ascend310_infer

model_zoo/official/cv/lenet_quant/Readme.md

@@ -84,6 +84,9 @@ python eval.py --device_target=Ascend --data_path=[DATA_PATH] --ckpt_path=[CKPT_
     ├── README.md                        // descriptions about all the models
     ├── lenet_quant
         ├── README.md                    // descriptions about LeNet-Quant
+        ├── ascend310_infer              // application for 310 inference
+        ├── scripts
+            ├── run_infer_310.sh         // shell script for 310 inference
         ├── src
         │   ├── config.py                // parameter configuration
         │   ├── dataset.py               // creating dataset
@@ -93,6 +96,8 @@ python eval.py --device_target=Ascend --data_path=[DATA_PATH] --ckpt_path=[CKPT_
         ├── requirements.txt             // package needed
         ├── train.py               // training LeNet-Quant network with device Ascend
         ├── eval.py                // evaluating LeNet-Quant network with device Ascend
+        ├── export_bin_file.py     // export bin file of MNIST for 310 inference
+        ├── postprocess.py         // post process for 310 inference
 ```
 
 ## [Script Parameters](#contents)
@@ -152,6 +157,34 @@ You can view the results through the file "log.txt". The accuracy of the test da
 'Accuracy': 0.9842
 ```
 
+## [Model Export](#contents)
+
+```shell
+python export.py --ckpt_path [CKPT_PATH] --data_path [DATA_PATH] --device_target [PLATFORM]
+```
+
+## [Ascend 310 inference](#contents)
+
+You should export AIR model at Ascend 910 before  running the command below.
+You can use export_bin_file.py to export MNIST bin and label for 310 inference.
+
+```shell
+python export_bin_file.py --dataset_dir [DATASET_PATH] --save_dir [SAVE_PATH]
+```
+
+Run run_infer_310.sh and get the accuracy：
+
+```shell
+# Ascend310 inference
+bash run_infer_310.sh [AIR_PATH] [DATA_PATH] [LABEL_PATH] [DEVICE_ID]
+```
+
+You can view the results through the file "acc.log". The accuracy of the test dataset will be as follows:
+
+```bash
+'Accuracy':0.9883
+```
+
 ## [Model Description](#contents)
 
 ### [Performance](#contents)

model_zoo/official/cv/lenet_quant/Readme_CN.md

@@ -90,6 +90,9 @@ python eval.py --device_target=Ascend --data_path=[DATA_PATH] --ckpt_path=[CKPT_
     ├── README.md                        // 所有型号的描述
     ├── lenet_quant
         ├── README.md                    // LeNet-Quant描述
+        ├── ascend310_infer              //实现310推理源代码
+        ├── scripts
+            ├── run_infer_310.sh         // Ascend推理shell脚本
         ├──src
         │   ├── config.py                // 参数配置
         │   ├── dataset.py               // 创建数据集
@@ -98,7 +101,9 @@ python eval.py --device_target=Ascend --data_path=[DATA_PATH] --ckpt_path=[CKPT_
         │   ├── loss_monitor.py          // 监控网络损失和其他数据
         ├── requirements.txt             // 需要的包
         ├── train.py               // 使用Ascend训练LeNet-Quant网络
-        ├── eval.py                // 使用Ascend评估LeNet-Quant网络d
+        ├── eval.py                // 使用Ascend评估LeNet-Quant网络
+        ├── export_bin_file.py     // 导出MNIST数据集的bin文件用于310推理
+        ├── postprocess.py         // 310推理后处理脚本
 ```
 
 ### 脚本参数
@@ -156,6 +161,34 @@ python eval.py --data_path Data --ckpt_path ckpt/checkpoint_lenet-1_937.ckpt > l
 'Accuracy':0.9842
 ```
 
+### 模型导出
+
+```shell
+python export.py --ckpt_path [CKPT_PATH] --data_path [DATA_PATH] --device_target [PLATFORM]
+```
+
+### Ascend 310推理
+
+在推理之前需要在昇腾910环境上完成AIR模型的导出。
+并使用export_bin_file.py导出MNIST数据集的bin文件和对应的label文件：
+
+```shell
+python export_bin_file.py --dataset_dir [DATASET_PATH] --save_dir [SAVE_PATH]
+```
+
+执行推理并得到推理精度：
+
+```shell
+# Ascend310 inference
+bash run_infer_310.sh [AIR_PATH] [DATA_PATH] [LABEL_PATH] [DEVICE_ID]
+```
+
+您可以通过acc.log文件查看结果。推理准确性如下：
+
+```bash
+'Accuracy':0.9883
+```
+
 ## 模型描述
 
 ### 性能

model_zoo/official/cv/lenet_quant/ascend310_infer/inc/ModelProcess.h

@@ -0,0 +1,112 @@
+/**
+ * Copyright 2021 Huawei Technologies Co., Ltd
+ * 
+ * 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 MODELPROCESS_H
+#define MODELPROCESS_H
+
+#include "acl/acl.h"
+#include "../inc/utils.h"
+
+/**
+* ModelProcess
+*/
+class ModelProcess {
+ public:
+    /**
+    * @brief Constructor
+    */
+    ModelProcess();
+
+    /**
+    * @brief Destructor
+    */
+    ~ModelProcess();
+
+    /**
+    * @brief load model from file with mem
+    * @param [in] modelPath: model path
+    * @return result
+    */
+    Result LoadModelFromFileWithMem(const char *modelPath);
+
+    /**
+    * @brief unload model
+    */
+    void Unload();
+
+    /**
+    * @brief create model desc
+    * @return result
+    */
+    Result CreateDesc();
+
+    /**
+    * @brief destroy desc
+    */
+    void DestroyDesc();
+
+    /**
+    * @brief create model input
+    * @param [in] inputDataBuffer: input buffer
+    * @param [in] bufferSize: input buffer size
+    * @return result
+    */
+    Result CreateInput(void *inputDataBuffer, size_t bufferSize);
+
+    /**
+    * @brief destroy input resource
+    */
+    void DestroyInput();
+
+    /**
+    * @brief create output buffer
+    * @return result
+    */
+    Result CreateOutput();
+
+    /**
+    * @brief destroy output resource
+    */
+    void DestroyOutput();
+
+    /**
+    * @brief model execute
+    * @return result
+    */
+    Result Execute();
+
+    /**
+    * @brief dump model output result to file
+    */
+    void DumpModelOutputResult(char *output_name);
+
+    /**
+    * @brief get model output result
+    */
+    void OutputModelResult();
+
+ private:
+    uint32_t modelId_;
+    size_t modelMemSize_;
+    size_t modelWeightSize_;
+    void *modelMemPtr_;
+    void *modelWeightPtr_;
+    bool loadFlag_;  // model load flag
+    aclmdlDesc *modelDesc_;
+    aclmdlDataset *input_;
+    aclmdlDataset *output_;
+};
+#endif

model_zoo/official/cv/lenet_quant/ascend310_infer/inc/SampleProcess.h

@@ -0,0 +1,62 @@
+/**
+ * Copyright 2021 Huawei Technologies Co., Ltd
+ * 
+ * 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 SAMPLEPROCESS_H
+#define SAMPLEPROCESS_H
+
+#include <string>
+#include <vector>
+#include "acl/acl.h"
+#include "../inc/utils.h"
+
+/**
+* SampleProcess
+*/
+class SampleProcess {
+ public:
+    /**
+    * @brief Constructor
+    */
+    explicit SampleProcess(int32_t deviceId);
+
+    /**
+    * @brief Destructor
+    */
+    ~SampleProcess();
+
+    /**
+    * @brief init reousce
+    * @return result
+    */
+    Result InitResource(const char *acl_config_path);
+
+    /**
+    * @brief sample process
+    * @return result
+    */
+    Result Process(const char *om_path, const char *input_folder);
+
+    void GetAllFiles(std::string path, std::vector<std::string> *files);
+
+ private:
+    void DestroyResource();
+
+    int32_t deviceId_;
+    aclrtContext context_;
+    aclrtStream stream_;
+};
+
+#endif

model_zoo/official/cv/lenet_quant/ascend310_infer/inc/utils.h

@@ -0,0 +1,53 @@
+/**
+ * Copyright 2021 Huawei Technologies Co., Ltd
+ * 
+ * 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 MINDSPORE_INFERENCE_UTILS_H_
+#define MINDSPORE_INFERENCE_UTILS_H_
+
+#include <iostream>
+#include <string>
+
+#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)
+
+typedef enum Result {
+    SUCCESS = 0,
+    FAILED = 1
+} Result;
+
+/**
+* Utils
+*/
+class Utils {
+ public:
+    /**
+    * @brief create device buffer of file
+    * @param [in] fileName: file name
+    * @param [out] fileSize: size of file
+    * @return device buffer of file
+    */
+    static void *GetDeviceBufferOfFile(std::string fileName, uint32_t *fileSize);
+
+    /**
+    * @brief Read bin file
+    * @param [in] fileName: file name
+    * @param [out] fileSize: size of file
+    * @return buffer of pic
+    */
+    static void* ReadBinFile(std::string fileName, uint32_t *fileSize);
+};
+#endif

model_zoo/official/cv/lenet_quant/ascend310_infer/src/CMakeLists.txt

@@ -0,0 +1,41 @@
+# Copyright (c) Huawei Technologies Co., Ltd. 2021. All rights reserved.
+
+# CMake lowest version requirement
+cmake_minimum_required(VERSION 3.5.1)
+# project information
+project(InferClassification)
+# Check environment variable
+if(NOT DEFINED ENV{ASCEND_HOME})
+    message(FATAL_ERROR "please define environment variable:ASCEND_HOME")
+endif()
+
+# Compile options
+add_compile_definitions(_GLIBCXX_USE_CXX11_ABI=0)
+set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -O0 -g -std=c++17 -Werror -Wall -fPIE -Wl,--allow-shlib-undefined")
+
+# Skip build rpath
+set(CMAKE_SKIP_BUILD_RPATH True)
+
+# Set output directory
+set(PROJECT_SRC_ROOT ${CMAKE_CURRENT_LIST_DIR}/)
+set(CMAKE_RUNTIME_OUTPUT_DIRECTORY ${PROJECT_SRC_ROOT}/out)
+
+# Set include directory and library directory
+set(ACL_LIB_DIR $ENV{ASCEND_HOME}/acllib)
+set(ATLAS_ACL_LIB_DIR $ENV{ASCEND_HOME}/ascend-toolkit/latest/acllib)
+
+# Header path
+include_directories(${ACL_LIB_DIR}/include/)
+include_directories(${ATLAS_ACL_LIB_DIR}/include/)
+include_directories(${PROJECT_SRC_ROOT}/../inc)
+
+# add host lib path
+link_directories(${ACL_LIB_DIR})
+find_library(acl libascendcl.so ${ACL_LIB_DIR}/lib64 ${ATLAS_ACL_LIB_DIR}/lib64)
+
+add_executable(main utils.cpp
+                    SampleProcess.cpp
+                    ModelProcess.cpp
+                    main.cpp)
+
+target_link_libraries(main ${acl} gflags pthread)

