MNN/tools/converter/source/TestConvertResult.cpp

237 lines
8.7 KiB
C++
Raw Normal View History

2020-02-26 09:57:17 +08:00
//
// TestConvertResult.cpp
// MNNConverter
//
// Created by MNN on 2020/01/22.
// Copyright © 2018, Alibaba Group Holding Limited
//
#include "MNN_generated.h"
#include "caffeConverter.hpp"
#include "liteConverter.hpp"
#include "onnxConverter.hpp"
#include "tensorflowConverter.hpp"
#include <MNN/expr/Expr.hpp>
#include <MNN/expr/ExprCreator.hpp>
#include "PostConverter.hpp"
#include "rapidjson/document.h"
2020-11-05 16:41:56 +08:00
#include "options.hpp"
2020-02-26 09:57:17 +08:00
#include <fstream>
#include <sstream>
2020-11-05 16:41:56 +08:00
#include "config.hpp"
#include "common/Global.hpp"
2020-02-26 09:57:17 +08:00
using namespace MNN::Express;
int main(int argc, char *argv[]) {
if (argc < 3) {
2020-11-05 16:41:56 +08:00
MNN_ERROR("Usage: ./TestConvertResult [Onnx, Tf] ${Dir}\n");
2020-02-26 09:57:17 +08:00
return 0;
}
2020-11-05 16:41:56 +08:00
std::string inputType = argv[1];
2020-02-26 09:57:17 +08:00
std::string directName = argv[2];
2020-11-05 16:41:56 +08:00
auto inputModel = modelConfig::ONNX;
auto converter = onnx2MNNNet;
auto suffix = ".onnx";
auto dataFormat = NCHW;
if (inputType == "Tf") {
inputModel = modelConfig::TENSORFLOW;
converter = tensorflow2MNNNet;
suffix = ".pb";
dataFormat = NHWC;
}
2020-02-26 09:57:17 +08:00
MNN_PRINT("Test %s\n", directName.c_str());
std::string defaultCacheFile = ".___temp.mnn";
{
2020-11-05 16:41:56 +08:00
modelConfig modelPath;
modelPath.model = inputModel;
Global<modelConfig>::Reset(&modelPath);
auto options = common::DefaultOptions();
2020-02-26 09:57:17 +08:00
std::ostringstream modelNameOs;
2020-11-05 16:41:56 +08:00
modelNameOs << directName << "/test" << suffix;
2020-02-26 09:57:17 +08:00
std::unique_ptr<MNN::NetT> netT = std::unique_ptr<MNN::NetT>(new MNN::NetT());
2020-11-05 16:41:56 +08:00
converter(modelNameOs.str().c_str(), "Test", options, netT);
2020-02-26 09:57:17 +08:00
std::unique_ptr<MNN::NetT> newNet = optimizeNet(netT, false);
flatbuffers::FlatBufferBuilder builderOutput(1024);
builderOutput.ForceDefaults(true);
auto len = MNN::Net::Pack(builderOutput, newNet.get());
builderOutput.Finish(len);
int sizeOutput = builderOutput.GetSize();
auto bufferOutput = builderOutput.GetBufferPointer();
std::ofstream output(defaultCacheFile.c_str(), std::ofstream::binary);
output.write((const char*)bufferOutput, sizeOutput);
}
rapidjson::Document document;
std::map<std::string, float> inputInfo;
2020-11-05 16:41:56 +08:00
std::map<std::string, std::vector<int>> inputShape;
2020-02-26 09:57:17 +08:00
std::vector<std::string> inputNames;
std::vector<std::string> outputNames;
{
std::ostringstream jsonNameOs;
jsonNameOs << directName << "/input.json";
std::ifstream fileNames(jsonNameOs.str().c_str());
std::ostringstream output;
output << fileNames.rdbuf();
auto outputStr = output.str();
document.Parse(outputStr.c_str());
if (document.HasParseError()) {
MNN_ERROR("Invalid json\n");
return 0;
}
if (document.HasMember("inputs")) {
auto inputsInfo = document["inputs"].GetArray();
for (auto iter = inputsInfo.begin(); iter !=inputsInfo.end(); iter++) {
auto obj = iter->GetObject();
std::string name = obj["name"].GetString();
inputNames.emplace_back(name);
MNN_PRINT("%s\n", name.c_str());
if (obj.HasMember("value")) {
float value = obj["value"].GetFloat();
inputInfo.insert(std::make_pair(name, value));
}
2020-11-05 16:41:56 +08:00
if (obj.HasMember("shape")) {
auto dims = obj["shape"].GetArray();
std::vector<int> shapes;
for (auto iter = dims.begin(); iter != dims.end(); iter++) {
shapes.emplace_back(iter->GetInt());
}
inputShape.insert(std::make_pair(name, shapes));
}
2020-02-26 09:57:17 +08:00
}
}
if (document.HasMember("outputs")) {
auto array = document["outputs"].GetArray();
for (auto iter = array.begin(); iter !=array.end(); iter++) {
std::string name = iter->GetString();
MNN_PRINT("output: %s\n", name.c_str());
outputNames.emplace_back(name);
}
}
}
auto varMap = Variable::loadMap(defaultCacheFile.c_str());
