Remove unused "sess" variables from tests; NFC

PiperOrigin-RevId: 357594586
Change-Id: Ia8c8274d12181aa59f2c46f8d7c8c3599aaffe74

tensorflow/python/framework/function_test.py

@@ -462,7 +462,7 @@ class FunctionTest(test.TestCase):
 
   @test_util.run_deprecated_v1
   def testWhileLoopCallsFunc(self):
-    with self.session() as sess:
+    with self.session():
 
       @function.Defun(dtypes.float32)
       def Times2(x):

tensorflow/python/kernel_tests/aggregate_ops_test.py

@@ -58,7 +58,7 @@ class AddNTest(test.TestCase):
 
   def testAddN(self):
     np.random.seed(12345)
-    with self.session() as sess:
+    with self.session():
       for dtype in self._supported_types():
         for count in range(1, self._MAX_N + 1):
           data = [self._buildData((2, 2), dtype) for _ in range(count)]

tensorflow/python/kernel_tests/array_ops/scatter_nd_ops_test.py

@@ -211,7 +211,7 @@ class StatefulScatterNdTest(test.TestCase):
     scatter = state_ops.scatter_nd_update(ref, indices, updates)
     init = variables.global_variables_initializer()
 
-    with self.session() as sess:
+    with self.session():
       self.evaluate(init)
       result = self.evaluate(scatter)
       self.assertAllClose(result, expected)
@@ -225,7 +225,7 @@ class StatefulScatterNdTest(test.TestCase):
     scatter = state_ops.scatter_nd_update(ref, indices, updates)
     init = variables.global_variables_initializer()
 
-    with self.session() as sess:
+    with self.session():
       self.evaluate(init)
       result = self.evaluate(scatter)
       self.assertAllClose(result, expected)

tensorflow/python/kernel_tests/array_ops_test.py

@@ -1001,7 +1001,7 @@ class StridedSliceGradTest(test_util.TensorFlowTestCase):
 
   @test_util.run_deprecated_v1
   def testInt64Indices(self):
-    with self.session() as sess:
+    with self.session():
       a = math_ops.range(3, dtype=dtypes.float32)
       index = constant_op.constant(1, dtype=dtypes.int64)
       b = 2. * a[index]

tensorflow/python/kernel_tests/basic_gpu_test.py

@@ -40,13 +40,13 @@ from tensorflow.python.platform import test
 class GPUBinaryOpsTest(test.TestCase):
 
   def _compareGPU(self, x, y, np_func, tf_func):
-    with self.cached_session() as sess:
+    with self.cached_session():
       inx = ops.convert_to_tensor(x)
       iny = ops.convert_to_tensor(y)
       out = tf_func(inx, iny)
       tf_gpu = self.evaluate(out)
 
-    with self.cached_session(use_gpu=False) as sess:
+    with self.cached_session(use_gpu=False):
       inx = ops.convert_to_tensor(x)
       iny = ops.convert_to_tensor(y)
       out = tf_func(inx, iny)
@@ -143,7 +143,7 @@ class MathBuiltinUnaryTest(test.TestCase):
 
     np_out = np.floor_divide(x, y + 0.1)
 
-    with self.session() as sess:
+    with self.session():
       inx = ops.convert_to_tensor(x)
       iny = ops.convert_to_tensor(y + 0.1)
       ofunc = inx / iny

tensorflow/python/kernel_tests/bucketize_op_test.py

@@ -36,7 +36,7 @@ class BucketizationOpTest(test.TestCase):
         constant_op.constant([-5, 0, 2, 3, 5, 8, 10, 11, 12]),
         boundaries=[0, 3, 8, 11])
     expected_out = [0, 1, 1, 2, 2, 3, 3, 4, 4]
-    with self.session() as sess:
+    with self.session():
       self.assertAllEqual(expected_out, self.evaluate(op))
 
   def testEmptyFloat(self):
@@ -51,7 +51,7 @@ class BucketizationOpTest(test.TestCase):
         constant_op.constant([-5., 0., 2., 3., 5., 8., 10., 11., 12.]),
         boundaries=[0., 3., 8., 11.])
     expected_out = [0, 1, 1, 2, 2, 3, 3, 4, 4]
-    with self.session() as sess:
+    with self.session():
       self.assertAllEqual(expected_out, self.evaluate(op))
 
   def test2DInput(self):
@@ -59,14 +59,14 @@ class BucketizationOpTest(test.TestCase):
         constant_op.constant([[-5, 0, 2, 3, 5], [8, 10, 11, 12, 0]]),
         boundaries=[0, 3, 8, 11])
     expected_out = [[0, 1, 1, 2, 2], [3, 3, 4, 4, 1]]
-    with self.session() as sess:
+    with self.session():
       self.assertAllEqual(expected_out, self.evaluate(op))
 
