wehub-resource-sync
64 lines
2.2 KiB
C++
64 lines
2.2 KiB
C++
// Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserved.
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//
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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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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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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 "paddle/fluid/framework/block_desc.h"
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#include "paddle/fluid/framework/op_desc.h"
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#include "paddle/fluid/framework/program_desc.h"
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#include "paddle/fluid/framework/scope.h"
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#include "paddle/fluid/inference/utils/singleton.h"
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#include "test/cpp/inference/api/tester_helper.h"
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namespace paddle {
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namespace inference {
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TEST(test_zerocopy_tensor, zerocopy_tensor) {
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AnalysisConfig config;
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config.SetModel(FLAGS_infer_model + "/inference.pdmodel",
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FLAGS_infer_model + "/inference.pdiparams");
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auto predictor = CreatePaddlePredictor(config);
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int batch_size = 1;
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int channels = 3;
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int height = 224;
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int width = 224;
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int nums = batch_size * channels * height * width;
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float* input = new float[nums];
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for (int i = 0; i < nums; ++i) input[i] = 0;
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auto input_names = predictor->GetInputNames();
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PaddlePlace p = PaddlePlace::kCPU;
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PaddlePlace* place = &p;
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int size;
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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<float>(input);
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input_t->data<float>(place, &size);
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input_t->mutable_data<float>(p);
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predictor->ZeroCopyRun();
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std::vector<float> out_data;
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auto output_names = predictor->GetOutputNames();
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auto output_t = predictor->GetOutputTensor(output_names[0]);
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std::vector<int> output_shape = output_t->shape();
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int out_num = std::accumulate(
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output_shape.begin(), output_shape.end(), 1, std::multiplies<int>());
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out_data.resize(out_num);
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output_t->copy_to_cpu<float>(out_data.data());
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}
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} // namespace inference
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} // namespace paddle
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