diff options
| author |  A. Unique TensorFlower <gardener@tensorflow.org> | 2018-04-26 12:42:54 -0700 |
|---|---|---|
| committer | TensorFlower Gardener <gardener@tensorflow.org> | 2018-04-26 12:45:22 -0700 |
| commit | f63750645826df65b05cad505546a86f0e347674 (patch) | |
| tree | 8467d73780d74b0f7ef4c87f8866d3bf0a233254 /tensorflow/contrib/compiler | |
| parent | 667077cbd2cc86c4a656233a2d5f579aa4caf1f1 (diff) | |
For tf.gradients(), do not backpropagate through integer tensors.
All integer tensors are now considered constant with respect to all `xs`.
This fixes a bug in gradients through tf.while_loop.
PiperOrigin-RevId: 194438529
Diffstat (limited to 'tensorflow/contrib/compiler')
| -rw-r--r-- | tensorflow/contrib/compiler/jit_test.py | 10 |
1 files changed, 5 insertions, 5 deletions
diff --git a/tensorflow/contrib/compiler/jit_test.py b/tensorflow/contrib/compiler/jit_test.py index 29a593f6bc..b2f678fb29 100644 --- a/tensorflow/contrib/compiler/jit_test.py +++ b/tensorflow/contrib/compiler/jit_test.py @@ -175,7 +175,7 @@ class CompilationEnabledInGradientTest(test.TestCase): def testCompilationInGradient(self): with self.test_session(): - x = constant_op.constant([[3]]) + x = constant_op.constant([[3.]]) y_nc = math_ops.matmul(x, x, name="not_compiled") with jit.experimental_jit_scope(): y_c = math_ops.matmul(y_nc, y_nc, name="compiled") @@ -200,11 +200,11 @@ class CompilationEnabledInGradientTest(test.TestCase): with self.test_session(graph=ops.Graph()): with jit.experimental_jit_scope(): # XlaScope 0 - a1 = constant_op.constant([[1]]) + a1 = constant_op.constant([[1.]]) a1t = math_ops.matmul(a1, a1) with jit.experimental_jit_scope(): # XlaScope 1 - a2 = constant_op.constant([[1]]) + a2 = constant_op.constant([[1.]]) a2t = math_ops.matmul(a2, a2) self.assertEqual(b"jit_scope_0", a1.op.get_attr("_XlaScope")) @@ -222,11 +222,11 @@ class CompilationEnabledInGradientTest(test.TestCase): with self.test_session(graph=ops.Graph()): with jit.experimental_jit_scope(True, separate_compiled_gradients=True): # XlaScope 0 - a1 = constant_op.constant([[1]]) + a1 = constant_op.constant([[1.]]) a1t = math_ops.matmul(a1, a1) with jit.experimental_jit_scope(True, separate_compiled_gradients=True): # XlaScope 1 - a2 = constant_op.constant([[1]]) + a2 = constant_op.constant([[1.]]) a2t = math_ops.matmul(a2, a2) self.assertEqual(b"jit_scope_0", a1.op.get_attr("_XlaScope")) |