Files
FastDeploy/csrcs/fastdeploy/backends/tensorrt/common/common.h
Jason ffbc5cc42d Move cpp code to directory csrcs (#42)
* move cpp code to csrcs

* move cpp code to csrcs
2022-07-26 17:59:02 +08:00

845 lines
26 KiB
C++

/*
* Copyright (c) 1993-2022, NVIDIA CORPORATION. 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.
*/
#ifndef TENSORRT_COMMON_H
#define TENSORRT_COMMON_H
// For loadLibrary
#ifdef _MSC_VER
// Needed so that the max/min definitions in windows.h do not conflict with
// std::max/min.
#define NOMINMAX
#include <windows.h>
#undef NOMINMAX
#else
#include <dlfcn.h>
#endif
#include "NvInfer.h"
#include "NvInferPlugin.h"
#include "logger.h"
#include <algorithm>
#include <cassert>
#include <chrono>
#include <cmath>
#include <cstring>
#include <cuda_runtime_api.h>
#include <fstream>
#include <iomanip>
#include <iostream>
#include <iterator>
#include <map>
#include <memory>
#include <new>
#include <numeric>
#include <ratio>
#include <sstream>
#include <string>
#include <utility>
#include <vector>
#include "safeCommon.h"
using namespace nvinfer1;
using namespace plugin;
#ifdef _MSC_VER
#define FN_NAME __FUNCTION__
#else
#define FN_NAME __func__
#endif
#if defined(__aarch64__) || defined(__QNX__)
#define ENABLE_DLA_API 1
#endif
#define CHECK_RETURN_W_MSG(status, val, errMsg) \
do { \
if (!(status)) { \
sample::gLogError << errMsg << " Error in " << __FILE__ << ", function " \
<< FN_NAME << "(), line " << __LINE__ << std::endl; \
return val; \
} \
} while (0)
#undef ASSERT
#define ASSERT(condition) \
do { \
if (!(condition)) { \
sample::gLogError << "Assertion failure: " << #condition << std::endl; \
abort(); \
} \
} while (0)
#define CHECK_RETURN(status, val) CHECK_RETURN_W_MSG(status, val, "")
#define OBJ_GUARD(A) std::unique_ptr<A, void (*)(A * t)>
template <typename T, typename T_> OBJ_GUARD(T) makeObjGuard(T_* t) {
CHECK(!(std::is_base_of<T, T_>::value || std::is_same<T, T_>::value));
auto deleter = [](T* t) { t->destroy(); };
return std::unique_ptr<T, decltype(deleter)>{static_cast<T*>(t), deleter};
}
constexpr long double operator"" _GiB(long double val) {
return val * (1 << 30);
}
constexpr long double operator"" _MiB(long double val) {
return val * (1 << 20);
}
constexpr long double operator"" _KiB(long double val) {
return val * (1 << 10);
}
// These is necessary if we want to be able to write 1_GiB instead of 1.0_GiB.
// Since the return type is signed, -1_GiB will work as expected.
