chore: import upstream snapshot with attribution

python/paddle/base/wrapped_decorator.py

@@ -0,0 +1,59 @@
+# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+
+import contextlib
+import functools
+import inspect
+from collections.abc import Callable
+from typing import TypeVar
+
+from typing_extensions import ParamSpec
+
+_InputT = ParamSpec("_InputT")
+_RetT1 = TypeVar("_RetT1")
+_RetT2 = TypeVar("_RetT2")
+
+__all__ = []
+
+
+def copy_signature(
+    src: Callable[_InputT, _RetT1], dst: Callable[_InputT, _RetT1]
+):
+    src_signature = inspect.signature(src)
+    dst.__signature__ = src_signature.replace(
+        parameters=list(src_signature.parameters.values())
+    )
+
+
+def wrap_decorator(
+    decorator_func: Callable[
+        [Callable[_InputT, _RetT1]], Callable[_InputT, _RetT2]
+    ],
+) -> Callable[[Callable[_InputT, _RetT1]], Callable[_InputT, _RetT2]]:
+    @functools.wraps(decorator_func)
+    def __impl__(func: Callable[_InputT, _RetT1]) -> Callable[_InputT, _RetT2]:
+        decorated = decorator_func(func)
+
+        @functools.wraps(func)
+        def wrapper(*args: _InputT.args, **kwargs: _InputT.kwargs) -> _RetT2:
+            return decorated(*args, **kwargs)
+
+        copy_signature(func, wrapper)
+        return wrapper
+
+    return __impl__
+
+
+signature_safe_contextmanager = wrap_decorator(contextlib.contextmanager)