Enable additional ruff rules (#6032)

Enable additional ruff rules and apply fixes

---------

Signed-off-by: Justin Chu <justinchu@microsoft.com>
Signed-off-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>

docs/Operators.md

@@ -277,6 +277,7 @@ expect(node, inputs=[x], outputs=[y], name="test_abs")
 
 ```python
 # SPDX-License-Identifier: Apache-2.0
+from __future__ import annotations
 
 import numpy as np
 
@@ -5266,7 +5267,7 @@ Other versions of this operator: <a href="Changelog.md#Concat-1">1</a>, <a href=
 <summary>concat</summary>
 
 ```python
-test_cases: Dict[str, Sequence[Any]] = {
+test_cases: dict[str, Sequence[Any]] = {
     "1d": ([1, 2], [3, 4]),
     "2d": ([[1, 2], [3, 4]], [[5, 6], [7, 8]]),
     "3d": (
@@ -14481,7 +14482,7 @@ node = onnx.helper.make_node(
 )
 
 trip_count = np.array(5).astype(np.int64)
-seq_empty: List[Any] = []
+seq_empty: list[Any] = []
 seq_res = [x[: int(i)] for i in x]
 cond = np.array(1).astype(bool)
 expect(
@@ -14678,7 +14679,7 @@ node = onnx.helper.make_node(
 trip_count = np.array(5).astype(np.int64)
 cond = np.array(1).astype(bool)
 seq_res = compute_loop_outputs(x, [x0], trip_count)
-opt_seq_in: List[Any] = [x0]
+opt_seq_in: list[Any] = [x0]
 expect(
     node,
     inputs=[trip_count, cond, opt_seq_in],