constexpr long long int operator"" _GiB(unsigned long long val) {
return val * (1 << 30);
}
constexpr long long int operator"" _MiB(unsigned long long val) {
return val * (1 << 20);
}
constexpr long long int operator"" _KiB(unsigned long long val) {
return val * (1 << 10);
}
struct SimpleProfiler : public nvinfer1::IProfiler {
struct Record {
float time{0};
int count{0};
};
virtual void reportLayerTime(const char* layerName, float ms) noexcept {
mProfile[layerName].count++;
mProfile[layerName].time += ms;
if (std::find(mLayerNames.begin(), mLayerNames.end(), layerName) ==
mLayerNames.end()) {
mLayerNames.push_back(layerName);
}
}
SimpleProfiler(const char* name,
const std::vector<SimpleProfiler>& srcProfilers =
std::vector<SimpleProfiler>())
: mName(name) {
for (const auto& srcProfiler : srcProfilers) {
for (const auto& rec : srcProfiler.mProfile) {
auto it = mProfile.find(rec.first);
if (it == mProfile.end()) {
mProfile.insert(rec);
} else {
it->second.time += rec.second.time;
it->second.count += rec.second.count;
}
}
}
}
friend std::ostream& operator<<(std::ostream& out,
const SimpleProfiler& value) {
out << "========== " << value.mName << " profile ==========" << std::endl;
float totalTime = 0;
std::string layerNameStr = "TensorRT layer name";
int maxLayerNameLength =
std::max(static_cast<int>(layerNameStr.size()), 70);
for (const auto& elem : value.mProfile) {
totalTime += elem.second.time;
maxLayerNameLength =
std::max(maxLayerNameLength, static_cast<int>(elem.first.size()));
}
auto old_settings = out.flags();
auto old_precision = out.precision();
// Output header
{
out << std::setw(maxLayerNameLength) << layerNameStr << " ";
out << std::setw(12) << "Runtime, "
<< "%"
<< " ";
out << std::setw(12) << "Invocations"
<< " ";
out << std::setw(12) << "Runtime, ms" << std::endl;
}
for (size_t i = 0; i < value.mLayerNames.size(); i++) {
const std::string layerName = value.mLayerNames[i];
auto elem = value.mProfile.at(layerName);
out << std::setw(maxLayerNameLength) << layerName << " ";
out << std::setw(12) << std::fixed << std::setprecision(1)
<< (elem.time * 100.0F / totalTime) << "%"
<< " ";
out << std::setw(12) << elem.count << " ";
out << std::setw(12) << std::fixed << std::setprecision(2) << elem.time
<< std::endl;
}
out.flags(old_settings);
out.precision(old_precision);
out << "========== " << value.mName << " total runtime = " << totalTime
<< " ms ==========" << std::endl;
return out;
}
private:
std::string mName;
std::vector<std::string> mLayerNames;
std::map<std::string, Record> mProfile;
};
//! Locate path to file, given its filename or filepath suffix and possible dirs
//! it might lie in.
//! Function will also walk back MAX_DEPTH dirs from CWD to check for such a
//! file path.
inline std::string locateFile(const std::string& filepathSuffix,
const std::vector<std::string>& directories,
bool reportError = true) {
const int MAX_DEPTH{10};
bool found{false};
std::string filepath;
for (auto& dir : directories) {
if (!dir.empty() && dir.back() != '/') {
#ifdef _MSC_VER
filepath = dir + "\\" + filepathSuffix;
#else
filepath = dir + "/" + filepathSuffix;
#endif
} else {
filepath = dir + filepathSuffix;
}
for (int i = 0; i < MAX_DEPTH && !found; i++) {
const std::ifstream checkFile(filepath);
found = checkFile.is_open();
if (found) {
break;
}
filepath = "../" + filepath; // Try again in parent dir
}
if (found) {
break;
}
filepath.clear();
}
// Could not find the file
if (filepath.empty()) {
const std::string dirList = std::accumulate(
directories.begin() + 1, directories.end(), directories.front(),
[](const std::string& a, const std::string& b) {
return a + "\n\t" + b;
});
std::cout << "Could not find " << filepathSuffix
<< " in data directories:\n\t" << dirList << std::endl;
if (reportError) {
std::cout << "&&&& FAILED" << std::endl;
exit(EXIT_FAILURE);
}
}
return filepath;
}
inline void readPGMFile(const std::string& fileName, uint8_t* buffer, int inH,
int inW) {
std::ifstream infile(fileName, std::ifstream::binary);
assert(infile.is_open() &&
"Attempting to read from a file that is not open.");
std::string magic, h, w, max;
infile >> magic >> h >> w >> max;
infile.seekg(1, infile.cur);
infile.read(reinterpret_cast<char*>(buffer), inH * inW);
}
namespace samplesCommon {
// Swaps endianness of an integral type.
