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add feature/infer demo/se resnext50 #11708
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Superjomn
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22aafcb
Init
Superjomn f5d0783
init
Superjomn 2e739cf
add automatic model deploy
Superjomn 190a871
Merge branch 'develop' of https://github.com/PaddlePaddle/Paddle into…
Superjomn 904297e
upadte
Superjomn 1c0bbfd
update
Superjomn c34da73
update
Superjomn 8b827d0
refine
tensor-tang c2d9c42
Merge branch 'Superjomn-demo/mobilenet' into feature/infer_demo/se-re…
tensor-tang c583513
add se-renext50 infer demo
tensor-tang c94cacc
update url
tensor-tang 75e5084
Merge remote-tracking branch 'ups/develop' into feature/infer_demo/se…
tensor-tang fc568f4
refine and add ocr
tensor-tang e8b0dcb
update readme
tensor-tang d509021
add check refer
tensor-tang 7449fe7
update and enable gpu test
tensor-tang 46285ed
Merge remote-tracking branch 'ups/develop' into feature/infer_demo/se…
tensor-tang 5c8e323
fix issue on gpu
tensor-tang 7e7df49
Merge remote-tracking branch 'ups/develop' into feature/infer_demo/se…
tensor-tang 33b8ea8
update threshold
tensor-tang ba0401a
disable inference mobilenet test
tensor-tang 529915c
Merge remote-tracking branch 'ups/develop' into feature/infer_demo/se…
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# Infernce Demos | ||
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Input data format: | ||
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- Each line contains a single record | ||
- Each record's format is | ||
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``` | ||
<space splitted floats as data>\t<space splitted ints as shape> | ||
``` | ||
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Follow the C++ codes in `vis_demo.cc`. | ||
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## MobileNet | ||
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To execute the demo, simply run | ||
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```sh | ||
./mobilenet_inference_demo --modeldir <model> --data <datafile> | ||
``` | ||
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## SE-ResNeXt-50 | ||
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To execute the demo, simply run | ||
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```sh | ||
./se_resnext50_inference_demo --modeldir <model> --data <datafile> | ||
``` | ||
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## OCR | ||
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To execute the demo, simply run | ||
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```sh | ||
./ocr_inference_demo --modeldir <model> --data <datafile> | ||
``` |
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// 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. | ||
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#pragma once | ||
#include <string> | ||
#include <vector> | ||
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#include "paddle/contrib/inference/paddle_inference_api.h" | ||
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namespace paddle { | ||
namespace demo { | ||
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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)); | ||
} | ||
} | ||
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/* | ||
* 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); | ||
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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(); | ||
} | ||
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} // namespace demo | ||
} // namespace paddle |
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/* 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. */ | ||
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/* | ||
* This file contains demo for mobilenet, se-resnext50 and ocr. | ||
*/ | ||
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#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" | ||
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#ifdef PADDLE_WITH_CUDA | ||
DECLARE_double(fraction_of_gpu_memory_to_use); | ||
#endif | ||
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namespace paddle { | ||
namespace demo { | ||
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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'"); | ||
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struct Record { | ||
std::vector<float> data; | ||
std::vector<int32_t> shape; | ||
}; | ||
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void split(const std::string& str, char sep, std::vector<std::string>* pieces); | ||
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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>"; | ||
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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)); | ||
} | ||
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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; | ||
} | ||
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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(); | ||
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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; | ||
} | ||
} | ||
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/* | ||
* 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 | ||
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LOG(INFO) << "init predictor"; | ||
auto predictor = | ||
CreatePaddlePredictor<NativeConfig, PaddleEngineKind::kNative>(config); | ||
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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(); | ||
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// Inference. | ||
PaddleTensor input{ | ||
.name = "xx", | ||
.shape = record.shape, | ||
.data = PaddleBuf(record.data.data(), record.data.size() * sizeof(float)), | ||
.dtype = PaddleDType::FLOAT32}; | ||
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LOG(INFO) << "run executor"; | ||
std::vector<PaddleTensor> output; | ||
predictor->Run({input}, &output); | ||
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LOG(INFO) << "output.size " << output.size(); | ||
auto& tensor = output.front(); | ||
LOG(INFO) << "output: " << SummaryTensor(tensor); | ||
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// compare with reference result | ||
CheckOutput(FLAGS_refer, tensor); | ||
} | ||
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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 |
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add description for resnet
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Got it.
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done