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update amexec

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This commit is contained in:
chen
2020-06-29 14:38:42 +08:00
parent 299a761988
commit d16702f038
10 changed files with 121 additions and 50 deletions
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AMEXEC/amexec测试用例.xlsx
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AMEXEC/inc/sample_process.h
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@@ -39,7 +39,7 @@ public:
* @brief sample process
* @return result
*/
Result Process(vector<string>& params, vector<string>& inputs, size_t idx);
Result Process(vector<string>& params, vector<string>& inputs);
private:
void DestroyResource();
AMEXEC/inc/utils.h
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@@ -20,13 +20,14 @@
#include <algorithm>
#include <stdio.h>
#include <time.h>
#include <sys/time.h>
#define INFO_LOG(fmt, args...) fprintf(stdout, "[INFO] " fmt "\n", ##args)
#define WARN_LOG(fmt, args...) fprintf(stdout, "[WARN] " fmt "\n", ##args)
#define ERROR_LOG(fmt, args...) fprintf(stdout, "[ERROR] " fmt "\n", ##args)
using namespace std;
static size_t loop = 1;
//static size_t loop = 1;
typedef enum Result {
SUCCESS = 0,
FAILED = 1
@@ -65,7 +66,10 @@ public:
static void printCurrentTime();
static void printHelpLetter();
static double printDiffTime(time_t begin, time_t end);
static double InferenceTimeAverage(double *x, int len);
};
#pragma once
AMEXEC/out/amexec
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AMEXEC/readMe.md
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@@ -1,25 +1,71 @@
**此工具为模型推理工具**
# amexec工具为模型推理工具
### 功能
输入.om模型和模型所需要的输入bin文件，输出模型的输出数据文件，支持多次推理（指对同一输入数据进行推理）。
模型必须是通过c7x版本的atc工具转换的om模型，输入bin文件需要符合模型的输入要求（支持模型多输入）
### 使用环境
Centos7.6或Ubuntu16.4
必须按照《驱动和开发环境安装指南》装好C7x环境
### 获取
1. 下载压缩包方式获取。
将 https://gitee.com/atlasdevelop/c7x_samples 仓中的脚本下载至服务器的任意目录。
例如存放路径为：$HOME/AscendProjects/amexec。
2. 命令行使用git命令方式获取。
在命令行中：$HOME/AscendProjects目录下执行以下命令下载代码。
**git clone https://gitee.com/atlasdevelop/c7x_samples.git**
功能：输入.om模型和模型所需要的输入bin文件，输出模型的输出数据文件
模型必须是通过c7x版本的atc工具转换的om模型，输入bin文件需要符合模型的输入要求
### 使用方法
进入AMEXEC目录
```
cd $HOME/AscendProjects/c7x_samples/amexec/
```
进入out目录
```
cd $HOME/AscendProjects/c7x_samples/amexec/out
```
工具就在out目录下
工具为命令行的运行方式，例如
```
./amexec --model /home/HwHiAiUser/ljj/colorization.om --input /home/HwHiAiUser/ljj/colorization_input.bin --output /home/HwHiAiUser/ljj/AMEXEC/out/output1 --outfmt TXT --loop 2
```
需要注意的是这几个参数的顺序不能颠倒，outfmt与loop为可选参数，默认值分别有BIN、1。
如果有多个输入，需要用“，”隔开。
其他参数详情可使用--help查询。
*./amexec --model /home/HwHiAiUser/ljj/colorization.om --input /home/HwHiAiUser/ljj/colorization_input.bin --output /home/HwHiAiUser/ljj/AMEXEC/out/output1 --outfmt TXT --loop 2*
需要注意的是这几个参数的顺序不能颠倒，outfmt与loop为可选参数，默认值分别有BIN、1。其他参数详情可使用--help查询。
### 编译
工具也支持源码编译，或者使用者需要添加或者修改代码，使用者重新编译
进入AMEXEC目录
```
cd $HOME/AscendProjects/c7x_samples/amexec/
```
运行编译脚本
```
./build.sh
```
重新编译的工具在out目录下
## 注意事项
运行工具的用户在当前目录需要有创建目录以及执行工具的权限，使用前请自行检查。
dump、profiling以及动态多batch功能暂不支持。
dump、profiling以及动态多batch功能暂不支持。
## 参数说明
| 参数名 | 说明 |
| -------- | ------------------------------- |
| --model | 需要进行推理的om模型 |
| --input | 模型需要的输入 |
| --output | 推理数据输出路径 |
| --outfmt | 输出数据的格式，TXT或者BIN |
| --loop | 推理次数 [1,100]，可选参数默认1 |
| --help | 工具使用帮助信 |
AMEXEC/src/main.cpp
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@@ -16,6 +16,7 @@ using namespace std;
bool f_isTXT = false;
bool g_isDevice = false;
int loop = 1;
string input_Ftype = ".bin";
string model_Ftype = ".om";
string check = "";
@@ -78,6 +79,7 @@ void InitAndCheckParams(int argc, char* argv[], vector<string>& params, vector<s
break;
case 'l':
loop = Utils::str2num(optarg);
cout << "loop:" << loop << endl;
if (loop > 100 || loop < 1)
{
printf("loop must in 1 to 100\n");
@@ -120,14 +122,13 @@ int main(int argc, char* argv[])
ERROR_LOG("Sample init resource failed.");
return FAILED;
}
for (size_t i = 0;i < loop;i++){
std::cout << i << endl;
ret = processSample.Process(params, inputs, i);
if (ret != SUCCESS) {
ERROR_LOG("Sample process failed.");