   @test_util.run_deprecated_v1
   def testInvalidBoundariesOrder(self):
     op = math_ops._bucketize(
         constant_op.constant([-5, 0]), boundaries=[0, 8, 3, 11])
-    with self.session() as sess:
+    with self.session():
       with self.assertRaisesRegex(errors_impl.InvalidArgumentError,
                                   "Expected sorted boundaries"):
         self.evaluate(op)

tensorflow/python/kernel_tests/clip_ops_test.py

@@ -176,7 +176,7 @@ class ClipTest(test.TestCase):
 
   def _testClipIndexedSlicesByValue(self, values, indices, shape,
                                     clip_value_min, clip_value_max, expected):
-    with self.session() as sess:
+    with self.session():
       values = constant_op.constant(values)
       indices = constant_op.constant(indices)
       shape = constant_op.constant(shape)

tensorflow/python/kernel_tests/conv_ops_test.py

@@ -2787,7 +2787,7 @@ class SeparableConv2DTest(test.TestCase):
       expected: An array containing the expected operation outputs.
       data_format: string data format for input tensor.
     """
-    with self.cached_session() as sess:
+    with self.cached_session():
       t1 = self._InitValues(tensor_in_sizes)
       f1 = self._InitValues(depthwise_filter_in_sizes)
       f1.set_shape(depthwise_filter_in_sizes)

tensorflow/python/kernel_tests/decode_image_op_test.py

@@ -37,7 +37,7 @@ class DecodeImageOpTest(test.TestCase):
   def testBmp(self):
     # Read a real bmp and verify shape
     path = os.path.join(prefix_path, "bmp", "testdata", "lena.bmp")
-    with self.session() as sess:
+    with self.session():
       bmp0 = io_ops.read_file(path)
       image0 = image_ops.decode_image(bmp0)
       image1 = image_ops.decode_bmp(bmp0)
@@ -53,7 +53,7 @@ class DecodeImageOpTest(test.TestCase):
     stride = 5
     shape = (12, height, width, 3)
 
-    with self.session() as sess:
+    with self.session():
       gif0 = io_ops.read_file(path)
       image0 = image_ops.decode_image(gif0)
       image1 = image_ops.decode_gif(gif0)
@@ -82,7 +82,7 @@ class DecodeImageOpTest(test.TestCase):
   def testJpeg(self):
     # Read a real jpeg and verify shape
     path = os.path.join(prefix_path, "jpeg", "testdata", "jpeg_merge_test1.jpg")
-    with self.session() as sess:
+    with self.session():
       jpeg0 = io_ops.read_file(path)
       image0 = image_ops.decode_image(jpeg0)
       image1 = image_ops.decode_jpeg(jpeg0)

tensorflow/python/kernel_tests/determinant_op_test.py

@@ -154,7 +154,7 @@ class DeterminantOpTest(test.TestCase):
 
   @test_util.run_v1_only("b/120545219")
   def testConcurrentExecutesWithoutError(self):
-    with self.session() as sess:
+    with self.session():
       matrix1 = random_ops.random_normal([5, 5], seed=42)
       matrix2 = random_ops.random_normal([5, 5], seed=42)
       det1 = linalg_ops.matrix_determinant(matrix1)

tensorflow/python/kernel_tests/dynamic_partition_op_test.py

@@ -39,7 +39,7 @@ class DynamicPartitionTest(test.TestCase):
 
   @test_util.run_deprecated_v1
   def testSimpleOneDimensional(self):
-    with self.session() as sess:
+    with self.session():
       data = constant_op.constant([0, 13, 2, 39, 4, 17], dtype=dtypes.float32)
       indices = constant_op.constant([0, 0, 2, 3, 2, 1])
       partitions = data_flow_ops.dynamic_partition(
@@ -60,7 +60,7 @@ class DynamicPartitionTest(test.TestCase):
 
   @test_util.run_deprecated_v1
   def testSimpleTwoDimensional(self):
-    with self.session() as sess:
+    with self.session():
       data = constant_op.constant([[0, 1, 2], [3, 4, 5], [6, 7, 8], [9, 10, 11],
                                    [12, 13, 14], [15, 16, 17]],
                                   dtype=dtypes.float32)
@@ -87,7 +87,7 @@ class DynamicPartitionTest(test.TestCase):
     indices_list = [x % 2 for x in range(num)]
     part1 = [x for x in range(num) if x % 2 == 0]
     part2 = [x for x in range(num) if x % 2 == 1]
-    with self.session() as sess:
+    with self.session():
       data = constant_op.constant(data_list, dtype=dtypes.float32)
       indices = constant_op.constant(indices_list, dtype=dtypes.int32)
       partitions = data_flow_ops.dynamic_partition(
@@ -109,7 +109,7 @@ class DynamicPartitionTest(test.TestCase):
     parts = [[] for _ in range(num_partitions)]
     for i in range(rows):
       parts[(i ** 2) % num_partitions].append(data_list[i])
-    with self.session() as sess:
+    with self.session():
       data = constant_op.constant(data_list, dtype=dtypes.float32)
       indices = constant_op.constant(indices_list, dtype=dtypes.int32)
       partitions = data_flow_ops.dynamic_partition(
@@ -125,7 +125,7 @@ class DynamicPartitionTest(test.TestCase):
   def testSimpleComplex(self):
     data_list = [1 + 2j, 3 + 4j, 5 + 6j, 7 + 8j]
     indices_list = [1, 0, 1, 0]
-    with self.session() as sess:
+    with self.session():
       data = constant_op.constant(data_list, dtype=dtypes.complex64)
       indices = constant_op.constant(indices_list, dtype=dtypes.int32)
       partitions = data_flow_ops.dynamic_partition(
@@ -138,7 +138,7 @@ class DynamicPartitionTest(test.TestCase):
 
