[BE] enable ruff rule RSE and remove useless parentheses in `rais…

…e` statements (pytorch#124261)

Remove useless parentheses in `raise` statements if the exception type is raised with no argument.

Pull Request resolved: pytorch#124261
Approved by: https://github.com/albanD

benchmarks/dynamo/common.py

@@ -1858,7 +1858,7 @@ class TimeOutException(Exception):
 
 
 def alarm_handler(signum, frame):
-    raise TimeOutException()
+    raise TimeOutException
 
 
 def exit_after(s):
@@ -2136,7 +2136,7 @@ def skip_models_due_to_control_flow(self):
         return set()
 
     def get_tolerance_and_cosine_flag(self, is_training, current_device, name):
-        raise NotImplementedError()
+        raise NotImplementedError
 
     @property
     def equal_nan(self):

benchmarks/dynamo/microbenchmarks/operator_inp_utils.py

@@ -80,7 +80,7 @@ def serialize_sparse_tensor(e):
 
 
 def deserialize_sparse_tensor(size, dtype, layout, is_coalesced, nnz=None):
-    raise NotImplementedError()
+    raise NotImplementedError
 
 
 def deserialize_tensor(size, dtype, stride=None):

pyproject.toml

@@ -126,6 +126,7 @@ select = [
     "PT025",
     "PT026",
     "PYI",
+    "RSE",
     "RUF008", # mutable dataclass default
     "RUF015", # access first ele in constant time
     "RUF016", # type error non-integer index

scripts/release_notes/commitlist.py

@@ -578,7 +578,7 @@ def main():
             with open(filename, "w") as f:
                 f.writelines(lines)
         return
-    raise AssertionError()
+    raise AssertionError
 
 
 if __name__ == "__main__":

test/cpp/jit/tests_setup.py

@@ -6,10 +6,10 @@
 
 class Setup:
     def setup(self):
-        raise NotImplementedError()
+        raise NotImplementedError
 
     def shutdown(self):
-        raise NotImplementedError()
+        raise NotImplementedError
 
 
 class FileSetup:

test/distributed/checkpoint/e2e/test_fsdp_ep.py

@@ -21,7 +21,7 @@ def __init__(self):
         super().__init__()
 
     def forward(self, x):
-        raise NotImplementedError()
+        raise NotImplementedError
 
 
 class EPModel(nn.Module):
@@ -31,7 +31,7 @@ def __init__(self, rank):
         self.net2 = nn.Sequential(nn.Linear(16, 16), nn.ReLU())
 
     def forward(self, x):
-        raise NotImplementedError()
+        raise NotImplementedError
 
 
 class SecondTier(nn.Module):
@@ -43,7 +43,7 @@ def __init__(self, rank):
         self.net = nn.Sequential(nn.Linear(16, 16), nn.ReLU())
 
     def forward(self, x):
-        raise NotImplementedError()
+        raise NotImplementedError
 
 
 class TopModel(nn.Module):
@@ -55,7 +55,7 @@ def __init__(self, rank):
         self.net = nn.Sequential(nn.Linear(16, 16), nn.ReLU())
 
     def forward(self, x):
-        raise NotImplementedError()
+        raise NotImplementedError
 
 
 class TestFSDPWithEP(DTensorTestBase, VerifyStateDictMixin):

test/distributed/elastic/metrics/api_test.py

@@ -34,7 +34,7 @@ def emit(self, metric_data: MetricData):
 class Parent(abc.ABC):
     @abc.abstractmethod
     def func(self):
-        raise NotImplementedError()
+        raise NotImplementedError
 
     def base_func(self):
         self.func()
@@ -57,7 +57,7 @@ def bar(self):
 
     @prof
     def throw(self):
-        raise RuntimeError()
+        raise RuntimeError
 
     @prof(group="torchelastic")
     def bar2(self):

test/distributed/elastic/rendezvous/api_test.py

@@ -197,7 +197,7 @@ def get_backend(self) -> str:
         return "dummy_backend"
 
     def next_rendezvous(self) -> Tuple[Store, int, int]:
-        raise NotImplementedError()
+        raise NotImplementedError
 
     def is_closed(self) -> bool:
         return False

test/distributed/elastic/utils/distributed_test.py

@@ -38,7 +38,7 @@ def _create_c10d_store_mp(is_server, server_addr, port, world_size, wait_for_wor
         timeout=2,
     )
     if store is None:
-        raise AssertionError()
+        raise AssertionError
 
     store.set(f"test_key/{os.getpid()}", b"test_value")
 

