Supersed pylint_allowlist

tensorflow/compiler/tests/binary_ops_test.py

@@ -1091,7 +1091,7 @@ def testBatchMatMul(self):
           math_ops.matmul,
           np.array([], dtype=dtype).reshape((0, 2, 4)),
           np.array([], dtype=dtype).reshape((0, 4, 3)),
-          expected=np.array([], dtype=dtype).reshape(0, 2, 3))
+          expected=np.array([], dtype=dtype).reshape(0, 2, 3))  # pylint: disable=too-many-function-args
 
       # Regression test for b/31472796.
       if dtype != np.float16 and hasattr(np, "matmul"):

tensorflow/compiler/tests/image_ops_test.py

@@ -91,13 +91,13 @@ def testRGBToHSVNumpy(self):
     """Tests the RGB to HSV conversion matches a reference implementation."""
     for nptype in self.float_types:
       rgb_flat = _generate_numpy_random_rgb((64, 3)).astype(nptype)
-      rgb_np = rgb_flat.reshape(4, 4, 4, 3)
+      rgb_np = rgb_flat.reshape(4, 4, 4, 3)  # pylint: disable=too-many-function-args
       hsv_np = np.array([
           colorsys.rgb_to_hsv(
               r.astype(np.float64), g.astype(np.float64), b.astype(np.float64))
           for r, g, b in rgb_flat
       ])
-      hsv_np = hsv_np.reshape(4, 4, 4, 3)
+      hsv_np = hsv_np.reshape(4, 4, 4, 3)  # pylint: disable=too-many-function-args
       with self.session():
         placeholder = array_ops.placeholder(nptype)
         with self.test_scope():

tensorflow/lite/python/interpreter_test.py

@@ -401,7 +401,7 @@ def testBaseProtectsFunctions(self):
       _ = self.interpreter.allocate_tensors()
     # Make sure we get an exception if we try to run an unsafe operation
     with self.assertRaisesRegex(RuntimeError, 'There is at least 1 reference'):
-      _ = self.interpreter.invoke()
+      _ = self.interpreter.invoke()  # pylint: disable=assignment-from-no-return
     # Now test that we can run
     del in0  # this is our only buffer reference, so now it is safe to change
     in0safe = self.interpreter.tensor(self.input0)

tensorflow/python/autograph/converters/directives_test.py

@@ -60,7 +60,7 @@ def test_loop_target(self):
     def f():
       a = True
       while True:
-        directives.set_loop_options(parallel_iterations=10, back_prop=a)
+        directives.set_loop_options(parallel_iterations=10, back_prop=a)  # pylint: disable=unexpected-keyword-arg
         pass
 
     _, node, _ = self.transform(f, directives_converter, include_ast=True)
@@ -86,7 +86,7 @@ def f():
       a = 1
       while True:
         a = 2
-        directives.set_loop_options(parallel_iterations=10, back_prop=a)
+        directives.set_loop_options(parallel_iterations=10, back_prop=a)  # pylint: disable=unexpected-keyword-arg
 
     with self.assertRaisesRegex(ValueError, 'must be the first statement'):
       self.transform(f, directives_converter, include_ast=True)

tensorflow/python/autograph/pyct/static_analysis/annos.py

@@ -26,7 +26,7 @@
 
 class NoValue(Enum):
 
-  def __repr__(self):
+  def __repr__(self):  # pylint: disable=invalid-repr-returned
     return self.name
 
 

tensorflow/python/client/session.py

@@ -1391,7 +1391,7 @@ def _do_call(self, fn, *args):
                     '\nby modifying the config for creating the session eg.'
                     '\nsession_config.graph_options.rewrite_options.'
                     'disable_meta_optimizer = True')
-      raise type(e)(node_def, op, message)
+      raise type(e)(node_def, op, message)  # pylint: disable=no-value-for-parameter
 
   def _extend_graph(self):
     with self._graph._session_run_lock():  # pylint: disable=protected-access

tensorflow/python/compiler/tensorrt/test/base_test.py

@@ -121,7 +121,7 @@ def ExpectedEnginesToBuild(self, run_params):
     }
 
   def setUp(self):
-    super(trt_test.TfTrtIntegrationTestBase, self).setUp()
+    super(trt_test.TfTrtIntegrationTestBase, self).setUp()  # pylint: disable=bad-super-call
     # Disable layout optimizer, since it will convert BiasAdd with NHWC
     # format to NCHW format under four dimentional input.
     self.DisableNonTrtOptimizers()