   def testScalarPartitions(self):
     data_list = [10, 13, 12, 11]
-    with self.session() as sess:
+    with self.session():
       data = constant_op.constant(data_list, dtype=dtypes.float64)
       indices = 3
       partitions = data_flow_ops.dynamic_partition(
@@ -184,7 +184,7 @@ class DynamicPartitionTest(test.TestCase):
   def testEmptyParts(self):
     data_list = [1, 2, 3, 4]
     indices_list = [1, 3, 1, 3]
-    with self.session() as sess:
+    with self.session():
       data = constant_op.constant(data_list, dtype=dtypes.float32)
       indices = constant_op.constant(indices_list, dtype=dtypes.int32)
       partitions = data_flow_ops.dynamic_partition(
@@ -200,7 +200,7 @@ class DynamicPartitionTest(test.TestCase):
   def testEmptyDataTwoDimensional(self):
     data_list = [[], []]
     indices_list = [0, 1]
-    with self.session() as sess:
+    with self.session():
       data = constant_op.constant(data_list, dtype=dtypes.float32)
       indices = constant_op.constant(indices_list, dtype=dtypes.int32)
       partitions = data_flow_ops.dynamic_partition(
@@ -216,7 +216,7 @@ class DynamicPartitionTest(test.TestCase):
   def testEmptyPartitions(self):
     data_list = []
     indices_list = []
-    with self.session() as sess:
+    with self.session():
       data = constant_op.constant(data_list, dtype=dtypes.float32)
       indices = constant_op.constant(indices_list, dtype=dtypes.int32)
       partitions = data_flow_ops.dynamic_partition(
@@ -237,7 +237,7 @@ class DynamicPartitionTest(test.TestCase):
 
     data_list = [1, 2, 3, 4, 5, 6]
     indices_list = [6, 5, 4, 3, 1, 0]
-    with self.session() as sess:
+    with self.session():
       data = constant_op.constant(data_list, dtype=dtypes.float32)
       indices = constant_op.constant(indices_list, dtype=dtypes.int32)
       partitions = data_flow_ops.dynamic_partition(
@@ -258,7 +258,7 @@ class DynamicPartitionTest(test.TestCase):
 
     data_list = [1, 2, 3, 4, 5, 6]
     indices_list = [10, 11, 2, 12, 0, 1000]
-    with self.session() as sess:
+    with self.session():
       data = constant_op.constant(data_list, dtype=dtypes.float32)
       indices = constant_op.constant(indices_list, dtype=dtypes.int32)
       partitions = data_flow_ops.dynamic_partition(
@@ -282,7 +282,7 @@ class DynamicPartitionTest(test.TestCase):
 
     data_list = [1.1, 2.1, 3.1, 4.1, 5.1, 6.1]
     indices_list = [90, 70, 60, 100, 110, 40]
-    with self.session() as sess:
+    with self.session():
       data = constant_op.constant(data_list, dtype=dtypes.float32)
       indices = constant_op.constant(indices_list, dtype=dtypes.int32)
       partitions = data_flow_ops.dynamic_partition(
@@ -295,7 +295,7 @@ class DynamicPartitionTest(test.TestCase):
 
   @test_util.run_deprecated_v1
   def testErrorIndexOutOfRange(self):
-    with self.cached_session() as sess:
+    with self.cached_session():
       data = constant_op.constant([[0, 1, 2], [3, 4, 5], [6, 7, 8], [9, 10, 11],
                                    [12, 13, 14]])
       indices = constant_op.constant([0, 2, 99, 2, 2])
@@ -346,7 +346,7 @@ class DynamicPartitionTest(test.TestCase):
     inds += [13]*194 + [14]*194 + [15]*192
     self.assertEqual(len(inds), x.shape[0])
     partitioned = data_flow_ops.dynamic_partition(x, inds, 16)
-    with self.cached_session() as sess:
+    with self.cached_session():
       res = self.evaluate(partitioned)
     self.assertEqual(res[-1].shape[0], 192)
 

tensorflow/python/kernel_tests/eig_op_test.py

@@ -55,7 +55,7 @@ class EigTest(test.TestCase):
   @test_util.run_deprecated_v1
   def testConcurrentExecutesWithoutError(self):
     all_ops = []
-    with self.session() as sess:
+    with self.session():
       for compute_v_ in True, False:
         matrix1 = random_ops.random_normal([5, 5], seed=42)
         matrix2 = random_ops.random_normal([5, 5], seed=42)

tensorflow/python/kernel_tests/functional_ops_test.py

@@ -340,7 +340,7 @@ class FunctionalOpsTest(test.TestCase):
         lambda elem_, input_: (a, b), elems, initializer=(0., 0.))
     loss = l0 + array_ops.stop_gradient(l1)
     grad = gradients_impl.gradients(ys=[loss], xs=[a, b])
-    with self.test_session() as sess:
+    with self.test_session():
       self.evaluate(variables.global_variables_initializer())
       self.evaluate(grad)
 