template <typename T,
typename std::enable_if<std::is_integral<T>::value, int>::type = 0>
inline T swapEndianness(const T& value) {
uint8_t bytes[sizeof(T)];
for (int i = 0; i < static_cast<int>(sizeof(T)); ++i) {
bytes[sizeof(T) - 1 - i] = *(reinterpret_cast<const uint8_t*>(&value) + i);
}
return *reinterpret_cast<T*>(bytes);
}
class HostMemory {
public:
HostMemory() = delete;
virtual void* data() const noexcept { return mData; }
virtual std::size_t size() const noexcept { return mSize; }
virtual DataType type() const noexcept { return mType; }
virtual ~HostMemory() {}
protected:
HostMemory(std::size_t size, DataType type)
: mData{nullptr}, mSize(size), mType(type) {}
void* mData;
std::size_t mSize;
DataType mType;
};
template <typename ElemType, DataType dataType>
class TypedHostMemory : public HostMemory {
public:
explicit TypedHostMemory(std::size_t size) : HostMemory(size, dataType) {
mData = new ElemType[size];
};
~TypedHostMemory() noexcept { delete[](ElemType*) mData; }
ElemType* raw() noexcept { return static_cast<ElemType*>(data()); }
};
using FloatMemory = TypedHostMemory<float, DataType::kFLOAT>;
using HalfMemory = TypedHostMemory<uint16_t, DataType::kHALF>;
using ByteMemory = TypedHostMemory<uint8_t, DataType::kINT8>;
inline void* safeCudaMalloc(size_t memSize) {
void* deviceMem;
CHECK(cudaMalloc(&deviceMem, memSize));
if (deviceMem == nullptr) {
std::cerr << "Out of memory" << std::endl;
exit(1);
}
return deviceMem;
}
inline bool isDebug() { return (std::getenv("TENSORRT_DEBUG") ? true : false); }
struct InferDeleter {
template <typename T> void operator()(T* obj) const { delete obj; }
};
template <typename T> using SampleUniquePtr = std::unique_ptr<T, InferDeleter>;
static auto StreamDeleter = [](cudaStream_t* pStream) {
if (pStream) {
cudaStreamDestroy(*pStream);
delete pStream;
}
};
inline std::unique_ptr<cudaStream_t, decltype(StreamDeleter)> makeCudaStream() {
std::unique_ptr<cudaStream_t, decltype(StreamDeleter)> pStream(
new cudaStream_t, StreamDeleter);
if (cudaStreamCreateWithFlags(pStream.get(), cudaStreamNonBlocking) !=
cudaSuccess) {
pStream.reset(nullptr);
}
return pStream;
}
//! Return vector of indices that puts magnitudes of sequence in descending
//! order.
template <class Iter>
std::vector<size_t> argMagnitudeSort(Iter begin, Iter end) {
std::vector<size_t> indices(end - begin);
std::iota(indices.begin(), indices.end(), 0);
std::sort(indices.begin(), indices.end(), [&begin](size_t i, size_t j) {
return std::abs(begin[j]) < std::abs(begin[i]);
});
return indices;
}
inline bool readReferenceFile(const std::string& fileName,
std::vector<std::string>& refVector) {
std::ifstream infile(fileName);
if (!infile.is_open()) {
std::cout << "ERROR: readReferenceFile: Attempting to read from a file "
"that is not open."
<< std::endl;
return false;
}
std::string line;
while (std::getline(infile, line)) {
if (line.empty())
continue;
refVector.push_back(line);
}
infile.close();
return true;
}
template <typename T>
std::vector<std::string> classify(const std::vector<std::string>& refVector,
const std::vector<T>& output,
const size_t topK) {
const auto inds =
samplesCommon::argMagnitudeSort(output.cbegin(), output.cend());
std::vector<std::string> result;
result.reserve(topK);
for (size_t k = 0; k < topK; ++k) {
result.push_back(refVector[inds[k]]);
}
return result;
}
// Returns indices of highest K magnitudes in v.
template <typename T>
std::vector<size_t> topKMagnitudes(const std::vector<T>& v, const size_t k) {
std::vector<size_t> indices =
samplesCommon::argMagnitudeSort(v.cbegin(), v.cend());
indices.resize(k);
return indices;
}
template <typename T>
bool readASCIIFile(const std::string& fileName, const size_t size,
std::vector<T>& out) {
std::ifstream infile(fileName);
if (!infile.is_open()) {
std::cout << "ERROR readASCIIFile: Attempting to read from a file that is "
"not open."
