提交 efa5bac7 编写于 作者: N nhzlx

fix demo_ci bug in vis_demo.cc

test=develop
上级 5428cb99
......@@ -100,19 +100,17 @@ for WITH_STATIC_LIB in ON OFF; do
rm -rf *
cmake .. -DPADDLE_LIB=${PADDLE_ROOT}/build/fluid_install_dir/ \
-DWITH_MKL=$TURN_ON_MKL \
-DDEMO_NAME=vis_demo \
-DDEMO_NAME=trt_mobilenet_demo \
-DWITH_GPU=$TEST_GPU_CPU \
-DWITH_STATIC_LIB=$WITH_STATIC_LIB \
-DUSE_TENSORRT=$USE_TENSORRT \
-DTENSORRT_INCLUDE_DIR=$TENSORRT_INCLUDE_DIR \
-DTENSORRT_LIB_DIR=$TENSORRT_LIB_DIR
make -j
./vis_demo \
./trt_mobilenet_demo \
--modeldir=$DATA_DIR/mobilenet/model \
--data=$DATA_DIR/mobilenet/data.txt \
--refer=$DATA_DIR/mobilenet/result.txt \
--use_gpu=true \
--use_trt=true
--refer=$DATA_DIR/mobilenet/result.txt
fi
done
set +x
/* 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. */
/*
* This file contains demo of mobilenet for tensorrt.
*/
#include <gflags/gflags.h>
#include <glog/logging.h> // use glog instead of CHECK to avoid importing other paddle header files.
#include <fstream>
#include <iostream>
// #include "paddle/fluid/platform/enforce.h"
#include "paddle/fluid/inference/demo_ci/utils.h"
#ifdef PADDLE_WITH_CUDA
DECLARE_double(fraction_of_gpu_memory_to_use);
#endif
DEFINE_string(modeldir, "", "Directory of the inference model.");
DEFINE_string(refer, "", "path to reference result for comparison.");
DEFINE_string(
data, "",
"path of data; each line is a record, format is "
"'<space splitted floats as data>\t<space splitted ints as shape'");
namespace paddle {
namespace demo {
/*
* Use the native fluid engine to inference the demo.
*/
void Main() {
std::unique_ptr<PaddlePredictor> predictor;
paddle::contrib::MixedRTConfig config;
config.param_file = FLAGS_modeldir + "/__params__";
config.prog_file = FLAGS_modeldir + "/__model__";
config.use_gpu = true;
config.device = 0;
config.max_batch_size = 1;
config.fraction_of_gpu_memory = 0.1; // set by yourself
predictor = CreatePaddlePredictor<paddle::contrib::MixedRTConfig>(config);
VLOG(3) << "begin to process data";
// Just a single batch of data.
std::string line;
std::ifstream file(FLAGS_data);
std::getline(file, line);
auto record = ProcessALine(line);
file.close();
// Inference.
PaddleTensor input;
input.shape = record.shape;
input.data =
PaddleBuf(record.data.data(), record.data.size() * sizeof(float));
input.dtype = PaddleDType::FLOAT32;
VLOG(3) << "run executor";
std::vector<PaddleTensor> output;
predictor->Run({input}, &output, 1);
VLOG(3) << "output.size " << output.size();
auto& tensor = output.front();
VLOG(3) << "output: " << SummaryTensor(tensor);
// compare with reference result
CheckOutput(FLAGS_refer, tensor);
}
} // namespace demo
} // namespace paddle
int main(int argc, char** argv) {
google::ParseCommandLineFlags(&argc, &argv, true);
paddle::demo::Main();
return 0;
}
......@@ -14,6 +14,8 @@
#pragma once
#include <algorithm>
#include <fstream>
#include <iostream>
#include <string>
#include <vector>
#include "paddle/fluid/inference/paddle_inference_api.h"
......@@ -21,6 +23,11 @@
namespace paddle {
namespace demo {
struct Record {
std::vector<float> data;
std::vector<int32_t> shape;
};
static void split(const std::string& str, char sep,
std::vector<std::string>* pieces) {
pieces->clear();
......@@ -39,6 +46,58 @@ static void split(const std::string& str, char sep,
}
}
Record ProcessALine(const std::string& line) {
VLOG(3) << "process a line";
std::vector<std::string> columns;
split(line, '\t', &columns);
CHECK_EQ(columns.size(), 2UL)
<< "data format error, should be <data>\t<shape>";
Record record;
std::vector<std::string> data_strs;
split(columns[0], ' ', &data_strs);
for (auto& d : data_strs) {
record.data.push_back(std::stof(d));
}
std::vector<std::string> shape_strs;
split(columns[1], ' ', &shape_strs);
for (auto& s : shape_strs) {
record.shape.push_back(std::stoi(s));
}
VLOG(3) << "data size " << record.data.size();
VLOG(3) << "data shape size " << record.shape.size();
return record;
}
void CheckOutput(const std::string& referfile, const PaddleTensor& output) {
std::string line;
std::ifstream file(referfile);
std::getline(file, line);
auto refer = ProcessALine(line);
file.close();
size_t numel = output.data.length() / PaddleDtypeSize(output.dtype);
VLOG(3) << "predictor output numel " << numel;
VLOG(3) << "reference output numel " << refer.data.size();
CHECK_EQ(numel, refer.data.size());
switch (output.dtype) {
case PaddleDType::INT64: {
for (size_t i = 0; i < numel; ++i) {
CHECK_EQ(static_cast<int64_t*>(output.data.data())[i], refer.data[i]);
}
break;
}
case PaddleDType::FLOAT32:
for (size_t i = 0; i < numel; ++i) {
CHECK_LT(
fabs(static_cast<float*>(output.data.data())[i] - refer.data[i]),
1e-5);
}
break;
}
}
/*
* Get a summary of a PaddleTensor content.
