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104 lines
3.4 KiB
104 lines
3.4 KiB
/* 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 <stddef.h>
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#include <stdint.h>
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#include <stdio.h>
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#include <string>
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#include <vector>
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#include "paddle/fluid/inference/capi/paddle_c_api.h"
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#include "paddle/fluid/inference/tests/api/tester_helper.h"
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namespace paddle {
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namespace inference {
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namespace analysis {
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void zero_copy_run() {
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std::string model_dir = FLAGS_infer_model;
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std::string prog_file = model_dir + "/model";
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std::string params_file = model_dir + "/params";
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PD_AnalysisConfig *config = PD_NewAnalysisConfig();
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PD_DisableGpu(config);
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PD_SetCpuMathLibraryNumThreads(config, 10);
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PD_SwitchUseFeedFetchOps(config, false);
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PD_SwitchSpecifyInputNames(config, true);
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PD_SwitchIrDebug(config, true);
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PD_SetModel(config, prog_file.c_str(), params_file.c_str());
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bool use_feed_fetch = PD_UseFeedFetchOpsEnabled(config);
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EXPECT_FALSE(use_feed_fetch);
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bool specify_input_names = PD_SpecifyInputName(config);
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EXPECT_TRUE(specify_input_names);
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const int batch_size = 1;
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const int channels = 3;
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const int height = 318;
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const int width = 318;
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float *input = new float[batch_size * channels * height * width]();
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int shape[4] = {batch_size, channels, height, width};
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int shape_size = 4;
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int in_size = 1;
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int out_size;
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PD_ZeroCopyData *inputs = new PD_ZeroCopyData;
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PD_ZeroCopyData *outputs = new PD_ZeroCopyData;
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inputs->data = static_cast<void *>(input);
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inputs->dtype = PD_FLOAT32;
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inputs->name = new char[5];
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inputs->name[0] = 'd';
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inputs->name[1] = 'a';
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inputs->name[2] = 't';
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inputs->name[3] = 'a';
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inputs->name[4] = '\0';
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inputs->shape = shape;
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inputs->shape_size = shape_size;
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PD_PredictorZeroCopyRun(config, inputs, in_size, &outputs, &out_size);
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delete[] input;
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delete[] inputs;
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delete[] outputs;
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}
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TEST(PD_PredictorZeroCopyRun, zero_copy_run) { zero_copy_run(); }
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#ifdef PADDLE_WITH_MKLDNN
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TEST(PD_AnalysisConfig, profile_mkldnn) {
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std::string model_dir = FLAGS_infer_model;
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std::string prog_file = model_dir + "/model";
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std::string params_file = model_dir + "/params";
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PD_AnalysisConfig *config = PD_NewAnalysisConfig();
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PD_DisableGpu(config);
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PD_SetCpuMathLibraryNumThreads(config, 10);
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PD_SwitchUseFeedFetchOps(config, false);
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PD_SwitchSpecifyInputNames(config, true);
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PD_SwitchIrDebug(config, true);
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PD_EnableMKLDNN(config);
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bool mkldnn_enable = PD_MkldnnEnabled(config);
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EXPECT_TRUE(mkldnn_enable);
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PD_EnableMkldnnQuantizer(config);
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bool quantizer_enable = PD_MkldnnQuantizerEnabled(config);
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EXPECT_TRUE(quantizer_enable);
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PD_EnableMkldnnBfloat16(config);
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bool bfloat16_enable = PD_MkldnnBfloat16Enabled(config);
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EXPECT_TRUE(bfloat16_enable);
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PD_SetMkldnnCacheCapacity(config, 0);
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PD_SetModel(config, prog_file.c_str(), params_file.c_str());
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PD_DeleteAnalysisConfig(config);
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}
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#endif
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} // namespace analysis
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} // namespace inference
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} // namespace paddle
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