tensorflow/python/compiler/tensorrt/test/biasadd_matmul_test.py

@@ -107,7 +107,7 @@ def GetParams(self):
                             [[4, 6680]])
 
   def setUp(self):
-    super(trt_test.TfTrtIntegrationTestBase, self).setUp()
+    super(trt_test.TfTrtIntegrationTestBase, self).setUp()  # pylint: disable=bad-super-call
     # Disable layout optimizer, since it will convert BiasAdd with NHWC
     # format to NCHW format under four dimentional input.
     self.DisableNonTrtOptimizers()

tensorflow/python/compiler/tensorrt/test/binary_tensor_weight_broadcast_test.py

@@ -65,7 +65,7 @@ def ExpectedEnginesToBuild(self, run_params):
   # TODO(b/176540862): remove this routine to disallow native segment execution
   # for TensorRT 7+.
   def setUp(self):
-    super(trt_test.TfTrtIntegrationTestBase, self).setUp()
+    super(trt_test.TfTrtIntegrationTestBase, self).setUp()  # pylint: disable=bad-super-call
     if trt_test.IsTensorRTVersionGreaterEqual(7):
       os.environ["TF_TRT_ALLOW_ENGINE_NATIVE_SEGMENT_EXECUTION"] = "True"
 

tensorflow/python/compiler/tensorrt/test/dynamic_input_shapes_test.py

@@ -81,7 +81,7 @@ def GetParams(self):
         expected_output_dims=expected_output_dims)
 
   def setUp(self):
-    super(trt_test.TfTrtIntegrationTestBase, self).setUp()
+    super(trt_test.TfTrtIntegrationTestBase, self).setUp()  # pylint: disable=bad-super-call
     # Disable layout optimizer, since it will convert BiasAdd with NHWC
     # format to NCHW format under four dimentional input.
     self.DisableNonTrtOptimizers()

tensorflow/python/compiler/tensorrt/test/int32_test.py

@@ -47,7 +47,7 @@ def GetParams(self):
     return self.BuildParams(self.GraphFn, dtypes.int32, [[100, 4]], [[100, 10]])
 
   def setUp(self):
-    super(trt_test.TfTrtIntegrationTestBase, self).setUp()
+    super(trt_test.TfTrtIntegrationTestBase, self).setUp()  # pylint: disable=bad-super-call
     # Disable layout optimizer, since it will convert BiasAdd with NHWC
     # format to NCHW format under four dimentional input.
     self.DisableNonTrtOptimizers()

tensorflow/python/compiler/tensorrt/test/testdata/gen_tftrt_model.py

@@ -77,7 +77,7 @@ def run(self, input1, input2):
   root = SimpleModel()
 
   # Saved TF model
-  save(root, tf_saved_model_dir,
+  save(root, tf_saved_model_dir,  # pylint: disable=not-callable
        {signature_constants.DEFAULT_SERVING_SIGNATURE_DEF_KEY: root.run})
 
   # Convert TF model to TensorRT

tensorflow/python/compiler/tensorrt/test/vgg_block_nchw_test.py

@@ -73,7 +73,7 @@ def ExpectedEnginesToBuild(self, run_params):
 
   # TODO(b/159459919): remove this routine to disallow native segment execution.
   def setUp(self):
-    super(trt_test.TfTrtIntegrationTestBase, self).setUp()
+    super(trt_test.TfTrtIntegrationTestBase, self).setUp()  # pylint: disable=bad-super-call
     os.environ["TF_TRT_ALLOW_ENGINE_NATIVE_SEGMENT_EXECUTION"] = "True"
 
 

tensorflow/python/compiler/tensorrt/test/vgg_block_test.py

@@ -64,7 +64,7 @@ def ExpectedEnginesToBuild(self, run_params):
 
   # TODO(b/159459919): remove this routine to disallow native segment execution.
   def setUp(self):
-    super(trt_test.TfTrtIntegrationTestBase, self).setUp()
+    super(trt_test.TfTrtIntegrationTestBase, self).setUp()  # pylint: disable=bad-super-call
     os.environ["TF_TRT_ALLOW_ENGINE_NATIVE_SEGMENT_EXECUTION"] = "True"
 
 

tensorflow/python/data/experimental/kernel_tests/parse_example_dataset_test.py

@@ -397,10 +397,10 @@ def testSerializedContainingDense(self):
 
     expected_output = {
         aname:
-            np.array(
+            np.array(  # pylint: disable=too-many-function-args
                 [[1, 1], [-1, -1]], dtype=np.float32).reshape(2, 1, 2, 1),
         bname:
-            np.array(
+            np.array(  # pylint: disable=too-many-function-args
                 ["b0_str", ""], dtype=bytes).reshape(2, 1, 1, 1, 1),
     }
 
