未验证 提交 fedb609d 编写于 作者: W Wilber 提交者: GitHub

[cherry-pick] fluid-lite subgraph resnet50 test. test=develop test=release/1.7 (#22224)

[cherry-pick] #22191
- 添加了fluid-lite子图方式运行resnet的单测
- 修改了依赖Lite的git commit id
上级 3acb9956
...@@ -43,7 +43,7 @@ if (NOT LITE_SOURCE_DIR OR NOT LITE_BINARY_DIR) ...@@ -43,7 +43,7 @@ if (NOT LITE_SOURCE_DIR OR NOT LITE_BINARY_DIR)
${LITE_PROJECT} ${LITE_PROJECT}
${EXTERNAL_PROJECT_LOG_ARGS} ${EXTERNAL_PROJECT_LOG_ARGS}
GIT_REPOSITORY "https://github.com/PaddlePaddle/Paddle-Lite.git" GIT_REPOSITORY "https://github.com/PaddlePaddle/Paddle-Lite.git"
GIT_TAG 947cda26637d46dc23f4e39d2b52e7d9a1fa6eef GIT_TAG b30dc65b264f7bc3753ba862ff4e529ea2af6665
PREFIX ${LITE_SOURCES_DIR} PREFIX ${LITE_SOURCES_DIR}
UPDATE_COMMAND "" UPDATE_COMMAND ""
BUILD_COMMAND ${LITE_BUILD_COMMAND} BUILD_COMMAND ${LITE_BUILD_COMMAND}
......
...@@ -367,6 +367,10 @@ download_data(${LITE_MODEL_INSTALL_DIR} "mul_model_fp32.tgz") ...@@ -367,6 +367,10 @@ download_data(${LITE_MODEL_INSTALL_DIR} "mul_model_fp32.tgz")
inference_analysis_test(lite_mul_model_test SRCS lite_mul_model_test.cc inference_analysis_test(lite_mul_model_test SRCS lite_mul_model_test.cc
EXTRA_DEPS ${INFERENCE_EXTRA_DEPS} EXTRA_DEPS ${INFERENCE_EXTRA_DEPS}
ARGS --infer_model=${LITE_MODEL_INSTALL_DIR}) ARGS --infer_model=${LITE_MODEL_INSTALL_DIR})
inference_analysis_test(lite_resnet50_test SRCS lite_resnet50_test.cc
EXTRA_DEPS ${INFERENCE_EXTRA_DEPS}
ARGS --infer_model=${RESNET50_MODEL_DIR})
inference_analysis_test(test_analyzer_capi SRCS analyzer_capi_tester.cc inference_analysis_test(test_analyzer_capi SRCS analyzer_capi_tester.cc
EXTRA_DEPS ${INFERENCE_EXTRA_DEPS} paddle_fluid_c EXTRA_DEPS ${INFERENCE_EXTRA_DEPS} paddle_fluid_c
ARGS --infer_model=${RESNET50_MODEL_DIR}/model) ARGS --infer_model=${RESNET50_MODEL_DIR}/model)
......
/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License. */
#include <gflags/gflags.h>
#include <glog/logging.h>
#include <gtest/gtest.h>
#include <cmath>
#include "paddle/fluid/inference/tests/api/tester_helper.h"
namespace paddle {
namespace inference {
TEST(AnalysisPredictor, use_gpu) {
std::string model_dir = FLAGS_infer_model + "/" + "model";
AnalysisConfig config;
config.EnableUseGpu(100, 0);
config.SetModel(model_dir + "/model", model_dir + "/params");
config.EnableLiteEngine(paddle::AnalysisConfig::Precision::kFloat32);
std::vector<PaddleTensor> inputs;
auto predictor = CreatePaddlePredictor(config);
const int batch = 1;
const int channel = 3;
const int height = 318;
const int width = 318;
const int input_num = batch * channel * height * width;
std::vector<float> input(input_num, 1);
PaddleTensor in;
in.shape = {1, 3, 318, 318};
in.data =
PaddleBuf(static_cast<void*>(input.data()), input_num * sizeof(float));
in.dtype = PaddleDType::FLOAT32;
inputs.emplace_back(in);
std::vector<PaddleTensor> outputs;
ASSERT_TRUE(predictor->Run(inputs, &outputs));
const std::vector<float> truth_values = {
127.780396, 738.16656, 1013.2264, -438.17206, 366.4022, 927.66187,
736.2241, -633.68567, -329.92737, -430.15637, -633.0639, -146.54858,
-1324.2804, -1349.3661, -242.67671, 117.44864, -801.7251, -391.51495,
-404.8202, 454.16132, 515.48206, -133.03114, 69.293076, 590.09753,
-1434.6917, -1070.8903, 307.0744, 400.52573, -316.12177, -587.1265,
-161.05742, 800.3663, -96.47157, 748.708, 868.17645, -447.9403,
112.73656, 1127.1992, 47.43518, 677.7219, 593.1881, -336.4011,
551.3634, 397.82474, 78.39835, -715.4006, 405.96988, 404.25684,
246.01978, -8.430191, 131.36617, -648.0528};
const size_t expected_size = 1;
EXPECT_EQ(outputs.size(), expected_size);
float* data_o = static_cast<float*>(outputs[0].data.data());
for (size_t j = 0; j < outputs[0].data.length() / sizeof(float); j += 10) {
EXPECT_NEAR((data_o[j] - truth_values[j / 10]) / truth_values[j / 10], 0.,
10e-5);
}
}
} // namespace inference
} // namespace paddle
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