model_zoo/official/cv/lenet_quant/ascend310_infer/src/ModelProcess.cpp

@@ -0,0 +1,326 @@
+/**
+ * Copyright 2021 Huawei Technologies Co., Ltd
+ * 
+ * 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.
+ */
+
+#include "../inc/ModelProcess.h"
+#include <iostream>
+#include <map>
+#include <sstream>
+#include <algorithm>
+#include "../inc/utils.h"
+
+extern bool g_isDevice;
+
+ModelProcess::ModelProcess() :modelId_(0), modelMemSize_(0), modelWeightSize_(0), modelMemPtr_(nullptr),
+modelWeightPtr_(nullptr), loadFlag_(false), modelDesc_(nullptr), input_(nullptr), output_(nullptr) {
+}
+
+ModelProcess::~ModelProcess() {
+    Unload();
+    DestroyDesc();
+    DestroyInput();
+    DestroyOutput();
+}
+
+Result ModelProcess::LoadModelFromFileWithMem(const char *modelPath) {
+    if (loadFlag_) {
+        ERROR_LOG("has already loaded a model");
+        return FAILED;
+    }
+
+    aclError ret = aclmdlQuerySize(modelPath, &modelMemSize_, &modelWeightSize_);
+    if (ret != ACL_ERROR_NONE) {
+        ERROR_LOG("query model failed, model file is %s", modelPath);
+        return FAILED;
+    }
+
+    ret = aclrtMalloc(&modelMemPtr_, modelMemSize_, ACL_MEM_MALLOC_HUGE_FIRST);
+    if (ret != ACL_ERROR_NONE) {
+        ERROR_LOG("malloc buffer for mem failed, require size is %zu", modelMemSize_);
+        return FAILED;
+    }
+
+    ret = aclrtMalloc(&modelWeightPtr_, modelWeightSize_, ACL_MEM_MALLOC_HUGE_FIRST);
+    if (ret != ACL_ERROR_NONE) {
+        ERROR_LOG("malloc buffer for weight failed, require size is %zu", modelWeightSize_);
+        return FAILED;
+    }
+
+    ret = aclmdlLoadFromFileWithMem(modelPath, &modelId_, modelMemPtr_,
+        modelMemSize_, modelWeightPtr_, modelWeightSize_);
+    if (ret != ACL_ERROR_NONE) {
+        ERROR_LOG("load model from file failed, model file is %s", modelPath);
+        return FAILED;
+    }
+
+    loadFlag_ = true;
+    INFO_LOG("load model %s success", modelPath);
+    return SUCCESS;
+}
+
+Result ModelProcess::CreateDesc() {
+    modelDesc_ = aclmdlCreateDesc();
+    if (modelDesc_ == nullptr) {
+        ERROR_LOG("create model description failed");
+        return FAILED;
+    }
+
+    aclError ret = aclmdlGetDesc(modelDesc_, modelId_);
+    if (ret != ACL_ERROR_NONE) {
+        ERROR_LOG("get model description failed");
+        return FAILED;
+    }
+
+    INFO_LOG("create model description success");
+
+    return SUCCESS;
+}
+
+void ModelProcess::DestroyDesc() {
+    if (modelDesc_ != nullptr) {
+        (void)aclmdlDestroyDesc(modelDesc_);
+        modelDesc_ = nullptr;
+    }
+}
+
+Result ModelProcess::CreateInput(void *inputDataBuffer, size_t bufferSize) {
+    input_ = aclmdlCreateDataset();
+    if (input_ == nullptr) {
+        ERROR_LOG("can't create dataset, create input failed");
+        return FAILED;
+    }
+
+    aclDataBuffer* inputData = aclCreateDataBuffer(inputDataBuffer, bufferSize);
+    if (inputData == nullptr) {
+        ERROR_LOG("can't create data buffer, create input failed");
+        return FAILED;
+    }
+
+    aclError ret = aclmdlAddDatasetBuffer(input_, inputData);
+    if (ret != ACL_ERROR_NONE) {
+        ERROR_LOG("add input dataset buffer failed");
+        aclDestroyDataBuffer(inputData);
+        inputData = nullptr;
+        return FAILED;
+    }
+
+    return SUCCESS;
+}
+
+void ModelProcess::DestroyInput() {
+    if (input_ == nullptr) {
+        return;
+    }
+
+    for (size_t i = 0; i < aclmdlGetDatasetNumBuffers(input_); ++i) {
+        aclDataBuffer* dataBuffer = aclmdlGetDatasetBuffer(input_, i);
+        aclDestroyDataBuffer(dataBuffer);
+    }
+    aclmdlDestroyDataset(input_);
+    input_ = nullptr;
+}
+
+Result ModelProcess::CreateOutput() {
+    if (modelDesc_ == nullptr) {
+        ERROR_LOG("no model description, create output failed");
+        return FAILED;
+    }
+
+    output_ = aclmdlCreateDataset();
+    if (output_ == nullptr) {
+        ERROR_LOG("can't create dataset, create output failed");
+        return FAILED;
+    }
+
+    size_t outputSize = aclmdlGetNumOutputs(modelDesc_);
+    for (size_t i = 0; i < outputSize; ++i) {
+        size_t buffer_size = aclmdlGetOutputSizeByIndex(modelDesc_, i);
+        void *outputBuffer = nullptr;
+        aclError ret = aclrtMalloc(&outputBuffer, buffer_size, ACL_MEM_MALLOC_NORMAL_ONLY);
+        if (ret != ACL_ERROR_NONE) {
+            ERROR_LOG("can't malloc buffer, size is %zu, create output failed", buffer_size);
+            return FAILED;
+        }
+
+        aclDataBuffer* outputData = aclCreateDataBuffer(outputBuffer, buffer_size);
+        if (ret != ACL_ERROR_NONE) {
+            ERROR_LOG("can't create data buffer, create output failed");
+            aclrtFree(outputBuffer);
+            return FAILED;
+        }
+
+        ret = aclmdlAddDatasetBuffer(output_, outputData);
+        if (ret != ACL_ERROR_NONE) {
+            ERROR_LOG("can't add data buffer, create output failed");
+            aclrtFree(outputBuffer);
+            aclDestroyDataBuffer(outputData);
+            return FAILED;
+        }
+    }
+
+    INFO_LOG("create model output success");
+    return SUCCESS;
+}
+
+void ModelProcess::DumpModelOutputResult(char *output_name) {
+    size_t outputNum = aclmdlGetDatasetNumBuffers(output_);
+    std::string homePath = "./result_Files";
+    for (size_t i = 0; i < outputNum; ++i) {
+        std::string fileName = std::string(output_name) + '_' + std::to_string(i) + ".bin";
+        std::string outputFileName = homePath + "/" + fileName;
+        FILE *outputFile = fopen(outputFileName.c_str(), "wb");
+        if (outputFile) {
+            aclDataBuffer* dataBuffer = aclmdlGetDatasetBuffer(output_, i);
+            void* data = aclGetDataBufferAddr(dataBuffer);
+            uint32_t len = aclGetDataBufferSizeV2(dataBuffer);
+            void* outHostData = NULL;
+            aclError ret = ACL_ERROR_NONE;
+            if (!g_isDevice) {
+                ret = aclrtMallocHost(&outHostData, len);
+                if (ret != ACL_ERROR_NONE) {
+                    ERROR_LOG("aclrtMallocHost failed, ret[%d]", ret);
+                    return;
+                }
+                ret = aclrtMemcpy(outHostData, len, data, len, ACL_MEMCPY_DEVICE_TO_HOST);
+                if (ret != ACL_ERROR_NONE) {
+                    ERROR_LOG("aclrtMemcpy failed, ret[%d]", ret);
+                    (void)aclrtFreeHost(outHostData);
+                    return;
+                }
+                fwrite(outHostData, len, sizeof(char), outputFile);
+                ret = aclrtFreeHost(outHostData);
+                if (ret != ACL_ERROR_NONE) {
+                    ERROR_LOG("aclrtFreeHost failed, ret[%d]", ret);
+                    return;
+                }
+            } else {
+                fwrite(data, len, sizeof(char), outputFile);
+            }
+            fclose(outputFile);
+            outputFile = nullptr;
+        } else {
+            ERROR_LOG("create output file [%s] failed", outputFileName.c_str());
+            return;
+        }
+    }
+    INFO_LOG("dump data success");
+    return;
+}
+
+void ModelProcess::OutputModelResult() {
+    for (size_t i = 0; i < aclmdlGetDatasetNumBuffers(output_); ++i) {
+        aclDataBuffer* dataBuffer = aclmdlGetDatasetBuffer(output_, i);
+        void* data = aclGetDataBufferAddr(dataBuffer);
+        uint32_t len = aclGetDataBufferSizeV2(dataBuffer);
+        void *outHostData = NULL;
+        aclError ret = ACL_ERROR_NONE;
+        float *outData = NULL;
+        if (!g_isDevice) {
+            ret = aclrtMallocHost(&outHostData, len);
+            if (ret != ACL_ERROR_NONE) {
+                ERROR_LOG("aclrtMallocHost failed, ret[%d]", ret);
+                return;
+            }
+            ret = aclrtMemcpy(outHostData, len, data, len, ACL_MEMCPY_DEVICE_TO_HOST);
+            if (ret != ACL_ERROR_NONE) {
+                ERROR_LOG("aclrtMemcpy failed, ret[%d]", ret);
+                return;
+            }
+            outData = reinterpret_cast<float*>(outHostData);
+        } else {
+            outData = reinterpret_cast<float*>(data);
+        }
+        std::map<float, unsigned int, std::greater<float> > resultMap;
+        for (unsigned int j = 0; j < len / sizeof(float); ++j) {
+            resultMap[*outData] = j;
+            outData++;
+        }
+        int cnt = 0;
+        for (auto it = resultMap.begin(); it != resultMap.end(); ++it) {
+            // print top 5
+            if (++cnt > 5) {
+                break;
+            }
+            INFO_LOG("top %d: index[%d] value[%lf]", cnt, it->second, it->first);
+        }
+        if (!g_isDevice) {
+            ret = aclrtFreeHost(outHostData);
+            if (ret != ACL_ERROR_NONE) {
+                ERROR_LOG("aclrtFreeHost failed, ret[%d]", ret);
+                return;
+            }
+        }
+    }
+    INFO_LOG("output data success");
+    return;
+}
+
+void ModelProcess::DestroyOutput() {
+    if (output_ == nullptr) {
+        return;
+    }
+    for (size_t i = 0; i < aclmdlGetDatasetNumBuffers(output_); ++i) {
+        aclDataBuffer* dataBuffer = aclmdlGetDatasetBuffer(output_, i);
+        void* data = aclGetDataBufferAddr(dataBuffer);
+        (void)aclrtFree(data);
+        (void)aclDestroyDataBuffer(dataBuffer);
+    }
+
+    (void)aclmdlDestroyDataset(output_);
+    output_ = nullptr;
+}
+
+Result ModelProcess::Execute() {
+    aclError ret = aclmdlExecute(modelId_, input_, output_);
+    if (ret != ACL_ERROR_NONE) {
+        ERROR_LOG("execute model failed, modelId is %u", modelId_);
+        return FAILED;
+    }
+
+    INFO_LOG("model execute success");
+    return SUCCESS;
+}
+
+void ModelProcess::Unload() {
+    if (!loadFlag_) {
+        WARN_LOG("no model had been loaded, unload failed");
+        return;
+    }
+
+    aclError ret = aclmdlUnload(modelId_);
+    if (ret != ACL_ERROR_NONE) {
+        ERROR_LOG("unload model failed, modelId is %u", modelId_);
+    }
+
+    if (modelDesc_ != nullptr) {
+        (void)aclmdlDestroyDesc(modelDesc_);
+        modelDesc_ = nullptr;
+    }
+
+    if (modelMemPtr_ != nullptr) {
+        aclrtFree(modelMemPtr_);
+        modelMemPtr_ = nullptr;
+        modelMemSize_ = 0;
+    }
+
+    if (modelWeightPtr_ != nullptr) {
+        aclrtFree(modelWeightPtr_);
+        modelWeightPtr_ = nullptr;
+        modelWeightSize_ = 0;
+    }
+
+    loadFlag_ = false;
+    INFO_LOG("unload model success, modelId is %u", modelId_);
+}

model_zoo/official/cv/lenet_quant/ascend310_infer/src/SampleProcess.cpp

@@ -0,0 +1,199 @@
+/**
+ * Copyright 2021 Huawei Technologies Co., Ltd
+ * 
+ * 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.
+ */
+
+#include "../inc/SampleProcess.h"
+#include <sys/types.h>
+#include <dirent.h>
+#include <string.h>
+#include <iostream>
+#include <fstream>
+#include "../inc/utils.h"
+#include "../inc/ModelProcess.h"
+#include "acl/acl.h"
+
+extern bool g_isDevice;
+using std::string;
+using std::vector;
+
+SampleProcess::SampleProcess(int32_t deviceId) : context_(nullptr), stream_(nullptr) {
+  deviceId_ = deviceId;
+}
+
+SampleProcess::~SampleProcess() {
+    DestroyResource();
+}
+
+Result SampleProcess::InitResource(const char *aclConfigPath) {
+    // ACL init
+    aclError ret = aclInit(aclConfigPath);
+    if (ret != ACL_ERROR_NONE) {
+        ERROR_LOG("acl init failed");
+        return FAILED;
+    }
+    INFO_LOG("acl init success");
+
+    // open device
+    ret = aclrtSetDevice(deviceId_);
+    if (ret != ACL_ERROR_NONE) {
+        ERROR_LOG("acl open device %d failed", deviceId_);
+        return FAILED;
+    }
+    INFO_LOG("open device %d success", deviceId_);
+
+    // create context (set current)
+    ret = aclrtCreateContext(&context_, deviceId_);
+    if (ret != ACL_ERROR_NONE) {
+        ERROR_LOG("acl create context failed");
+        return FAILED;
+    }
+    INFO_LOG("create context success");
+
+    // create stream
+    ret = aclrtCreateStream(&stream_);
+    if (ret != ACL_ERROR_NONE) {
+        ERROR_LOG("acl create stream failed");
+        return FAILED;
+    }
+    INFO_LOG("create stream success");
+
+    // get run mode
+    aclrtRunMode runMode;
+    ret = aclrtGetRunMode(&runMode);
+    if (ret != ACL_ERROR_NONE) {
+        ERROR_LOG("acl get run mode failed");
+        return FAILED;
+    }
+    g_isDevice = (runMode == ACL_DEVICE);
+    INFO_LOG("get run mode success");
+    return SUCCESS;
+}
+
+void SampleProcess::GetAllFiles(std::string path, std::vector<string> *files) {
+    DIR *pDir;
+    struct dirent* ptr;
+    if (!(pDir = opendir(path.c_str())))
+        return;
+    while ((ptr = readdir(pDir)) != 0) {
+        if (strcmp(ptr->d_name, ".") != 0 && strcmp(ptr->d_name, "..") != 0)
+            files->push_back(path + "/" + ptr->d_name);
+    }
+    closedir(pDir);
+}
+
+Result SampleProcess::Process(const char *om_path, const char *input_folder) {
+    // model init
+    ModelProcess processModel;
+
+    Result ret = processModel.LoadModelFromFileWithMem(om_path);
+    if (ret != SUCCESS) {
+        ERROR_LOG("execute LoadModelFromFileWithMem failed");
+        return FAILED;
+    }
+
+    ret = processModel.CreateDesc();
+    if (ret != SUCCESS) {
+        ERROR_LOG("execute CreateDesc failed");
+        return FAILED;
+    }
+
+    ret = processModel.CreateOutput();
+    if (ret != SUCCESS) {
+        ERROR_LOG("execute CreateOutput failed");
+        return FAILED;
+    }
+
+    std::vector<string> testFile;
+    GetAllFiles(input_folder, &testFile);
+
+    if (testFile.size() == 0) {
+        WARN_LOG("no input data under folder");
+    }
+
+    // loop begin
+    for (size_t index = 0; index < testFile.size(); ++index) {
+        INFO_LOG("start to process file:%s", testFile[index].c_str());
+        // model process
+        uint32_t devBufferSize;
+        void *picDevBuffer = Utils::GetDeviceBufferOfFile(testFile[index], &devBufferSize);
+        if (picDevBuffer == nullptr) {
+            ERROR_LOG("get pic device buffer failed,index is %zu", index);
+            return FAILED;
+        }
+        ret = processModel.CreateInput(picDevBuffer, devBufferSize);
+        if (ret != SUCCESS) {
+            ERROR_LOG("execute CreateInput failed");
+            aclrtFree(picDevBuffer);
+            return FAILED;
+        }
+
+        ret = processModel.Execute();
+        if (ret != SUCCESS) {
+            ERROR_LOG("execute inference failed");
+            aclrtFree(picDevBuffer);
+            return FAILED;
+        }
+
+        int pos = testFile[index].find_last_of('/');
+        std::string name = testFile[index].substr(pos+1);
+        std::string outputname = name.substr(0, name.rfind("."));
+
+        // print the top 5 confidence values
+        processModel.OutputModelResult();
+        // dump output result to file in the current directory
+        processModel.DumpModelOutputResult(const_cast<char *>(outputname.c_str()));
+
+        // release model input buffer
+        aclrtFree(picDevBuffer);
+        processModel.DestroyInput();
+    }
+    // loop end
+
+    return SUCCESS;
+}
+
+void SampleProcess::DestroyResource() {
+    aclError ret;
+    if (stream_ != nullptr) {
+        ret = aclrtDestroyStream(stream_);
+        if (ret != ACL_ERROR_NONE) {
+            ERROR_LOG("destroy stream failed");
+        }
+        stream_ = nullptr;
+    }
+    INFO_LOG("end to destroy stream");
+
+    if (context_ != nullptr) {
+        ret = aclrtDestroyContext(context_);
+        if (ret != ACL_ERROR_NONE) {
+            ERROR_LOG("destroy context failed");
+        }
+        context_ = nullptr;
+    }
+    INFO_LOG("end to destroy context");
+
+    ret = aclrtResetDevice(deviceId_);
+    if (ret != ACL_ERROR_NONE) {
+        ERROR_LOG("reset device failed");
+    }
+    INFO_LOG("end to reset device is %d", deviceId_);
+
+    ret = aclFinalize();
+    if (ret != ACL_ERROR_NONE) {
+        ERROR_LOG("finalize acl failed");
+    }
+    INFO_LOG("end to finalize acl");
+}
+

model_zoo/official/cv/lenet_quant/ascend310_infer/src/acl.json

@@ -0,0 +1 @@
+{}

model_zoo/official/cv/lenet_quant/ascend310_infer/src/build.sh

@@ -0,0 +1,55 @@
+#!/bin/bash
+# Copyright 2021 Huawei Technologies Co., Ltd
+#
+# 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.
+# ============================================================================
+path_cur=$(cd "`dirname $0`" || exit; pwd)
+
+function preparePath() {
+    rm -rf $1
+    mkdir -p $1
+    cd $1 || exit
+}
+
+function buildA300() {
+    if [ ! "${ARCH_PATTERN}" ]; then
+        # set ARCH_PATTERN to acllib when it was not specified by user
+        export ARCH_PATTERN=acllib
+        echo "ARCH_PATTERN is set to the default value: ${ARCH_PATTERN}"
+    else
+        echo "ARCH_PATTERN is set to ${ARCH_PATTERN} by user, reset it to ${ARCH_PATTERN}/acllib"
+        export ARCH_PATTERN=${ARCH_PATTERN}/acllib
+    fi
+
+    path_build=$path_cur/build
+    preparePath $path_build
+    cmake ..
+    make -j
+    ret=$?
+    cd ..
+    return ${ret}
+}
+
+# set ASCEND_VERSION to ascend-toolkit/latest when it was not specified by user
+if [ ! "${ASCEND_VERSION}" ]; then
+    export ASCEND_VERSION=ascend-toolkit/latest
+    echo "Set ASCEND_VERSION to the default value: ${ASCEND_VERSION}"
+else
+    echo "ASCEND_VERSION is set to ${ASCEND_VERSION} by user"
+fi
+
+buildA300
+
+if [ $? -ne 0 ]; then
+    exit 1
+fi

