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63 lines
1.9 KiB
63 lines
1.9 KiB
6 years ago
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/* Copyright (c) 2019 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 <gflags/gflags.h>
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#include <glog/logging.h>
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#include <gtest/gtest.h>
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#include "paddle/fluid/inference/tests/api/trt_test_helper.h"
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namespace paddle {
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namespace inference {
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TEST(TensorRT, cascade_rcnn) {
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std::string model_dir = FLAGS_infer_model + "/cascade_rcnn";
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AnalysisConfig config;
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int batch_size = 1;
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config.EnableUseGpu(100, 0);
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config.SetModel(model_dir + "/model", model_dir + "/params");
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config.SwitchUseFeedFetchOps(false);
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config.EnableTensorRtEngine(1 << 30, batch_size, 40,
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AnalysisConfig::Precision::kFloat32, false);
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auto predictor = CreatePaddlePredictor(config);
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int channels = 3;
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int height = 640;
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int width = 640;
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int input_num = batch_size * channels * height * width;
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float *input = new float[input_num];
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memset(input, 1.0, input_num * sizeof(float));
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float *im_shape = new float[3];
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im_shape[0] = 3.0;
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im_shape[1] = 640.0;
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im_shape[2] = 640.0;
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auto input_names = predictor->GetInputNames();
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auto input_t = predictor->GetInputTensor(input_names[0]);
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input_t->Reshape({batch_size, channels, height, width});
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input_t->copy_from_cpu(input);
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auto input_t1 = predictor->GetInputTensor(input_names[1]);
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input_t1->Reshape({batch_size, 3});
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input_t1->copy_from_cpu(im_shape);
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ASSERT_TRUE(predictor->ZeroCopyRun());
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}
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} // namespace inference
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} // namespace paddle
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