@@ -445,10 +445,10 @@ def testSerializedContainingDenseWithConcat(self):
 
     expected_output = {
         aname:
-            np.array(
+            np.array(  # pylint: disable=too-many-function-args
                 [[1, 1], [-1, -1]], dtype=np.float32).reshape(2, 1, 2, 1),
         bname:
-            np.array(
+            np.array(  # pylint: disable=too-many-function-args
                 ["b0_str", "b1"], dtype=bytes).reshape(2, 1, 1, 1, 1),
     }
 
@@ -506,11 +506,11 @@ def testSerializedContainingDenseWithDefaults(self):
 
     expected_output = {
         "a":
-            np.array(
+            np.array(  # pylint: disable=too-many-function-args
                 [[1, 1], [3, -3], [3, -3]], dtype=np.float32).reshape(3, 1, 2,
                                                                       1),
         "b":
-            np.array(
+            np.array(  # pylint: disable=too-many-function-args
                 ["tmp_str", "b1", "tmp_str"], dtype=bytes).reshape(3, 1, 1, 1,
                                                                    1),
     }
@@ -771,7 +771,7 @@ def testSerializedContainingVarLenDense(self):
 
     expected_output = {
         aname:
-            np.array(
+            np.array(  # pylint: disable=too-many-function-args
                 [
                     [0, 0, 0, 0],
                     [1, 1, 0, 0],
@@ -780,7 +780,7 @@ def testSerializedContainingVarLenDense(self):
                 ],
                 dtype=np.float32).reshape(4, 2, 2, 1),
         bname:
-            np.array(
+            np.array(  # pylint: disable=too-many-function-args
                 [["", ""], ["b0_str", "b1_str"], ["b1", ""], ["", ""]],
                 dtype=bytes).reshape(4, 2, 1, 1, 1),
         cname:
@@ -809,7 +809,7 @@ def testSerializedContainingVarLenDense(self):
 
     # Test with padding values.
     expected_output_custom_padding = dict(expected_output)
-    expected_output_custom_padding[aname] = np.array(
+    expected_output_custom_padding[aname] = np.array(  # pylint: disable=too-many-function-args
         [
             [-2, -2, -2, -2],
             [1, 1, -2, -2],

tensorflow/python/data/experimental/ops/optimization.py

@@ -31,7 +31,7 @@ def model():
 
   def _apply_fn(dataset):
     """Function from `Dataset` to `Dataset` that applies the transformation."""
-    return dataset_ops._ModelDataset(dataset)  # pylint: disable=protected-access
+    return dataset_ops._ModelDataset(dataset)  # pylint: disable=protected-access  # pylint: disable=no-value-for-parameter
 
   return _apply_fn
 

tensorflow/python/debug/lib/grpc_debug_server.py

@@ -391,7 +391,7 @@ def stop_server(self, grace=1.0):
     finally:
       self._server_lock.release()
 
-  def request_watch(self, node_name, output_slot, debug_op, breakpoint=False):
+  def request_watch(self, node_name, output_slot, debug_op, breakpoint=False):  # pylint: disable=redefined-builtin
     """Request enabling a debug tensor watchpoint or breakpoint.
 
     This will let the server send a EventReply to the client side

tensorflow/python/distribute/combinations_test.py

@@ -39,7 +39,7 @@ class ClusterCombinationTest(test.TestCase, parameterized.TestCase):
   # Note that we don't have a standalone combination for ClusterParameters, so
   # we should use GPUCombination which contains it.
 
-  @framework_combinations.generate(
+  @framework_combinations.generate(  # pylint: disable=redundant-keyword-arg
       framework_combinations.combine(distribution=[
           combinations.NamedDistribution(
               "HasClusterParams", lambda: None, has_chief=True, num_workers=2),
@@ -49,7 +49,7 @@ def testClusterParams(self, distribution, has_chief, num_workers):
     self.assertTrue(has_chief)
     self.assertEqual(num_workers, 2)
 
-  @framework_combinations.generate(
+  @framework_combinations.generate(  # pylint: disable=redundant-keyword-arg
       framework_combinations.combine(distribution=[
           combinations.NamedDistribution("NoClusterParams", lambda: None),
       ]),
@@ -58,14 +58,14 @@ def testClusterParamsHasDefault(self, distribution, has_chief, num_workers):
     self.assertFalse(has_chief)
     self.assertEqual(num_workers, 1)
 