model_zoo/official/cv/lenet_quant/ascend310_infer/src/main.cpp

@@ -0,0 +1,58 @@
+/**
+ * Copyright 2021 Huawei Technologies Co., Ltd
+ * 
+ * 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.
+ */
+
+#include <gflags/gflags.h>
+#include <iostream>
+#include <fstream>
+#include <memory>
+#include "../inc/SampleProcess.h"
+#include "../inc/utils.h"
+
+bool g_isDevice = false;
+
+DEFINE_string(om_path, "", "om path");
+DEFINE_string(dataset_path, "", "dataset path");
+DEFINE_string(acljson_path, "", "acl json path");
+DEFINE_int32(device_id, 0, "device id");
+
+int main(int argc, char **argv) {
+  gflags::ParseCommandLineFlags(&argc, &argv, true);
+  std::string om_path = FLAGS_om_path;
+  std::string dataset_path = FLAGS_dataset_path;
+  std::string acljson_path = FLAGS_acljson_path;
+  int32_t device_id = FLAGS_device_id;
+  std::ifstream fin(om_path);
+  if (!fin) {
+    std::cout << "Invalid om path." << std::endl;
+    return FAILED;
+  }
+  SampleProcess processSample(device_id);
+  // acl.json is deployed for dump data.
+  Result ret = processSample.InitResource(acljson_path.c_str());
+  if (ret != SUCCESS) {
+    ERROR_LOG("sample init resource failed");
+    return FAILED;
+  }
+
+  ret = processSample.Process(om_path.c_str(), dataset_path.c_str());
+  if (ret != SUCCESS) {
+    ERROR_LOG("sample process failed");
+    return FAILED;
+  }
+
+  INFO_LOG("execute sample success");
+  return SUCCESS;
+}

model_zoo/official/cv/lenet_quant/ascend310_infer/src/utils.cpp

@@ -0,0 +1,113 @@
+/**
+ * Copyright 2021 Huawei Technologies Co., Ltd
+ * 
+ * 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.
+ */
+
+#include "../inc/utils.h"
+#include <sys/stat.h>
+#include <iostream>
+#include <fstream>
+#include <cstring>
+#include "acl/acl.h"
+
+extern bool g_isDevice;
+
+void* Utils::ReadBinFile(std::string fileName, uint32_t *fileSize) {
+    struct stat sBuf;
+    int fileStatus = stat(fileName.data(), &sBuf);
+    if (fileStatus == -1) {
+        ERROR_LOG("failed to get file");
+        return nullptr;
+    }
+    if (S_ISREG(sBuf.st_mode) == 0) {
+        ERROR_LOG("%s is not a file, please enter a file", fileName.c_str());
+        return nullptr;
+    }
+
+    std::ifstream binFile(fileName, std::ifstream::binary);
+    if (binFile.is_open() == false) {
+        ERROR_LOG("open file %s failed", fileName.c_str());
+        return nullptr;
+    }
+
+    binFile.seekg(0, binFile.end);
+    uint32_t binFileBufferLen = binFile.tellg();
+    if (binFileBufferLen == 0) {
+        ERROR_LOG("binfile is empty, filename is %s", fileName.c_str());
+        binFile.close();
+        return nullptr;
+    }
+
+    binFile.seekg(0, binFile.beg);
+
+    void* binFileBufferData = nullptr;
+    aclError ret = ACL_ERROR_NONE;
+    if (!g_isDevice) {
+        ret = aclrtMallocHost(&binFileBufferData, binFileBufferLen);
+        if (ret != ACL_ERROR_NONE) {
+            ERROR_LOG("malloc for binFileBufferData failed");
+            binFile.close();
+            return nullptr;
+        }
+        if (binFileBufferData == nullptr) {
+            ERROR_LOG("malloc binFileBufferData failed");
+            binFile.close();
+            return nullptr;
+        }
+    } else {
+        ret = aclrtMalloc(&binFileBufferData, binFileBufferLen, ACL_MEM_MALLOC_NORMAL_ONLY);
+        if (ret != ACL_ERROR_NONE) {
+            ERROR_LOG("malloc device buffer failed. size is %u", binFileBufferLen);
+            binFile.close();
+            return nullptr;
+        }
+    }
+    binFile.read(static_cast<char *>(binFileBufferData), binFileBufferLen);
+    binFile.close();
+    *fileSize = binFileBufferLen;
+    return binFileBufferData;
+}
+
+void* Utils::GetDeviceBufferOfFile(std::string fileName, uint32_t *fileSize) {
+    uint32_t inputHostBuffSize = 0;
+    void* inputHostBuff = Utils::ReadBinFile(fileName, &inputHostBuffSize);
+    if (inputHostBuff == nullptr) {
+        return nullptr;
+    }
+    if (!g_isDevice) {
+        void *inBufferDev = nullptr;
+        uint32_t inBufferSize = inputHostBuffSize;
+        aclError ret = aclrtMalloc(&inBufferDev, inBufferSize, ACL_MEM_MALLOC_NORMAL_ONLY);
+        if (ret != ACL_ERROR_NONE) {
+            ERROR_LOG("malloc device buffer failed. size is %u", inBufferSize);
+            aclrtFreeHost(inputHostBuff);
+            return nullptr;
+        }
+
+        ret = aclrtMemcpy(inBufferDev, inBufferSize, inputHostBuff, inputHostBuffSize, ACL_MEMCPY_HOST_TO_DEVICE);
+        if (ret != ACL_ERROR_NONE) {
+            ERROR_LOG("memcpy failed. device buffer size is %u, input host buffer size is %u",
+                inBufferSize, inputHostBuffSize);
+            aclrtFree(inBufferDev);
+            aclrtFreeHost(inputHostBuff);
+            return nullptr;
+        }
+        aclrtFreeHost(inputHostBuff);
+        *fileSize = inBufferSize;
+        return inBufferDev;
+    } else {
+        *fileSize = inputHostBuffSize;
+        return inputHostBuff;
+    }
+}

model_zoo/official/cv/lenet_quant/export_bin_file.py

@@ -0,0 +1,63 @@
+# Copyright 2021 Huawei Technologies Co., Ltd
+#
+# 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.
+# ============================================================================
+"""
+export mnist dataset to bin.
+"""
+import os
+import argparse
+from mindspore import context
+from src.dataset import create_dataset
+
+def parse_args():
+    parser = argparse.ArgumentParser(description='MNIST to bin')
+    parser.add_argument('--device_target', type=str, default="Ascend",
+                        choices=['Ascend', 'GPU'],
+                        help='device where the code will be implemented (default: Ascend)')
+    parser.add_argument('--dataset_dir', type=str, default='', help='dataset path')
+    parser.add_argument('--save_dir', type=str, default='', help='path to save bin file')
+    parser.add_argument('--batch_size', type=int, default=1, help='batch size for bin')
+    args_, _ = parser.parse_known_args()
+    return args_
+
+if __name__ == "__main__":
+    args = parse_args()
+    os.environ["RANK_SIZE"] = '1'
+    os.environ["RANK_ID"] = '0'
+    device_id = int(os.getenv('DEVICE_ID')) if os.getenv('DEVICE_ID') else 0
+    context.set_context(mode=context.GRAPH_MODE, device_target=args.device_target, device_id=device_id)
+    mnist_path = os.path.join(args.dataset_dir, 'test')
+    batch_size = args.batch_size
+    save_dir = os.path.join(args.save_dir, 'lenet_quant_mnist_310_infer_data')
+    folder = os.path.join(save_dir, 'mnist_bs_' + str(batch_size) + '_bin')
+    if not os.path.exists(folder):
+        os.makedirs(folder)
+    ds = create_dataset(mnist_path, batch_size)
+    iter_num = 0
+    label_file = os.path.join(save_dir, './mnist_bs_' + str(batch_size) + '_label.txt')
+    with open(label_file, 'w') as f:
+        for data in ds.create_dict_iterator():
+            image = data['image']
+            label = data['label']
+            file_name = "mnist_" + str(iter_num) + ".bin"
+            file_path = folder + "/" + file_name
+            image.asnumpy().tofile(file_path)
+            f.write(file_name)
+            for i in label:
+                f.write(',' + str(i))
+            f.write('\n')
+            iter_num += 1
+    print("=====iter_num:{}=====".format(iter_num))
+    print("=====image_data:{}=====".format(image))
+    print("=====label_data:{}=====".format(label))

model_zoo/official/cv/lenet_quant/postprocess.py

@@ -0,0 +1,57 @@
+# Copyright 2021 Huawei Technologies Co., Ltd
+#
+# 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.
+# ============================================================================
+"""
+post process for 310 inference.
+"""
+import os
+import argparse
+import numpy as np
+
+def parse_args():
+    parser = argparse.ArgumentParser(description='lenet_quant inference')
+    parser.add_argument('--result_path', type=str, default='', help='result files path')
+    parser.add_argument('--label_path', type=str, default='', help='label file path')
+    args_, _ = parser.parse_known_args()
+    return args_
+
+if __name__ == "__main__":
+    args = parse_args()
+    path = args.result_path
+    label_path = args.label_path
+    files = os.listdir(path)
+    step = 0
+    sum_right = 0
+    label_dict = {}
+    with open(label_path, 'r') as f:
+        for line in f.readlines():
+            batch_label = line.strip().split(',')
+            label_dict[batch_label[0]] = batch_label[1:]
+    for file in files:
+        full_file_path = os.path.join(path, file)
+        if os.path.isfile(full_file_path):
+            label_file = file.split('_0.bin')[0] + '.bin'
+            label_array = np.array(label_dict[label_file])
+            line = np.fromfile(full_file_path, dtype=np.float32)
+            batch_size = label_array.shape[0]
+            line_comp = line.reshape(batch_size, int(line.shape[0] / batch_size))
+        for i in range(0, batch_size):
+            pred = np.argmax(line_comp[i], axis=0)
+            step += 1
+            if pred == label_array[i].astype(np.int64):
+                sum_right += 1
+    print("=====step:{}=====".format(step))
+    print("=====sum_right:{}=====".format(sum_right))
+    accuracy = sum_right * 100.0 / step
+    print("=====accuracy:{}=====".format(accuracy))

model_zoo/official/cv/lenet_quant/scripts/run_infer_310.sh

@@ -0,0 +1,107 @@
+#!/bin/bash
+# Copyright 2021 Huawei Technologies Co., Ltd
+#
+# 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.
+# ============================================================================
+
+if [[ $# -lt 3 || $# -gt 4 ]]; then
+    echo "Usage: bash run_infer_310.sh [AIR_PATH] [DATA_PATH] [LABEL_PATH] [DEVICE_ID]
+    DEVICE_ID is optional, it can be set by environment variable device_id, otherwise the value is zero"
+exit 1
+fi
+
+get_real_path(){
+    if [ "${1:0:1}" == "/" ]; then
+        echo "$1"
+    else
+        echo "$(realpath -m $PWD/$1)"
+    fi
+}
+model=$(get_real_path $1)
+data_path=$(get_real_path $2)
+label_path=$(get_real_path $3)
+
+device_id=0
+if [ $# == 4 ]; then
+    device_id=$4
+fi
+
+echo "mindir name: "$model
+echo "dataset path: "$data_path
+echo "label path: "$label_path
+echo "device id: "$device_id
+
+export ASCEND_HOME=/usr/local/Ascend/
+if [ -d ${ASCEND_HOME}/ascend-toolkit ]; then
+    export PATH=$ASCEND_HOME/ascend-toolkit/latest/fwkacllib/ccec_compiler/bin:$ASCEND_HOME/ascend-toolkit/latest/atc/bin:$PATH
+    export LD_LIBRARY_PATH=/usr/local/lib:$ASCEND_HOME/ascend-toolkit/latest/atc/lib64:$ASCEND_HOME/ascend-toolkit/latest/fwkacllib/lib64:$ASCEND_HOME/driver/lib64:$ASCEND_HOME/add-ons:$LD_LIBRARY_PATH
+    export TBE_IMPL_PATH=$ASCEND_HOME/ascend-toolkit/latest/opp/op_impl/built-in/ai_core/tbe
+    export PYTHONPATH=${TBE_IMPL_PATH}:$ASCEND_HOME/ascend-toolkit/latest/fwkacllib/python/site-packages:$PYTHONPATH
+    export ASCEND_OPP_PATH=$ASCEND_HOME/ascend-toolkit/latest/opp
+else
+    export PATH=$ASCEND_HOME/atc/ccec_compiler/bin:$ASCEND_HOME/atc/bin:$PATH
+    export LD_LIBRARY_PATH=/usr/local/lib:$ASCEND_HOME/atc/lib64:$ASCEND_HOME/acllib/lib64:$ASCEND_HOME/driver/lib64:$ASCEND_HOME/add-ons:$LD_LIBRARY_PATH
+    export PYTHONPATH=$ASCEND_HOME/atc/python/site-packages:$PYTHONPATH
+    export ASCEND_OPP_PATH=$ASCEND_HOME/opp
+fi
+
+function air_to_om()
+{
+    atc --input_format=NCHW --framework=1 --model=$model --output=lenet_quant --soc_version=Ascend310 &> atc.log
+}
+
+function compile_app()
+{
+    cd ../ascend310_infer/src || exit
+    bash build.sh &> build.log
+}
+
+function infer()
+{
+    cd - || exit
+    if [ -d result_Files ]; then
+        rm -rf ./result_Files
+    fi
+    if [ -d time_Result ]; then
+        rm -rf ./time_Result
+    fi
+    mkdir result_Files
+    mkdir time_Result
+    ../ascend310_infer/src/out/main --om_path=./lenet_quant.om --dataset_path=$data_path --acljson_path=../ascend310_infer/src/acl.json --device_id=$device_id &> infer.log
+}
+
+function cal_acc()
+{
+    python3.7 ../postprocess.py --result_path=./result_Files --label_path=$label_path  &> acc.log
+}
+
+air_to_om
+if [ $? -ne 0 ]; then
+    echo " air to om failed"
+    exit 1
+fi
+compile_app
+if [ $? -ne 0 ]; then
+    echo "compile app code failed"
+    exit 1
+fi
+infer
+if [ $? -ne 0 ]; then
+    echo " execute inference failed"
+    exit 1
+fi
+cal_acc
+if [ $? -ne 0 ]; then
+    echo "calculate accuracy failed"
+    exit 1
+fi

model_zoo/official/cv/mobilenetv2_quant/README_CN.md

@@ -86,11 +86,13 @@ MobileNetV2总体网络架构如下：
 ```python
 ├── mobileNetv2_quant
   ├── Readme.md     # MobileNetV2-Quant相关描述
+  ├── ascend310_infer   # 实现310推理源代码
   ├── scripts
   │   ├──run_train.sh    # 使用Ascend或GPU进行训练的shell脚本
   │   ├──run_infer.sh    # 使用Ascend或GPU进行评估的shell脚本
   │   ├──run_lsq_train.sh    # 使用Ascend或GPU进行LSQ训练的shell脚本
   │   ├──run_lsq_infer.sh    # 使用Ascend或GPU进行LSQ评估的shell脚本
+  │   ├──run_infer_310.sh    # Ascend 310 推理shell脚本
   ├── src
   │   ├──config.py      # 参数配置
   │   ├──dataset.py     # 创建数据集
@@ -101,6 +103,8 @@ MobileNetV2总体网络架构如下：
   ├── train.py      # 训练脚本
   ├── eval.py       # 评估脚本
   ├── export.py     # 导出检查点文件到air/mindir中
+  ├── export_bin_file.py     # 导出ImageNet数据集的bin文件用于310推理
+  ├── postprocess.py         # 310推理后处理脚本
 ```
 
 ## 脚本参数
@@ -241,6 +245,28 @@ python export.py --checkpoint_path [CKPT_PATH] --file_format [EXPORT_FORMAT] --d
 
 `OptimizeOption` 可选 ["QAT", "LEARNED_SCALE"].
 