return FAILED;
}
ret = processSample.Process(params, inputs);
if (ret != SUCCESS) {
ERROR_LOG("Sample process failed.");
return FAILED;
}
INFO_LOG("Execute sample success.");
printf("Test Finish!\n");
printf("******************************\n");
AMEXEC/src/model_process.cpp
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@@ -567,5 +567,5 @@ void ModelProcess::Unload()
}
loadFlag_ = false;
INFO_LOG("unload model syccess, model Id is %u", modelId_);
INFO_LOG("unload model success, model Id is %u", modelId_);
}
AMEXEC/src/sample_process.cpp
+29 -24
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@@ -16,6 +16,7 @@
using namespace std;
extern bool g_isDevice;
extern bool f_isTXT;
extern int loop;
SampleProcess::SampleProcess() :deviceId_(0), context_(nullptr), stream_(nullptr)
{
@@ -73,7 +74,7 @@ Result SampleProcess::InitResource()
return SUCCESS;
}
Result SampleProcess::Process(vector<string>& params, vector<string>& input_files, size_t idx)
Result SampleProcess::Process(vector<string>& params, vector<string>& input_files)
{
// model init
ModelProcess processModel;
@@ -86,9 +87,12 @@ Result SampleProcess::Process(vector<string>& params, vector<string>& input_file
const char* profConf = params[5].c_str();
const char* dymBatch = params[6].c_str();
std::string modelPath = params[0].c_str();
std::string modelName = Utils::modelName(modelPath);
std::string modelPath = params[0].c_str();
std::string modelName = Utils::modelName(modelPath);
struct timeval begin;
struct timeval end;
double inference_time[loop];
Result ret = processModel.LoadModelFromFileWithMem(omModelPath);
if (ret != SUCCESS) {
ERROR_LOG("load model from file failed");
@@ -122,33 +126,34 @@ Result SampleProcess::Process(vector<string>& params, vector<string>& input_file
ret = processModel.CreateInput(picDevBuffer[index], devBufferSize);
if (ret != SUCCESS) {
ERROR_LOG("model create input failed");
for (size_t i = 0; i <= index; i++) {
for (size_t i = 0; i < index; i++) {
aclrtFree(picDevBuffer[i]);
}
return FAILED;
}
// loop end
printf("Inference begin time: ");
Utils::printCurrentTime();
ret = processModel.Execute();
printf("Inference end time: ");
Utils::printCurrentTime();
if (ret != SUCCESS) {
ERROR_LOG("model execute failed");
for (size_t i = 0; i < index; i++) {
aclrtFree(picDevBuffer[i]);
}
return FAILED;
}
// print the top 5 confidence values with indexes.use function DumpModelOutputResult
// if want to dump output result to file in the current directory
//processModel.DumpModelOutputResult();
processModel.OutputModelResult(output_path,modelName,idx);
// loop end
for (size_t t = 0; t < loop; ++t){
gettimeofday(&begin,NULL);
ret = processModel.Execute();
gettimeofday(&end,NULL);
inference_time[t] = 1000*(end.tv_sec - begin.tv_sec) + (end.tv_usec - begin.tv_usec)/1000.000;
//std::cout << "usec: " << end.tv_usec - begin.tv_usec << endl;
std::cout << "Inference time: "<<inference_time[t] << "ms" << endl;
if (ret != SUCCESS) {
ERROR_LOG("model execute failed");
for (size_t i = 0; i < input_files.size(); i++) {
aclrtFree(picDevBuffer[i]);
}
return FAILED;
}
processModel.OutputModelResult(output_path,modelName,t);
}
double infer_time_ave = Utils::InferenceTimeAverage(inference_time, loop);
printf("Inference average time: %f ms\n", infer_time_ave);
processModel.DestroyInput();
}
// release model input buffer
for (size_t i = 0; i < input_files.size(); i++) {
aclrtFree(picDevBuffer[i]);
AMEXEC/src/utils.cpp
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@@ -175,3 +175,18 @@ void Utils::printHelpLetter()
cout<< "NOTECE: " << endl;
cout<< " The order of parameter must follow in --model --input --output --outfmt --loop " << endl;
}
double Utils::printDiffTime(time_t begin, time_t end)
{
double diffT = difftime(begin, end);
printf("The inference time is: %f millisecond\n", 1000*diffT);
return diffT*1000;
}
double Utils::InferenceTimeAverage(double *x, int len)
{
double sum = 0;
for (int i = 0; i < len; i++)
sum += x[i];
return sum/len;
}
AMEXEC/模型推理工具.docx
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