-  @framework_combinations.generate(
+  @framework_combinations.generate(  # pylint: disable=redundant-keyword-arg
       framework_combinations.combine(v=1),
       test_combinations=(combinations.ClusterCombination(),))
   def testClusterParamsNoStrategy(self, v, has_chief, num_workers):
     self.assertFalse(has_chief)
     self.assertEqual(num_workers, 1)
 
-  @framework_combinations.generate(
+  @framework_combinations.generate(  # pylint: disable=redundant-keyword-arg
       framework_combinations.combine(distribution=[
           combinations.NamedDistribution(
               "WithClusterParams", lambda: None, has_chief=True, num_workers=2),
@@ -76,7 +76,7 @@ def testClusterParamsAreOptional(self, distribution):
     # If combinations library doesn't raise an exception, the test is passed.
     pass
 
-  @framework_combinations.generate(
+  @framework_combinations.generate(  # pylint: disable=redundant-keyword-arg
       framework_combinations.combine(
           ds1=combinations.NamedDistribution(
               "Strategy1", lambda: None, has_chief=True, num_workers=0),
@@ -121,7 +121,7 @@ def testUpdateEnvInWorker(self):
 @unittest.expectedFailure
 class ClusterParametersShouldFailTest(test.TestCase, parameterized.TestCase):
 
-  @framework_combinations.generate(
+  @framework_combinations.generate(  # pylint: disable=redundant-keyword-arg
       framework_combinations.combine(
           ds1=combinations.NamedDistribution(
               "Strategy1", lambda: None, has_chief=True, num_workers=2),

tensorflow/python/distribute/parameter_server_strategy_test.py

@@ -785,7 +785,7 @@ def test_prefetch_to_device_dataset(self, prefetch_to_device):
           experimental_fetch_to_device=prefetch_to_device)
     dataset = dataset_ops.Dataset.range(100)
     dataset = dataset.batch(distribution.num_replicas_in_sync)
-    dataset = distribution.experimental_distribute_dataset(
+    dataset = distribution.experimental_distribute_dataset(  # pylint: disable=assignment-from-no-return
         dataset, options=input_options)
     if isinstance(dataset, input_lib.DistributedDatasetV1):
       item = dataset.make_initializable_iterator().get_next()
@@ -807,7 +807,7 @@ def test_prefetch_to_host_dataset(self):
         experimental_fetch_to_device=False)
     dataset = dataset_ops.Dataset.range(100)
     dataset = dataset.batch(distribution.num_replicas_in_sync)
-    dataset = distribution.experimental_distribute_dataset(
+    dataset = distribution.experimental_distribute_dataset(  # pylint: disable=assignment-from-no-return
         dataset, options=input_options)
     if isinstance(dataset, input_lib.DistributedDatasetV1):
       item = dataset.make_initializable_iterator().get_next()

tensorflow/python/distribute/strategy_test_lib.py

@@ -751,7 +751,7 @@ def _testDeviceScope(self, distribution):
 
   def _testMakeInputFnIteratorWithDataset(self, distribution):
     dataset_fn = lambda: dataset_ops.Dataset.range(100)
-    num_gpus = self._get_num_gpus()
+    num_gpus = self._get_num_gpus()  # pylint: disable=assignment-from-no-return
     num_workers = 1
 
     expected_values = [[i+j for j in range(num_gpus)] * num_workers
@@ -775,7 +775,7 @@ def fn():
       dataset = dataset_ops.Dataset.range(100)
       it = dataset_ops.make_one_shot_iterator(dataset)
       return it.get_next
-    num_gpus = self._get_num_gpus()
+    num_gpus = self._get_num_gpus()  # pylint: disable=assignment-from-no-return
     num_workers = 1
 
     expected_values = []

tensorflow/python/eager/pywrap_tfe_test.py

@@ -297,7 +297,7 @@ def testGraphResourceVariableRaisesFallback(self):
                                         False)
 
   def testOpDefDefaultType(self):
-    im = np.random.randint(
+    im = np.random.randint(  # pylint: disable=too-many-function-args
         low=0, high=65535, size=100, dtype=np.uint16).reshape(10, 10, 1)
 
     context.ensure_initialized()

tensorflow/python/eager/tensor_test.py

@@ -488,9 +488,9 @@ def testUnicode(self):
     self.assertEqual(constant_op.constant(u"asdf").numpy(), b"asdf")
 