+## Ascend 310 推理
+
+在推理之前需要在昇腾910环境上完成AIR模型的导出。
+并使用export_bin_file.py导出ImageNet数据集的bin文件和对应的label文件：
+
+```shell
+python export_bin_file.py --dataset_dir [EVAL_DATASET_PATH] --save_dir [SAVE_PATH]
+```
+
+执行推理并得到推理精度：
+
+```shell
+# Ascend310 inference
+bash run_infer_310.sh [AIR_PATH] [DATA_PATH] [LABEL_PATH] [DEVICE_ID]
+```
+
+您可以通过acc.log文件查看结果。QAT量化推理准确性如下：
+
+```bash
+'Accuracy':0.7221
+```
+
 # 模型描述
 
 ## 性能

model_zoo/official/cv/mobilenetv2_quant/Readme.md

@@ -73,11 +73,13 @@ Users are free to choose whether to use the LEARNED_SCALE optimize option for qu
 ```python
 ├── mobileNetv2_quant
   ├── Readme.md     # descriptions about MobileNetV2-Quant
+  ├── ascend310_infer   # application for 310 inference
   ├── scripts
   │   ├──run_train.sh    # shell script for train on Ascend or GPU
   │   ├──run_infer.sh    # shell script for evaluation on Ascend or GPU
   │   ├──run_lsq_train.sh    # shell script for train (using the LEARNED_SCALE optimize option) on Ascend or GPU
   │   ├──run_lsq_infer.sh    # shell script for evaluation (using the LEARNED_SCALE optimize option) on Ascend or GPU
+  │   ├──run_infer_310.sh   # shell script for 310 inference
   ├── src
   │   ├──config.py      # parameter configuration
   │   ├──dataset.py     # creating dataset
@@ -87,7 +89,9 @@ Users are free to choose whether to use the LEARNED_SCALE optimize option for qu
   │   ├──utils.py       # supply the monitor module
   ├── train.py      # training script
   ├── eval.py       # evaluation script
-  ├── export.py     # export checkpoint files into air/onnx
+  ├── export.py     # export checkpoint files into air/mindir
+  ├── export_bin_file.py   # export bin file of ImageNet for 310 inference
+  ├── postprocess.py       # post process for 310 inference
 ```
 
 ## [Script Parameters](#contents)
@@ -231,6 +235,28 @@ python export.py --checkpoint_path [CKPT_PATH] --file_format [EXPORT_FORMAT] --d
 `EXPORT_FORMAT` should be in ["AIR", "MINDIR"].
 `OptimizeOption` should be in ["QAT", "LEARNED_SCALE"].
 
+## [Ascend 310 inference](#contents)
+
+You should export AIR model at Ascend 910 before  running the command below.
+You can use export_bin_file.py to export ImageNet bin and label for 310 inference.
+
+```shell
+python export_bin_file.py --dataset_dir [EVAL_DATASET_PATH] --save_dir [SAVE_PATH]
+```
+
+Run run_infer_310.sh and get the accuracy：
+
+```shell
+# Ascend310 inference
+bash run_infer_310.sh [AIR_PATH] [DATA_PATH] [LABEL_PATH] [DEVICE_ID]
+```
+
+You can view the results through the file "acc.log". The accuracy of the test dataset will be as follows:
+
+```bash
+'Accuracy':0.7221
+```
+
 # [Model description](#contents)
 
 ## [Performance](#contents)

model_zoo/official/cv/mobilenetv2_quant/ascend310_infer/inc/ModelProcess.h

@@ -0,0 +1,112 @@
+/**
+ * Copyright 2021 Huawei Technologies Co., Ltd
+ * 
+ * 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 MODELPROCESS_H
+#define MODELPROCESS_H
+
+#include "acl/acl.h"
+#include "../inc/utils.h"
+
+/**
+* ModelProcess
+*/
+class ModelProcess {
+ public:
+    /**
+    * @brief Constructor
+    */
+    ModelProcess();
+
+    /**
+    * @brief Destructor
+    */
+    ~ModelProcess();
+
+    /**
+    * @brief load model from file with mem
+    * @param [in] modelPath: model path
+    * @return result
+    */
+    Result LoadModelFromFileWithMem(const char *modelPath);
+
+    /**
+    * @brief unload model
+    */
+    void Unload();
+
+    /**
+    * @brief create model desc
+    * @return result
+    */
+    Result CreateDesc();
+
+    /**
+    * @brief destroy desc
+    */
+    void DestroyDesc();
+
+    /**
+    * @brief create model input
+    * @param [in] inputDataBuffer: input buffer
+    * @param [in] bufferSize: input buffer size
+    * @return result
+    */
+    Result CreateInput(void *inputDataBuffer, size_t bufferSize);
+
+    /**
+    * @brief destroy input resource
+    */
+    void DestroyInput();
+
+    /**
+    * @brief create output buffer
+    * @return result
+    */
+    Result CreateOutput();
+
+    /**
+    * @brief destroy output resource
+    */
+    void DestroyOutput();
+
+    /**
+    * @brief model execute
+    * @return result
+    */
+    Result Execute();
+
+    /**
+    * @brief dump model output result to file
+    */
+    void DumpModelOutputResult(char *output_name);
+
+    /**
+    * @brief get model output result
+    */
+    void OutputModelResult();
+
+ private:
+    uint32_t modelId_;
+    size_t modelMemSize_;
+    size_t modelWeightSize_;
+    void *modelMemPtr_;
+    void *modelWeightPtr_;
+    bool loadFlag_;  // model load flag
+    aclmdlDesc *modelDesc_;
+    aclmdlDataset *input_;
+    aclmdlDataset *output_;
+};
+#endif

model_zoo/official/cv/mobilenetv2_quant/ascend310_infer/inc/SampleProcess.h

@@ -0,0 +1,62 @@
+/**
+ * Copyright 2021 Huawei Technologies Co., Ltd
+ * 
+ * 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 SAMPLEPROCESS_H
+#define SAMPLEPROCESS_H
+
+#include <string>
+#include <vector>
+#include "acl/acl.h"
+#include "../inc/utils.h"
+
+/**
+* SampleProcess
+*/
+class SampleProcess {
+ public:
+    /**
+    * @brief Constructor
+    */
+    explicit SampleProcess(int32_t deviceId);
+
+    /**
+    * @brief Destructor
+    */
+    ~SampleProcess();
+
+    /**
+    * @brief init reousce
+    * @return result
+    */
+    Result InitResource(const char *acl_config_path);
+
+    /**
+    * @brief sample process
+    * @return result
+    */
+    Result Process(const char *om_path, const char *input_folder);
+
+    void GetAllFiles(std::string path, std::vector<std::string> *files);
+
+ private:
+    void DestroyResource();
+
+    int32_t deviceId_;
+    aclrtContext context_;
+    aclrtStream stream_;
+};
+
+#endif

model_zoo/official/cv/mobilenetv2_quant/ascend310_infer/inc/utils.h

@@ -0,0 +1,53 @@
+/**
+ * Copyright 2021 Huawei Technologies Co., Ltd
+ * 
+ * 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 MINDSPORE_INFERENCE_UTILS_H_
+#define MINDSPORE_INFERENCE_UTILS_H_
+
+#include <iostream>
+#include <string>
+
+#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)
+
+typedef enum Result {
+    SUCCESS = 0,
+    FAILED = 1
+} Result;
+
+/**
+* Utils
+*/
+class Utils {
+ public:
+    /**
+    * @brief create device buffer of file
+    * @param [in] fileName: file name
+    * @param [out] fileSize: size of file
+    * @return device buffer of file
+    */
+    static void *GetDeviceBufferOfFile(std::string fileName, uint32_t *fileSize);
+
+    /**
+    * @brief Read bin file
+    * @param [in] fileName: file name
+    * @param [out] fileSize: size of file
+    * @return buffer of pic
+    */
+    static void* ReadBinFile(std::string fileName, uint32_t *fileSize);
+};
+#endif

model_zoo/official/cv/mobilenetv2_quant/ascend310_infer/src/CMakeLists.txt

@@ -0,0 +1,41 @@
+# Copyright (c) Huawei Technologies Co., Ltd. 2021. All rights reserved.
+
+# CMake lowest version requirement
+cmake_minimum_required(VERSION 3.5.1)
+# project information
+project(InferClassification)
+# Check environment variable
+if(NOT DEFINED ENV{ASCEND_HOME})
+    message(FATAL_ERROR "please define environment variable:ASCEND_HOME")
+endif()
+
+# Compile options
+add_compile_definitions(_GLIBCXX_USE_CXX11_ABI=0)
+set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -O0 -g -std=c++17 -Werror -Wall -fPIE -Wl,--allow-shlib-undefined")
+
+# Skip build rpath
+set(CMAKE_SKIP_BUILD_RPATH True)
+
+# Set output directory
+set(PROJECT_SRC_ROOT ${CMAKE_CURRENT_LIST_DIR}/)
+set(CMAKE_RUNTIME_OUTPUT_DIRECTORY ${PROJECT_SRC_ROOT}/out)
+
+# Set include directory and library directory
+set(ACL_LIB_DIR $ENV{ASCEND_HOME}/acllib)
+set(ATLAS_ACL_LIB_DIR $ENV{ASCEND_HOME}/ascend-toolkit/latest/acllib)
+
+# Header path
+include_directories(${ACL_LIB_DIR}/include/)
+include_directories(${ATLAS_ACL_LIB_DIR}/include/)
+include_directories(${PROJECT_SRC_ROOT}/../inc)
+
+# add host lib path
+link_directories(${ACL_LIB_DIR})
+find_library(acl libascendcl.so ${ACL_LIB_DIR}/lib64 ${ATLAS_ACL_LIB_DIR}/lib64)
+
+add_executable(main utils.cpp
+                    SampleProcess.cpp
+                    ModelProcess.cpp
+                    main.cpp)
+
+target_link_libraries(main ${acl} gflags pthread)

