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add paddle detection model in PR-CI-INFERENCE #34986

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Aug 18, 2021
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2 changes: 1 addition & 1 deletion paddle/fluid/inference/api/analysis_config.cc
Original file line number Diff line number Diff line change
Expand Up @@ -740,7 +740,7 @@ std::string AnalysisConfig::Summary() {
// cpu info
os.InsertRow(
{"cpu_math_thread", std::to_string(cpu_math_library_num_threads_)});
os.InsertRow({"enable_mkdlnn", use_mkldnn_ ? "true" : "false"});
os.InsertRow({"enable_mkldnn", use_mkldnn_ ? "true" : "false"});
os.InsertRow(
{"mkldnn_cache_capacity", std::to_string(mkldnn_cache_capacity_)});
os.InsetDivider();
Expand Down
122 changes: 75 additions & 47 deletions paddle/fluid/inference/tests/infer_ut/run.sh
Original file line number Diff line number Diff line change
Expand Up @@ -24,8 +24,14 @@ MSVC_STATIC_CRT=$6
inference_install_dir=${PADDLE_ROOT}/build/paddle_inference_install_dir
EXIT_CODE=0 # init default exit code

export RED='\033[0;31m' # red color
export NC='\033[0m' # no color
export YELLOW='\033[33m' # yellow color

cd `dirname $0`
current_dir=`pwd`
build_dir=${current_dir}/build
log_dir=${current_dir}/log
if [ $2 == ON ]; then
# You can export yourself if move the install path
MKL_LIB=${inference_install_dir}/third_party/install/mklml/lib
Expand Down Expand Up @@ -83,43 +89,52 @@ for model_name in $nlp_download_list; do
download $url_prefix $model_name
done

det_download_list='yolov3 ppyolo_mbv3 ppyolov2_r50vd'
for model_name in $det_download_list; do
url_prefix="https://paddle-qa.bj.bcebos.com/inference_model/2.1.1/detection"
download $url_prefix $model_name
done

function compile_test() {
mkdir -p ${build_dir}
cd ${build_dir}
TEST_NAME=$1
cmake .. -DPADDLE_LIB=${inference_install_dir} \
-DWITH_MKL=$TURN_ON_MKL \
-DDEMO_NAME=${TEST_NAME} \
-DWITH_GPU=$TEST_GPU_CPU \
-DWITH_STATIC_LIB=OFF \
-DUSE_TENSORRT=$USE_TENSORRT \
-DTENSORRT_ROOT=$TENSORRT_ROOT_DIR \
-DWITH_GTEST=ON
make -j$(nproc)
cd -
}


# compile and run test
cd $current_dir
mkdir -p build
cd build
mkdir -p ${build_dir}
mkdir -p ${log_dir}
cd ${build_dir}
rm -rf *

# ---------tensorrt resnet50 on linux---------
# ---------tensorrt gpu tests on linux---------
if [ $USE_TENSORRT == ON -a $TEST_GPU_CPU == ON ]; then
rm -rf *
cmake .. -DPADDLE_LIB=${inference_install_dir} \
-DWITH_MKL=$TURN_ON_MKL \
-DDEMO_NAME=test_resnet50 \
-DWITH_GPU=$TEST_GPU_CPU \
-DWITH_STATIC_LIB=OFF \
-DUSE_TENSORRT=$USE_TENSORRT \
-DTENSORRT_ROOT=$TENSORRT_ROOT_DIR \
-DWITH_GTEST=ON
make -j$(nproc)

printf "${YELLOW} start test_resnet50 ${NC} \n";
compile_test "test_resnet50"
./test_resnet50 \
--modeldir=$DATA_DIR/resnet50/resnet50 \
--gtest_output=xml:test_resnet50.xml
if [ $? -ne 0 ]; then
echo "test_resnet50 runs failed" >> ${current_dir}/build/test_summary.txt
EXIT_CODE=1
fi
fi

# ---------tensorrt det_mv3_db on linux---------
if [ $USE_TENSORRT == ON -a $TEST_GPU_CPU == ON ]; then
cmake .. -DPADDLE_LIB=${inference_install_dir} \
-DWITH_MKL=$TURN_ON_MKL \
-DDEMO_NAME=test_det_mv3_db \
-DWITH_GPU=$TEST_GPU_CPU \
-DWITH_STATIC_LIB=OFF \
-DUSE_TENSORRT=$USE_TENSORRT \
-DTENSORRT_ROOT=$TENSORRT_ROOT_DIR \
-DWITH_GTEST=ON
printf "${YELLOW} start test_det_mv3_db ${NC} \n";
compile_test "test_det_mv3_db"
make -j$(nproc)
./test_det_mv3_db \
--modeldir=$DATA_DIR/ocr_det_mv3_db/ocr_det_mv3_db \
Expand All @@ -128,48 +143,61 @@ if [ $USE_TENSORRT == ON -a $TEST_GPU_CPU == ON ]; then
echo "test_det_mv3_db runs failed" >> ${current_dir}/build/test_summary.txt
EXIT_CODE=1
fi
fi

