Annotate some functions that return None

Summary: Test functions return None. This codemod fixes that so type annotation efforts can focus on trickier cases.

Reviewed By: azad-meta

Differential Revision: D52570249

fbshipit-source-id: 6ea7be3e707ce5dfdf5a900e959459deebe1eff6

test/test_serialization.py

@@ -97,13 +97,13 @@ def _convert_to_tensor(data):
 
 
 class TestIterDataPipeSerialization(expecttest.TestCase):
-    def setUp(self):
+    def setUp(self) -> None:
         self.temp_dir = create_temp_dir()
         self.temp_files = create_temp_files(self.temp_dir)
         self.temp_sub_dir = create_temp_dir(self.temp_dir.name)
         self.temp_sub_files = create_temp_files(self.temp_sub_dir, 4, False)
 
-    def tearDown(self):
+    def tearDown(self) -> None:
         try:
             self.temp_sub_dir.cleanup()
             self.temp_dir.cleanup()
@@ -168,7 +168,7 @@ def _serialization_test_for_dp_with_children(self, dp1, dp2, use_dill):
         self._serialization_test_helper(dp1, use_dill=use_dill)
         self._serialization_test_helper(dp2, use_dill=use_dill)
 
-    def test_serializable(self):
+    def test_serializable(self) -> None:
         # A tuple of 4 objects
         # (DataPipeConstructor, custom_input_datapipe=None, dp_args=(), dp_kwargs={})
         picklable_datapipes: List = [
@@ -355,7 +355,7 @@ def test_serializable(self):
                 print(f"{dpipe} is failing.")
                 raise e
 
-    def test_serializable_with_dill(self):
+    def test_serializable_with_dill(self) -> None:
         """Only for DataPipes that take in a function as argument"""
         input_dp = IterableWrapper(range(10))
         ref_idp = IterableWrapper(range(10))
@@ -416,7 +416,7 @@ def _serialization_test_for_dp_with_children(self, dp1, dp2):
         self._serialization_test_helper(dp1)
         self._serialization_test_helper(dp2)
 
-    def test_serializable(self):
+    def test_serializable(self) -> None:
         picklable_datapipes: List = [
             (mapdp.InMemoryCacheHolder, None, (), {}),
             (mapdp.IterToMapConverter, IterableWrapper([(i, i) for i in range(10)]), (), {}),
@@ -447,7 +447,7 @@ def test_serializable(self):
                 print(f"{dpipe} is failing.")
                 raise e
 
-    def test_serializable_with_dill(self):
+    def test_serializable_with_dill(self) -> None:
         """Only for DataPipes that take in a function as argument"""
         pass
 

test/test_tfrecord.py

@@ -35,7 +35,7 @@
 
 
 class TestDataPipeTFRecord(expecttest.TestCase):
-    def setUp(self):
+    def setUp(self) -> None:
         self.temp_dir = os.path.join(os.path.dirname(os.path.abspath(__file__)), "_fakedata", "tfrecord")
 
     def assertArrayEqual(self, arr1, arr2):
@@ -45,7 +45,7 @@ def assertArrayEqual(self, arr1, arr2):
             arr2 = torch.stack(arr2)
         torch.testing.assert_close(arr1, arr2, check_dtype=False)
 
-    def _ground_truth_data(self):
+    def _ground_truth_data(self) -> None:
         for i in range(4):
             x = torch.arange(i * 10, (i + 1) * 10)
             yield {
@@ -54,7 +54,7 @@ def _ground_truth_data(self):
                 "x_byte": [b"test str"],
             }
 
-    def _ground_truth_seq_data(self):
+    def _ground_truth_seq_data(self) -> None:
         for i in range(4):
             x = torch.arange(i * 10, (i + 1) * 10)
             rep = 2 * i + 3
@@ -69,7 +69,7 @@ def _ground_truth_seq_data(self):
         IS_M1, "Protobuf 3.19.* is not supported on MacOS M1, but Tensorflow is incompatible with Protobuf 4"
     )
     @torch.no_grad()
-    def test_tfrecord_loader_example_iterdatapipe(self):
+    def test_tfrecord_loader_example_iterdatapipe(self) -> None:
         filename = f"{self.temp_dir}/example.tfrecord"
         datapipe1 = IterableWrapper([filename])
         datapipe2 = FileOpener(datapipe1, mode="b")
@@ -168,7 +168,7 @@ def test_tfrecord_loader_example_iterdatapipe(self):
         IS_M1, "Protobuf 3.19.* is not supported on MacOS M1, but Tensorflow is incompatible with Protobuf 4"
     )
     @torch.no_grad()
-    def test_tfrecord_loader_sequence_example_iterdatapipe(self):
+    def test_tfrecord_loader_sequence_example_iterdatapipe(self) -> None:
         filename = f"{self.temp_dir}/sequence_example.tfrecord"
         datapipe1 = IterableWrapper([filename])
         datapipe2 = FileOpener(datapipe1, mode="b")