model_zoo/official/cv/mobilenetv2_quant/ascend310_infer/src/ModelProcess.cpp

@@ -0,0 +1,326 @@
+/**
+ * Copyright 2021 Huawei Technologies Co., Ltd
+ * 
+ * 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.
+ */
+
+#include "../inc/ModelProcess.h"
+#include <iostream>
+#include <map>
+#include <sstream>
+#include <algorithm>
+#include "../inc/utils.h"
+
+extern bool g_isDevice;
+
+ModelProcess::ModelProcess() :modelId_(0), modelMemSize_(0), modelWeightSize_(0), modelMemPtr_(nullptr),
+modelWeightPtr_(nullptr), loadFlag_(false), modelDesc_(nullptr), input_(nullptr), output_(nullptr) {
+}
+
+ModelProcess::~ModelProcess() {
+    Unload();
+    DestroyDesc();
+    DestroyInput();
+    DestroyOutput();
+}
+
+Result ModelProcess::LoadModelFromFileWithMem(const char *modelPath) {
+    if (loadFlag_) {
+        ERROR_LOG("has already loaded a model");
+        return FAILED;
+    }
+
+    aclError ret = aclmdlQuerySize(modelPath, &modelMemSize_, &modelWeightSize_);
+    if (ret != ACL_ERROR_NONE) {
+        ERROR_LOG("query model failed, model file is %s", modelPath);
+        return FAILED;
+    }
+
+    ret = aclrtMalloc(&modelMemPtr_, modelMemSize_, ACL_MEM_MALLOC_HUGE_FIRST);
+    if (ret != ACL_ERROR_NONE) {
+        ERROR_LOG("malloc buffer for mem failed, require size is %zu", modelMemSize_);
+        return FAILED;
+    }
+
+    ret = aclrtMalloc(&modelWeightPtr_, modelWeightSize_, ACL_MEM_MALLOC_HUGE_FIRST);
+    if (ret != ACL_ERROR_NONE) {
+        ERROR_LOG("malloc buffer for weight failed, require size is %zu", modelWeightSize_);
+        return FAILED;
+    }
+
+    ret = aclmdlLoadFromFileWithMem(modelPath, &modelId_, modelMemPtr_,
+        modelMemSize_, modelWeightPtr_, modelWeightSize_);
+    if (ret != ACL_ERROR_NONE) {
+        ERROR_LOG("load model from file failed, model file is %s", modelPath);
+        return FAILED;
+    }
+
+    loadFlag_ = true;
+    INFO_LOG("load model %s success", modelPath);
+    return SUCCESS;
+}
+
+Result ModelProcess::CreateDesc() {
+    modelDesc_ = aclmdlCreateDesc();
+    if (modelDesc_ == nullptr) {
+        ERROR_LOG("create model description failed");
+        return FAILED;
+    }
+
+    aclError ret = aclmdlGetDesc(modelDesc_, modelId_);
+    if (ret != ACL_ERROR_NONE) {
+        ERROR_LOG("get model description failed");
+        return FAILED;
+    }
+
+    INFO_LOG("create model description success");
+
+    return SUCCESS;
+}
+
+void ModelProcess::DestroyDesc() {
+    if (modelDesc_ != nullptr) {
+        (void)aclmdlDestroyDesc(modelDesc_);
+        modelDesc_ = nullptr;
+    }
+}
+
+Result ModelProcess::CreateInput(void *inputDataBuffer, size_t bufferSize) {
+    input_ = aclmdlCreateDataset();
+    if (input_ == nullptr) {
+        ERROR_LOG("can't create dataset, create input failed");
+        return FAILED;
+    }
+
+    aclDataBuffer* inputData = aclCreateDataBuffer(inputDataBuffer, bufferSize);
+    if (inputData == nullptr) {
+        ERROR_LOG("can't create data buffer, create input failed");
+        return FAILED;
+    }
+
+    aclError ret = aclmdlAddDatasetBuffer(input_, inputData);
+    if (ret != ACL_ERROR_NONE) {
+        ERROR_LOG("add input dataset buffer failed");
+        aclDestroyDataBuffer(inputData);
+        inputData = nullptr;
+        return FAILED;
+    }
+
+    return SUCCESS;
+}
+
+void ModelProcess::DestroyInput() {
+    if (input_ == nullptr) {
+        return;
+    }
+
+    for (size_t i = 0; i < aclmdlGetDatasetNumBuffers(input_); ++i) {
+        aclDataBuffer* dataBuffer = aclmdlGetDatasetBuffer(input_, i);
+        aclDestroyDataBuffer(dataBuffer);
+    }
+    aclmdlDestroyDataset(input_);
+    input_ = nullptr;
+}
+
+Result ModelProcess::CreateOutput() {
+    if (modelDesc_ == nullptr) {
+        ERROR_LOG("no model description, create output failed");
+        return FAILED;
+    }
+
+    output_ = aclmdlCreateDataset();
+    if (output_ == nullptr) {
+        ERROR_LOG("can't create dataset, create output failed");
+        return FAILED;
+    }
+
+    size_t outputSize = aclmdlGetNumOutputs(modelDesc_);
+    for (size_t i = 0; i < outputSize; ++i) {
+        size_t buffer_size = aclmdlGetOutputSizeByIndex(modelDesc_, i);
+        void *outputBuffer = nullptr;
+        aclError ret = aclrtMalloc(&outputBuffer, buffer_size, ACL_MEM_MALLOC_NORMAL_ONLY);
+        if (ret != ACL_ERROR_NONE) {
+            ERROR_LOG("can't malloc buffer, size is %zu, create output failed", buffer_size);
+            return FAILED;
+        }
+
+        aclDataBuffer* outputData = aclCreateDataBuffer(outputBuffer, buffer_size);
+        if (ret != ACL_ERROR_NONE) {
+            ERROR_LOG("can't create data buffer, create output failed");
+            aclrtFree(outputBuffer);
+            return FAILED;
+        }
+
+        ret = aclmdlAddDatasetBuffer(output_, outputData);
+        if (ret != ACL_ERROR_NONE) {
+            ERROR_LOG("can't add data buffer, create output failed");
+            aclrtFree(outputBuffer);
+            aclDestroyDataBuffer(outputData);
+            return FAILED;
+        }
+    }
+
+    INFO_LOG("create model output success");
+    return SUCCESS;
+}
+
+void ModelProcess::DumpModelOutputResult(char *output_name) {
+    size_t outputNum = aclmdlGetDatasetNumBuffers(output_);
+    std::string homePath = "./result_Files";
+    for (size_t i = 0; i < outputNum; ++i) {
+        std::string fileName = std::string(output_name) + '_' + std::to_string(i) + ".bin";
+        std::string outputFileName = homePath + "/" + fileName;
+        FILE *outputFile = fopen(outputFileName.c_str(), "wb");
+        if (outputFile) {
+            aclDataBuffer* dataBuffer = aclmdlGetDatasetBuffer(output_, i);
+            void* data = aclGetDataBufferAddr(dataBuffer);
+            uint32_t len = aclGetDataBufferSizeV2(dataBuffer);
+            void* outHostData = NULL;
+            aclError ret = ACL_ERROR_NONE;
+            if (!g_isDevice) {
+                ret = aclrtMallocHost(&outHostData, len);
+                if (ret != ACL_ERROR_NONE) {
+                    ERROR_LOG("aclrtMallocHost failed, ret[%d]", ret);
+                    return;
+                }
+                ret = aclrtMemcpy(outHostData, len, data, len, ACL_MEMCPY_DEVICE_TO_HOST);
+                if (ret != ACL_ERROR_NONE) {
+                    ERROR_LOG("aclrtMemcpy failed, ret[%d]", ret);
+                    (void)aclrtFreeHost(outHostData);
+                    return;
+                }
+                fwrite(outHostData, len, sizeof(char), outputFile);
+                ret = aclrtFreeHost(outHostData);
+                if (ret != ACL_ERROR_NONE) {
+                    ERROR_LOG("aclrtFreeHost failed, ret[%d]", ret);
+                    return;
+                }
+            } else {
+                fwrite(data, len, sizeof(char), outputFile);
+            }
+            fclose(outputFile);
+            outputFile = nullptr;
+        } else {
+            ERROR_LOG("create output file [%s] failed", outputFileName.c_str());
+            return;
+        }
+    }
+    INFO_LOG("dump data success");
+    return;
+}
+
+void ModelProcess::OutputModelResult() {
+    for (size_t i = 0; i < aclmdlGetDatasetNumBuffers(output_); ++i) {
+        aclDataBuffer* dataBuffer = aclmdlGetDatasetBuffer(output_, i);
+        void* data = aclGetDataBufferAddr(dataBuffer);
+        uint32_t len = aclGetDataBufferSizeV2(dataBuffer);
+        void *outHostData = NULL;
+        aclError ret = ACL_ERROR_NONE;
+        float *outData = NULL;
+        if (!g_isDevice) {
+            ret = aclrtMallocHost(&outHostData, len);
+            if (ret != ACL_ERROR_NONE) {
+                ERROR_LOG("aclrtMallocHost failed, ret[%d]", ret);
+                return;
+            }
+            ret = aclrtMemcpy(outHostData, len, data, len, ACL_MEMCPY_DEVICE_TO_HOST);
+            if (ret != ACL_ERROR_NONE) {
+                ERROR_LOG("aclrtMemcpy failed, ret[%d]", ret);
+                return;
+            }
+            outData = reinterpret_cast<float*>(outHostData);
+        } else {
+            outData = reinterpret_cast<float*>(data);
+        }
+        std::map<float, unsigned int, std::greater<float> > resultMap;
+        for (unsigned int j = 0; j < len / sizeof(float); ++j) {
+            resultMap[*outData] = j;
+            outData++;
+        }
+        int cnt = 0;
+        for (auto it = resultMap.begin(); it != resultMap.end(); ++it) {
+            // print top 5
+            if (++cnt > 5) {
+                break;
+            }
+            INFO_LOG("top %d: index[%d] value[%lf]", cnt, it->second, it->first);
+        }
+        if (!g_isDevice) {
+            ret = aclrtFreeHost(outHostData);
+            if (ret != ACL_ERROR_NONE) {
+                ERROR_LOG("aclrtFreeHost failed, ret[%d]", ret);
+                return;
+            }
+        }
+    }
+    INFO_LOG("output data success");
+    return;
+}
+
+void ModelProcess::DestroyOutput() {
+    if (output_ == nullptr) {
+        return;
+    }
+    for (size_t i = 0; i < aclmdlGetDatasetNumBuffers(output_); ++i) {
+        aclDataBuffer* dataBuffer = aclmdlGetDatasetBuffer(output_, i);
+        void* data = aclGetDataBufferAddr(dataBuffer);
+        (void)aclrtFree(data);
+        (void)aclDestroyDataBuffer(dataBuffer);
+    }
+
+    (void)aclmdlDestroyDataset(output_);
+    output_ = nullptr;
+}
+
+Result ModelProcess::Execute() {
+    aclError ret = aclmdlExecute(modelId_, input_, output_);
+    if (ret != ACL_ERROR_NONE) {
+        ERROR_LOG("execute model failed, modelId is %u", modelId_);
+        return FAILED;
+    }
+
+    INFO_LOG("model execute success");
+    return SUCCESS;
+}
+
+void ModelProcess::Unload() {
+    if (!loadFlag_) {
+        WARN_LOG("no model had been loaded, unload failed");
+        return;
+    }
+
+    aclError ret = aclmdlUnload(modelId_);
+    if (ret != ACL_ERROR_NONE) {
+        ERROR_LOG("unload model failed, modelId is %u", modelId_);
+    }
+
+    if (modelDesc_ != nullptr) {
+        (void)aclmdlDestroyDesc(modelDesc_);
+        modelDesc_ = nullptr;
+    }
+
+    if (modelMemPtr_ != nullptr) {
+        aclrtFree(modelMemPtr_);
+        modelMemPtr_ = nullptr;
+        modelMemSize_ = 0;
+    }
+
+    if (modelWeightPtr_ != nullptr) {
+        aclrtFree(modelWeightPtr_);
+        modelWeightPtr_ = nullptr;
+        modelWeightSize_ = 0;
+    }
+
+    loadFlag_ = false;
+    INFO_LOG("unload model success, modelId is %u", modelId_);
+}

model_zoo/official/cv/mobilenetv2_quant/ascend310_infer/src/SampleProcess.cpp

@@ -0,0 +1,199 @@
+/**
+ * Copyright 2021 Huawei Technologies Co., Ltd
+ * 
+ * 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.
+ */
+
+#include "../inc/SampleProcess.h"
+#include <sys/types.h>
+#include <dirent.h>
+#include <string.h>
+#include <iostream>
+#include <fstream>
+#include "../inc/utils.h"
+#include "../inc/ModelProcess.h"
+#include "acl/acl.h"
+
+extern bool g_isDevice;
+using std::string;
+using std::vector;
+
+SampleProcess::SampleProcess(int32_t deviceId) : context_(nullptr), stream_(nullptr) {
+    deviceId_ = deviceId;
+}
+
+SampleProcess::~SampleProcess() {
+    DestroyResource();
+}
+
+Result SampleProcess::InitResource(const char *aclConfigPath) {
+    // ACL init
+    aclError ret = aclInit(aclConfigPath);
+    if (ret != ACL_ERROR_NONE) {
+        ERROR_LOG("acl init failed");
+        return FAILED;
+    }
+    INFO_LOG("acl init success");
+
+    // open device
+    ret = aclrtSetDevice(deviceId_);
+    if (ret != ACL_ERROR_NONE) {
+        ERROR_LOG("acl open device %d failed", deviceId_);
+        return FAILED;
+    }
+    INFO_LOG("open device %d success", deviceId_);
+
+    // create context (set current)
+    ret = aclrtCreateContext(&context_, deviceId_);
+    if (ret != ACL_ERROR_NONE) {
+        ERROR_LOG("acl create context failed");
+        return FAILED;
+    }
+    INFO_LOG("create context success");
+
+    // create stream
+    ret = aclrtCreateStream(&stream_);
+    if (ret != ACL_ERROR_NONE) {
+        ERROR_LOG("acl create stream failed");
+        return FAILED;
+    }
+    INFO_LOG("create stream success");
+
+    // get run mode
+    aclrtRunMode runMode;
+    ret = aclrtGetRunMode(&runMode);
+    if (ret != ACL_ERROR_NONE) {
+        ERROR_LOG("acl get run mode failed");
+        return FAILED;
+    }
+    g_isDevice = (runMode == ACL_DEVICE);
+    INFO_LOG("get run mode success");
+    return SUCCESS;
+}
+
+void SampleProcess::GetAllFiles(std::string path, std::vector<string> *files) {
+    DIR *pDir;
+    struct dirent* ptr;
+    if (!(pDir = opendir(path.c_str())))
+        return;
+    while ((ptr = readdir(pDir)) != 0) {
+        if (strcmp(ptr->d_name, ".") != 0 && strcmp(ptr->d_name, "..") != 0)
+            files->push_back(path + "/" + ptr->d_name);
+    }
+    closedir(pDir);
+}
+
+Result SampleProcess::Process(const char *om_path, const char *input_folder) {
+    // model init
+    ModelProcess processModel;
+
+    Result ret = processModel.LoadModelFromFileWithMem(om_path);
+    if (ret != SUCCESS) {
+        ERROR_LOG("execute LoadModelFromFileWithMem failed");
+        return FAILED;
+    }
+
+    ret = processModel.CreateDesc();
+    if (ret != SUCCESS) {
+        ERROR_LOG("execute CreateDesc failed");
+        return FAILED;
+    }
+
+    ret = processModel.CreateOutput();
+    if (ret != SUCCESS) {
+        ERROR_LOG("execute CreateOutput failed");
+        return FAILED;
+    }
+
+    std::vector<string> testFile;
+    GetAllFiles(input_folder, &testFile);
+
+    if (testFile.size() == 0) {
+        WARN_LOG("no input data under folder");
+    }
+
+    // loop begin
+    for (size_t index = 0; index < testFile.size(); ++index) {
+        INFO_LOG("start to process file:%s", testFile[index].c_str());
+        // model process
+        uint32_t devBufferSize;
+        void *picDevBuffer = Utils::GetDeviceBufferOfFile(testFile[index], &devBufferSize);
+        if (picDevBuffer == nullptr) {
+            ERROR_LOG("get pic device buffer failed,index is %zu", index);
+            return FAILED;
+        }
+        ret = processModel.CreateInput(picDevBuffer, devBufferSize);
+        if (ret != SUCCESS) {
+            ERROR_LOG("execute CreateInput failed");
+            aclrtFree(picDevBuffer);
+            return FAILED;
+        }
+
+        ret = processModel.Execute();
+        if (ret != SUCCESS) {
+            ERROR_LOG("execute inference failed");
+            aclrtFree(picDevBuffer);
+            return FAILED;
+        }
+
+        int pos = testFile[index].find_last_of('/');
+        std::string name = testFile[index].substr(pos+1);
+        std::string outputname = name.substr(0, name.rfind("."));
+
+        // print the top 5 confidence values
+        processModel.OutputModelResult();
+        // dump output result to file in the current directory
+        processModel.DumpModelOutputResult(const_cast<char *>(outputname.c_str()));
+
+        // release model input buffer
+        aclrtFree(picDevBuffer);
+        processModel.DestroyInput();
+    }
+    // loop end
+
+    return SUCCESS;
+}
+
+void SampleProcess::DestroyResource() {
+    aclError ret;
+    if (stream_ != nullptr) {
+        ret = aclrtDestroyStream(stream_);
+        if (ret != ACL_ERROR_NONE) {
+            ERROR_LOG("destroy stream failed");
+        }
+        stream_ = nullptr;
+    }
+    INFO_LOG("end to destroy stream");
+
+    if (context_ != nullptr) {
+        ret = aclrtDestroyContext(context_);
+        if (ret != ACL_ERROR_NONE) {
+            ERROR_LOG("destroy context failed");
+        }
+        context_ = nullptr;
+    }
+    INFO_LOG("end to destroy context");
+
+    ret = aclrtResetDevice(deviceId_);
+    if (ret != ACL_ERROR_NONE) {
+        ERROR_LOG("reset device failed");
+    }
+    INFO_LOG("end to reset device is %d", deviceId_);
+
+    ret = aclFinalize();
+    if (ret != ACL_ERROR_NONE) {
+        ERROR_LOG("finalize acl failed");
+    }
+    INFO_LOG("end to finalize acl");
+}
+

model_zoo/official/cv/mobilenetv2_quant/ascend310_infer/src/acl.json

@@ -0,0 +1 @@
+{}

model_zoo/official/cv/mobilenetv2_quant/ascend310_infer/src/build.sh

@@ -0,0 +1,55 @@
+#!/bin/bash
+# Copyright 2021 Huawei Technologies Co., Ltd
+#
+# 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.
+# ============================================================================
+path_cur=$(cd "`dirname $0`" || exit; pwd)
+
+function preparePath() {
+    rm -rf $1
+    mkdir -p $1
+    cd $1 || exit
+}
+
+function buildA300() {
+    if [ ! "${ARCH_PATTERN}" ]; then
+        # set ARCH_PATTERN to acllib when it was not specified by user
+        export ARCH_PATTERN=acllib
+        echo "ARCH_PATTERN is set to the default value: ${ARCH_PATTERN}"
+    else
+        echo "ARCH_PATTERN is set to ${ARCH_PATTERN} by user, reset it to ${ARCH_PATTERN}/acllib"
+        export ARCH_PATTERN=${ARCH_PATTERN}/acllib
+    fi
+
+    path_build=$path_cur/build
+    preparePath $path_build
+    cmake ..
+    make -j
+    ret=$?
+    cd ..
+    return ${ret}
+}
+
+# set ASCEND_VERSION to ascend-toolkit/latest when it was not specified by user
+if [ ! "${ASCEND_VERSION}" ]; then
+    export ASCEND_VERSION=ascend-toolkit/latest
+    echo "Set ASCEND_VERSION to the default value: ${ASCEND_VERSION}"
+else
+    echo "ASCEND_VERSION is set to ${ASCEND_VERSION} by user"
+fi
+
+buildA300
+
+if [ $? -ne 0 ]; then
+    exit 1
+fi