<< std::endl;
return false;
}
out.clear();
out.reserve(size);
out.assign(std::istream_iterator<T>(infile), std::istream_iterator<T>());
infile.close();
return true;
}
template <typename T>
bool writeASCIIFile(const std::string& fileName, const std::vector<T>& in) {
std::ofstream outfile(fileName);
if (!outfile.is_open()) {
std::cout << "ERROR: writeASCIIFile: Attempting to write to a file that is "
"not open."
<< std::endl;
return false;
}
for (auto fn : in) {
outfile << fn << "\n";
}
outfile.close();
return true;
}
inline void print_version() {
std::cout << " TensorRT version: " << NV_TENSORRT_MAJOR << "."
<< NV_TENSORRT_MINOR << "." << NV_TENSORRT_PATCH << "."
<< NV_TENSORRT_BUILD << std::endl;
}
inline std::string getFileType(const std::string& filepath) {
return filepath.substr(filepath.find_last_of(".") + 1);
}
inline std::string toLower(const std::string& inp) {
std::string out = inp;
std::transform(out.begin(), out.end(), out.begin(), ::tolower);
return out;
}
inline float getMaxValue(const float* buffer, int64_t size) {
assert(buffer != nullptr);
assert(size > 0);
return *std::max_element(buffer, buffer + size);
}
// Ensures that every tensor used by a network has a dynamic range set.
//
// All tensors in a network must have a dynamic range specified if a calibrator
// is not used.
// This function is just a utility to globally fill in missing scales and
// zero-points for the entire network.
//
// If a tensor does not have a dyanamic range set, it is assigned inRange or
// outRange as follows:
//
// * If the tensor is the input to a layer or output of a pooling node, its
// dynamic range is derived from inRange.
// * Otherwise its dynamic range is derived from outRange.
//
// The default parameter values are intended to demonstrate, for final layers in
// the network,
// cases where dynamic ranges are asymmetric.
//
// The default parameter values choosen arbitrarily. Range values should be
// choosen such that
// we avoid underflow or overflow. Also range value should be non zero to avoid
// uniform zero scale tensor.
inline void setAllDynamicRanges(INetworkDefinition* network,
float inRange = 2.0f, float outRange = 4.0f) {
// Ensure that all layer inputs have a scale.
for (int i = 0; i < network->getNbLayers(); i++) {
auto layer = network->getLayer(i);
for (int j = 0; j < layer->getNbInputs(); j++) {
ITensor* input{layer->getInput(j)};
// Optional inputs are nullptr here and are from RNN layers.
if (input != nullptr && !input->dynamicRangeIsSet()) {
ASSERT(input->setDynamicRange(-inRange, inRange));
}
}
}
// Ensure that all layer outputs have a scale.
// Tensors that are also inputs to layers are ingored here
// since the previous loop nest assigned scales to them.
for (int i = 0; i < network->getNbLayers(); i++) {
auto layer = network->getLayer(i);
for (int j = 0; j < layer->getNbOutputs(); j++) {
ITensor* output{layer->getOutput(j)};
// Optional outputs are nullptr here and are from RNN layers.
if (output != nullptr && !output->dynamicRangeIsSet()) {
// Pooling must have the same input and output scales.
if (layer->getType() == LayerType::kPOOLING) {
ASSERT(output->setDynamicRange(-inRange, inRange));
} else {
ASSERT(output->setDynamicRange(-outRange, outRange));
}
}
}
}
}
inline void setDummyInt8DynamicRanges(const IBuilderConfig* c,
INetworkDefinition* n) {
// Set dummy per-tensor dynamic range if Int8 mode is requested.
if (c->getFlag(BuilderFlag::kINT8)) {
sample::gLogWarning << "Int8 calibrator not provided. Generating dummy "
"per-tensor dynamic range. Int8 accuracy is not "
"guaranteed."
