2025-08-31 09:09:30 +08:00
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# Copyright (c) 2025 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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2026-04-05 08:41:42 +08:00
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# The file has been adapted from pytorch project
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# Licensed under BSD-style license -
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# https://github.com/pytorch/pytorch/blob/main/LICENSE
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2025-09-04 18:42:48 +08:00
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2025-08-31 09:09:30 +08:00
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from __future__ import annotations
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import contextlib
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import ctypes
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import importlib
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import os
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import sys
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import types
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from functools import cached_property
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from typing import Any, Callable, Generic, TypeVar
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from typing_extensions import ParamSpec
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import paddle
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_InputT = ParamSpec("_InputT")
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_RetT = TypeVar("_RetT")
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PADDLE_OPS_MODULE_NAME = "paddle.ops"
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# Query `hasattr` only once.
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_SET_GLOBAL_FLAGS = hasattr(sys, "getdlopenflags") and hasattr(
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sys, "setdlopenflags"
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)
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@contextlib.contextmanager
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def dl_open_guard():
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"""
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Context manager to set the RTLD_GLOBAL dynamic linker flag while we open a
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shared library to load custom operators.
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"""
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if not _SET_GLOBAL_FLAGS:
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yield
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return
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old_flags = sys.getdlopenflags()
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sys.setdlopenflags(old_flags | ctypes.RTLD_GLOBAL)
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try:
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yield
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finally:
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sys.setdlopenflags(old_flags)
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def import_module(module: str):
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return importlib.import_module(module)
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def load_library(path: str):
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"""
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Load a shared library at the specified path.
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"""
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path = os.path.realpath(path)
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with dl_open_guard():
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ctypes.CDLL(path)
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2025-09-04 18:42:48 +08:00
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class PythonOpRegistry:
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def __init__(self):
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self._registry: dict[str, Callable[..., object]] = {}
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def register(self, name: str, fn: Callable[..., object]):
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if name in self._registry:
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raise ValueError(f"Operator '{name}' is already registered.")
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self._registry[name] = fn
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def has_operator(self, name: str) -> bool:
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return name in self._registry
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def get_operator(self, name: str) -> Callable[..., object]:
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if name not in self._registry:
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raise ValueError(f"Operator '{name}' is not registered.")
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return self._registry[name]
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PYTHON_OP_REGISTRY = PythonOpRegistry()
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2025-08-31 09:09:30 +08:00
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class OverloadedOpFunction(Generic[_InputT, _RetT]):
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def __init__(self, namespace: str, name: str):
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self.namespace = namespace
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self.name = name
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@cached_property
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def callable_fn(self) -> Callable[_InputT, _RetT]:
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2025-09-04 18:42:48 +08:00
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if PYTHON_OP_REGISTRY.has_operator(f"{self.namespace}::{self.name}"):
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return PYTHON_OP_REGISTRY.get_operator( # type: ignore
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f"{self.namespace}::{self.name}"
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)
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2025-08-31 09:09:30 +08:00
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return paddle.base.core.torch_compat._get_operation(
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f"{self.namespace}::{self.name}"
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)
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def __getattr__(self, name: str) -> Callable[_InputT, _RetT]:
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if name == "default":
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return self.callable_fn
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raise AttributeError(
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f"'{self.namespace}.{self.name}' has no attribute '{name}'"
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)
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def __call__(self, *args: _InputT.args, **kwargs: _InputT.kwargs) -> _RetT:
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return self.callable_fn(*args, **kwargs)
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class OpNameSpace(types.ModuleType):
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def __init__(self, name):
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super().__init__(f"{PADDLE_OPS_MODULE_NAME}.{name}")
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self.name = name
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def __getattr__(self, name: str) -> OverloadedOpFunction[..., Any]:
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if name == "__file__":
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return PADDLE_OPS_MODULE_NAME # type: ignore
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return OverloadedOpFunction(self.name, name)
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class PaddleOpsModule(types.ModuleType):
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__file__ = "_ops.py"
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def __init__(self):
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super().__init__(PADDLE_OPS_MODULE_NAME)
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def __getattr__(self, name: str):
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namespace = OpNameSpace(name)
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# Insert to __dict__ to avoid repeatedly __getattr__ overhead
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setattr(self, name, namespace)
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return namespace
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def import_module(self, module):
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return import_module(module)
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def load_library(self, path):
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return load_library(path)
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ops = PaddleOpsModule()
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