for (auto inputName : inputNames) {
if (varMap.find(inputName) == varMap.end()) {
MNN_ERROR("TESTERROR Can't find var: %s\n", inputName.c_str());
continue;
}
2020-11-05 16:41:56 +08:00
// Resize
auto shapeIter = inputShape.find(inputName);
if (shapeIter != inputShape.end()) {
auto s = shapeIter->second;
varMap[inputName]->resize(s);
}
varMap[inputName] = _ChangeInputFormat(varMap[inputName], dataFormat);
#define LOAD_DATA(TYPE)\
if (inputInfo.find(inputName) != inputInfo.end()) {\
auto value = inputInfo[inputName];\
for (int i=0; i<info->size; ++i) {\
ptr[i] = value;\
}\
} else {\
std::ostringstream fileNameOs;\
fileNameOs << directName << "/" << inputName << ".txt";\
auto fileName = fileNameOs.str();\
std::ifstream inputOs(fileName.c_str());\
if (inputOs.fail()) {\
MNN_ERROR("TESTERROR Can't open %s\n", fileName.c_str());\
continue;\
}\
for (int i=0; i<info->size; ++i) {\
inputOs >> ptr[i];\
}\
}
2020-02-26 09:57:17 +08:00
auto info = varMap[inputName]->getInfo();
if (info->type == halide_type_of<float>()){
auto ptr = varMap[inputName]->writeMap<float>();
2020-11-05 16:41:56 +08:00
LOAD_DATA(float)
2020-02-26 09:57:17 +08:00
} else {
auto floatVar = _Input(info->dim, info->order, halide_type_of<float>());
auto ptr = floatVar->writeMap<float>();
LOAD_DATA(float)
auto temp = _Cast(floatVar, info->type);
varMap[inputName]->input(temp);
2020-02-26 09:57:17 +08:00
}
2020-11-05 16:41:56 +08:00
#undef LOAD_DATA
2020-02-26 09:57:17 +08:00
}
2020-11-05 16:41:56 +08:00
bool modelError = false;
2020-02-26 09:57:17 +08:00
for (int i=0; i<outputNames.size(); ++i) {
auto name = outputNames[i];
if (varMap.find(name) == varMap.end()) {
MNN_ERROR("TESTERROR, Can't find var: %s\n", name.c_str());
return 0;
}
auto output = varMap[name];
auto info = output->getInfo();
auto ptr = output->readMap<float>();
if (nullptr == info || nullptr == ptr) {
MNN_ERROR("TESTERROR ptr / info nullptr\n");
return 0;
}
2020-07-04 01:21:30 +08:00
std::ifstream outputOrigin;
// First find key
{
std::ostringstream outputFileOs;
outputFileOs << directName << "/" << name <<".txt";
outputOrigin.open(outputFileOs.str().c_str());
}
// Second find order
if (outputOrigin.fail()) {
std::ostringstream outputFileOs;
outputFileOs << directName << "/" << i <<".txt";
outputOrigin.open(outputFileOs.str().c_str());
}
2020-02-26 09:57:17 +08:00
if (info->order == NC4HW4) {
2020-11-05 16:41:56 +08:00
output = _Convert(output, dataFormat);
info = output->getInfo();
}
if (info->type.code != halide_type_float) {
output = _Cast<float>(output);
2020-02-26 09:57:17 +08:00
info = output->getInfo();
}
auto targetValue = _Input({info->dim}, info->order, info->type);
auto targetPtr = targetValue->writeMap<float>();
for (int i=0; i<info->size; ++i) {
outputOrigin >> targetPtr[i];
}
auto absMax = _ReduceMax(_Abs(targetValue), {});
auto diff = _Abs(targetValue - output);
auto diffAbsMax = _ReduceMax(diff);
auto absMaxV = absMax->readMap<float>()[0];
auto diffAbsMaxV = diffAbsMax->readMap<float>()[0];
if (absMaxV * 0.01f < diffAbsMaxV || isnan(absMaxV)) {
2020-02-26 09:57:17 +08:00
MNN_ERROR("TESTERROR %s value error : absMaxV:%f - DiffMax %f\n", name.c_str(), absMaxV, diffAbsMaxV);
2020-11-05 16:41:56 +08:00
modelError = true;
}
}
if (modelError) {
std::vector<VARP> outputs;
MNN_ERROR("Save mnn result to .error director\n");
for (int i=0; i<outputNames.size(); ++i) {
auto name = outputNames[i];
auto v = varMap[name];
auto info = v->getInfo();
if (info->order == NC4HW4) {
v = _Convert(v, NCHW);
}
if (info->type.code != halide_type_float) {
v = _Cast<float>(v);
info = v->getInfo();
}
v.fix(VARP::CONSTANT);
info = v->getInfo();
std::ofstream _output((".error/" + name + ".txt").c_str());
auto ptr = v->readMap<float>();
for (int v=0; v<info->size; ++v) {
_output << ptr[v] << "\n";
}
v->setName(name);
outputs.emplace_back(v);
2020-02-26 09:57:17 +08:00
}
2020-11-05 16:41:56 +08:00
Variable::save(outputs, ".Error.mnn");
return 0;
2020-02-26 09:57:17 +08:00
}
MNN_PRINT("TEST_SUCCESS\n");
return 0;
}