diff options
Diffstat (limited to 'tensorflow/python/training/gradient_descent_test.py')
| -rw-r--r-- | tensorflow/python/training/gradient_descent_test.py | 18 |
1 files changed, 9 insertions, 9 deletions
diff --git a/tensorflow/python/training/gradient_descent_test.py b/tensorflow/python/training/gradient_descent_test.py index b304e92421..56d82a5b88 100644 --- a/tensorflow/python/training/gradient_descent_test.py +++ b/tensorflow/python/training/gradient_descent_test.py @@ -37,7 +37,7 @@ class GradientDescentOptimizerTest(test.TestCase): def testBasic(self): for dtype in [dtypes.half, dtypes.float32, dtypes.float64]: - with self.test_session(): + with self.cached_session(): var0 = variables.Variable([1.0, 2.0], dtype=dtype) var1 = variables.Variable([3.0, 4.0], dtype=dtype) grads0 = constant_op.constant([0.1, 0.1], dtype=dtype) @@ -60,7 +60,7 @@ class GradientDescentOptimizerTest(test.TestCase): def testBasicResourceVariable(self): for dtype in [dtypes.half, dtypes.float32, dtypes.float64]: - with self.test_session(): + with self.cached_session(): var0 = resource_variable_ops.ResourceVariable([1.0, 2.0], dtype=dtype) var1 = resource_variable_ops.ResourceVariable([3.0, 4.0], dtype=dtype) grads0 = constant_op.constant([0.1, 0.1], dtype=dtype) @@ -85,7 +85,7 @@ class GradientDescentOptimizerTest(test.TestCase): def testBasicCallableParams(self): for dtype in [dtypes.half, dtypes.float32, dtypes.float64]: - with self.test_session(): + with self.cached_session(): var0 = resource_variable_ops.ResourceVariable([1.0, 2.0], dtype=dtype) var1 = resource_variable_ops.ResourceVariable([3.0, 4.0], dtype=dtype) grads0 = constant_op.constant([0.1, 0.1], dtype=dtype) @@ -111,7 +111,7 @@ class GradientDescentOptimizerTest(test.TestCase): def testMinimizeResourceVariable(self): for dtype in [dtypes.half, dtypes.float32, dtypes.float64]: - with self.test_session(): + with self.cached_session(): var0 = resource_variable_ops.ResourceVariable([[1.0, 2.0]], dtype=dtype) var1 = resource_variable_ops.ResourceVariable([3.0], dtype=dtype) x = constant_op.constant([[4.0], [5.0]], dtype=dtype) @@ -137,7 +137,7 @@ class GradientDescentOptimizerTest(test.TestCase): def testMinimizeSparseResourceVariable(self): for dtype in [dtypes.half, dtypes.float32, dtypes.float64]: - with self.test_session(): + with self.cached_session(): var0 = resource_variable_ops.ResourceVariable([[1.0, 2.0]], dtype=dtype) var1 = resource_variable_ops.ResourceVariable([3.0], dtype=dtype) x = constant_op.constant([[4.0], [5.0]], dtype=dtype) @@ -164,7 +164,7 @@ class GradientDescentOptimizerTest(test.TestCase): def testTensorLearningRate(self): for dtype in [dtypes.half, dtypes.float32, dtypes.float64]: - with self.test_session(): + with self.cached_session(): var0 = variables.Variable([1.0, 2.0], dtype=dtype) var1 = variables.Variable([3.0, 4.0], dtype=dtype) grads0 = constant_op.constant([0.1, 0.1], dtype=dtype) @@ -186,7 +186,7 @@ class GradientDescentOptimizerTest(test.TestCase): def testGradWrtRef(self): for dtype in [dtypes.half, dtypes.float32, dtypes.float64]: - with self.test_session(): + with self.cached_session(): opt = gradient_descent.GradientDescentOptimizer(3.0) values = [1.0, 3.0] vars_ = [variables.Variable([v], dtype=dtype) for v in values] @@ -197,7 +197,7 @@ class GradientDescentOptimizerTest(test.TestCase): def testWithGlobalStep(self): for dtype in [dtypes.half, dtypes.float32, dtypes.float64]: - with self.test_session(): + with self.cached_session(): global_step = variables.Variable(0, trainable=False) var0 = variables.Variable([1.0, 2.0], dtype=dtype) var1 = variables.Variable([3.0, 4.0], dtype=dtype) @@ -220,7 +220,7 @@ class GradientDescentOptimizerTest(test.TestCase): def testSparseBasic(self): for dtype in [dtypes.half, dtypes.float32, dtypes.float64]: - with self.test_session(): + with self.cached_session(): var0 = variables.Variable([[1.0], [2.0]], dtype=dtype) var1 = variables.Variable([[3.0], [4.0]], dtype=dtype) grads0 = ops.IndexedSlices( |