# ---------tensorrt LeViT on linux---------
if [ $USE_TENSORRT == ON -a $TEST_GPU_CPU == ON ]; then
cmake .. -DPADDLE_LIB=${inference_install_dir} \
-DWITH_MKL=$TURN_ON_MKL \
-DDEMO_NAME=test_LeViT \
-DWITH_GPU=$TEST_GPU_CPU \
-DWITH_STATIC_LIB=OFF \
-DUSE_TENSORRT=$USE_TENSORRT \
-DTENSORRT_ROOT=$TENSORRT_ROOT_DIR \
-DWITH_GTEST=ON
make -j$(nproc)
printf "${YELLOW} start test_LeViT ${NC} \n";
compile_test "test_LeViT"
./test_LeViT \
--modeldir=$DATA_DIR/LeViT/LeViT \
--gtest_output=xml:test_LeViT.xml
if [ $? -ne 0 ]; then
echo "test_LeViT runs failed" >> ${current_dir}/build/test_summary.txt
EXIT_CODE=1
fi
fi

# ---------gpu ernie_text_cls on linux---------
if [ $USE_TENSORRT == ON -a $TEST_GPU_CPU == ON ]; then
cmake .. -DPADDLE_LIB=${inference_install_dir} \
-DWITH_MKL=$TURN_ON_MKL \
-DDEMO_NAME=test_ernie_text_cls \
-DWITH_GPU=$TEST_GPU_CPU \
-DWITH_STATIC_LIB=OFF \
-DUSE_TENSORRT=$USE_TENSORRT \
-DTENSORRT_ROOT=$TENSORRT_ROOT_DIR \
-DWITH_GTEST=ON
make -j$(nproc)
printf "${YELLOW} start test_ernie_text_cls ${NC} \n";
compile_test "test_ernie_text_cls"
./test_ernie_text_cls \
--modeldir=$DATA_DIR/ernie_text_cls/ernie_text_cls \
--gtest_output=xml:test_ernie_text_cls.xml
if [ $? -ne 0 ]; then
echo "test_ernie_text_cls runs failed" >> ${current_dir}/build/test_summary.txt
EXIT_CODE=1
fi

printf "${YELLOW} start test_yolov3 ${NC} \n";
compile_test "test_yolov3"
./test_yolov3 \
--modeldir=$DATA_DIR/yolov3/yolov3 \
--gtest_output=xml:test_yolov3.xml
if [ $? -ne 0 ]; then
echo "test_yolov3 runs failed" >> ${current_dir}/build/test_summary.txt
EXIT_CODE=1
fi

printf "${YELLOW} start test_ppyolo_mbv3 ${NC} \n";
compile_test "test_ppyolo_mbv3"
./test_ppyolo_mbv3 \
--modeldir=$DATA_DIR/ppyolo_mbv3/ppyolo_mbv3 \
--gtest_output=xml:test_ppyolo_mbv3.xml
if [ $? -ne 0 ]; then
echo "test_ppyolo_mbv3 runs failed" >> ${current_dir}/build/test_summary.txt
EXIT_CODE=1
fi

printf "${YELLOW} start test_ppyolov2_r50vd ${NC} \n";
compile_test "test_ppyolov2_r50vd"
./test_ppyolov2_r50vd \
--modeldir=$DATA_DIR/ppyolov2_r50vd/ppyolov2_r50vd \
--gtest_output=xml:test_ppyolov2_r50vd.xml
if [ $? -ne 0 ]; then
echo "test_ppyolov2_r50vd runs failed" >> ${current_dir}/build/test_summary.txt
EXIT_CODE=1
fi

cp ./*.xml ${log_dir};
fi


if [[ -f ${current_dir}/build/test_summary.txt ]];then
echo "=====================test summary======================"
cat ${current_dir}/build/test_summary.txt
Expand Down
156 changes: 156 additions & 0 deletions paddle/fluid/inference/tests/infer_ut/test_ppyolo_mbv3.cc
Original file line number Diff line number Diff line change
@@ -0,0 +1,156 @@
// Copyright (c) 2021 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 "test_suite.h" // NOLINT