docs/TestCoverage.md

@@ -3773,7 +3773,7 @@ There are 1 test cases, listed as following:
 <summary>concat</summary>
 
 ```python
-test_cases: Dict[str, Sequence[Any]] = {
+test_cases: dict[str, Sequence[Any]] = {
     "1d": ([1, 2], [3, 4]),
     "2d": ([[1, 2], [3, 4]], [[5, 6], [7, 8]]),
     "3d": (
@@ -9665,7 +9665,7 @@ node = onnx.helper.make_node(
 )
 
 trip_count = np.array(5).astype(np.int64)
-seq_empty: List[Any] = []
+seq_empty: list[Any] = []
 seq_res = [x[: int(i)] for i in x]
 cond = np.array(1).astype(bool)
 expect(
@@ -9860,7 +9860,7 @@ node = onnx.helper.make_node(
 trip_count = np.array(5).astype(np.int64)
 cond = np.array(1).astype(bool)
 seq_res = compute_loop_outputs(x, [x0], trip_count)
-opt_seq_in: List[Any] = [x0]
+opt_seq_in: list[Any] = [x0]
 expect(
     node,
     inputs=[trip_count, cond, opt_seq_in],

onnx/__init__.py

@@ -134,7 +134,9 @@
 # Supported model formats that can be loaded from and saved to
 # The literals are formats with built-in support. But we also allow users to
 # register their own formats. So we allow str as well.
-_SupportedFormat = Union[Literal["protobuf", "textproto", "onnxtxt", "json"], str]
+_SupportedFormat = Union[
+    Literal["protobuf", "textproto", "onnxtxt", "json"], str  # noqa: PYI051
+]
 # Default serialization format
 _DEFAULT_FORMAT = "protobuf"
 

onnx/backend/base.py

@@ -1,10 +1,10 @@
 # Copyright (c) ONNX Project Contributors
 #
 # SPDX-License-Identifier: Apache-2.0
-
+from __future__ import annotations
 
 from collections import namedtuple
-from typing import Any, Dict, NewType, Optional, Sequence, Tuple, Type
+from typing import Any, NewType, Sequence
 
 import numpy
 
@@ -37,11 +37,11 @@ def __init__(self, device: str) -> None:
 
 def namedtupledict(
     typename: str, field_names: Sequence[str], *args: Any, **kwargs: Any
-) -> Type[Tuple[Any, ...]]:
+) -> type[tuple[Any, ...]]:
     field_names_map = {n: i for i, n in enumerate(field_names)}
     # Some output names are invalid python identifier, e.g. "0"
     kwargs.setdefault("rename", True)
-    data = namedtuple(typename, field_names, *args, **kwargs)  # type: ignore
+    data = namedtuple(typename, field_names, *args, **kwargs)  # type: ignore  # noqa: PYI024
 
     def getitem(self: Any, key: Any) -> Any:
         if isinstance(key, str):
@@ -58,7 +58,7 @@ class BackendRep:
     BackendRep to retrieve the corresponding results.
     """
 
-    def run(self, inputs: Any, **kwargs: Any) -> Tuple[Any, ...]:
+    def run(self, inputs: Any, **kwargs: Any) -> tuple[Any, ...]:  # noqa: ARG002
         """Abstract function."""
         return (None,)
 
@@ -76,23 +76,23 @@ class Backend:
 
     @classmethod
     def is_compatible(
-        cls, model: ModelProto, device: str = "CPU", **kwargs: Any
+        cls, model: ModelProto, device: str = "CPU", **kwargs: Any  # noqa: ARG003
     ) -> bool:
         # Return whether the model is compatible with the backend.
         return True
 
     @classmethod
     def prepare(
-        cls, model: ModelProto, device: str = "CPU", **kwargs: Any
-    ) -> Optional[BackendRep]:
+        cls, model: ModelProto, device: str = "CPU", **kwargs: Any  # noqa: ARG003
+    ) -> BackendRep | None:
         # TODO Remove Optional from return type
         onnx.checker.check_model(model)
         return None
 
     @classmethod
     def run_model(
         cls, model: ModelProto, inputs: Any, device: str = "CPU", **kwargs: Any
-    ) -> Tuple[Any, ...]:
+    ) -> tuple[Any, ...]:
         backend = cls.prepare(model, device, **kwargs)
         assert backend is not None
         return backend.run(inputs)
@@ -101,11 +101,13 @@ def run_model(
     def run_node(
         cls,
         node: NodeProto,
-        inputs: Any,
-        device: str = "CPU",
-        outputs_info: Optional[Sequence[Tuple[numpy.dtype, Tuple[int, ...]]]] = None,
-        **kwargs: Dict[str, Any],
-    ) -> Optional[Tuple[Any, ...]]:
+        inputs: Any,  # noqa: ARG003
+        device: str = "CPU",  # noqa: ARG003
+        outputs_info: (  # noqa: ARG003
+            Sequence[tuple[numpy.dtype, tuple[int, ...]]] | None
+        ) = None,
+        **kwargs: dict[str, Any],
+    ) -> tuple[Any, ...] | None:
         """Simple run one operator and return the results.
 
         Args:
@@ -130,7 +132,7 @@ def run_node(
         return None
 
     @classmethod
-    def supports_device(cls, device: str) -> bool:
+    def supports_device(cls, device: str) -> bool:  # noqa: ARG003
         """Checks whether the backend is compiled with particular device support.
         In particular it's used in the testing suite.
         """

onnx/backend/sample/ops/__init__.py

@@ -1,22 +1,22 @@
 # Copyright (c) ONNX Project Contributors
 
 # SPDX-License-Identifier: Apache-2.0
+from __future__ import annotations
 
 import importlib
 import inspect
 import pkgutil
 import sys
 from types import ModuleType
-from typing import Dict
 
 
