wehub-resource-sync
100 lines
2.9 KiB
C++
100 lines
2.9 KiB
C++
/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
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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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http://www.apache.org/licenses/LICENSE-2.0
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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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#include <fstream>
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#include <iostream>
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#include "test/cpp/inference/api/tester_helper.h"
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PD_DEFINE_bool(disable_onednn_fc, false, "Disable usage of ONE-DNN's FC op");
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namespace paddle {
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namespace inference {
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namespace analysis {
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void SetConfig(AnalysisConfig *cfg) {
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cfg->SetModel(FLAGS_infer_model + "/model", FLAGS_infer_model + "/params");
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cfg->DisableGpu();
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cfg->SwitchIrOptim();
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cfg->SwitchSpecifyInputNames();
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cfg->SetCpuMathLibraryNumThreads(FLAGS_cpu_num_threads);
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cfg->DeletePass("constant_folding_pass");
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}
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void SetInput(std::vector<std::vector<PaddleTensor>> *inputs) {
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SetFakeImageInput(inputs, FLAGS_infer_model);
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}
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// Easy for profiling independently.
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void profile(bool use_onednn = false) {
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AnalysisConfig cfg;
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SetConfig(&cfg);
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if (use_onednn) {
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cfg.EnableONEDNN();
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if (FLAGS_disable_onednn_fc) {
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cfg.DisableOnednnFcPasses();
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}
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}
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std::vector<std::vector<PaddleTensor>> outputs;
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std::vector<std::vector<PaddleTensor>> input_slots_all;
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SetInput(&input_slots_all);
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TestPrediction(reinterpret_cast<const PaddlePredictor::Config *>(&cfg),
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input_slots_all,
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&outputs,
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FLAGS_num_threads);
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}
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TEST(Analyzer_resnet50, profile) { profile(); }
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#ifdef PADDLE_WITH_DNNL
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TEST(Analyzer_resnet50, profile_onednn) { profile(true /* use_onednn */); }
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#endif
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// Compare result of NativeConfig and AnalysisConfig
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void compare(bool use_onednn = false) {
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AnalysisConfig cfg;
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SetConfig(&cfg);
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if (use_onednn) {
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cfg.EnableONEDNN();
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if (FLAGS_disable_onednn_fc) {
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cfg.DisableOnednnFcPasses();
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}
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}
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std::vector<std::vector<PaddleTensor>> input_slots_all;
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SetInput(&input_slots_all);
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CompareNativeAndAnalysis(
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reinterpret_cast<const PaddlePredictor::Config *>(&cfg), input_slots_all);
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}
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TEST(Analyzer_resnet50, compare) { compare(); }
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#ifdef PADDLE_WITH_DNNL
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TEST(Analyzer_resnet50, compare_onednn) { compare(true /* use_onednn */); }
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#endif
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// Compare Deterministic result
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TEST(Analyzer_resnet50, compare_determine) {
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AnalysisConfig cfg;
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SetConfig(&cfg);
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std::vector<std::vector<PaddleTensor>> input_slots_all;
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SetInput(&input_slots_all);
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CompareDeterministic(reinterpret_cast<const PaddlePredictor::Config *>(&cfg),
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input_slots_all);
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}
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} // namespace analysis
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} // namespace inference
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} // namespace paddle
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