.assertAllClose([1.0, 2.0], var0.eval()) self.assertAllClose([3.0, 4.0], var1.eval()) - # Run 3 steps of powersign + # Run 7 steps of powersign # first 4 steps with positive gradient # last 3 steps with negative gradient (sign(gm) should be -1) for t in range(1, 8): |