model_zoo/official/cv/mobilenetv2_quant/ascend310_infer/src/main.cpp

@@ -0,0 +1,58 @@
+/**
+ * Copyright 2021 Huawei Technologies Co., Ltd
+ * 
+ * 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.
+ */
+
+#include <gflags/gflags.h>
+#include <iostream>
+#include <fstream>
+#include <memory>
+#include "../inc/SampleProcess.h"
+#include "../inc/utils.h"
+
+bool g_isDevice = false;
+
+DEFINE_string(om_path, "", "om path");
+DEFINE_string(dataset_path, "", "dataset path");
+DEFINE_string(acljson_path, "", "acl json path");
+DEFINE_int32(device_id, 0, "device id");
+
+int main(int argc, char **argv) {
+  gflags::ParseCommandLineFlags(&argc, &argv, true);
+  std::string om_path = FLAGS_om_path;
+  std::string dataset_path = FLAGS_dataset_path;
+  std::string acljson_path = FLAGS_acljson_path;
+  int32_t device_id = FLAGS_device_id;
+  std::ifstream fin(om_path);
+  if (!fin) {
+    std::cout << "Invalid om path." << std::endl;
+    return FAILED;
+  }
+  SampleProcess processSample(device_id);
+  // acl.json is deployed for dump data.
+  Result ret = processSample.InitResource(acljson_path.c_str());
+  if (ret != SUCCESS) {
+    ERROR_LOG("sample init resource failed");
+    return FAILED;
+  }
+
+  ret = processSample.Process(om_path.c_str(), dataset_path.c_str());
+  if (ret != SUCCESS) {
+    ERROR_LOG("sample process failed");
+    return FAILED;
+  }
+
+  INFO_LOG("execute sample success");
+  return SUCCESS;
+}

model_zoo/official/cv/mobilenetv2_quant/ascend310_infer/src/utils.cpp

@@ -0,0 +1,113 @@
+/**
+ * Copyright 2021 Huawei Technologies Co., Ltd
+ * 
+ * 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.
+ */
+
+#include "../inc/utils.h"
+#include <sys/stat.h>
+#include <iostream>
+#include <fstream>
+#include <cstring>
+#include "acl/acl.h"
+
+extern bool g_isDevice;
+
+void* Utils::ReadBinFile(std::string fileName, uint32_t *fileSize) {
+    struct stat sBuf;
+    int fileStatus = stat(fileName.data(), &sBuf);
+    if (fileStatus == -1) {
+        ERROR_LOG("failed to get file");
+        return nullptr;
+    }
+    if (S_ISREG(sBuf.st_mode) == 0) {
+        ERROR_LOG("%s is not a file, please enter a file", fileName.c_str());
+        return nullptr;
+    }
+
+    std::ifstream binFile(fileName, std::ifstream::binary);
+    if (binFile.is_open() == false) {
+        ERROR_LOG("open file %s failed", fileName.c_str());
+        return nullptr;
+    }
+
+    binFile.seekg(0, binFile.end);
+    uint32_t binFileBufferLen = binFile.tellg();
+    if (binFileBufferLen == 0) {
+        ERROR_LOG("binfile is empty, filename is %s", fileName.c_str());
+        binFile.close();
+        return nullptr;
+    }
+
+    binFile.seekg(0, binFile.beg);
+
+    void* binFileBufferData = nullptr;
+    aclError ret = ACL_ERROR_NONE;
+    if (!g_isDevice) {
+        ret = aclrtMallocHost(&binFileBufferData, binFileBufferLen);
+        if (ret != ACL_ERROR_NONE) {
+            ERROR_LOG("malloc for binFileBufferData failed");
+            binFile.close();
+            return nullptr;
+        }
+        if (binFileBufferData == nullptr) {
+            ERROR_LOG("malloc binFileBufferData failed");
+            binFile.close();
+            return nullptr;
+        }
+    } else {
+        ret = aclrtMalloc(&binFileBufferData, binFileBufferLen, ACL_MEM_MALLOC_NORMAL_ONLY);
+        if (ret != ACL_ERROR_NONE) {
+            ERROR_LOG("malloc device buffer failed. size is %u", binFileBufferLen);
+            binFile.close();
+            return nullptr;
+        }
+    }
+    binFile.read(static_cast<char *>(binFileBufferData), binFileBufferLen);
+    binFile.close();
+    *fileSize = binFileBufferLen;
+    return binFileBufferData;
+}
+
+void* Utils::GetDeviceBufferOfFile(std::string fileName, uint32_t *fileSize) {
+    uint32_t inputHostBuffSize = 0;
+    void* inputHostBuff = Utils::ReadBinFile(fileName, &inputHostBuffSize);
+    if (inputHostBuff == nullptr) {
+        return nullptr;
+    }
+    if (!g_isDevice) {
+        void *inBufferDev = nullptr;
+        uint32_t inBufferSize = inputHostBuffSize;
+        aclError ret = aclrtMalloc(&inBufferDev, inBufferSize, ACL_MEM_MALLOC_NORMAL_ONLY);
+        if (ret != ACL_ERROR_NONE) {
+            ERROR_LOG("malloc device buffer failed. size is %u", inBufferSize);
+            aclrtFreeHost(inputHostBuff);
+            return nullptr;
+        }
+
+        ret = aclrtMemcpy(inBufferDev, inBufferSize, inputHostBuff, inputHostBuffSize, ACL_MEMCPY_HOST_TO_DEVICE);
+        if (ret != ACL_ERROR_NONE) {
+            ERROR_LOG("memcpy failed. device buffer size is %u, input host buffer size is %u",
+                inBufferSize, inputHostBuffSize);
+            aclrtFree(inBufferDev);
+            aclrtFreeHost(inputHostBuff);
+            return nullptr;
+        }
+        aclrtFreeHost(inputHostBuff);
+        *fileSize = inBufferSize;
+        return inBufferDev;
+    } else {
+        *fileSize = inputHostBuffSize;
+        return inputHostBuff;
+    }
+}

model_zoo/official/cv/mobilenetv2_quant/export_bin_file.py

@@ -0,0 +1,65 @@
+# Copyright 2021 Huawei Technologies Co., Ltd
+#
+# 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.
+# ============================================================================
+"""
+export imagenet2012 dataset to bin.
+"""
+import os
+import argparse
+from mindspore import context
+from src.dataset import create_dataset
+from src.config import config_ascend_quant
+
+def parse_args():
+    parser = argparse.ArgumentParser(description='ImageNet2012 to bin')
+    parser.add_argument('--device_target', type=str, default="Ascend",
+                        choices=['Ascend', 'GPU'],
+                        help='device where the code will be implemented (default: Ascend)')
+    parser.add_argument('--dataset_dir', type=str, default='', help='dataset path')
+    parser.add_argument('--save_dir', type=str, default='', help='path to save bin file')
+    parser.add_argument('--batch_size', type=int, default=1, help='batch size for bin')
+    args_, _ = parser.parse_known_args()
+    return args_
+
+if __name__ == "__main__":
+    args = parse_args()
+    os.environ["RANK_SIZE"] = '1'
+    os.environ["RANK_ID"] = '0'
+    device_id = int(os.getenv('DEVICE_ID')) if os.getenv('DEVICE_ID') else 0
+    context.set_context(mode=context.GRAPH_MODE, device_target=args.device_target, device_id=device_id)
+    imagenet2012_path = args.dataset_dir
+    batch_size = args.batch_size
+    save_dir = os.path.join(args.save_dir, 'imagenet2012_310_infer_data')
+    folder = os.path.join(save_dir, 'imagenet2012_bs_' + str(batch_size) + '_bin')
+    if not os.path.exists(folder):
+        os.makedirs(folder)
+    ds = create_dataset(imagenet2012_path, do_train=False, config=config_ascend_quant,
+                        device_target=args.device_target, repeat_num=1, batch_size=batch_size)
+    iter_num = 0
+    label_file = os.path.join(save_dir, './imagenet2012_bs_' + str(batch_size) + '_label.txt')
+    with open(label_file, 'w') as f:
+        for data in ds.create_dict_iterator():
+            image = data['image']
+            label = data['label']
+            file_name = "imagenet2012_" + str(iter_num) + ".bin"
+            file_path = folder + "/" + file_name
+            image.asnumpy().tofile(file_path)
+            f.write(file_name)
+            for i in label:
+                f.write(',' + str(i))
+            f.write('\n')
+            iter_num += 1
+    print("=====iter_num:{}=====".format(iter_num))
+    print("=====image_data:{}=====".format(image))
+    print("=====label_data:{}=====".format(label))

model_zoo/official/cv/mobilenetv2_quant/postprocess.py

@@ -0,0 +1,57 @@
+# Copyright 2021 Huawei Technologies Co., Ltd
+#
+# 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.
+# ============================================================================
+"""
+post process for 310 inference.
+"""
+import os
+import argparse
+import numpy as np
+
+def parse_args():
+    parser = argparse.ArgumentParser(description='mobilenetv2_quant inference')
+    parser.add_argument('--result_path', type=str, default='', help='result files path')
+    parser.add_argument('--label_path', type=str, default='', help='label file path')
+    args_, _ = parser.parse_known_args()
+    return args_
+
+if __name__ == "__main__":
+    args = parse_args()
+    path = args.result_path
+    label_path = args.label_path
+    files = os.listdir(path)
+    step = 0
+    sum_right = 0
+    label_dict = {}
+    with open(label_path, 'r') as f:
+        for line in f.readlines():
+            batch_label = line.strip().split(',')
+            label_dict[batch_label[0]] = batch_label[1:]
+    for file in files:
+        full_file_path = os.path.join(path, file)
+        if os.path.isfile(full_file_path):
+            label_file = file.split('_0.bin')[0] + '.bin'
+            label_array = np.array(label_dict[label_file])
+            line = np.fromfile(full_file_path, dtype=np.float32)
+            batch_size = label_array.shape[0]
+            line_comp = line.reshape(batch_size, int(line.shape[0] / batch_size))
+        for i in range(0, batch_size):
+            pred = np.argmax(line_comp[i], axis=0)
+            step += 1
+            if pred == label_array[i].astype(np.int64):
+                sum_right += 1
+    print("=====step:{}=====".format(step))
+    print("=====sum_right:{}=====".format(sum_right))
+    accuracy = sum_right * 100.0 / step
+    print("=====accuracy:{}=====".format(accuracy))

model_zoo/official/cv/mobilenetv2_quant/scripts/run_infer_310.sh

@@ -0,0 +1,107 @@
+#!/bin/bash
+# Copyright 2021 Huawei Technologies Co., Ltd
+#
+# 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.
+# ============================================================================
+
+if [[ $# -lt 3 || $# -gt 4 ]]; then
+    echo "Usage: bash run_infer_310.sh [AIR_PATH] [DATA_PATH] [LABEL_PATH] [DEVICE_ID]
+    DEVICE_ID is optional, it can be set by environment variable device_id, otherwise the value is zero"
+exit 1
+fi
+
+get_real_path(){
+    if [ "${1:0:1}" == "/" ]; then
+        echo "$1"
+    else
+        echo "$(realpath -m $PWD/$1)"
+    fi
+}
+model=$(get_real_path $1)
+data_path=$(get_real_path $2)
+label_path=$(get_real_path $3)
+
+device_id=0
+if [ $# == 4 ]; then
+    device_id=$4
+fi
+
+echo "mindir name: "$model
+echo "dataset path: "$data_path
+echo "label path: "$label_path
+echo "device id: "$device_id
+
+export ASCEND_HOME=/usr/local/Ascend/
+if [ -d ${ASCEND_HOME}/ascend-toolkit ]; then
+    export PATH=$ASCEND_HOME/ascend-toolkit/latest/fwkacllib/ccec_compiler/bin:$ASCEND_HOME/ascend-toolkit/latest/atc/bin:$PATH
+    export LD_LIBRARY_PATH=/usr/local/lib:$ASCEND_HOME/ascend-toolkit/latest/atc/lib64:$ASCEND_HOME/ascend-toolkit/latest/fwkacllib/lib64:$ASCEND_HOME/driver/lib64:$ASCEND_HOME/add-ons:$LD_LIBRARY_PATH
+    export TBE_IMPL_PATH=$ASCEND_HOME/ascend-toolkit/latest/opp/op_impl/built-in/ai_core/tbe
+    export PYTHONPATH=${TBE_IMPL_PATH}:$ASCEND_HOME/ascend-toolkit/latest/fwkacllib/python/site-packages:$PYTHONPATH
+    export ASCEND_OPP_PATH=$ASCEND_HOME/ascend-toolkit/latest/opp
+else
+    export PATH=$ASCEND_HOME/atc/ccec_compiler/bin:$ASCEND_HOME/atc/bin:$PATH
+    export LD_LIBRARY_PATH=/usr/local/lib:$ASCEND_HOME/atc/lib64:$ASCEND_HOME/acllib/lib64:$ASCEND_HOME/driver/lib64:$ASCEND_HOME/add-ons:$LD_LIBRARY_PATH
+    export PYTHONPATH=$ASCEND_HOME/atc/python/site-packages:$PYTHONPATH
+    export ASCEND_OPP_PATH=$ASCEND_HOME/opp
+fi
+
+function air_to_om()
+{
+    atc --input_format=NCHW --framework=1 --model=$model --output=mobilenetv2_quant --soc_version=Ascend310 &> atc.log
+}
+
+function compile_app()
+{
+    cd ../ascend310_infer/src || exit
+    bash build.sh &> build.log
+}
+
+function infer()
+{
+    cd - || exit
+    if [ -d result_Files ]; then
+        rm -rf ./result_Files
+    fi
+    if [ -d time_Result ]; then
+        rm -rf ./time_Result
+    fi
+    mkdir result_Files
+    mkdir time_Result
+    ../ascend310_infer/src/out/main --om_path=./mobilenetv2_quant.om --dataset_path=$data_path --acljson_path=../ascend310_infer/src/acl.json --device_id=$device_id &> infer.log
+}
+
+function cal_acc()
+{
+    python3.7 ../postprocess.py --result_path=./result_Files --label_path=$label_path  &> acc.log
+}
+
+air_to_om
+if [ $? -ne 0 ]; then
+    echo " air to om failed"
+    exit 1
+fi
+compile_app
+if [ $? -ne 0 ]; then
+    echo "compile app code failed"
+    exit 1
+fi
+infer
+if [ $? -ne 0 ]; then
+    echo " execute inference failed"
+    exit 1
+fi
+cal_acc
+if [ $? -ne 0 ]; then
+    echo "calculate accuracy failed"
+    exit 1
+fi

model_zoo/official/cv/resnet50_quant/README.md

@@ -73,9 +73,11 @@ For FP16 operators, if the input data type is FP32, the backend of MindSpore wil
 ```python
 ├── resnet50_quant
   ├── README.md     # descriptions about Resnet50-Quant
+  ├── ascend310_infer   # application for 310 inference
   ├── scripts
   │   ├──run_train.sh   # shell script for train on Ascend
   │   ├──run_infer.sh   # shell script for evaluation on Ascend
+  │   ├──run_infer_310.sh   # shell script for 310 inference
   ├── models
   │   ├──resnet_quant.py           # define the network model of resnet50-quant
   │   ├──resnet_quant_manual.py    # define the manually quantized network model of resnet50-quant
@@ -88,6 +90,8 @@ For FP16 operators, if the input data type is FP32, the backend of MindSpore wil
   ├── train.py      # training script
   ├── eval.py       # evaluation script
   ├── export.py     # export script
+  ├── export_bin_file.py   # export bin file of ImageNet for 310 inference
+  ├── postprocess.py       # post process for 310 inference
 
