Enable UFMT on test_decomp.py, test_expanded_weights.py and some files

.lintrunner.toml

@@ -1052,12 +1052,6 @@ exclude_patterns = [
     'test/quantization/fx/test_quantize_fx.py',
     'test/quantization/fx/test_subgraph_rewriter.py',
     'test/test_datapipe.py',
-    'test/test_decomp.py',
-    'test/test_deploy.py',
-    'test/test_determination.py',
-    'test/test_dlpack.py',
-    'test/test_dynamic_shapes.py',
-    'test/test_expanded_weights.py',
     'test/test_fake_tensor.py',
     'test/test_flop_counter.py',
     'test/test_function_schema.py',

test/test_deploy.py

@@ -3,9 +3,10 @@
 import textwrap
 import types
 
-from torch.utils._freeze import Freezer, PATH_MARKER
 from torch.testing._internal.common_utils import run_tests, TestCase
 
+from torch.utils._freeze import Freezer, PATH_MARKER
+
 
 class TestFreezer(TestCase):
     """Tests the freeze.py script"""

test/test_determination.py

@@ -3,7 +3,7 @@
 import os
 
 import run_test
-from torch.testing._internal.common_utils import TestCase, run_tests
+from torch.testing._internal.common_utils import run_tests, TestCase
 
 
 class DummyOptions:
@@ -30,7 +30,9 @@ def determined_tests(cls, changed_files):
         return [
             test
             for test in cls.TESTS
-            if run_test.should_run_test(run_test.TARGET_DET_LIST, test, changed_files, DummyOptions())
+            if run_test.should_run_test(
+                run_test.TARGET_DET_LIST, test, changed_files, DummyOptions()
+            )
         ]
 
     def test_target_det_list_is_sorted(self):
@@ -42,9 +44,7 @@ def test_target_det_list_is_sorted(self):
 
     def test_config_change_only(self):
         """CI configs trigger all tests"""
-        self.assertEqual(
-            self.determined_tests([".ci/pytorch/test.sh"]), self.TESTS
-        )
+        self.assertEqual(self.determined_tests([".ci/pytorch/test.sh"]), self.TESTS)
 
     def test_run_test(self):
         """run_test.py is imported by determination tests"""
@@ -68,14 +68,17 @@ def test_cpp_file(self):
     def test_test_file(self):
         """Test files trigger themselves and dependent tests"""
         self.assertEqual(
-            self.determined_tests(["test/test_jit.py"]), ["test_jit_profiling", "test_jit"]
+            self.determined_tests(["test/test_jit.py"]),
+            ["test_jit_profiling", "test_jit"],
         )
         self.assertEqual(
             self.determined_tests(["test/jit/test_custom_operators.py"]),
             ["test_jit_profiling", "test_jit"],
         )
         self.assertEqual(
-            self.determined_tests(["test/quantization/eager/test_quantize_eager_ptq.py"]),
+            self.determined_tests(
+                ["test/quantization/eager/test_quantize_eager_ptq.py"]
+            ),
             ["test_quantization"],
         )
 

test/test_dlpack.py

@@ -2,11 +2,16 @@
 
 import torch
 from torch.testing import make_tensor
-from torch.testing._internal.common_utils import TestCase, run_tests, IS_JETSON
 from torch.testing._internal.common_device_type import (
-    instantiate_device_type_tests, onlyCUDA, dtypes, skipMeta, skipCUDAIfRocm,
-    onlyNativeDeviceTypes)
+    dtypes,
+    instantiate_device_type_tests,
+    onlyCUDA,
+    onlyNativeDeviceTypes,
+    skipCUDAIfRocm,
+    skipMeta,
+)
 from torch.testing._internal.common_dtype import all_types_and_complex_and
+from torch.testing._internal.common_utils import IS_JETSON, run_tests, TestCase
 from torch.utils.dlpack import from_dlpack, to_dlpack
 
 
@@ -15,15 +20,33 @@ class TestTorchDlPack(TestCase):
 
     @skipMeta
     @onlyNativeDeviceTypes
-    @dtypes(*all_types_and_complex_and(torch.half, torch.bfloat16, torch.bool, torch.uint16, torch.uint32, torch.uint64))
+    @dtypes(
+        *all_types_and_complex_and(
+            torch.half,
+            torch.bfloat16,
+            torch.bool,
+            torch.uint16,
+            torch.uint32,
+            torch.uint64,
+        )
+    )
     def test_dlpack_capsule_conversion(self, device, dtype):
         x = make_tensor((5,), dtype=dtype, device=device)
         z = from_dlpack(to_dlpack(x))
         self.assertEqual(z, x)
 
     @skipMeta
     @onlyNativeDeviceTypes
-    @dtypes(*all_types_and_complex_and(torch.half, torch.bfloat16, torch.bool, torch.uint16, torch.uint32, torch.uint64))
+    @dtypes(
+        *all_types_and_complex_and(
+            torch.half,
+            torch.bfloat16,
+            torch.bool,
+            torch.uint16,
+            torch.uint32,
+            torch.uint64,
+        )
+    )
     def test_dlpack_protocol_conversion(self, device, dtype):
         x = make_tensor((5,), dtype=dtype, device=device)
         z = from_dlpack(x)
@@ -62,15 +85,33 @@ def test_dlpack_conversion_with_streams(self, device, dtype):
 
     @skipMeta
     @onlyNativeDeviceTypes
-    @dtypes(*all_types_and_complex_and(torch.half, torch.bfloat16, torch.bool, torch.uint16, torch.uint32, torch.uint64))
+    @dtypes(
+        *all_types_and_complex_and(
+            torch.half,
+            torch.bfloat16,
+            torch.bool,
+            torch.uint16,
+            torch.uint32,
+            torch.uint64,
+        )
+    )
     def test_from_dlpack(self, device, dtype):
         x = make_tensor((5,), dtype=dtype, device=device)
         y = torch.from_dlpack(x)
         self.assertEqual(x, y)
 
     @skipMeta
     @onlyNativeDeviceTypes
-    @dtypes(*all_types_and_complex_and(torch.half, torch.bfloat16, torch.bool, torch.uint16, torch.uint32, torch.uint64))
+    @dtypes(
+        *all_types_and_complex_and(
+            torch.half,
+            torch.bfloat16,
+            torch.bool,
+            torch.uint16,
+            torch.uint32,
+            torch.uint64,
+        )
+    )
     def test_from_dlpack_noncontinguous(self, device, dtype):
         x = make_tensor((25,), dtype=dtype, device=device).reshape(5, 5)
 
@@ -113,7 +154,16 @@ def test_dlpack_conversion_with_diff_streams(self, device, dtype):
 
     @skipMeta
     @onlyNativeDeviceTypes
-    @dtypes(*all_types_and_complex_and(torch.half, torch.bfloat16, torch.bool, torch.uint16, torch.uint32, torch.uint64))
+    @dtypes(
+        *all_types_and_complex_and(
+            torch.half,
+            torch.bfloat16,
+            torch.bool,
+            torch.uint16,
+            torch.uint32,
+            torch.uint64,
+        )
+    )
     def test_from_dlpack_dtype(self, device, dtype):
         x = make_tensor((5,), dtype=dtype, device=device)
         y = torch.from_dlpack(x)
@@ -204,5 +254,5 @@ def test_dlpack_normalize_strides(self):
 
 instantiate_device_type_tests(TestTorchDlPack, globals())
 
-if __name__ == '__main__':
+if __name__ == "__main__":
     run_tests()