<< std::endl;
setAllDynamicRanges(n);
}
}
inline void enableDLA(IBuilder* builder, IBuilderConfig* config, int useDLACore,
bool allowGPUFallback = true) {
if (useDLACore >= 0) {
if (builder->getNbDLACores() == 0) {
std::cerr << "Trying to use DLA core " << useDLACore
<< " on a platform that doesn't have any DLA cores"
<< std::endl;
assert(
"Error: use DLA core on a platfrom that doesn't have any DLA cores" &&
false);
}
if (allowGPUFallback) {
config->setFlag(BuilderFlag::kGPU_FALLBACK);
}
if (!config->getFlag(BuilderFlag::kINT8)) {
// User has not requested INT8 Mode.
// By default run in FP16 mode. FP32 mode is not permitted.
config->setFlag(BuilderFlag::kFP16);
}
config->setDefaultDeviceType(DeviceType::kDLA);
config->setDLACore(useDLACore);
}
}
inline int32_t parseDLA(int32_t argc, char** argv) {
for (int32_t i = 1; i < argc; i++) {
if (strncmp(argv[i], "--useDLACore=", 13) == 0) {
return std::stoi(argv[i] + 13);
}
}
return -1;
}
inline uint32_t getElementSize(nvinfer1::DataType t) noexcept {
switch (t) {
case nvinfer1::DataType::kINT32:
return 4;
case nvinfer1::DataType::kFLOAT:
return 4;
case nvinfer1::DataType::kHALF:
return 2;
case nvinfer1::DataType::kBOOL:
case nvinfer1::DataType::kINT8:
return 1;
}
return 0;
}
inline int64_t volume(const nvinfer1::Dims& d) {
return std::accumulate(d.d, d.d + d.nbDims, 1, std::multiplies<int64_t>());
}
template <int C, int H, int W> struct PPM {
std::string magic, fileName;
int h, w, max;
uint8_t buffer[C * H * W];
};
// New vPPM(variable sized PPM) class with variable dimensions.
struct vPPM {
std::string magic, fileName;
int h, w, max;
std::vector<uint8_t> buffer;
};
struct BBox {
float x1, y1, x2, y2;
};
template <int C, int H, int W>
void readPPMFile(const std::string& filename,
samplesCommon::PPM<C, H, W>& ppm) {
ppm.fileName = filename;
std::ifstream infile(filename, std::ifstream::binary);
assert(infile.is_open() &&
"Attempting to read from a file that is not open.");
infile >> ppm.magic >> ppm.w >> ppm.h >> ppm.max;
infile.seekg(1, infile.cur);
infile.read(reinterpret_cast<char*>(ppm.buffer), ppm.w * ppm.h * 3);
}
inline void readPPMFile(const std::string& filename, vPPM& ppm,
std::vector<std::string>& input_dir) {
ppm.fileName = filename;
std::ifstream infile(locateFile(filename, input_dir), std::ifstream::binary);
infile >> ppm.magic >> ppm.w >> ppm.h >> ppm.max;
infile.seekg(1, infile.cur);
for (int i = 0; i < ppm.w * ppm.h * 3; ++i) {
ppm.buffer.push_back(0);
}
infile.read(reinterpret_cast<char*>(&ppm.buffer[0]), ppm.w * ppm.h * 3);
}
template <int C, int H, int W>
void writePPMFileWithBBox(const std::string& filename, PPM<C, H, W>& ppm,
const BBox& bbox) {
std::ofstream outfile("./" + filename, std::ofstream::binary);
assert(!outfile.fail());
outfile << "P6"
<< "\n"
<< ppm.w << " " << ppm.h << "\n"
<< ppm.max << "\n";
auto round = [](float x) -> int { return int(std::floor(x + 0.5f)); };
const int x1 = std::min(std::max(0, round(int(bbox.x1))), W - 1);