tensorflow/python/kernel_tests/init_ops_test.py

@@ -910,7 +910,7 @@ class ConvolutionDeltaOrthogonalInitializerTest(test.TestCase):
         outputs_2norm = linalg_ops.norm(outputs)
         ratio = outputs_2norm / inputs_2norm
         my_ops = variables.global_variables_initializer()
-        with self.session() as sess:
+        with self.session():
           self.evaluate(my_ops)
           # Check the shape of the outputs
           t = self.evaluate(outputs)
@@ -1063,7 +1063,7 @@ class ConvolutionOrthogonal1dInitializerTest(test.TestCase):
       outputs_2norm = linalg_ops.norm(outputs)
       ratio = outputs_2norm / inputs_2norm
       my_ops = variables.global_variables_initializer()
-      with self.session() as sess:
+      with self.session():
         self.evaluate(my_ops)
         # Check the shape of the outputs
         t = self.evaluate(outputs)
@@ -1167,7 +1167,7 @@ class ConvolutionOrthogonal2dInitializerTest(test.TestCase):
       outputs_2norm = linalg_ops.norm(outputs)
       ratio = outputs_2norm / inputs_2norm
       my_ops = variables.global_variables_initializer()
-      with self.session() as sess:
+      with self.session():
         self.evaluate(my_ops)
         # Check the shape of the outputs
         t = self.evaluate(outputs)
@@ -1302,7 +1302,7 @@ class ConvolutionOrthogonal3dInitializerTest(test.TestCase):
       outputs_2norm = linalg_ops.norm(outputs)
       ratio = outputs_2norm / inputs_2norm
       my_ops = variables.global_variables_initializer()
-      with self.cached_session() as sess:
+      with self.cached_session():
         self.evaluate(my_ops)
         # Check the shape of the outputs
         t = self.evaluate(outputs)

tensorflow/python/kernel_tests/matrix_exponential_op_test.py

@@ -157,7 +157,7 @@ class ExponentialOpTest(test.TestCase):
 
   @test_util.run_deprecated_v1
   def testConcurrentExecutesWithoutError(self):
-    with self.session() as sess:
+    with self.session():
       matrix1 = random_ops.random_normal([5, 5], seed=42)
       matrix2 = random_ops.random_normal([5, 5], seed=42)
       expm1 = linalg_impl.matrix_exponential(matrix1)

tensorflow/python/kernel_tests/random/multinomial_op_big_test.py

@@ -34,7 +34,7 @@ class MultinomialTest(test.TestCase):
   def testLargeDynamicRange(self):
     random_seed.set_random_seed(10)
     counts_by_indices = {}
-    with self.test_session() as sess:
+    with self.test_session():
       samples = random_ops.multinomial(
           constant_op.constant([[-30, 0]], dtype=dtypes.float32),
           num_samples=1000000,
@@ -52,7 +52,7 @@ class MultinomialTest(test.TestCase):
   def testLargeDynamicRange2(self):
     random_seed.set_random_seed(10)
     counts_by_indices = {}
-    with self.test_session() as sess:
+    with self.test_session():
       samples = random_ops.multinomial(
           constant_op.constant([[0, -30]], dtype=dtypes.float32),
           num_samples=1000000,
@@ -72,7 +72,7 @@ class MultinomialTest(test.TestCase):
     random_seed.set_random_seed(10)
     counts_by_indices = {}
     # here the cpu undersamples and won't pass this test either
-    with self.test_session() as sess:
+    with self.test_session():
       samples = random_ops.multinomial(
           constant_op.constant([[0, -17]], dtype=dtypes.float32),
           num_samples=1000000,

tensorflow/python/kernel_tests/reduction_ops_test.py

@@ -208,7 +208,7 @@ class SumReductionTest(BaseReductionTest):
 
   def testAxesType(self):
     for dtype in [dtypes.int64, dtypes.int32]:
-      with self.cached_session() as sess:
+      with self.cached_session():
         v = math_ops.reduce_sum([0, 0], constant_op.constant(0, dtype=dtype))
         tf_v = self.evaluate(v)
       self.assertAllEqual(tf_v, 0)
@@ -446,7 +446,7 @@ class MeanReductionTest(BaseReductionTest):
 
   def testAxesType(self):
     for dtype in [dtypes.int64, dtypes.int32]:
-      with self.cached_session() as sess:
+      with self.cached_session():
         v = math_ops.reduce_mean([0, 0], constant_op.constant(0, dtype=dtype))
         tf_v = self.evaluate(v)
       self.assertAllEqual(tf_v, 0)
@@ -640,7 +640,7 @@ class ProdReductionTest(BaseReductionTest):
 
   def testAxesType(self):
     for dtype in [dtypes.int64, dtypes.int32]:
-      with self.cached_session() as sess:
+      with self.cached_session():
         v = math_ops.reduce_prod([0, 0], constant_op.constant(0, dtype=dtype))
         tf_v = self.evaluate(v)
       self.assertAllEqual(tf_v, 0)
@@ -750,7 +750,7 @@ class MinReductionTest(test.TestCase):
 
