add feature/vis infer demos (#11708)
tensor-tang
7 years ago
committed by
Yan Chunwei
parent
8df303c09b
commit
52993878a4
@ -0,0 +1,36 @@
|
||||
# Infernce Demos
|
||||
|
||||
Input data format:
|
||||
|
||||
- Each line contains a single record
|
||||
- Each record's format is
|
||||
|
||||
```
|
||||
<space splitted floats as data>\t<space splitted ints as shape>
|
||||
```
|
||||
|
||||
Follow the C++ codes in `vis_demo.cc`.
|
||||
|
||||
## MobileNet
|
||||
|
||||
To execute the demo, simply run
|
||||
|
||||
```sh
|
||||
./mobilenet_inference_demo --modeldir <model> --data <datafile>
|
||||
```
|
||||
|
||||
## SE-ResNeXt-50
|
||||
|
||||
To execute the demo, simply run
|
||||
|
||||
```sh
|
||||
./se_resnext50_inference_demo --modeldir <model> --data <datafile>
|
||||
```
|
||||
|
||||
## OCR
|
||||
|
||||
To execute the demo, simply run
|
||||
|
||||
```sh
|
||||
./ocr_inference_demo --modeldir <model> --data <datafile>
|
||||
```
|
||||
@ -0,0 +1,68 @@
|
||||
// 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.
|
||||
|
||||
#pragma once
|
||||
#include <string>
|
||||
#include <vector>
|
||||
|
||||
#include "paddle/contrib/inference/paddle_inference_api.h"
|
||||
|
||||
namespace paddle {
|
||||
namespace demo {
|
||||
|
||||
static void split(const std::string& str,
|
||||
char sep,
|
||||
std::vector<std::string>* pieces) {
|
||||
pieces->clear();
|
||||
if (str.empty()) {
|
||||
return;
|
||||
}
|
||||
size_t pos = 0;
|
||||
size_t next = str.find(sep, pos);
|
||||
while (next != std::string::npos) {
|
||||
pieces->push_back(str.substr(pos, next - pos));
|
||||
pos = next + 1;
|
||||
next = str.find(sep, pos);
|
||||
}
|
||||
if (!str.substr(pos).empty()) {
|
||||
pieces->push_back(str.substr(pos));
|
||||
}
|
||||
}
|
||||
|
||||
/*
|
||||
* Get a summary of a PaddleTensor content.
|
||||
*/
|
||||
static std::string SummaryTensor(const PaddleTensor& tensor) {
|
||||
std::stringstream ss;
|
||||
int num_elems = tensor.data.length() / PaddleDtypeSize(tensor.dtype);
|
||||
|
||||
ss << "data[:10]\t";
|
||||
switch (tensor.dtype) {
|
||||
case PaddleDType::INT64: {
|
||||
for (int i = 0; i < std::min(num_elems, 10); i++) {
|
||||
ss << static_cast<int64_t*>(tensor.data.data())[i] << " ";
|
||||
}
|
||||
break;
|
||||
}
|
||||
case PaddleDType::FLOAT32:
|
||||
for (int i = 0; i < std::min(num_elems, 10); i++) {
|
||||
ss << static_cast<float*>(tensor.data.data())[i] << " ";
|
||||
}
|
||||
break;
|
||||
}
|
||||
return ss.str();
|
||||
}
|
||||
|
||||
} // namespace demo
|
||||
} // namespace paddle
|
||||
@ -0,0 +1,149 @@
|
||||
/* 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 for mobilenet, se-resnext50 and ocr.
|
||||
*/
|
||||
|
||||
#include <gflags/gflags.h>
|
||||
#include <glog/logging.h> // use glog instead of PADDLE_ENFORCE to avoid importing other paddle header files.
|
||||
#include <gtest/gtest.h>
|
||||
#include <fstream>
|
||||
#include <iostream>
|
||||
#include "paddle/contrib/inference/demo/utils.h"
|
||||
#include "paddle/contrib/inference/paddle_inference_api.h"
|
||||
|
||||
#ifdef PADDLE_WITH_CUDA
|
||||
DECLARE_double(fraction_of_gpu_memory_to_use);
|
||||
#endif
|
||||
|
||||
namespace paddle {
|
||||
namespace demo {
|
||||
|
||||
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'");
|
||||
|
||||
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) {
|
||||
LOG(INFO) << "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));
|
||||
}
|
||||
LOG(INFO) << "data size " << record.data.size();
|
||||
LOG(INFO) << "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);
|
||||
LOG(INFO) << "predictor output numel " << numel;
|
||||
LOG(INFO) << "reference output numel " << refer.data.size();
|
||||
EXPECT_EQ(numel, refer.data.size());
|
||||
switch (output.dtype) {
|
||||
case PaddleDType::INT64: {
|
||||
for (size_t i = 0; i < numel; ++i) {
|
||||
EXPECT_EQ(static_cast<int64_t*>(output.data.data())[i], refer.data[i]);
|
||||
}
|
||||
break;
|
||||
}
|
||||
case PaddleDType::FLOAT32:
|
||||
for (size_t i = 0; i < numel; ++i) {
|
||||
EXPECT_NEAR(
|
||||
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) {
|
||||
NativeConfig config;
|
||||
config.param_file = FLAGS_modeldir + "/__params__";
|
||||
config.prog_file = FLAGS_modeldir + "/__model__";
|
||||
config.use_gpu = use_gpu;
|
||||
config.device = 0;
|
||||
#ifdef PADDLE_WITH_CUDA
|
||||
config.fraction_of_gpu_memory = FLAGS_fraction_of_gpu_memory_to_use;
|
||||
#endif
|
||||
|
||||
LOG(INFO) << "init predictor";
|
||||
auto predictor =
|
||||
CreatePaddlePredictor<NativeConfig, PaddleEngineKind::kNative>(config);
|
||||
|
||||
LOG(INFO) << "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{
|
||||
.name = "xx",
|
||||
.shape = record.shape,
|
||||
.data = PaddleBuf(record.data.data(), record.data.size() * sizeof(float)),
|
||||
.dtype = PaddleDType::FLOAT32};
|
||||
|
||||
LOG(INFO) << "run executor";
|
||||
std::vector<PaddleTensor> output;
|
||||
predictor->Run({input}, &output);
|
||||
|
||||
LOG(INFO) << "output.size " << output.size();
|
||||
auto& tensor = output.front();
|
||||
LOG(INFO) << "output: " << SummaryTensor(tensor);
|
||||
|
||||
// compare with reference result
|
||||
CheckOutput(FLAGS_refer, tensor);
|
||||
}
|
||||
|
||||
TEST(demo, vis_demo_cpu) { Main(false /*use_gpu*/); }
|
||||
#ifdef PADDLE_WITH_CUDA
|
||||
TEST(demo, vis_demo_gpu) { Main(true /*use_gpu*/); }
|
||||
#endif
|
||||
} // namespace demo
|
||||
} // namespace paddle
|
||||
Loading…
Reference in new issue