-def collect_sample_implementations() -> Dict[str, str]:
-    dict_: Dict[str, str] = {}
+def collect_sample_implementations() -> dict[str, str]:
+    dict_: dict[str, str] = {}
     _recursive_scan(sys.modules[__name__], dict_)
     return dict_
 
 
-def _recursive_scan(package: ModuleType, dict_: Dict[str, str]) -> None:
+def _recursive_scan(package: ModuleType, dict_: dict[str, str]) -> None:
     pkg_dir = package.__path__  # type: ignore
     module_location = package.__name__
     for _module_loader, name, ispkg in pkgutil.iter_modules(pkg_dir):  # type: ignore

onnx/backend/sample/ops/abs.py

@@ -1,4 +1,5 @@
 # SPDX-License-Identifier: Apache-2.0
+from __future__ import annotations
 
 import numpy as np
 

onnx/backend/test/__init__.py

@@ -1,6 +1,7 @@
 # Copyright (c) ONNX Project Contributors
 #
 # SPDX-License-Identifier: Apache-2.0
+from __future__ import annotations
 
 __all__ = ["BackendTest"]
 # for backward compatibility

onnx/backend/test/case/__init__.py

@@ -1,14 +1,14 @@
 # Copyright (c) ONNX Project Contributors
 
 # SPDX-License-Identifier: Apache-2.0
+from __future__ import annotations
 
 import sys
-from typing import Dict, List, Tuple
 
 from onnx.backend.test.case.base import Snippets
 from onnx.backend.test.case.utils import import_recursive
 
 
-def collect_snippets() -> Dict[str, List[Tuple[str, str]]]:
+def collect_snippets() -> dict[str, list[tuple[str, str]]]:
     import_recursive(sys.modules[__name__])
     return Snippets

onnx/backend/test/case/base.py

@@ -1,16 +1,17 @@
 # Copyright (c) ONNX Project Contributors
 
 # SPDX-License-Identifier: Apache-2.0
+from __future__ import annotations
 
 import inspect
 from collections import defaultdict
 from textwrap import dedent
-from typing import Any, ClassVar, Dict, List, Tuple, Type
+from typing import Any, ClassVar
 
 import numpy as np
 
 
-def process_snippet(op_name: str, name: str, export: Any) -> Tuple[str, str]:
+def process_snippet(op_name: str, name: str, export: Any) -> tuple[str, str]:
     snippet_name = name[len("export_") :] or op_name.lower()
     source_code = dedent(inspect.getsource(export))
     # remove the function signature line
@@ -20,14 +21,14 @@ def process_snippet(op_name: str, name: str, export: Any) -> Tuple[str, str]:
     return snippet_name, dedent("\n".join(lines[2:]))
 
 
-Snippets: Dict[str, List[Tuple[str, str]]] = defaultdict(list)
+Snippets: dict[str, list[tuple[str, str]]] = defaultdict(list)
 
 
 class _Exporter(type):
-    exports: ClassVar[Dict[str, List[Tuple[str, str]]]] = defaultdict(list)
+    exports: ClassVar[dict[str, list[tuple[str, str]]]] = defaultdict(list)
 
     def __init__(
-        cls, name: str, bases: Tuple[Type[Any], ...], dct: Dict[str, Any]
+        cls, name: str, bases: tuple[type[Any], ...], dct: dict[str, Any]
     ) -> None:
         for k, v in dct.items():
             if k.startswith("export"):

onnx/backend/test/case/model/__init__.py

@@ -1,9 +1,10 @@
 # Copyright (c) ONNX Project Contributors
 
 # SPDX-License-Identifier: Apache-2.0
+from __future__ import annotations
 
 import sys
-from typing import List, Optional, Sequence
+from typing import Sequence
 
 import numpy as np
 
@@ -18,7 +19,7 @@ def expect(
     model: ModelProto,
     inputs: Sequence[np.ndarray],
     outputs: Sequence[np.ndarray],
-    name: Optional[str] = None,
+    name: str | None = None,
 ) -> None:
     name = name or model.graph.name
     _SimpleModelTestCases.append(
@@ -40,7 +41,7 @@ def expect(
 BASE_URL = "onnx/backend/test/data/light/light_%s.onnx"
 
 
-def collect_testcases() -> List[TestCase]:
+def collect_testcases() -> list[TestCase]:
     """Collect model test cases defined in python/numpy code."""
     real_model_testcases = []
 

onnx/backend/test/case/model/expand.py

@@ -1,6 +1,7 @@
 # Copyright (c) ONNX Project Contributors
 
 # SPDX-License-Identifier: Apache-2.0
+from __future__ import annotations
 
 from typing import Sequence
 

onnx/backend/test/case/model/gradient.py

@@ -1,6 +1,7 @@
 # Copyright (c) ONNX Project Contributors
 
 # SPDX-License-Identifier: Apache-2.0
+from __future__ import annotations
 
 import numpy as np
 

onnx/backend/test/case/model/shrink.py

@@ -1,6 +1,7 @@
 # Copyright (c) ONNX Project Contributors
 
 # SPDX-License-Identifier: Apache-2.0
+from __future__ import annotations
 
 import numpy as np
 

onnx/backend/test/case/model/sign.py

@@ -1,6 +1,7 @@
 # Copyright (c) ONNX Project Contributors
 
 # SPDX-License-Identifier: Apache-2.0
+from __future__ import annotations
 
 import numpy as np
 

onnx/backend/test/case/model/single-relu.py

@@ -1,6 +1,7 @@
 # Copyright (c) ONNX Project Contributors
 
 # SPDX-License-Identifier: Apache-2.0
+from __future__ import annotations
 
 import numpy as np
 

onnx/backend/test/case/model/stringnormalizer.py

@@ -1,7 +1,7 @@
 # Copyright (c) ONNX Project Contributors
 
 # SPDX-License-Identifier: Apache-2.0
-
+from __future__ import annotations
 
 from typing import Sequence