   def testAxesType(self):
     for dtype in [dtypes.int64, dtypes.int32]:
-      with self.cached_session() as sess:
+      with self.cached_session():
         v = math_ops.reduce_min([0, 0], constant_op.constant(0, dtype=dtype))
         tf_v = self.evaluate(v)
       self.assertAllEqual(tf_v, 0)
@@ -866,7 +866,7 @@ class MaxReductionTest(test.TestCase):
 
   def testAxesType(self):
     for dtype in [dtypes.int64, dtypes.int32]:
-      with self.cached_session() as sess:
+      with self.cached_session():
         v = math_ops.reduce_max([0, 0], constant_op.constant(0, dtype=dtype))
         tf_v = self.evaluate(v)
       self.assertAllEqual(tf_v, 0)
@@ -998,7 +998,7 @@ class AllReductionTest(test.TestCase):
 
   def testAxesType(self):
     for dtype in [dtypes.int64, dtypes.int32]:
-      with self.session() as sess:
+      with self.session():
         v = math_ops.reduce_all([True, True],
                                 constant_op.constant(0, dtype=dtype))
         tf_v = self.evaluate(v)
@@ -1047,7 +1047,7 @@ class AnyReductionTest(test.TestCase):
 
   def testAxesType(self):
     for dtype in [dtypes.int64, dtypes.int32]:
-      with self.session() as sess:
+      with self.session():
         v = math_ops.reduce_any([True, True],
                                 constant_op.constant(0, dtype=dtype))
         tf_v = self.evaluate(v)

tensorflow/python/kernel_tests/self_adjoint_eig_op_test.py

@@ -55,7 +55,7 @@ class SelfAdjointEigTest(test.TestCase):
   @test_util.run_deprecated_v1
   def testConcurrentExecutesWithoutError(self):
     all_ops = []
-    with self.session() as sess:
+    with self.session():
       for compute_v_ in True, False:
         matrix1 = random_ops.random_normal([5, 5], seed=42)
         matrix2 = random_ops.random_normal([5, 5], seed=42)
@@ -84,7 +84,7 @@ class SelfAdjointEigTest(test.TestCase):
             "self_adjoint_eig_fail_if_denorms_flushed.txt")).astype(np.float32)
     self.assertEqual(matrix.shape, (32, 32))
     matrix_tensor = constant_op.constant(matrix)
-    with self.session() as sess:
+    with self.session():
       (e, v) = self.evaluate(linalg_ops.self_adjoint_eig(matrix_tensor))
       self.assertEqual(e.size, 32)
       self.assertAllClose(

tensorflow/python/kernel_tests/sparse_xent_op_test.py

@@ -64,7 +64,7 @@ class SparseXentTest(test.TestCase):
 
   def _testXent(self, np_features, np_labels):
     np_loss, np_backprop = self._npXent(np_features, np_labels)
-    with self.cached_session() as sess:
+    with self.cached_session():
       loss, backprop = gen_nn_ops.sparse_softmax_cross_entropy_with_logits(
           np_features, np_labels)
       tf_loss, tf_backprop = self.evaluate([loss, backprop])
@@ -73,7 +73,7 @@ class SparseXentTest(test.TestCase):
 
   def testSingleClass(self):
     for label_dtype in np.int32, np.int64:
-      with self.cached_session() as sess:
+      with self.cached_session():
         loss, backprop = gen_nn_ops.sparse_softmax_cross_entropy_with_logits(
             np.array([[1.], [-1.], [0.]]).astype(np.float32),
             np.array([0, 0, 0]).astype(label_dtype))

tensorflow/python/kernel_tests/tensor_array_ops_test.py

@@ -801,7 +801,7 @@ class TensorArrayTest(test.TestCase):
       self._testTensorArrayGradientWriteReadType(dtype)
 
   def _testTensorArrayGradientWritePackConcatAndRead(self):
-    with self.cached_session() as sess:
+    with self.cached_session():
       ta = tensor_array_ops.TensorArray(
           dtype=dtypes.float32,
           tensor_array_name="foo",
@@ -1371,7 +1371,7 @@ class TensorArrayTest(test.TestCase):
       self.assertAllEqual(grad_r0_x1_vals, [1.0, 0.0])
 
   def _testTensorArrayUnpackDynamic(self):
-    with self.cached_session() as sess:
+    with self.cached_session():
       ta = tensor_array_ops.TensorArray(
           dtype=dtypes.float32, size=3, dynamic_size=True)
       x = constant_op.constant([1.0, 2.0, 3.0])
@@ -1388,7 +1388,7 @@ class TensorArrayTest(test.TestCase):
 
   @test_util.run_deprecated_v1
   def testSkipEagerTensorArraySplitDynamic(self):
-    with self.session() as sess:
+    with self.session():
       ta = tensor_array_ops.TensorArray(
           dtype=dtypes.float32, size=3, dynamic_size=True)
       x = constant_op.constant([1.0, 2.0, 3.0])
@@ -1771,7 +1771,7 @@ class TensorArrayTest(test.TestCase):
       # dy is outside of the gradients name scope; tf.gradients must
       # wrap it in the correct name scope.
       dx, = gradients_impl.gradients(ys=[y], xs=[x], grad_ys=[dy])
-      with self.cached_session() as sess:
+      with self.cached_session():
         vdx, vdy = self.evaluate([dx, dy])
       self.assertAllClose(vdx, vdy)
 