 ```
 
@@ -169,6 +173,36 @@ Inference result will be stored in the example path, you can find result like th
 result: {'acc': 0.76576314102564111}
 ```
 
+## [Model Export](#contents)
+
+```shell
+python export.py --checkpoint_path [CKPT_PATH] --file_format [EXPORT_FORMAT] --device_target [PLATFORM]
+```
+
+`EXPORT_FORMAT` should be in ["AIR", "MINDIR"].
+
+## [Ascend 310 inference](#contents)
+
+You should export AIR model at Ascend 910 before  running the command below.
+You can use export_bin_file.py to export ImageNet bin and label for 310 inference.
+
+```shell
+python export_bin_file.py --dataset_dir [EVAL_DATASET_PATH] --save_dir [SAVE_PATH]
+```
+
+Run run_infer_310.sh and get the accuracy：
+
+```shell
+# Ascend310 inference
+bash run_infer_310.sh [AIR_PATH] [DATA_PATH] [LABEL_PATH] [DEVICE_ID]
+```
+
+You can view the results through the file "acc.log". The accuracy of the test dataset will be as follows:
+
+```bash
+'Accuracy':0.77052
+```
+
 # [Model description](#contents)
 
 ## [Performance](#contents)

model_zoo/official/cv/resnet50_quant/README_CN.md

@@ -82,9 +82,11 @@ ResNet-50总体网络架构如下：
 ```python
 ├── resnet50_quant
   ├── Readme.md # ResNet-50-Quant相关描述
+  ├── ascend310_infer   # 实现310推理源代码
   ├── scripts
   │   ├──run_train.sh # 使用昇腾处理器进行训练的shell脚本
   │   ├──run_infer.sh # 使用昇腾处理器进行评估的shell脚本
+  │   ├──run_infer_310.sh # Ascend 310 推理shell脚本
   ├── model
   │   ├──resnet_quant.py # 定义ResNet50-Quant的网络模型
   ├──src
@@ -96,6 +98,8 @@ ResNet-50总体网络架构如下：
   ├── train.py # 训练脚本
   ├── eval.py # 评估脚本
   ├── export.py # 导出脚本
+  ├── export_bin_file.py # 导出ImageNet数据集的bin文件用于310推理
+  ├── postprocess.py  # 310推理后处理脚本
 
 ```
 
@@ -177,6 +181,36 @@ epoch: 5 step: 5004, loss is 3.1978393
 result:{'acc'：0.76576314102564111}
 ```
 
+## 模型导出
+
+```shell
+python export.py --checkpoint_path [CKPT_PATH] --file_format [EXPORT_FORMAT] --device_target [PLATFORM]
+```
+
+`EXPORT_FORMAT` 可选 ["AIR", "MINDIR"].
+
+## Ascend 310 推理
+
+在推理之前需要在昇腾910环境上完成AIR模型的导出。
+并使用export_bin_file.py导出ImageNet数据集的bin文件和对应的label文件：
+
+```shell
+python export_bin_file.py --dataset_dir [EVAL_DATASET_PATH] --save_dir [SAVE_PATH]
+```
+
+执行推理并得到推理精度：
+
+```shell
+# Ascend310 inference
+bash run_infer_310.sh [AIR_PATH] [DATA_PATH] [LABEL_PATH] [DEVICE_ID]
+```
+
+您可以通过acc.log文件查看结果。推理准确性如下：
+
+```bash
+'Accuracy':0.77052
+```
+
 # 模型描述
 
 ## 性能

model_zoo/official/cv/resnet50_quant/ascend310_infer/inc/ModelProcess.h

@@ -0,0 +1,112 @@
+/**
+ * Copyright 2021 Huawei Technologies Co., Ltd
+ * 
+ * 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 MODELPROCESS_H
+#define MODELPROCESS_H
+
+#include "acl/acl.h"
+#include "../inc/utils.h"
+
+/**
+* ModelProcess
+*/
+class ModelProcess {
+ public:
+    /**
+    * @brief Constructor
+    */
+    ModelProcess();
+
+    /**
+    * @brief Destructor
+    */
+    ~ModelProcess();
+
+    /**
+    * @brief load model from file with mem
+    * @param [in] modelPath: model path
+    * @return result
+    */
+    Result LoadModelFromFileWithMem(const char *modelPath);
+
+    /**
+    * @brief unload model
+    */
+    void Unload();
+
+    /**
+    * @brief create model desc
+    * @return result
+    */
+    Result CreateDesc();
+
+    /**
+    * @brief destroy desc
+    */
+    void DestroyDesc();
+
+    /**
+    * @brief create model input
+    * @param [in] inputDataBuffer: input buffer
+    * @param [in] bufferSize: input buffer size
+    * @return result
+    */
+    Result CreateInput(void *inputDataBuffer, size_t bufferSize);
+
+    /**
+    * @brief destroy input resource
+    */
+    void DestroyInput();
+
+    /**
+    * @brief create output buffer
+    * @return result
+    */
+    Result CreateOutput();
+
+    /**
+    * @brief destroy output resource
+    */
+    void DestroyOutput();
+
+    /**
+    * @brief model execute
+    * @return result
+    */
+    Result Execute();
+
+    /**
+    * @brief dump model output result to file
+    */
+    void DumpModelOutputResult(char *output_name);
+
+    /**
+    * @brief get model output result
+    */
+    void OutputModelResult();
+
+ private:
+    uint32_t modelId_;
+    size_t modelMemSize_;
+    size_t modelWeightSize_;
+    void *modelMemPtr_;
+    void *modelWeightPtr_;
+    bool loadFlag_;  // model load flag
+    aclmdlDesc *modelDesc_;
+    aclmdlDataset *input_;
+    aclmdlDataset *output_;
+};
+#endif

model_zoo/official/cv/resnet50_quant/ascend310_infer/inc/SampleProcess.h

@@ -0,0 +1,62 @@
+/**
+ * Copyright 2021 Huawei Technologies Co., Ltd
+ * 
+ * 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 SAMPLEPROCESS_H
+#define SAMPLEPROCESS_H
+
+#include <string>
+#include <vector>
+#include "acl/acl.h"
+#include "../inc/utils.h"
+
+/**
+* SampleProcess
+*/
+class SampleProcess {
+ public:
+    /**
+    * @brief Constructor
+    */
+    explicit SampleProcess(int32_t deviceId);
+
+    /**
+    * @brief Destructor
+    */
+    ~SampleProcess();
+
+    /**
+    * @brief init reousce
+    * @return result
+    */
+    Result InitResource(const char *acl_config_path);
+
+    /**
+    * @brief sample process
+    * @return result
+    */
+    Result Process(const char *om_path, const char *input_folder);
+
+    void GetAllFiles(std::string path, std::vector<std::string> *files);
+
+ private:
+    void DestroyResource();
+
+    int32_t deviceId_;
+    aclrtContext context_;
+    aclrtStream stream_;
+};
+
+#endif

model_zoo/official/cv/resnet50_quant/ascend310_infer/inc/utils.h

@@ -0,0 +1,53 @@
+/**
+ * Copyright 2021 Huawei Technologies Co., Ltd
+ * 
+ * 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 MINDSPORE_INFERENCE_UTILS_H_
+#define MINDSPORE_INFERENCE_UTILS_H_
+
+#include <iostream>
+#include <string>
+
+#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)
+
+typedef enum Result {
+    SUCCESS = 0,
+    FAILED = 1
+} Result;
+
+/**
+* Utils
+*/
+class Utils {
+ public:
+    /**
+    * @brief create device buffer of file
+    * @param [in] fileName: file name
+    * @param [out] fileSize: size of file
+    * @return device buffer of file
+    */
+    static void *GetDeviceBufferOfFile(std::string fileName, uint32_t *fileSize);
+
+    /**
+    * @brief Read bin file
+    * @param [in] fileName: file name
+    * @param [out] fileSize: size of file
+    * @return buffer of pic
+    */
+    static void* ReadBinFile(std::string fileName, uint32_t *fileSize);
+};
+#endif

model_zoo/official/cv/resnet50_quant/ascend310_infer/src/CMakeLists.txt

@@ -0,0 +1,41 @@
+# Copyright (c) Huawei Technologies Co., Ltd. 2021. All rights reserved.
+
+# CMake lowest version requirement
+cmake_minimum_required(VERSION 3.5.1)
+# project information
+project(InferClassification)
+# Check environment variable
+if(NOT DEFINED ENV{ASCEND_HOME})
+    message(FATAL_ERROR "please define environment variable:ASCEND_HOME")
+endif()
+
+# Compile options
+add_compile_definitions(_GLIBCXX_USE_CXX11_ABI=0)
+set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -O0 -g -std=c++17 -Werror -Wall -fPIE -Wl,--allow-shlib-undefined")
+
+# Skip build rpath
+set(CMAKE_SKIP_BUILD_RPATH True)
+
+# Set output directory
+set(PROJECT_SRC_ROOT ${CMAKE_CURRENT_LIST_DIR}/)
+set(CMAKE_RUNTIME_OUTPUT_DIRECTORY ${PROJECT_SRC_ROOT}/out)
+
+# Set include directory and library directory
+set(ACL_LIB_DIR $ENV{ASCEND_HOME}/acllib)
+set(ATLAS_ACL_LIB_DIR $ENV{ASCEND_HOME}/ascend-toolkit/latest/acllib)
+
+# Header path
+include_directories(${ACL_LIB_DIR}/include/)
+include_directories(${ATLAS_ACL_LIB_DIR}/include/)
+include_directories(${PROJECT_SRC_ROOT}/../inc)
+
+# add host lib path
+link_directories(${ACL_LIB_DIR})
+find_library(acl libascendcl.so ${ACL_LIB_DIR}/lib64 ${ATLAS_ACL_LIB_DIR}/lib64)
+
+add_executable(main utils.cpp
+                    SampleProcess.cpp
+                    ModelProcess.cpp
+                    main.cpp)
+
+target_link_libraries(main ${acl} gflags pthread)

