# Copyright (c) 2022 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 abc import inspect from functools import partial from paddle.nn import Layer from .base_quanter import BaseQuanter class ClassWithArguments(metaclass=abc.ABCMeta): def __init__(self, *args, **kwargs): self._args = args self._kwargs = kwargs @property def args(self): return self._args @property def kwargs(self): return self._kwargs @abc.abstractmethod def _get_class(self): pass def __str__(self): args_str = ",".join( list(self.args) + [f"{k}={v}" for k, v in self.kwargs.items()] ) return f"{self.__class__.__name__}({args_str})" def __repr__(self): return self.__str__() class QuanterFactory(ClassWithArguments): r""" The factory holds the quanter's class information and the arguments used to create quanter instance. """ def __init__(self, *args, **kwargs): super().__init__(*args, **kwargs) self.partial_class = None def _instance(self, layer: Layer) -> BaseQuanter: r""" Create an instance of quanter for target layer. """ if self.partial_class is None: self.partial_class = partial( self._get_class(), *self.args, **self.kwargs ) return self.partial_class(layer) ObserverFactory = QuanterFactory def quanter(class_name): r""" Annotation to declare a factory class for quanter. Args: class_name (str) - The name of factory class to be declared. Examples: .. code-block:: python # Given codes in ./customized_quanter.py from paddle.quantization import quanter from paddle.quantization import BaseQuanter @quanter("CustomizedQuanter") class CustomizedQuanterLayer(BaseQuanter): def __init__(self, arg1, kwarg1=None): pass # Used in ./test.py # from .customized_quanter import CustomizedQuanter from paddle.quantization import QuantConfig arg1_value = "test" kwarg1_value = 20 quanter = CustomizedQuanter(arg1_value, kwarg1=kwarg1_value) q_config = QuantConfig(activation=quanter, weight=quanter) """ def wrapper(target_class): init_function_str = f""" def init_function(self, *args, **kwargs): super(type(self), self).__init__(*args, **kwargs) import importlib module = importlib.import_module("{target_class.__module__}") my_class = getattr(module, "{target_class.__name__}") globals()["{target_class.__name__}"] = my_class def get_class_function(self): return {target_class.__name__} locals()["init_function"]=init_function locals()["get_class_function"]=get_class_function """ exec(init_function_str) frm = inspect.stack()[1] mod = inspect.getmodule(frm[0]) new_class = type( class_name, (QuanterFactory,), { "__init__": locals()["init_function"], "_get_class": locals()["get_class_function"], }, ) setattr(mod, class_name, new_class) if "__all__" in mod.__dict__: mod.__all__.append(class_name) return target_class return wrapper