const int x2 = std::min(std::max(0, round(int(bbox.x2))), W - 1);
const int y1 = std::min(std::max(0, round(int(bbox.y1))), H - 1);
const int y2 = std::min(std::max(0, round(int(bbox.y2))), H - 1);
for (int x = x1; x <= x2; ++x) {
// bbox top border
ppm.buffer[(y1 * ppm.w + x) * 3] = 255;
ppm.buffer[(y1 * ppm.w + x) * 3 + 1] = 0;
ppm.buffer[(y1 * ppm.w + x) * 3 + 2] = 0;
// bbox bottom border
ppm.buffer[(y2 * ppm.w + x) * 3] = 255;
ppm.buffer[(y2 * ppm.w + x) * 3 + 1] = 0;
ppm.buffer[(y2 * ppm.w + x) * 3 + 2] = 0;
}
for (int y = y1; y <= y2; ++y) {
// bbox left border
ppm.buffer[(y * ppm.w + x1) * 3] = 255;
ppm.buffer[(y * ppm.w + x1) * 3 + 1] = 0;
ppm.buffer[(y * ppm.w + x1) * 3 + 2] = 0;
// bbox right border
ppm.buffer[(y * ppm.w + x2) * 3] = 255;
ppm.buffer[(y * ppm.w + x2) * 3 + 1] = 0;
ppm.buffer[(y * ppm.w + x2) * 3 + 2] = 0;
}
outfile.write(reinterpret_cast<char*>(ppm.buffer), ppm.w * ppm.h * 3);
}
inline void writePPMFileWithBBox(const std::string& filename, vPPM ppm,
std::vector<BBox>& dets) {
std::ofstream outfile("./" + filename, std::ofstream::binary);
assert(!outfile.fail());
outfile << "P6"
<< "\n"
<< ppm.w << " " << ppm.h << "\n"
<< ppm.max << "\n";
auto round = [](float x) -> int { return int(std::floor(x + 0.5f)); };
for (auto bbox : dets) {
for (int x = int(bbox.x1); x < int(bbox.x2); ++x) {
// bbox top border
ppm.buffer[(round(bbox.y1) * ppm.w + x) * 3] = 255;
ppm.buffer[(round(bbox.y1) * ppm.w + x) * 3 + 1] = 0;
ppm.buffer[(round(bbox.y1) * ppm.w + x) * 3 + 2] = 0;
// bbox bottom border
ppm.buffer[(round(bbox.y2) * ppm.w + x) * 3] = 255;
ppm.buffer[(round(bbox.y2) * ppm.w + x) * 3 + 1] = 0;
ppm.buffer[(round(bbox.y2) * ppm.w + x) * 3 + 2] = 0;
}
for (int y = int(bbox.y1); y < int(bbox.y2); ++y) {
// bbox left border
ppm.buffer[(y * ppm.w + round(bbox.x1)) * 3] = 255;
ppm.buffer[(y * ppm.w + round(bbox.x1)) * 3 + 1] = 0;
ppm.buffer[(y * ppm.w + round(bbox.x1)) * 3 + 2] = 0;
// bbox right border
ppm.buffer[(y * ppm.w + round(bbox.x2)) * 3] = 255;
ppm.buffer[(y * ppm.w + round(bbox.x2)) * 3 + 1] = 0;
ppm.buffer[(y * ppm.w + round(bbox.x2)) * 3 + 2] = 0;
}
}
outfile.write(reinterpret_cast<char*>(&ppm.buffer[0]), ppm.w * ppm.h * 3);
}
class TimerBase {
public:
virtual void start() {}
virtual void stop() {}
float microseconds() const noexcept { return mMs * 1000.f; }
float milliseconds() const noexcept { return mMs; }
float seconds() const noexcept { return mMs / 1000.f; }
void reset() noexcept { mMs = 0.f; }
protected:
float mMs{0.0f};
};
class GpuTimer : public TimerBase {
public:
explicit GpuTimer(cudaStream_t stream) : mStream(stream) {
CHECK(cudaEventCreate(&mStart));
CHECK(cudaEventCreate(&mStop));
}
~GpuTimer() {
CHECK(cudaEventDestroy(mStart));
CHECK(cudaEventDestroy(mStop));
}
void start() { CHECK(cudaEventRecord(mStart, mStream)); }
void stop() {
CHECK(cudaEventRecord(mStop, mStream));
float ms{0.0f};
CHECK(cudaEventSynchronize(mStop));
CHECK(cudaEventElapsedTime(&ms, mStart, mStop));
mMs += ms;
}
private:
cudaEvent_t mStart, mStop;
