UFMT formatting on test/autograd test/ao test/cpp test/backends (#123369)

Partially addresses #123062

Ran lintrunner on
- test/_test_bazel.py
- test/ao
- test/autograd test/backends test/benchmark_uitls test/conftest.py test/bottleneck_test test/cpp

Pull Request resolved: https://github.com/pytorch/pytorch/pull/123369
Approved by: https://github.com/huydhn

test/cpp/jit/tests_setup.py

@@ -1,5 +1,6 @@
-import sys
 import os
+import sys
+
 import torch
 
 
@@ -21,7 +22,7 @@ class FileSetup:
 
 
 class EvalModeForLoadedModule(FileSetup):
-    path = 'dropout_model.pt'
+    path = "dropout_model.pt"
 
     def setup(self):
         class Model(torch.jit.ScriptModule):
@@ -40,7 +41,7 @@ class EvalModeForLoadedModule(FileSetup):
 
 
 class SerializationInterop(FileSetup):
-    path = 'ivalue.pt'
+    path = "ivalue.pt"
 
     def setup(self):
         ones = torch.ones(2, 2)
@@ -53,7 +54,7 @@ class SerializationInterop(FileSetup):
 
 # See testTorchSaveError in test/cpp/jit/tests.h for usage
 class TorchSaveError(FileSetup):
-    path = 'eager_value.pt'
+    path = "eager_value.pt"
 
     def setup(self):
         ones = torch.ones(2, 2)
@@ -63,8 +64,9 @@ class TorchSaveError(FileSetup):
 
         torch.save(value, self.path, _use_new_zipfile_serialization=False)
 
+
 class TorchSaveJitStream_CUDA(FileSetup):
-    path = 'saved_stream_model.pt'
+    path = "saved_stream_model.pt"
 
     def setup(self):
         if not torch.cuda.is_available():
@@ -77,7 +79,9 @@ class TorchSaveJitStream_CUDA(FileSetup):
                 b = torch.rand(3, 4, device="cuda")
 
                 with torch.cuda.stream(s):
-                    is_stream_s = torch.cuda.current_stream(s.device_index()).id() == s.id()
+                    is_stream_s = (
+                        torch.cuda.current_stream(s.device_index()).id() == s.id()
+                    )
                     c = torch.cat((a, b), 0).to("cuda")
                 s.synchronize()
                 return is_stream_s, a, b, c
@@ -93,9 +97,10 @@ tests = [
     EvalModeForLoadedModule(),
     SerializationInterop(),
     TorchSaveError(),
-    TorchSaveJitStream_CUDA()
+    TorchSaveJitStream_CUDA(),
 ]
 
+
 def setup():
     for test in tests:
         test.setup()