diff options
Diffstat (limited to 'tensorflow/contrib/optimizer_v2/adam_test.py')
| -rw-r--r-- | tensorflow/contrib/optimizer_v2/adam_test.py | 12 |
1 files changed, 6 insertions, 6 deletions
diff --git a/tensorflow/contrib/optimizer_v2/adam_test.py b/tensorflow/contrib/optimizer_v2/adam_test.py index d9ad58b0a6..b1ad0ade42 100644 --- a/tensorflow/contrib/optimizer_v2/adam_test.py +++ b/tensorflow/contrib/optimizer_v2/adam_test.py @@ -56,7 +56,7 @@ class AdamOptimizerTest(test.TestCase): def doTestSparse(self, use_resource=False): for dtype in [dtypes.half, dtypes.float32, dtypes.float64]: - with self.test_session(): + with self.cached_session(): # Initialize variables for numpy implementation. m0, v0, m1, v1 = 0.0, 0.0, 0.0, 0.0 var0_np = np.array([1.0, 2.0], dtype=dtype.as_numpy_dtype) @@ -122,7 +122,7 @@ class AdamOptimizerTest(test.TestCase): def testSparseRepeatedIndices(self): for dtype in [dtypes.half, dtypes.float32, dtypes.float64]: - with self.test_session(): + with self.cached_session(): repeated_index_update_var = variables.Variable( [[1.0], [2.0]], dtype=dtype) aggregated_update_var = variables.Variable( @@ -152,7 +152,7 @@ class AdamOptimizerTest(test.TestCase): def doTestBasic(self, use_resource=False): for i, dtype in enumerate([dtypes.half, dtypes.float32, dtypes.float64]): - with self.test_session(graph=ops.Graph()): + with self.session(graph=ops.Graph()): # Initialize variables for numpy implementation. m0, v0, m1, v1 = 0.0, 0.0, 0.0, 0.0 var0_np = np.array([1.0, 2.0], dtype=dtype.as_numpy_dtype) @@ -215,7 +215,7 @@ class AdamOptimizerTest(test.TestCase): opt.get_slot(var=var0, name="m").name) def testBasic(self): - with self.test_session(): + with self.cached_session(): self.doTestBasic(use_resource=False) @test_util.run_in_graph_and_eager_modes(reset_test=True) @@ -224,7 +224,7 @@ class AdamOptimizerTest(test.TestCase): def testTensorLearningRate(self): for dtype in [dtypes.half, dtypes.float32, dtypes.float64]: - with self.test_session(): + with self.cached_session(): # Initialize variables for numpy implementation. m0, v0, m1, v1 = 0.0, 0.0, 0.0, 0.0 var0_np = np.array([1.0, 2.0], dtype=dtype.as_numpy_dtype) @@ -261,7 +261,7 @@ class AdamOptimizerTest(test.TestCase): def testSharing(self): for dtype in [dtypes.half, dtypes.float32, dtypes.float64]: - with self.test_session(): + with self.cached_session(): # Initialize variables for numpy implementation. m0, v0, m1, v1 = 0.0, 0.0, 0.0, 0.0 var0_np = np.array([1.0, 2.0], dtype=dtype.as_numpy_dtype) |