# Copyright (c) 2020 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 os from typing import Set import numpy as np import paddle.fluid.core as core from paddle.fluid.core import ( AnalysisConfig, PaddleDType, PaddleInferPredictor, PaddleInferTensor, PaddlePlace, convert_to_mixed_precision_bind, ) DataType = PaddleDType PlaceType = PaddlePlace PrecisionType = AnalysisConfig.Precision Config = AnalysisConfig Tensor = PaddleInferTensor Predictor = PaddleInferPredictor def tensor_copy_from_cpu(self, data): ''' Support input type check based on tensor.copy_from_cpu. ''' if isinstance(data, np.ndarray) or ( isinstance(data, list) and len(data) > 0 and isinstance(data[0], str) ): self.copy_from_cpu_bind(data) else: raise TypeError( "In copy_from_cpu, we only support numpy ndarray and list[str] data type." ) def tensor_share_external_data(self, data): ''' Support input type check based on tensor.share_external_data. ''' if isinstance(data, core.LoDTensor): self.share_external_data_bind(data) else: raise TypeError( "In share_external_data, we only support LoDTensor data type." ) def convert_to_mixed_precision( model_file: str, params_file: str, mixed_model_file: str, mixed_params_file: str, mixed_precision: PrecisionType, backend: PlaceType, keep_io_types: bool = True, black_list: Set = set(), ): ''' Convert a fp32 model to mixed precision model. Args: model_file: fp32 model file, e.g. inference.pdmodel. params_file: fp32 params file, e.g. inference.pdiparams. mixed_model_file: The storage path of the converted mixed-precision model. mixed_params_file: The storage path of the converted mixed-precision params. mixed_precision: The precision, e.g. PrecisionType.Half. backend: The backend, e.g. PlaceType.GPU. keep_io_types: Whether the model input and output dtype remains unchanged. black_list: Operators that do not convert precision. ''' mixed_model_dirname = os.path.dirname(mixed_model_file) mixed_params_dirname = os.path.dirname(mixed_params_file) if not os.path.exists(mixed_model_dirname): os.makedirs(mixed_model_dirname) if not os.path.exists(mixed_params_dirname): os.makedirs(mixed_params_dirname) convert_to_mixed_precision_bind( model_file, params_file, mixed_model_file, mixed_params_file, mixed_precision, backend, keep_io_types, black_list, ) Tensor.copy_from_cpu = tensor_copy_from_cpu Tensor.share_external_data = tensor_share_external_data