tensorflow/python/kernel_tests/topk_op_test.py

@@ -47,7 +47,7 @@ class TopKTest(test.TestCase):
                     sorted=True):  # pylint: disable=redefined-builtin
     np_expected_values = np.array(expected_values)
     np_expected_indices = np.array(expected_indices)
-    with self.cached_session() as sess:
+    with self.cached_session():
       values_op, indices_op = nn_ops.top_k(inputs, k, sorted=sorted)
       values, indices = self.evaluate([values_op, indices_op])
 

tensorflow/python/kernel_tests/xent_op_test.py

@@ -319,7 +319,7 @@ class XentTest(test.TestCase):
     features = np.zeros([0, 2, 4]).astype(np.float32)
     labels = np.zeros([0, 2, 4]).astype(np.float32)
     np_loss, _ = self._npXent(features, labels)
-    with self.session() as sess:
+    with self.session():
       loss = nn_ops.softmax_cross_entropy_with_logits(
           labels=labels, logits=features)
       tf_loss = self.evaluate(loss)

tensorflow/python/ops/bitwise_ops_test.py

@@ -62,7 +62,7 @@ class BitwiseOpTest(test_util.TensorFlowTestCase):
     def count_bits(x):
       return sum(bin(z).count("1") for z in six.iterbytes(x.tobytes()))
     for dtype in dtype_list:
-      with self.cached_session() as sess:
+      with self.cached_session():
         print("PopulationCount test: ", dtype)
         inputs = np.array(raw_inputs, dtype=dtype.as_numpy_dtype)
         truth = [count_bits(x) for x in inputs]

tensorflow/python/ops/image_grad_test_base.py

@@ -444,7 +444,7 @@ class CropAndResizeOpTestBase(test.TestCase):
         constant_op.constant(boxes, shape=[num_boxes, 4]),
         constant_op.constant(box_ind, shape=[num_boxes]),
         constant_op.constant(crop_size, shape=[2]))
-    with self.session() as sess:
+    with self.session():
       self.assertEqual(crops_shape, list(crops.get_shape()))
       crops = self.evaluate(crops)
       self.assertEqual(crops_shape, list(crops.shape))

tensorflow/python/ops/image_ops_test.py

@@ -71,7 +71,7 @@ class RGBToHSVTest(test_util.TensorFlowTestCase):
       inp = np.random.rand(*shape).astype(nptype)
 
       # Convert to HSV and back, as a batch and individually
-      with self.cached_session() as sess:
+      with self.cached_session():
         batch0 = constant_op.constant(inp)
         batch1 = image_ops.rgb_to_hsv(batch0)
         batch2 = image_ops.hsv_to_rgb(batch1)
@@ -113,7 +113,7 @@ class RGBToYIQTest(test_util.TensorFlowTestCase):
       inp = np.random.rand(*shape).astype(nptype)
 
       # Convert to YIQ and back, as a batch and individually
-      with self.cached_session() as sess:
+      with self.cached_session():
         batch0 = constant_op.constant(inp)
         batch1 = image_ops.rgb_to_yiq(batch0)
         batch2 = image_ops.yiq_to_rgb(batch1)
@@ -145,7 +145,7 @@ class RGBToYUVTest(test_util.TensorFlowTestCase):
       inp = np.random.rand(*shape).astype(nptype)
 
       # Convert to YUV and back, as a batch and individually
-      with self.cached_session() as sess:
+      with self.cached_session():
         batch0 = constant_op.constant(inp)
         batch1 = image_ops.rgb_to_yuv(batch0)
         batch2 = image_ops.yuv_to_rgb(batch1)
@@ -3199,7 +3199,7 @@ class ResizeImagesTest(test_util.TensorFlowTestCase,
       img_np = np.array(data, dtype=nptype).reshape(img_shape)
 
       for method in self.METHODS:
-        with self.cached_session() as sess:
+        with self.cached_session():
           image = constant_op.constant(img_np, shape=img_shape)
           y = image_ops.resize_images(image, [target_height, target_width],
                                       method)
@@ -4176,7 +4176,7 @@ class JpegTest(test_util.TensorFlowTestCase):
     # Read a real jpeg and verify shape
     path = ("tensorflow/core/lib/jpeg/testdata/"
             "jpeg_merge_test1.jpg")
-    with self.cached_session() as sess:
+    with self.cached_session():
       jpeg0 = io_ops.read_file(path)
       image0 = image_ops.decode_jpeg(jpeg0)
       image1 = image_ops.decode_jpeg(image_ops.encode_jpeg(image0))
@@ -4192,7 +4192,7 @@ class JpegTest(test_util.TensorFlowTestCase):
     cmyk_path = os.path.join(base, "jpeg_merge_test1_cmyk.jpg")
     shape = 256, 128, 3
     for channels in 3, 0:
-      with self.cached_session() as sess:
+      with self.cached_session():
         rgb = image_ops.decode_jpeg(
             io_ops.read_file(rgb_path), channels=channels)
         cmyk = image_ops.decode_jpeg(
@@ -4248,7 +4248,7 @@ class JpegTest(test_util.TensorFlowTestCase):
           self.evaluate(result)
 