*/
......
......@@ -18,10 +18,6 @@ limitations under the License. */
#include <gflags/gflags.h>
#include <glog/logging.h> // use glog instead of CHECK to avoid importing other paddle header files.
#include <fstream>
#include <iostream>
// #include "paddle/fluid/platform/enforce.h"
#include "paddle/fluid/inference/demo_ci/utils.h"
#ifdef PADDLE_WITH_CUDA
......@@ -34,99 +30,28 @@ DEFINE_string(
"path of data; each line is a record, format is "
"'<space splitted floats as data>\t<space splitted ints as shape'");
DEFINE_bool(use_gpu, false, "Whether use gpu.");
DEFINE_bool(use_trt, false, "Whether use trt.");
namespace paddle {
namespace demo {
struct Record {
std::vector<float> data;
std::vector<int32_t> shape;
};
void split(const std::string& str, char sep, std::vector<std::string>* pieces);
Record ProcessALine(const std::string& line) {
VLOG(3) << "process a line";
std::vector<std::string> columns;
split(line, '\t', &columns);
CHECK_EQ(columns.size(), 2UL)
<< "data format error, should be <data>\t<shape>";
Record record;
std::vector<std::string> data_strs;
split(columns[0], ' ', &data_strs);
for (auto& d : data_strs) {
record.data.push_back(std::stof(d));
}
std::vector<std::string> shape_strs;
split(columns[1], ' ', &shape_strs);
for (auto& s : shape_strs) {
record.shape.push_back(std::stoi(s));
}
VLOG(3) << "data size " << record.data.size();
VLOG(3) << "data shape size " << record.shape.size();
return record;
}
void CheckOutput(const std::string& referfile, const PaddleTensor& output) {
std::string line;
std::ifstream file(referfile);
std::getline(file, line);
auto refer = ProcessALine(line);
file.close();
size_t numel = output.data.length() / PaddleDtypeSize(output.dtype);
VLOG(3) << "predictor output numel " << numel;
VLOG(3) << "reference output numel " << refer.data.size();
CHECK_EQ(numel, refer.data.size());
switch (output.dtype) {
case PaddleDType::INT64: {
for (size_t i = 0; i < numel; ++i) {
CHECK_EQ(static_cast<int64_t*>(output.data.data())[i], refer.data[i]);
}
break;
}
case PaddleDType::FLOAT32:
for (size_t i = 0; i < numel; ++i) {
CHECK_LT(
fabs(static_cast<float*>(output.data.data())[i] - refer.data[i]),
1e-5);
}
break;
}
}
/*
* Use the native fluid engine to inference the demo.
*/
void Main(bool use_gpu, bool use_trt) {
void Main(bool use_gpu) {
std::unique_ptr<PaddlePredictor> predictor;
if (!use_trt) {
NativeConfig config;
config.param_file = FLAGS_modeldir + "/__params__";
config.prog_file = FLAGS_modeldir + "/__model__";
config.use_gpu = use_gpu;
config.device = 0;
if (FLAGS_use_gpu) {
config.fraction_of_gpu_memory = 0.1; // set by yourself
}
VLOG(3) << "init predictor";
predictor =
CreatePaddlePredictor<NativeConfig, PaddleEngineKind::kNative>(config);
} else {
paddle::contrib::MixedRTConfig config;
config.param_file = FLAGS_modeldir + "/__params__";
config.prog_file = FLAGS_modeldir + "/__model__";
config.use_gpu = true;
config.device = 0;
config.max_batch_size = 1;
NativeConfig config;
config.param_file = FLAGS_modeldir + "/__params__";
config.prog_file = FLAGS_modeldir + "/__model__";
config.use_gpu = use_gpu;
config.device = 0;
if (FLAGS_use_gpu) {
config.fraction_of_gpu_memory = 0.1; // set by yourself
predictor = CreatePaddlePredictor<paddle::contrib::MixedRTConfig>(config);
}
VLOG(3) << "init predictor";
predictor =
CreatePaddlePredictor<NativeConfig, PaddleEngineKind::kNative>(config);
VLOG(3) << "begin to process data";
// Just a single batch of data.
std::string line;
......@@ -159,12 +84,10 @@ void Main(bool use_gpu, bool use_trt) {
int main(int argc, char** argv) {
google::ParseCommandLineFlags(&argc, &argv, true);
if (FLAGS_use_gpu && FLAGS_use_trt) {
paddle::demo::Main(true /*use_gpu*/, true);
} else if (FLAGS_use_gpu) {
paddle::demo::Main(true /*use_gpu*/, false);
if (FLAGS_use_gpu) {
paddle::demo::Main(true /*use_gpu*/);
} else {
paddle::demo::Main(false /*use_gpu*/, false /*use_tensorrt*/);
paddle::demo::Main(false /*use_gpu*/);
}
return 0;
}
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