DEFINE_string(modeldir, "", "Directory of the inference model.");

namespace paddle_infer {

std::map<std::string, paddle::test::Record> PrepareInput(int batch_size) {
// init input data
int channel = 3;
int width = 320;
int height = 320;
paddle::test::Record image, im_shape, scale_factor;
int input_num = batch_size * channel * width * height;
int shape_num = batch_size * 2;
std::vector<float> image_data(input_num, 1);
for (int i = 1; i < input_num + 1; ++i) {
image_data[i] = i % 10 * 0.5;
}
std::vector<float> im_shape_data(shape_num, 1);
std::vector<float> scale_factor_data(shape_num, 1);

image.data = std::vector<float>(image_data.begin(), image_data.end());
image.shape = std::vector<int>{batch_size, channel, width, height};
image.type = paddle::PaddleDType::FLOAT32;

im_shape.data =
std::vector<float>(im_shape_data.begin(), im_shape_data.end());
im_shape.shape = std::vector<int>{batch_size, 2};
im_shape.type = paddle::PaddleDType::FLOAT32;

scale_factor.data =
std::vector<float>(scale_factor_data.begin(), scale_factor_data.end());
scale_factor.shape = std::vector<int>{batch_size, 2};
scale_factor.type = paddle::PaddleDType::FLOAT32;

std::map<std::string, paddle::test::Record> input_data_map;
input_data_map.insert({"image", image});
input_data_map.insert({"im_shape", im_shape});
input_data_map.insert({"scale_factor", scale_factor});

return input_data_map;
}

TEST(test_ppyolo_mbv3, multi_thread4_trt_fp32_bz2) {
int thread_num = 4;
// init input data
auto input_data_map = PrepareInput(2);
// init output data
std::map<std::string, paddle::test::Record> infer_output_data,
truth_output_data;
// prepare groudtruth config
paddle_infer::Config config, config_no_ir;
config_no_ir.SetModel(FLAGS_modeldir + "/model.pdmodel",
FLAGS_modeldir + "/model.pdiparams");
config_no_ir.EnableUseGpu(100, 0);
config_no_ir.SwitchIrOptim(false);
// prepare inference config
config.SetModel(FLAGS_modeldir + "/model.pdmodel",
FLAGS_modeldir + "/model.pdiparams");
config.EnableUseGpu(100, 0);
config.EnableTensorRtEngine(
1 << 20, 2, 3, paddle_infer::PrecisionType::kFloat32, false, false);
LOG(INFO) << config.Summary();
// get groudtruth by disbale ir
paddle_infer::services::PredictorPool pred_pool_no_ir(config_no_ir, 1);
SingleThreadPrediction(pred_pool_no_ir.Retrive(0), &input_data_map,
&truth_output_data, 1);

// get infer results from multi threads
std::vector<std::thread> threads;
services::PredictorPool pred_pool(config, thread_num);
for (int i = 0; i < thread_num; ++i) {
threads.emplace_back(paddle::test::SingleThreadPrediction,
pred_pool.Retrive(i), &input_data_map,
&infer_output_data, 2);
}

// thread join & check outputs
for (int i = 0; i < thread_num; ++i) {
LOG(INFO) << "join tid : " << i;
threads[i].join();
CompareRecord(&truth_output_data, &infer_output_data, 1e-2);
// TODO(OliverLPH): precision set to 1e-2 since input is fake, change to
// real input later
}

std::cout << "finish multi-thread test" << std::endl;
}

TEST(DISABLED_test_ppyolo_mbv3, multi_thread4_mkl_bz2) {
// TODO(OliverLPH): mkldnn multi thread will fail
int thread_num = 4;
// init input data
auto input_data_map = PrepareInput(2);
// init output data
std::map<std::string, paddle::test::Record> infer_output_data,
truth_output_data;
// prepare groudtruth config
paddle_infer::Config config, config_no_ir;
config_no_ir.SetModel(FLAGS_modeldir + "/model.pdmodel",
FLAGS_modeldir + "/model.pdiparams");
config_no_ir.DisableGpu();
config_no_ir.SwitchIrOptim(false);
// prepare inference config
config.SetModel(FLAGS_modeldir + "/model.pdmodel",
FLAGS_modeldir + "/model.pdiparams");
config.DisableGpu();
config.EnableMKLDNN();
config.SetMkldnnCacheCapacity(10);
config.SetCpuMathLibraryNumThreads(10);
LOG(INFO) << config.Summary();
// get groudtruth by disbale ir
paddle_infer::services::PredictorPool pred_pool_no_ir(config_no_ir, 1);
SingleThreadPrediction(pred_pool_no_ir.Retrive(0), &input_data_map,
&truth_output_data, 1);

// get infer results from multi threads
std::vector<std::thread> threads;
services::PredictorPool pred_pool(config, thread_num);
for (int i = 0; i < thread_num; ++i) {
threads.emplace_back(paddle::test::SingleThreadPrediction,
pred_pool.Retrive(i), &input_data_map,
&infer_output_data, 2);
}

// thread join & check outputs
for (int i = 0; i < thread_num; ++i) {
LOG(INFO) << "join tid : " << i;
threads[i].join();
CompareRecord(&truth_output_data, &infer_output_data, 1e-4);
}

std::cout << "finish multi-thread test" << std::endl;
}

} // namespace paddle_infer

int main(int argc, char** argv) {
::testing::InitGoogleTest(&argc, argv);
::google::ParseCommandLineFlags(&argc, &argv, true);
return RUN_ALL_TESTS();
}
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