cudaStream_t mStream;
}; // class GpuTimer
template <typename Clock> class CpuTimer : public TimerBase {
public:
using clock_type = Clock;
void start() { mStart = Clock::now(); }
void stop() {
mStop = Clock::now();
mMs += std::chrono::duration<float, std::milli>{mStop - mStart}.count();
}
private:
std::chrono::time_point<Clock> mStart, mStop;
}; // class CpuTimer
using PreciseCpuTimer = CpuTimer<std::chrono::high_resolution_clock>;
inline std::vector<std::string> splitString(std::string str,
char delimiter = ',') {
std::vector<std::string> splitVect;
std::stringstream ss(str);
std::string substr;
while (ss.good()) {
getline(ss, substr, delimiter);
splitVect.emplace_back(std::move(substr));
}
return splitVect;
}
// Return m rounded up to nearest multiple of n
inline int roundUp(int m, int n) { return ((m + n - 1) / n) * n; }
inline int getC(const Dims& d) { return d.nbDims >= 3 ? d.d[d.nbDims - 3] : 1; }
inline int getH(const Dims& d) { return d.nbDims >= 2 ? d.d[d.nbDims - 2] : 1; }
inline int getW(const Dims& d) { return d.nbDims >= 1 ? d.d[d.nbDims - 1] : 1; }
inline void loadLibrary(const std::string& path) {
#ifdef _MSC_VER
void* handle = LoadLibrary(path.c_str());
#else
int32_t flags{RTLD_LAZY};
#if ENABLE_ASAN
// https://github.com/google/sanitizers/issues/89
// asan doesn't handle module unloading correctly and there are no plans on
// doing
// so. In order to get proper stack traces, don't delete the shared library on
// close so that asan can resolve the symbols correctly.
flags |= RTLD_NODELETE;
#endif // ENABLE_ASAN
void* handle = dlopen(path.c_str(), flags);
#endif
if (handle == nullptr) {
#ifdef _MSC_VER
sample::gLogError << "Could not load plugin library: " << path << std::endl;
#else
sample::gLogError << "Could not load plugin library: " << path
<< ", due to: " << dlerror() << std::endl;
#endif
}
}
inline int32_t getSMVersion() {
int32_t deviceIndex = 0;
CHECK(cudaGetDevice(&deviceIndex));
int32_t major, minor;
CHECK(cudaDeviceGetAttribute(&major, cudaDevAttrComputeCapabilityMajor,
deviceIndex));
CHECK(cudaDeviceGetAttribute(&minor, cudaDevAttrComputeCapabilityMinor,
deviceIndex));
return ((major << 8) | minor);
}
inline bool isSMSafe() {
const int32_t smVersion = getSMVersion();
return smVersion == 0x0700 || smVersion == 0x0702 || smVersion == 0x0705 ||
smVersion == 0x0800 || smVersion == 0x0806 || smVersion == 0x0807;
}
inline bool isDataTypeSupported(DataType dataType) {
auto builder = SampleUniquePtr<nvinfer1::IBuilder>(
nvinfer1::createInferBuilder(sample::gLogger.getTRTLogger()));
if (!builder) {
return false;
}
if ((dataType == DataType::kINT8 && !builder->platformHasFastInt8()) ||
(dataType == DataType::kHALF && !builder->platformHasFastFp16())) {
return false;
}
return true;
}
} // namespace samplesCommon
inline std::ostream& operator<<(std::ostream& os, const nvinfer1::Dims& dims) {
os << "(";
for (int i = 0; i < dims.nbDims; ++i) {
os << (i ? ", " : "") << dims.d[i];
}
return os << ")";
}
#endif // TENSORRT_COMMON_H