test/distributed/fsdp/test_fsdp_optim_state.py

@@ -363,7 +363,7 @@ def _init_transformer_model(
             # these settings are not implemented since the transformer is
             # wrapped with FSDP at the top-level, which means that there is
             # only a single flat parameter, making these booleans vacuous
-            raise NotImplementedError()
+            raise NotImplementedError
         if group is None:
             group = dist.distributed_c10d._get_default_group()
         model = TransformerWithSharedParams.init(

test/distributed/pipeline/sync/test_bugs.py

@@ -63,7 +63,7 @@ def forward(self, x):
 
     class Raise(nn.Module):
         def forward(self, x):
-            raise ExpectedException()
+            raise ExpectedException
 
     model = nn.Sequential(Pass(), Pass(), Raise())
     model = Pipe(model, chunks=3)

test/distributed/pipeline/sync/test_pipe.py

@@ -231,7 +231,7 @@ class ExpectedException(Exception):
 
     class Raise(nn.Module):
         def forward(self, *_):
-            raise ExpectedException()
+            raise ExpectedException
 
     model = nn.Sequential(Raise())
     model = Pipe(model, chunks=1)
@@ -265,7 +265,7 @@ def forward(self, x):
 
     class Raise(nn.Module):
         def forward(self, x):
-            raise ExpectedException()
+            raise ExpectedException
 
     model = nn.Sequential(Pass(), Pass(), Counter(), Raise())
     model = Pipe(model, chunks=3)

test/dynamo/test_autograd_function.py

@@ -752,7 +752,7 @@ def __torch_dispatch__(cls, func, types, args, kwargs=None):
                     new_data = args[0]._data.view(*args[1:])
                     return FooTensor(new_data, args[0]._config, args[0]._scale)
 
-                raise NotImplementedError()
+                raise NotImplementedError
 
         class foo_autograd_fn(torch.autograd.Function):
             @staticmethod

test/dynamo/test_exc.py

@@ -47,7 +47,7 @@ def fn001(x):
     def test_internal_error_suppress_errors(self, records):
         def fn001(x):
             def f(ctx):
-                raise AssertionError()
+                raise AssertionError
 
             comptime(f)
 
@@ -62,7 +62,7 @@ def f(ctx):
 ========== TorchDynamo Stack Trace ==========
 Traceback (most recent call last):
   File "test_exc.py", line N, in f
-    raise AssertionError()
+    raise AssertionError
 AssertionError:
 
 from user code:
@@ -84,7 +84,7 @@ def f(ctx):
     def test_not_implemented_error(self, records):
         def fn001(x):
             def f(ctx):
-                raise NotImplementedError()
+                raise NotImplementedError
 
             # Ensure graph break is not possible
             for i in range(3):
@@ -101,7 +101,7 @@ def f(ctx):
 due to:
 Traceback (most recent call last):
   File "test_exc.py", line N, in f
-    raise NotImplementedError()
+    raise NotImplementedError
 torch._dynamo.exc.InternalTorchDynamoError:
 
 from user code:
@@ -128,7 +128,7 @@ def fn001(x):
             # NB: avoid decorator, as 3.11 changed the line number attributed
             # in this situation
             def f(ctx):
-                raise AssertionError()
+                raise AssertionError
 
             comptime(f)
 

test/dynamo/test_logging.py

@@ -164,7 +164,7 @@ def test_inductor_error(self, records):
         import torch._inductor.lowering
 
         def throw(x):
-            raise AssertionError()
+            raise AssertionError
 
         # inject an error in the lowerings
         dict_entries = {}
@@ -189,7 +189,7 @@ def throw(x):
 due to:
 Traceback (most recent call last):
   File "test_logging.py", line N, in throw
-    raise AssertionError()
+    raise AssertionError
 torch._dynamo.exc.BackendCompilerFailed: backend='inductor' raised:
 LoweringException: AssertionError:
   target: aten.round.default

test/dynamo/test_repros.py

@@ -396,12 +396,12 @@ def __next__(self) -> Any:
             if self.resolve:
                 x = x._dereference_node()
                 if x._is_missing():
-                    raise AssertionError()
+                    raise AssertionError
 
             self.index = self.index + 1
             if isinstance(x, ListConfig.ValueNode):
                 return x._value()
-            raise AssertionError()
+            raise AssertionError
 
     def __iter__(self):
         return self._iter_ex(True)
@@ -410,7 +410,7 @@ def _iter_ex(self, resolve: bool) -> Iterator[Any]:
         try:
             return ListConfig.ListIterator(self, resolve)
         except Exception:
-            raise AssertionError()
+            raise AssertionError
 
     def __init__(self):
         self._content = [
@@ -545,7 +545,7 @@ def apply_chunking_to_forward(forward_fn, *input_tensors):
     assert all(input_tensor.shape[1] == tensor_shape for input_tensor in input_tensors)
     num_args_in_forward_chunk_fn = len(inspect.signature(forward_fn).parameters)
     if num_args_in_forward_chunk_fn != len(input_tensors):
-        raise ValueError()
+        raise ValueError
 
     return forward_fn(*input_tensors)
 