   def testSynthetic(self):
-    with self.cached_session() as sess:
+    with self.cached_session():
       # Encode it, then decode it, then encode it
       image0 = constant_op.constant(simple_color_ramp())
       jpeg0 = image_ops.encode_jpeg(image0)
@@ -4269,7 +4269,7 @@ class JpegTest(test_util.TensorFlowTestCase):
       self.assertLessEqual(len(jpeg0), 6000)
 
   def testSyntheticFasterAlgorithm(self):
-    with self.cached_session() as sess:
+    with self.cached_session():
       # Encode it, then decode it, then encode it
       image0 = constant_op.constant(simple_color_ramp())
       jpeg0 = image_ops.encode_jpeg(image0)
@@ -4293,7 +4293,7 @@ class JpegTest(test_util.TensorFlowTestCase):
       self.assertLessEqual(len(jpeg0), 6000)
 
   def testDefaultDCTMethodIsIntegerFast(self):
-    with self.cached_session() as sess:
+    with self.cached_session():
       # Compare decoding with both dct_option=INTEGER_FAST and
       # default.  They should be the same.
       image0 = constant_op.constant(simple_color_ramp())
@@ -4308,7 +4308,7 @@ class JpegTest(test_util.TensorFlowTestCase):
   def testShape(self):
     # Shape function requires placeholders and a graph.
     with ops.Graph().as_default():
-      with self.cached_session() as sess:
+      with self.cached_session():
         jpeg = constant_op.constant("nonsense")
         for channels in 0, 1, 3:
           image = image_ops.decode_jpeg(jpeg, channels=channels)
@@ -4418,7 +4418,7 @@ class PngTest(test_util.TensorFlowTestCase):
               (3, "lena_palette.png"), (4, "lena_palette_trns.png"))
     for channels_in, filename in inputs:
       for channels in 0, 1, 3, 4:
-        with self.cached_session() as sess:
+        with self.cached_session():
           png0 = io_ops.read_file(prefix + filename)
           image0 = image_ops.decode_png(png0, channels=channels)
           png0, image0 = self.evaluate([png0, image0])
@@ -4428,7 +4428,7 @@ class PngTest(test_util.TensorFlowTestCase):
             self.assertAllEqual(image0, self.evaluate(image1))
 
   def testSynthetic(self):
-    with self.cached_session() as sess:
+    with self.cached_session():
       # Encode it, then decode it
       image0 = constant_op.constant(simple_color_ramp())
       png0 = image_ops.encode_png(image0, compression=7)
@@ -4443,7 +4443,7 @@ class PngTest(test_util.TensorFlowTestCase):
       self.assertLessEqual(len(png0), 750)
 
   def testSyntheticUint16(self):
-    with self.cached_session() as sess:
+    with self.cached_session():
       # Encode it, then decode it
       image0 = constant_op.constant(simple_color_ramp(), dtype=dtypes.uint16)
       png0 = image_ops.encode_png(image0, compression=7)
@@ -4458,7 +4458,7 @@ class PngTest(test_util.TensorFlowTestCase):
       self.assertLessEqual(len(png0), 1500)
 
   def testSyntheticTwoChannel(self):
-    with self.cached_session() as sess:
+    with self.cached_session():
       # Strip the b channel from an rgb image to get a two-channel image.
       gray_alpha = simple_color_ramp()[:, :, 0:2]
       image0 = constant_op.constant(gray_alpha)
@@ -4469,7 +4469,7 @@ class PngTest(test_util.TensorFlowTestCase):
       self.assertAllEqual(image0, image1)
 
   def testSyntheticTwoChannelUint16(self):
-    with self.cached_session() as sess:
+    with self.cached_session():
       # Strip the b channel from an rgb image to get a two-channel image.
       gray_alpha = simple_color_ramp()[:, :, 0:2]
       image0 = constant_op.constant(gray_alpha, dtype=dtypes.uint16)
@@ -4500,7 +4500,7 @@ class GifTest(test_util.TensorFlowTestCase):
     STRIDE = 5
     shape = (12, HEIGHT, WIDTH, 3)
 
