fix E711 none-comparison (#2469)

Author: Borda

pyproject.toml

@@ -160,7 +160,6 @@ ignore = [
     "F401",  # https://docs.astral.sh/ruff/rules/unused-import/
     "F405",  # https://docs.astral.sh/ruff/rules/undefined-local-with-import-star-usage/
     "E712",  # https://docs.astral.sh/ruff/rules/true-false-comparison/
-    "E711",  # https://docs.astral.sh/ruff/rules/none-comparison/
     "E721",  # https://docs.astral.sh/ruff/rules/type-comparison/
     "E722",  # https://docs.astral.sh/ruff/rules/bare-except/
     "E741",  # https://docs.astral.sh/ruff/rules/ambiguous-variable-name/

thunder/core/interpreter.py

@@ -902,7 +902,7 @@ def get_python_tb(tb: list | TracebackType | None) -> list:
         return tb
 
     res = []
-    while tb != None:
+    while tb is not None:
         res.append(PythonFrameWrapper(tb.tb_frame))
         tb = tb.tb_next
     return res
@@ -4283,7 +4283,7 @@ def _end_async_for_handler_3_10(
         frame.interpreter_stack.pop()  # we ignore that and assume == type(exc_value)
         exc_value = frame.interpreter_stack.pop()
         exc_traceback = frame.interpreter_stack.pop()
-        if exc_value != None:
+        if exc_value is not None:
             exc_value.__traceback__ = exc_traceback
         assert runtimectx.exception_stack
         # CPython sets exc_info->exc_type/value/traceback
@@ -5787,7 +5787,7 @@ def do_raise(exc: Any = Py_NULL(), cause: Any = Py_NULL()) -> Literal[INTERPRETE
         # Re-raise
         assert runtimectx.exception_stack
         value = runtimectx.exception_stack[0]
-        if value == None:
+        if value is None:
             return do_raise(RuntimeError("No active exception to reraise"))
         assert isinstance(value, BaseException)
         # check for cause being PY_NULL? Python does not do this, but it would seem to be a bug
@@ -7307,7 +7307,7 @@ def _run_frame(
                                 frame.interpreter_stack.pop()  # we ignore that and assume == type(exc_value)
                                 exc_value = frame.interpreter_stack.pop()
                                 exc_traceback = frame.interpreter_stack.pop()
-                            if exc_value != None:
+                            if exc_value is not None:
                                 exc_value.__traceback__ = exc_traceback
                             assert runtimectx.exception_stack
                             # CPython sets exc_info->exc_type/value/traceback

thunder/core/utils.py

@@ -1028,7 +1028,7 @@ def producers(trace_or_bsyms: TraceCtx | list[BoundSymbolInterface], *, _map_to_
 
         for out in bsym.flat_proxy_outs:
             # if a producer has already been traversed, skip
-            if producers.get(out, None) != None:
+            if producers.get(out, None) is not None:
                 continue
 
             vout = variableify(out)

thunder/dynamo/report.py

@@ -371,15 +371,15 @@ def model(x):
 
         folder = Path(folder)
         folder.mkdir(exist_ok=True, parents=True)
-        if inputs == None:
+        if inputs is None:
             inputs = self.example_input_meta
         has_cuda_args = any(hasattr(arg, "device") and arg.device.type == "cuda" for arg in inputs)
         has_requires_grad_args = any(hasattr(arg, "requires_grad") and arg.requires_grad for arg in inputs)
         torch_env, thunder_pkgs = get_env()
         readable = _readable(self.graph, "DynamoModule", print_output=False)
         # The packages that are likely to be used by the code generated from the Torch GraphModule
         torch_import_str = "\n".join([v.import_str for v in torch.fx.graph._custom_builtins.values()])
-        import_str = "" if import_str == None else "\n".join(import_str)
+        import_str = "" if import_str is None else "\n".join(import_str)
         input_str = textwrap.indent(self._get_input_str(folder, inputs, serialize_inputs), "    ")
         call_bench_str = f"benchmark_for_compute_type(compute_type, benchmark, compiled_model, inputs, {{}}, has_cuda={True if has_cuda_args else False})"
         compute_type_decorator = (
@@ -502,7 +502,7 @@ def write_repro(
         """
         folder = Path(folder)
         folder.mkdir(exist_ok=True, parents=True)
-        if inputs == None:
+        if inputs is None:
             inputs = self.example_input_meta
         code_str = self._get_repro_code(folder, compile_fn, None, serialize_inputs, inputs)
         comment_str = self._get_comment_str(extra_comment_str)
@@ -602,7 +602,7 @@ def write_benchmark(
         """
         folder = Path(folder)
         folder.mkdir(exist_ok=True, parents=True)
-        if inputs == None:
+        if inputs is None:
             inputs = self.example_input_meta
         forward_only = not any(hasattr(arg, "requires_grad") and arg.requires_grad for arg in inputs)
         code_str = self._get_repro_code(folder, compile_fn, time_fn, serialize_inputs, inputs)
@@ -923,7 +923,7 @@ def write_nvfuser_benchmark(self, folder, time_fn: TimerInterface, file_name=Non
 print(measurement)
 {comment_str}
 """
-        if file_name == None:
+        if file_name is None:
             file_name = f"{self.name}_benchmark_nvfuser.py"
         with open(folder / file_name, "w") as f:
             print(code_str, file=f)
@@ -936,7 +936,7 @@ def write_nvfuser_repro(self, folder, file_name=None):
         comment_str = f'"""\n{self.nvfusion_bsym}\n"""'
         repro_code_str = f"{repro_code_str}\n{comment_str}"
 
-        if file_name == None:
+        if file_name is None:
             file_name = f"{self.name}_repro_nvfuser.py"
         with open(folder / file_name, "w") as f:
             print(repro_code_str, file=f)
@@ -966,7 +966,7 @@ def write_inductor_repro(self, folder: PathLike, file_name=None):
         code_str = f"""{code_str}
 out = torch_compiled_callable(*inputs)
 """
-        if file_name == None:
+        if file_name is None:
             file_name = f"{self.name}_repro_inductor.py"
         with open(folder / file_name, "w") as f:
             f.write(code_str)
@@ -982,7 +982,7 @@ def write_inductor_benchmark(self, folder: PathLike, time_fn: TimerInterface, fi
 measurement = {time_fn.to_source("torch_compiled_callable", "inputs")}
 print(measurement)
 """
-        if file_name == None:
+        if file_name is None:
             file_name = f"{self.name}_benchmark_inductor.py"
         with open(folder / file_name, "w") as f:
             f.write(code_str)

thunder/tests/test_dynamo.py

@@ -1076,7 +1076,7 @@ def test_get_example_input_tensor_metadata():
 
     t0 = torch.randn((5, 10), device="meta")
     meta_t0 = _get_example_input_tensor_metadata(t0)
-    assert meta_t0.min_val == None and meta_t0.max_val == None and meta_t0.device.type == "meta"
+    assert meta_t0.min_val is None and meta_t0.max_val is None and meta_t0.device.type == "meta"
     t0_str = arg_like_tensor(meta_t0)
     assert (
         t0_str

thunder/torch/__init__.py

@@ -5660,7 +5660,7 @@ def interpolate(
     utils.check(a.ndim >= 3, lambda: f"Expected {a.ndim=} >= 3")
     utils.check(a.numel() > 0, lambda: f"Expected {a.numel=} to be greater than 0")
     utils.check(
-        align_corners == None,
+        align_corners is None,
         lambda: "Thunder does not yet support 'align_corners'.",
         exception_type=NotImplementedError,
     )