@@ -848,7 +848,7 @@ def _merge_criteria_processor_list(default_list, custom_list):
     for default in default_list:
         for custom in custom_list:
             if type(custom) is type(default):
-                raise ValueError()
+                raise ValueError
     default_list.extend(custom_list)
     return default_list
 
@@ -2573,7 +2573,7 @@ def __next__(self):
                 if self.i < 3:
                     self.i += 1
                     return self.i
-                raise StopIteration()
+                raise StopIteration
 
         @torch.compile(backend="eager", fullgraph=True)
         def fn(x):

test/dynamo/test_skip_non_tensor.py

@@ -147,10 +147,10 @@ def fn(x):
 
         class Foo(list):
             def __iter__(self):
-                raise Exception()
+                raise Exception
 
             def __len__(self):
-                raise Exception()
+                raise Exception
 
         x = Foo()
         x.append(torch.randn(4))

test/dynamo/test_structured_trace.py

@@ -233,7 +233,7 @@ def test_inductor_error(self):
         import torch._inductor.lowering
 
         def throw(x):
-            raise AssertionError()
+            raise AssertionError
 
         # inject an error in the lowerings
         dict_entries = {}

test/functorch/discover_coverage.py

@@ -732,12 +732,12 @@ def no_opinfos_skip_test(self, test_name):
 
     def any_opinfo_attr(self, attr):
         if not self.has_opinfo():
-            raise RuntimeError()
+            raise RuntimeError
         return any(getattr(opinfo, attr) for opinfo in self.opinfos)
 
     def all_opinfo_attr(self, attr):
         if not self.has_opinfo():
-            raise RuntimeError()
+            raise RuntimeError
         return all(getattr(opinfo, attr) for opinfo in self.opinfos)
 
     def supports_vjp(self):
@@ -870,7 +870,7 @@ def all(cls):
             elif n.startswith(torch_dot):
                 names_sanitized.append(n[len(torch_dot) :])
             else:
-                raise AssertionError()
+                raise AssertionError
         return cls.from_names(names_sanitized)
 
     def query(self, operator_method, filter=(Support.NO, Support.YES, Support.UNKNOWN)):

test/functorch/test_dims.py

@@ -403,7 +403,7 @@ def test_hello(self):
         # test with too many elements
         try:
             A[1, ..., 1, 1]
-            raise NotImplementedError()
+            raise NotImplementedError
         except IndexError:
             pass
         c, d = dims()
@@ -415,7 +415,7 @@ def test_hello(self):
         )
         try:
             A[..., 3, ...]
-            raise NotImplementedError()
+            raise NotImplementedError
         except DimensionBindError:
             pass
 

test/inductor/test_torchinductor_dynamic_shapes.py

@@ -285,7 +285,7 @@ def test_item_to_inputs_kernel_nobreak(self, device):
 
                 @custom_ops.custom_op("test::foo")
                 def foo(x: torch.Tensor, y: int) -> torch.Tensor:
-                    raise NotImplementedError()
+                    raise NotImplementedError
 
                 @custom_ops.impl("test::foo")
                 def foo_impl(x: torch.Tensor, y: int) -> torch.Tensor:
@@ -401,7 +401,7 @@ def test_dynamic_stride_nobreak(self, device):
 
                 @custom_ops.custom_op("test::foo")
                 def foo(x: torch.Tensor) -> torch.Tensor:
-                    raise NotImplementedError()
+                    raise NotImplementedError
 
                 @custom_ops.impl("test::foo")
                 def foo_impl(x: torch.Tensor) -> torch.Tensor:

test/jit/test_freezing.py

@@ -2632,7 +2632,7 @@ def forward(self, in_tensor1, in_tensor2, cond: bool):
                     res3 = torch._C._nn.linear(in_tensor2, self.w2, self.b2)
                     res4 = torch._C._nn.linear(in_tensor1, self.w2, self.b1)
                 else:
-                    raise AssertionError()
+                    raise AssertionError
                 res2 = torch._C._nn.linear(in_tensor1, self.w2, self.b1)
                 return res1, res2, res3, res4
 

test/jit/test_list_dict.py

@@ -2871,7 +2871,7 @@ def __iter__(self):
 
             def __next__(self):
                 if self.value == limit:  # noqa: F821
-                    raise StopIteration()
+                    raise StopIteration
 
                 ret = self.value
                 self.value += 1