-    with self.cached_session() as sess:
+    with self.cached_session():
       gif0 = io_ops.read_file(prefix + filename)
       image0 = image_ops.decode_gif(gif0)
       gif0, image0 = self.evaluate([gif0, image0])
@@ -4528,7 +4528,7 @@ class GifTest(test_util.TensorFlowTestCase):
   def testShape(self):
     # Shape function requires placeholders and a graph.
     with ops.Graph().as_default():
-      with self.cached_session() as sess:
+      with self.cached_session():
         gif = constant_op.constant("nonsense")
         image = image_ops.decode_gif(gif)
         self.assertEqual(image.get_shape().as_list(), [None, None, None, 3])
@@ -5842,7 +5842,7 @@ class DecodeImageTest(test_util.TensorFlowTestCase, parameterized.TestCase):
   def testJpegUint16(self):
     for horizon in self._FORWARD_COMPATIBILITY_HORIZONS:
       with compat.forward_compatibility_horizon(*horizon):
-        with self.cached_session() as sess:
+        with self.cached_session():
           base = "tensorflow/core/lib/jpeg/testdata"
           jpeg0 = io_ops.read_file(os.path.join(base, "jpeg_merge_test1.jpg"))
           image0 = image_ops.decode_image(jpeg0, dtype=dtypes.uint16)
@@ -5854,7 +5854,7 @@ class DecodeImageTest(test_util.TensorFlowTestCase, parameterized.TestCase):
   def testPngUint16(self):
     for horizon in self._FORWARD_COMPATIBILITY_HORIZONS:
       with compat.forward_compatibility_horizon(*horizon):
-        with self.cached_session() as sess:
+        with self.cached_session():
           base = "tensorflow/core/lib/png/testdata"
           png0 = io_ops.read_file(os.path.join(base, "lena_rgba.png"))
           image0 = image_ops.decode_image(png0, dtype=dtypes.uint16)
@@ -5873,7 +5873,7 @@ class DecodeImageTest(test_util.TensorFlowTestCase, parameterized.TestCase):
   def testGifUint16(self):
     for horizon in self._FORWARD_COMPATIBILITY_HORIZONS:
       with compat.forward_compatibility_horizon(*horizon):
-        with self.cached_session() as sess:
+        with self.cached_session():
           base = "tensorflow/core/lib/gif/testdata"
           gif0 = io_ops.read_file(os.path.join(base, "scan.gif"))
           image0 = image_ops.decode_image(gif0, dtype=dtypes.uint16)
@@ -5885,7 +5885,7 @@ class DecodeImageTest(test_util.TensorFlowTestCase, parameterized.TestCase):
   def testBmpUint16(self):
     for horizon in self._FORWARD_COMPATIBILITY_HORIZONS:
       with compat.forward_compatibility_horizon(*horizon):
-        with self.cached_session() as sess:
+        with self.cached_session():
           base = "tensorflow/core/lib/bmp/testdata"
           bmp0 = io_ops.read_file(os.path.join(base, "lena.bmp"))
           image0 = image_ops.decode_image(bmp0, dtype=dtypes.uint16)
@@ -5897,7 +5897,7 @@ class DecodeImageTest(test_util.TensorFlowTestCase, parameterized.TestCase):
   def testJpegFloat32(self):
     for horizon in self._FORWARD_COMPATIBILITY_HORIZONS:
       with compat.forward_compatibility_horizon(*horizon):
-        with self.cached_session() as sess:
+        with self.cached_session():
           base = "tensorflow/core/lib/jpeg/testdata"
           jpeg0 = io_ops.read_file(os.path.join(base, "jpeg_merge_test1.jpg"))
           image0 = image_ops.decode_image(jpeg0, dtype=dtypes.float32)
@@ -5909,7 +5909,7 @@ class DecodeImageTest(test_util.TensorFlowTestCase, parameterized.TestCase):
   def testPngFloat32(self):
     for horizon in self._FORWARD_COMPATIBILITY_HORIZONS:
       with compat.forward_compatibility_horizon(*horizon):
-        with self.cached_session() as sess:
+        with self.cached_session():
           base = "tensorflow/core/lib/png/testdata"
           png0 = io_ops.read_file(os.path.join(base, "lena_rgba.png"))
           image0 = image_ops.decode_image(png0, dtype=dtypes.float32)
@@ -5921,7 +5921,7 @@ class DecodeImageTest(test_util.TensorFlowTestCase, parameterized.TestCase):
   def testGifFloat32(self):
     for horizon in self._FORWARD_COMPATIBILITY_HORIZONS:
       with compat.forward_compatibility_horizon(*horizon):
-        with self.cached_session() as sess:
+        with self.cached_session():
           base = "tensorflow/core/lib/gif/testdata"
           gif0 = io_ops.read_file(os.path.join(base, "scan.gif"))
           image0 = image_ops.decode_image(gif0, dtype=dtypes.float32)
@@ -5933,7 +5933,7 @@ class DecodeImageTest(test_util.TensorFlowTestCase, parameterized.TestCase):
   def testBmpFloat32(self):
     for horizon in self._FORWARD_COMPATIBILITY_HORIZONS:
       with compat.forward_compatibility_horizon(*horizon):
-        with self.cached_session() as sess:
+        with self.cached_session():
           base = "tensorflow/core/lib/bmp/testdata"
           bmp0 = io_ops.read_file(os.path.join(base, "lena.bmp"))
           image0 = image_ops.decode_image(bmp0, dtype=dtypes.float32)
@@ -5945,7 +5945,7 @@ class DecodeImageTest(test_util.TensorFlowTestCase, parameterized.TestCase):
   def testExpandAnimations(self):
     for horizon in self._FORWARD_COMPATIBILITY_HORIZONS:
       with compat.forward_compatibility_horizon(*horizon):
-        with self.cached_session() as sess:
+        with self.cached_session():
           base = "tensorflow/core/lib/gif/testdata"
           gif0 = io_ops.read_file(os.path.join(base, "scan.gif"))
 

tensorflow/python/ops/nccl_ops_test.py

@@ -76,7 +76,7 @@ class NcclTestCase(test.TestCase):
     for dtype in [np.float16, np.float32, np.int32, np.int64, np.float64]:
       # Create session inside outer loop to test use of
       # same communicator across multiple sessions.
-      with self.test_session() as sess:
+      with self.test_session():
 
         for devices in device_sets:
           shape = (3, 4)