wehub-resource-sync
90 lines
3.3 KiB
C++
90 lines
3.3 KiB
C++
/* Copyright (c) 2023 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 <glog/logging.h>
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#include <gtest/gtest.h>
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#include <cmath>
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#include "paddle/common/flags.h"
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#include "test/cpp/inference/api/tester_helper.h"
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namespace paddle_infer {
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static const std::vector<float> TRUTH_VALUES = {
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127.779f, 738.165f, 1013.22f, -438.17f, 366.401f, 927.659f, 736.222f,
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-633.684f, -329.927f, -430.155f, -633.062f, -146.548f, -1324.28f, -1349.36f,
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-242.675f, 117.448f, -801.723f, -391.514f, -404.818f, 454.16f, 515.48f,
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-133.031f, 69.293f, 590.096f, -1434.69f, -1070.89f, 307.074f, 400.525f,
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-316.12f, -587.125f, -161.056f, 800.363f, -96.4708f, 748.706f, 868.174f,
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-447.938f, 112.737f, 1127.2f, 47.4355f, 677.72f, 593.186f, -336.4f,
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551.362f, 397.823f, 78.3979f, -715.398f, 405.969f, 404.256f, 246.019f,
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-8.42969f, 131.365f, -648.051f};
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void PrepareInput(std::shared_ptr<Predictor> predictor) {
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const int batch = 1;
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const int channel = 3;
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const int height = 318;
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const int width = 318;
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const int input_num = batch * channel * height * width;
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std::vector<float> input(input_num, 1);
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auto input_names = predictor->GetInputNames();
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auto input_t = predictor->GetInputHandle(input_names[0]);
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input_t->Reshape({batch, channel, height, width});
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input_t->CopyFromCpu(input.data());
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}
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void CompareOutput(std::shared_ptr<Predictor> predictor) {
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auto output_names = predictor->GetOutputNames();
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auto output_t = predictor->GetOutputHandle(output_names[0]);
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std::vector<int> output_shape = output_t->shape();
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size_t out_num = std::accumulate(
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output_shape.begin(), output_shape.end(), 1, std::multiplies<int>());
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std::vector<float> out_data;
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out_data.resize(out_num);
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output_t->CopyToCpu(out_data.data());
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float* data_o = out_data.data();
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for (size_t j = 0; j < out_num; j += 10) {
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EXPECT_NEAR(
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(data_o[j] - TRUTH_VALUES[j / 10]) / TRUTH_VALUES[j / 10], 0., 10e-3);
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}
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}
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TEST(xpu_config, inference) {
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size_t l3_size = 10 * 1024 * 1024;
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XpuConfig xpu_config;
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xpu_config.l3_size = l3_size;
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std::string model_dir = FLAGS_infer_model + "/" + "model";
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Config config;
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config.SetModel(model_dir + "/model", model_dir + "/params");
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config.EnableXpu();
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config.SetXpuConfig(xpu_config);
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XpuConfig xpu_config_test = config.xpu_config();
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PADDLE_ENFORCE_EQ(xpu_config_test.l3_size,
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l3_size,
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common::errors::InvalidArgument(
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"xpu_config_test.l3_size %d is different from our "
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"expected value l3_size %d.",
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xpu_config_test.l3_size,
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l3_size));
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auto predictor = CreatePredictor(config);
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PrepareInput(predictor);
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predictor->Run();
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CompareOutput(predictor);
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}
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} // namespace paddle_infer
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