diff options
| -rw-r--r-- | tensorflow/cc/BUILD | 1 | ||||
| -rw-r--r-- | tensorflow/python/kernel_tests/relu_op_test.py | 4 | ||||
| -rw-r--r-- | tensorflow/python/ops/nn_ops.py | 2 |
3 files changed, 4 insertions, 3 deletions
diff --git a/tensorflow/cc/BUILD b/tensorflow/cc/BUILD index f56521dac0..e99d15f85d 100644 --- a/tensorflow/cc/BUILD +++ b/tensorflow/cc/BUILD @@ -410,6 +410,7 @@ tf_cc_test( srcs = ["gradients/nn_grad_test.cc"], deps = [ ":cc_ops", + ":cc_ops_internal", ":grad_op_registry", ":grad_testutil", ":gradient_checker", diff --git a/tensorflow/python/kernel_tests/relu_op_test.py b/tensorflow/python/kernel_tests/relu_op_test.py index 86d9c90e83..d97a1613b9 100644 --- a/tensorflow/python/kernel_tests/relu_op_test.py +++ b/tensorflow/python/kernel_tests/relu_op_test.py @@ -351,7 +351,7 @@ class LeakyReluTest(test.TestCase): self.assertLess(err, 1e-10) def testGradGradFloat32(self): - with compat.forward_compatibility_horizon(2018, 10, 2): + with compat.forward_compatibility_horizon(2018, 11, 2): with self.test_session(): x = constant_op.constant( [-0.9, -0.7, -0.5, -0.3, -0.1, 0.1, 0.3, 0.5, 0.7, 0.9], @@ -369,7 +369,7 @@ class LeakyReluTest(test.TestCase): self.assertLess(err, 1e-4) def testGradGradFloat64(self): - with compat.forward_compatibility_horizon(2018, 10, 2): + with compat.forward_compatibility_horizon(2018, 11, 2): with self.test_session(): x = constant_op.constant( [-0.9, -0.7, -0.5, -0.3, -0.1, 0.1, 0.3, 0.5, 0.7, 0.9], diff --git a/tensorflow/python/ops/nn_ops.py b/tensorflow/python/ops/nn_ops.py index d646245ce3..2861f40586 100644 --- a/tensorflow/python/ops/nn_ops.py +++ b/tensorflow/python/ops/nn_ops.py @@ -1601,7 +1601,7 @@ def leaky_relu(features, alpha=0.2, name=None): features = ops.convert_to_tensor(features, name="features") if features.dtype.is_integer: features = math_ops.to_float(features) - if compat.forward_compatible(2018, 10, 1): + if compat.forward_compatible(2018, 11, 1): return gen_nn_ops.leaky_relu(features, alpha=alpha, name=name) alpha = ops.convert_to_tensor(alpha, dtype=features.dtype, name="alpha") return math_ops.maximum(alpha * features, features, name=name) |