   def testFloatTensor(self):
-    self.assertEqual(dtypes.float64, _create_tensor(np.float64()).dtype)
-    self.assertEqual(dtypes.float32, _create_tensor(np.float32()).dtype)
-    self.assertEqual(dtypes.float16, _create_tensor(np.float16()).dtype)
+    self.assertEqual(dtypes.float64, _create_tensor(np.float64()).dtype)  # pylint: disable=no-value-for-parameter
+    self.assertEqual(dtypes.float32, _create_tensor(np.float32()).dtype)  # pylint: disable=no-value-for-parameter
+    self.assertEqual(dtypes.float16, _create_tensor(np.float16()).dtype)  # pylint: disable=no-value-for-parameter
     self.assertEqual(dtypes.float32, _create_tensor(0.0).dtype)
 
   def testSliceDimOutOfRange(self):

tensorflow/python/feature_column/feature_column_test.py

@@ -3259,14 +3259,14 @@ def test_invalid_type(self):
         ValueError,
         'All feature_columns must be _FeatureColumn instances.*invalid_column'):
       fc.make_parse_example_spec(
-          (self._TestFeatureColumn({key1: parse_spec1}), 'invalid_column'))
+          (self._TestFeatureColumn({key1: parse_spec1}), 'invalid_column'))  # pylint: disable=abstract-class-instantiated
 
   def test_one_feature_column(self):
     key1 = 'key1'
     parse_spec1 = parsing_ops.FixedLenFeature(
         shape=(2,), dtype=dtypes.float32, default_value=0.)
     actual = fc.make_parse_example_spec(
-        (self._TestFeatureColumn({key1: parse_spec1}),))
+        (self._TestFeatureColumn({key1: parse_spec1}),))  # pylint: disable=abstract-class-instantiated
     self.assertDictEqual({key1: parse_spec1}, actual)
 
   def test_two_feature_columns(self):
@@ -3276,8 +3276,8 @@ def test_two_feature_columns(self):
     key2 = 'key2'
     parse_spec2 = parsing_ops.VarLenFeature(dtype=dtypes.string)
     actual = fc.make_parse_example_spec(
-        (self._TestFeatureColumn({key1: parse_spec1}),
-         self._TestFeatureColumn({key2: parse_spec2})))
+        (self._TestFeatureColumn({key1: parse_spec1}),  # pylint: disable=abstract-class-instantiated
+         self._TestFeatureColumn({key2: parse_spec2})))  # pylint: disable=abstract-class-instantiated
     self.assertDictEqual({key1: parse_spec1, key2: parse_spec2}, actual)
 
   def test_equal_keys_different_parse_spec(self):
@@ -3289,16 +3289,16 @@ def test_equal_keys_different_parse_spec(self):
         ValueError,
         'feature_columns contain different parse_spec for key key1'):
       fc.make_parse_example_spec(
-          (self._TestFeatureColumn({key1: parse_spec1}),
-           self._TestFeatureColumn({key1: parse_spec2})))
+          (self._TestFeatureColumn({key1: parse_spec1}),  # pylint: disable=abstract-class-instantiated
+           self._TestFeatureColumn({key1: parse_spec2})))  # pylint: disable=abstract-class-instantiated
 
   def test_equal_keys_equal_parse_spec(self):
     key1 = 'key1'
     parse_spec1 = parsing_ops.FixedLenFeature(
         shape=(2,), dtype=dtypes.float32, default_value=0.)
     actual = fc.make_parse_example_spec(
-        (self._TestFeatureColumn({key1: parse_spec1}),
-         self._TestFeatureColumn({key1: parse_spec1})))
+        (self._TestFeatureColumn({key1: parse_spec1}),  # pylint: disable=abstract-class-instantiated
+         self._TestFeatureColumn({key1: parse_spec1})))  # pylint: disable=abstract-class-instantiated
     self.assertDictEqual({key1: parse_spec1}, actual)
 
   def test_multiple_features_dict(self):
@@ -3311,8 +3311,8 @@ def test_multiple_features_dict(self):
     key3 = 'key3'
     parse_spec3 = parsing_ops.VarLenFeature(dtype=dtypes.int32)
     actual = fc.make_parse_example_spec(
-        (self._TestFeatureColumn({key1: parse_spec1}),
-         self._TestFeatureColumn({key2: parse_spec2, key3: parse_spec3})))
+        (self._TestFeatureColumn({key1: parse_spec1}),  # pylint: disable=abstract-class-instantiated
+         self._TestFeatureColumn({key2: parse_spec2, key3: parse_spec3})))  # pylint: disable=abstract-class-instantiated
     self.assertDictEqual(
         {key1: parse_spec1, key2: parse_spec2, key3: parse_spec3}, actual)