diff options
Diffstat (limited to 'tensorflow/python/kernel_tests/reduction_ops_test.py')
| -rw-r--r-- | tensorflow/python/kernel_tests/reduction_ops_test.py | 30 |
1 files changed, 15 insertions, 15 deletions
diff --git a/tensorflow/python/kernel_tests/reduction_ops_test.py b/tensorflow/python/kernel_tests/reduction_ops_test.py index ea78b58d88..496a452a03 100644 --- a/tensorflow/python/kernel_tests/reduction_ops_test.py +++ b/tensorflow/python/kernel_tests/reduction_ops_test.py @@ -61,7 +61,7 @@ class ReducedShapeTest(test.TestCase): self.assertAllEqual(output.eval(), result) def testSimple(self): - with self.test_session(): + with self.cached_session(): self._check([3], [], [3]) self._check([3], [0], [1]) self._check([5, 3], [], [5, 3]) @@ -71,7 +71,7 @@ class ReducedShapeTest(test.TestCase): def testZeros(self): """Check that reduced_shape does the right thing with zero dimensions.""" - with self.test_session(): + with self.cached_session(): self._check([0], [], [0]) self._check([0], [0], [1]) self._check([0, 3], [], [0, 3]) @@ -84,7 +84,7 @@ class ReducedShapeTest(test.TestCase): self._check([3, 0], [0, 1], [1, 1]) def testNegAxes(self): - with self.test_session(): + with self.cached_session(): self._check([10, 10, 10], [-1], [10, 10, 1]) self._check([10, 10, 10], [-1, 2], [10, 10, 1]) self._check([10, 10, 10], [-1, -1], [10, 10, 1]) @@ -95,7 +95,7 @@ class ReducedShapeTest(test.TestCase): class ReductionUnknownShape(test.TestCase): def testBasic(self): - with self.test_session(): + with self.cached_session(): for dtype, reductions in [(dtypes.float32, (math_ops.reduce_sum, math_ops.reduce_mean, math_ops.reduce_prod, math_ops.reduce_max, @@ -617,7 +617,7 @@ class MinReductionTest(test.TestCase): def testGradient(self): s = [2, 3, 4, 2] x = np.arange(1.0, 49.0).reshape(s).astype(np.float64) - with self.test_session(): + with self.cached_session(): t = ops.convert_to_tensor(x) su = math_ops.reduce_min(t, [1, 2]) jacob_t, jacob_n = gradient_checker.compute_gradient( @@ -627,7 +627,7 @@ class MinReductionTest(test.TestCase): def testGradient2(self): s = [2, 3, 4, 2] x = np.arange(1.0, 49.0).reshape(s).astype(np.float64) - with self.test_session(): + with self.cached_session(): t = ops.convert_to_tensor(x) su = math_ops.reduce_min(t, [1]) jacob_t, jacob_n = gradient_checker.compute_gradient( @@ -637,7 +637,7 @@ class MinReductionTest(test.TestCase): def testGradient3(self): s = [2, 3, 4, 2] x = np.arange(1.0, 49.0).reshape(s).astype(np.float64) - with self.test_session(): + with self.cached_session(): t = ops.convert_to_tensor(x) su = math_ops.reduce_min(t, [2]) jacob_t, jacob_n = gradient_checker.compute_gradient( @@ -647,7 +647,7 @@ class MinReductionTest(test.TestCase): def testGradient4(self): s = [2, 3, 4, 2] x = np.arange(1.0, 49.0).reshape(s).astype(np.float64) - with self.test_session(): + with self.cached_session(): t = ops.convert_to_tensor(x) su = math_ops.reduce_min(t) jacob_t, jacob_n = gradient_checker.compute_gradient( @@ -655,7 +655,7 @@ class MinReductionTest(test.TestCase): self.assertAllClose(jacob_t, jacob_n, rtol=1e-8, atol=1e-8) def testEmptyGradients(self): - with self.test_session(): + with self.cached_session(): x = array_ops.zeros([0, 3]) y = math_ops.reduce_min(x, [1]) error = gradient_checker.compute_gradient_error(x, [0, 3], y, [0]) @@ -744,7 +744,7 @@ class MaxReductionTest(test.TestCase): def testGradient(self): s = [2, 3, 4, 2] x = np.arange(-49.0, -1.0).reshape(s).astype(np.float64) - with self.test_session(): + with self.cached_session(): t = ops.convert_to_tensor(x) su = math_ops.reduce_max(t, [1, 2]) jacob_t, jacob_n = gradient_checker.compute_gradient( @@ -754,7 +754,7 @@ class MaxReductionTest(test.TestCase): def testGradient2(self): s = [2, 3, 4, 2] x = np.arange(-49.0, -1.0).reshape(s).astype(np.float64) - with self.test_session(): + with self.cached_session(): t = ops.convert_to_tensor(x) su = math_ops.reduce_max(t, [1]) jacob_t, jacob_n = gradient_checker.compute_gradient( @@ -764,7 +764,7 @@ class MaxReductionTest(test.TestCase): def testGradient3(self): s = [2, 3, 4, 2] x = np.arange(-49.0, -1.0).reshape(s).astype(np.float64) - with self.test_session(): + with self.cached_session(): t = ops.convert_to_tensor(x) su = math_ops.reduce_max(t, [2]) jacob_t, jacob_n = gradient_checker.compute_gradient( @@ -774,7 +774,7 @@ class MaxReductionTest(test.TestCase): def testGradient4(self): s = [2, 3, 4, 2] x = np.arange(-49.0, -1.0).reshape(s).astype(np.float64) - with self.test_session(): + with self.cached_session(): t = ops.convert_to_tensor(x) su = math_ops.reduce_max(t) jacob_t, jacob_n = gradient_checker.compute_gradient( @@ -782,7 +782,7 @@ class MaxReductionTest(test.TestCase): self.assertAllClose(jacob_t, jacob_n, rtol=1e-8, atol=1e-8) def testEmptyGradients(self): - with self.test_session(): + with self.cached_session(): x = array_ops.zeros([0, 3]) y = math_ops.reduce_max(x, [1]) error = gradient_checker.compute_gradient_error(x, [0, 3], y, [0]) @@ -960,7 +960,7 @@ class CountNonzeroReductionTest(test.TestCase): def testStringReduce(self): # Test case for GitHub issue 18712 - with self.test_session() as sess: + with self.cached_session() as sess: v = math_ops.count_nonzero(constant_op.constant(["test"])) self.assertAllClose(sess.run(v), 1) |