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| author |  Tom Hennigan <tomhennigan@google.com> | 2018-06-22 01:46:03 -0700 |
|---|---|---|
| committer |  TensorFlower Gardener <gardener@tensorflow.org> | 2018-06-22 01:49:29 -0700 |
| commit | 945d1a77aebb2071b571598cb1d02fac5b1370c1 (patch) | |
| tree | efce5ed23c87ad2460916ad1b08211ee6359a98c /tensorflow/contrib/cudnn_rnn | |
| parent | 9682324b40ed36963cced138e21de29518d6843c (diff) | |
Replace unnecessary `()` in `run_in_graph_and_eager_modes()`.
PiperOrigin-RevId: 201652888
Diffstat (limited to 'tensorflow/contrib/cudnn_rnn')
| -rw-r--r-- | tensorflow/contrib/cudnn_rnn/python/kernel_tests/cudnn_rnn_test.py | 6 |
1 files changed, 3 insertions, 3 deletions
diff --git a/tensorflow/contrib/cudnn_rnn/python/kernel_tests/cudnn_rnn_test.py b/tensorflow/contrib/cudnn_rnn/python/kernel_tests/cudnn_rnn_test.py index 8285ea0492..252ea1560d 100644 --- a/tensorflow/contrib/cudnn_rnn/python/kernel_tests/cudnn_rnn_test.py +++ b/tensorflow/contrib/cudnn_rnn/python/kernel_tests/cudnn_rnn_test.py @@ -768,7 +768,7 @@ class CudnnRNNTestSaveRestoreCheckpointable(test_util.TensorFlowTestCase): @unittest.skipUnless(test.is_built_with_cuda(), "Test only applicable when running on GPUs") - @test_util.run_in_graph_and_eager_modes() + @test_util.run_in_graph_and_eager_modes def testLSTMCheckpointableSingleLayer(self): num_units = 2 direction = CUDNN_RNN_UNIDIRECTION @@ -781,7 +781,7 @@ class CudnnRNNTestSaveRestoreCheckpointable(test_util.TensorFlowTestCase): @unittest.skipUnless(test.is_built_with_cuda(), "Test only applicable when running on GPUs") - @test_util.run_in_graph_and_eager_modes() + @test_util.run_in_graph_and_eager_modes def testGRUCheckpointableSingleLayer(self): num_units = 2 direction = CUDNN_RNN_UNIDIRECTION @@ -826,7 +826,7 @@ class CudnnRNNTestSaveRestoreCheckpointable(test_util.TensorFlowTestCase): @unittest.skipUnless(test.is_built_with_cuda(), "Test only applicable when running on GPUs") - @test_util.run_in_graph_and_eager_modes() + @test_util.run_in_graph_and_eager_modes def testCudnnCompatibleLSTMCheckpointablMultiLayer(self): num_units = 2 num_layers = 3 |