model_zoo/official/cv/resnet50_quant/ascend310_infer/src/ModelProcess.cpp

@@ -0,0 +1,326 @@
+/**
+ * Copyright 2021 Huawei Technologies Co., Ltd
+ * 
+ * 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.
+ */
+
+#include "../inc/ModelProcess.h"
+#include <iostream>
+#include <map>
+#include <sstream>
+#include <algorithm>
+#include "../inc/utils.h"
+
+extern bool g_isDevice;
+
+ModelProcess::ModelProcess() :modelId_(0), modelMemSize_(0), modelWeightSize_(0), modelMemPtr_(nullptr),
+modelWeightPtr_(nullptr), loadFlag_(false), modelDesc_(nullptr), input_(nullptr), output_(nullptr) {
+}
+
+ModelProcess::~ModelProcess() {
+    Unload();
+    DestroyDesc();
+    DestroyInput();
+    DestroyOutput();
+}
+
+Result ModelProcess::LoadModelFromFileWithMem(const char *modelPath) {
+    if (loadFlag_) {
+        ERROR_LOG("has already loaded a model");
+        return FAILED;
+    }
+
+    aclError ret = aclmdlQuerySize(modelPath, &modelMemSize_, &modelWeightSize_);
+    if (ret != ACL_ERROR_NONE) {
+        ERROR_LOG("query model failed, model file is %s", modelPath);
+        return FAILED;
+    }
+
+    ret = aclrtMalloc(&modelMemPtr_, modelMemSize_, ACL_MEM_MALLOC_HUGE_FIRST);
+    if (ret != ACL_ERROR_NONE) {
+        ERROR_LOG("malloc buffer for mem failed, require size is %zu", modelMemSize_);
+        return FAILED;
+    }
+
+    ret = aclrtMalloc(&modelWeightPtr_, modelWeightSize_, ACL_MEM_MALLOC_HUGE_FIRST);
+    if (ret != ACL_ERROR_NONE) {
+        ERROR_LOG("malloc buffer for weight failed, require size is %zu", modelWeightSize_);
+        return FAILED;
+    }
+
+    ret = aclmdlLoadFromFileWithMem(modelPath, &modelId_, modelMemPtr_,
+        modelMemSize_, modelWeightPtr_, modelWeightSize_);
+    if (ret != ACL_ERROR_NONE) {
+        ERROR_LOG("load model from file failed, model file is %s", modelPath);
+        return FAILED;
+    }
+
+    loadFlag_ = true;
+    INFO_LOG("load model %s success", modelPath);
+    return SUCCESS;
+}
+
+Result ModelProcess::CreateDesc() {
+    modelDesc_ = aclmdlCreateDesc();
+    if (modelDesc_ == nullptr) {
+        ERROR_LOG("create model description failed");
+        return FAILED;
+    }
+
+    aclError ret = aclmdlGetDesc(modelDesc_, modelId_);
+    if (ret != ACL_ERROR_NONE) {
+        ERROR_LOG("get model description failed");
+        return FAILED;
+    }
+
+    INFO_LOG("create model description success");
+
+    return SUCCESS;
+}
+
+void ModelProcess::DestroyDesc() {
+    if (modelDesc_ != nullptr) {
+        (void)aclmdlDestroyDesc(modelDesc_);
+        modelDesc_ = nullptr;
+    }
+}
+
+Result ModelProcess::CreateInput(void *inputDataBuffer, size_t bufferSize) {
+    input_ = aclmdlCreateDataset();
+    if (input_ == nullptr) {
+        ERROR_LOG("can't create dataset, create input failed");
+        return FAILED;
+    }
+
+    aclDataBuffer* inputData = aclCreateDataBuffer(inputDataBuffer, bufferSize);
+    if (inputData == nullptr) {
+        ERROR_LOG("can't create data buffer, create input failed");
+        return FAILED;
+    }
+
+    aclError ret = aclmdlAddDatasetBuffer(input_, inputData);
+    if (ret != ACL_ERROR_NONE) {
+        ERROR_LOG("add input dataset buffer failed");
+        aclDestroyDataBuffer(inputData);
+        inputData = nullptr;
+        return FAILED;
+    }
+
+    return SUCCESS;
+}
+
+void ModelProcess::DestroyInput() {
+    if (input_ == nullptr) {
+        return;
+    }
+
+    for (size_t i = 0; i < aclmdlGetDatasetNumBuffers(input_); ++i) {
+        aclDataBuffer* dataBuffer = aclmdlGetDatasetBuffer(input_, i);
+        aclDestroyDataBuffer(dataBuffer);
+    }
+    aclmdlDestroyDataset(input_);
+    input_ = nullptr;
+}
+
+Result ModelProcess::CreateOutput() {
+    if (modelDesc_ == nullptr) {
+        ERROR_LOG("no model description, create output failed");
+        return FAILED;
+    }
+
+    output_ = aclmdlCreateDataset();
+    if (output_ == nullptr) {
+        ERROR_LOG("can't create dataset, create output failed");
+        return FAILED;
+    }
+
+    size_t outputSize = aclmdlGetNumOutputs(modelDesc_);
+    for (size_t i = 0; i < outputSize; ++i) {
+        size_t buffer_size = aclmdlGetOutputSizeByIndex(modelDesc_, i);
+        void *outputBuffer = nullptr;
+        aclError ret = aclrtMalloc(&outputBuffer, buffer_size, ACL_MEM_MALLOC_NORMAL_ONLY);
+        if (ret != ACL_ERROR_NONE) {
+            ERROR_LOG("can't malloc buffer, size is %zu, create output failed", buffer_size);
+            return FAILED;
+        }
+
+        aclDataBuffer* outputData = aclCreateDataBuffer(outputBuffer, buffer_size);
+        if (ret != ACL_ERROR_NONE) {
+            ERROR_LOG("can't create data buffer, create output failed");
+            aclrtFree(outputBuffer);
+            return FAILED;
+        }
+
+        ret = aclmdlAddDatasetBuffer(output_, outputData);
+        if (ret != ACL_ERROR_NONE) {
+            ERROR_LOG("can't add data buffer, create output failed");
+            aclrtFree(outputBuffer);
+            aclDestroyDataBuffer(outputData);
+            return FAILED;
+        }
+    }
+
+    INFO_LOG("create model output success");
+    return SUCCESS;
+}
+
+void ModelProcess::DumpModelOutputResult(char *output_name) {
+    size_t outputNum = aclmdlGetDatasetNumBuffers(output_);
+    std::string homePath = "./result_Files";
+    for (size_t i = 0; i < outputNum; ++i) {
+        std::string fileName = std::string(output_name) + '_' + std::to_string(i) + ".bin";
+        std::string outputFileName = homePath + "/" + fileName;
+        FILE *outputFile = fopen(outputFileName.c_str(), "wb");
+        if (outputFile) {
+            aclDataBuffer* dataBuffer = aclmdlGetDatasetBuffer(output_, i);
+            void* data = aclGetDataBufferAddr(dataBuffer);
+            uint32_t len = aclGetDataBufferSizeV2(dataBuffer);
+            void* outHostData = NULL;
+            aclError ret = ACL_ERROR_NONE;
+            if (!g_isDevice) {
+                ret = aclrtMallocHost(&outHostData, len);
+                if (ret != ACL_ERROR_NONE) {
+                    ERROR_LOG("aclrtMallocHost failed, ret[%d]", ret);
+                    return;
+                }
+                ret = aclrtMemcpy(outHostData, len, data, len, ACL_MEMCPY_DEVICE_TO_HOST);
+                if (ret != ACL_ERROR_NONE) {
+                    ERROR_LOG("aclrtMemcpy failed, ret[%d]", ret);
+                    (void)aclrtFreeHost(outHostData);
+                    return;
+                }
+                fwrite(outHostData, len, sizeof(char), outputFile);
+                ret = aclrtFreeHost(outHostData);
+                if (ret != ACL_ERROR_NONE) {
+                    ERROR_LOG("aclrtFreeHost failed, ret[%d]", ret);
+                    return;
+                }
+            } else {
+                fwrite(data, len, sizeof(char), outputFile);
+            }
+            fclose(outputFile);
+            outputFile = nullptr;
+        } else {
+            ERROR_LOG("create output file [%s] failed", outputFileName.c_str());
+            return;
+        }
+    }
+    INFO_LOG("dump data success");
+    return;
+}
+
+void ModelProcess::OutputModelResult() {
+    for (size_t i = 0; i < aclmdlGetDatasetNumBuffers(output_); ++i) {
+        aclDataBuffer* dataBuffer = aclmdlGetDatasetBuffer(output_, i);
+        void* data = aclGetDataBufferAddr(dataBuffer);
+        uint32_t len = aclGetDataBufferSizeV2(dataBuffer);
+        void *outHostData = NULL;
+        aclError ret = ACL_ERROR_NONE;
+        float *outData = NULL;
+        if (!g_isDevice) {
+            ret = aclrtMallocHost(&outHostData, len);
+            if (ret != ACL_ERROR_NONE) {
+                ERROR_LOG("aclrtMallocHost failed, ret[%d]", ret);
+                return;
+            }
+            ret = aclrtMemcpy(outHostData, len, data, len, ACL_MEMCPY_DEVICE_TO_HOST);
+            if (ret != ACL_ERROR_NONE) {
+                ERROR_LOG("aclrtMemcpy failed, ret[%d]", ret);
+                return;
+            }
+            outData = reinterpret_cast<float*>(outHostData);
+        } else {
+            outData = reinterpret_cast<float*>(data);
+        }
+        std::map<float, unsigned int, std::greater<float> > resultMap;
+        for (unsigned int j = 0; j < len / sizeof(float); ++j) {
+            resultMap[*outData] = j;
+            outData++;
+        }
+        int cnt = 0;
+        for (auto it = resultMap.begin(); it != resultMap.end(); ++it) {
+            // print top 5
+            if (++cnt > 5) {
+                break;
+            }
+            INFO_LOG("top %d: index[%d] value[%lf]", cnt, it->second, it->first);
+        }
+        if (!g_isDevice) {
+            ret = aclrtFreeHost(outHostData);
+            if (ret != ACL_ERROR_NONE) {
+                ERROR_LOG("aclrtFreeHost failed, ret[%d]", ret);
+                return;
+            }
+        }
+    }
+    INFO_LOG("output data success");
+    return;
+}
+
+void ModelProcess::DestroyOutput() {
+    if (output_ == nullptr) {
+        return;
+    }
+    for (size_t i = 0; i < aclmdlGetDatasetNumBuffers(output_); ++i) {
+        aclDataBuffer* dataBuffer = aclmdlGetDatasetBuffer(output_, i);
+        void* data = aclGetDataBufferAddr(dataBuffer);
+        (void)aclrtFree(data);
+        (void)aclDestroyDataBuffer(dataBuffer);
+    }
+
+    (void)aclmdlDestroyDataset(output_);
+    output_ = nullptr;
+}
+
+Result ModelProcess::Execute() {
+    aclError ret = aclmdlExecute(modelId_, input_, output_);
+    if (ret != ACL_ERROR_NONE) {
+        ERROR_LOG("execute model failed, modelId is %u", modelId_);
+        return FAILED;
+    }
+
+    INFO_LOG("model execute success");
+    return SUCCESS;
+}
+
+void ModelProcess::Unload() {
+    if (!loadFlag_) {
+        WARN_LOG("no model had been loaded, unload failed");
+        return;
+    }
+
+    aclError ret = aclmdlUnload(modelId_);
+    if (ret != ACL_ERROR_NONE) {
+        ERROR_LOG("unload model failed, modelId is %u", modelId_);
+    }
+
+    if (modelDesc_ != nullptr) {
+        (void)aclmdlDestroyDesc(modelDesc_);
+        modelDesc_ = nullptr;
+    }
+
+    if (modelMemPtr_ != nullptr) {
+        aclrtFree(modelMemPtr_);
+        modelMemPtr_ = nullptr;
+        modelMemSize_ = 0;
+    }
+
+    if (modelWeightPtr_ != nullptr) {
+        aclrtFree(modelWeightPtr_);
+        modelWeightPtr_ = nullptr;
+        modelWeightSize_ = 0;
+    }
+
+    loadFlag_ = false;
+    INFO_LOG("unload model success, modelId is %u", modelId_);
+}

model_zoo/official/cv/resnet50_quant/ascend310_infer/src/SampleProcess.cpp

@@ -0,0 +1,199 @@
+/**
+ * Copyright 2021 Huawei Technologies Co., Ltd
+ * 
+ * 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.
+ */
+
+#include "../inc/SampleProcess.h"
+#include <sys/types.h>
+#include <dirent.h>
+#include <string.h>
+#include <iostream>
+#include <fstream>
+#include "../inc/utils.h"
+#include "../inc/ModelProcess.h"
+#include "acl/acl.h"
+
+extern bool g_isDevice;
+using std::string;
+using std::vector;
+
+SampleProcess::SampleProcess(int32_t deviceId) : context_(nullptr), stream_(nullptr) {
+    deviceId_ = deviceId;
+}
+
+SampleProcess::~SampleProcess() {
+    DestroyResource();
+}
+
+Result SampleProcess::InitResource(const char *aclConfigPath) {
+    // ACL init
+    aclError ret = aclInit(aclConfigPath);
+    if (ret != ACL_ERROR_NONE) {
+        ERROR_LOG("acl init failed");
+        return FAILED;
+    }
+    INFO_LOG("acl init success");
+
+    // open device
+    ret = aclrtSetDevice(deviceId_);
+    if (ret != ACL_ERROR_NONE) {
+        ERROR_LOG("acl open device %d failed", deviceId_);
+        return FAILED;
+    }
+    INFO_LOG("open device %d success", deviceId_);
+
+    // create context (set current)
+    ret = aclrtCreateContext(&context_, deviceId_);
+    if (ret != ACL_ERROR_NONE) {
+        ERROR_LOG("acl create context failed");
+        return FAILED;
+    }
+    INFO_LOG("create context success");
+
+    // create stream
+    ret = aclrtCreateStream(&stream_);
+    if (ret != ACL_ERROR_NONE) {
+        ERROR_LOG("acl create stream failed");
+        return FAILED;
+    }
+    INFO_LOG("create stream success");
+
+    // get run mode
+    aclrtRunMode runMode;
+    ret = aclrtGetRunMode(&runMode);
+    if (ret != ACL_ERROR_NONE) {
+        ERROR_LOG("acl get run mode failed");
+        return FAILED;
+    }
+    g_isDevice = (runMode == ACL_DEVICE);
+    INFO_LOG("get run mode success");
+    return SUCCESS;
+}
+
+void SampleProcess::GetAllFiles(std::string path, std::vector<string> *files) {
+    DIR *pDir;
+    struct dirent* ptr;
+    if (!(pDir = opendir(path.c_str())))
+        return;
+    while ((ptr = readdir(pDir)) != 0) {
+        if (strcmp(ptr->d_name, ".") != 0 && strcmp(ptr->d_name, "..") != 0)
+            files->push_back(path + "/" + ptr->d_name);
+    }
+    closedir(pDir);
+}
+
+Result SampleProcess::Process(const char *om_path, const char *input_folder) {
+    // model init
+    ModelProcess processModel;
+
+    Result ret = processModel.LoadModelFromFileWithMem(om_path);
+    if (ret != SUCCESS) {
+        ERROR_LOG("execute LoadModelFromFileWithMem failed");
+        return FAILED;
+    }
+
+    ret = processModel.CreateDesc();
+    if (ret != SUCCESS) {
+        ERROR_LOG("execute CreateDesc failed");
+        return FAILED;
+    }
+
+    ret = processModel.CreateOutput();
+    if (ret != SUCCESS) {
+        ERROR_LOG("execute CreateOutput failed");
+        return FAILED;
+    }
+
+    std::vector<string> testFile;
+    GetAllFiles(input_folder, &testFile);
+
+    if (testFile.size() == 0) {
+        WARN_LOG("no input data under folder");
+    }
+
+    // loop begin
+    for (size_t index = 0; index < testFile.size(); ++index) {
+        INFO_LOG("start to process file:%s", testFile[index].c_str());
+        // model process
+        uint32_t devBufferSize;
+        void *picDevBuffer = Utils::GetDeviceBufferOfFile(testFile[index], &devBufferSize);
+        if (picDevBuffer == nullptr) {
+            ERROR_LOG("get pic device buffer failed,index is %zu", index);
+            return FAILED;
+        }
+        ret = processModel.CreateInput(picDevBuffer, devBufferSize);
+        if (ret != SUCCESS) {
+            ERROR_LOG("execute CreateInput failed");
+            aclrtFree(picDevBuffer);
+            return FAILED;
+        }
+
+        ret = processModel.Execute();
+        if (ret != SUCCESS) {
+            ERROR_LOG("execute inference failed");
+            aclrtFree(picDevBuffer);
+            return FAILED;
+        }
+
+        int pos = testFile[index].find_last_of('/');
+        std::string name = testFile[index].substr(pos+1);
+        std::string outputname = name.substr(0, name.rfind("."));
+
+        // print the top 5 confidence values
+        processModel.OutputModelResult();
+        // dump output result to file in the current directory
+        processModel.DumpModelOutputResult(const_cast<char *>(outputname.c_str()));
+
+        // release model input buffer
+        aclrtFree(picDevBuffer);
+        processModel.DestroyInput();
+    }
+    // loop end
+
+    return SUCCESS;
+}
+
+void SampleProcess::DestroyResource() {
+    aclError ret;
+    if (stream_ != nullptr) {
+        ret = aclrtDestroyStream(stream_);
+        if (ret != ACL_ERROR_NONE) {
+            ERROR_LOG("destroy stream failed");
+        }
+        stream_ = nullptr;
+    }
+    INFO_LOG("end to destroy stream");
+
+    if (context_ != nullptr) {
+        ret = aclrtDestroyContext(context_);
+        if (ret != ACL_ERROR_NONE) {
+            ERROR_LOG("destroy context failed");
+        }
+        context_ = nullptr;
+    }
+    INFO_LOG("end to destroy context");
+
+    ret = aclrtResetDevice(deviceId_);
+    if (ret != ACL_ERROR_NONE) {
+        ERROR_LOG("reset device failed");
+    }
+    INFO_LOG("end to reset device is %d", deviceId_);
+
+    ret = aclFinalize();
+    if (ret != ACL_ERROR_NONE) {
+        ERROR_LOG("finalize acl failed");
+    }
+    INFO_LOG("end to finalize acl");
+}
+

model_zoo/official/cv/resnet50_quant/ascend310_infer/src/acl.json

@@ -0,0 +1 @@
+{}

model_zoo/official/cv/resnet50_quant/ascend310_infer/src/build.sh

@@ -0,0 +1,55 @@
+#!/bin/bash
+# Copyright 2021 Huawei Technologies Co., Ltd
+#
+# 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.
+# ============================================================================
+path_cur=$(cd "`dirname $0`" || exit; pwd)
+
+function preparePath() {
+    rm -rf $1
+    mkdir -p $1
+    cd $1 || exit
+}
+
+function buildA300() {
+    if [ ! "${ARCH_PATTERN}" ]; then
+        # set ARCH_PATTERN to acllib when it was not specified by user
+        export ARCH_PATTERN=acllib
+        echo "ARCH_PATTERN is set to the default value: ${ARCH_PATTERN}"
+    else
+        echo "ARCH_PATTERN is set to ${ARCH_PATTERN} by user, reset it to ${ARCH_PATTERN}/acllib"
+        export ARCH_PATTERN=${ARCH_PATTERN}/acllib
+    fi
+
+    path_build=$path_cur/build
+    preparePath $path_build
+    cmake ..
+    make -j
+    ret=$?
+    cd ..
+    return ${ret}
+}
+
+# set ASCEND_VERSION to ascend-toolkit/latest when it was not specified by user
+if [ ! "${ASCEND_VERSION}" ]; then
+    export ASCEND_VERSION=ascend-toolkit/latest
+    echo "Set ASCEND_VERSION to the default value: ${ASCEND_VERSION}"
+else
+    echo "ASCEND_VERSION is set to ${ASCEND_VERSION} by user"
+fi
+
+buildA300
+
+if [ $? -ne 0 ]; then
+    exit 1
+fi

model_zoo/official/cv/resnet50_quant/ascend310_infer/src/main.cpp

@@ -0,0 +1,58 @@
+/**
+ * Copyright 2021 Huawei Technologies Co., Ltd
+ * 
+ * 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.
+ */
+
+#include <gflags/gflags.h>
+#include <iostream>
+#include <fstream>
+#include <memory>
+#include "../inc/SampleProcess.h"
+#include "../inc/utils.h"
+
+bool g_isDevice = false;
+
+DEFINE_string(om_path, "", "om path");
+DEFINE_string(dataset_path, "", "dataset path");
+DEFINE_string(acljson_path, "", "acl json path");
+DEFINE_int32(device_id, 0, "device id");
+
+int main(int argc, char **argv) {
+  gflags::ParseCommandLineFlags(&argc, &argv, true);
+  std::string om_path = FLAGS_om_path;
+  std::string dataset_path = FLAGS_dataset_path;
+  std::string acljson_path = FLAGS_acljson_path;
+  int32_t device_id = FLAGS_device_id;
+  std::ifstream fin(om_path);
+  if (!fin) {
+    std::cout << "Invalid om path." << std::endl;
+    return FAILED;
+  }
+  SampleProcess processSample(device_id);
+  // acl.json is deployed for dump data.
+  Result ret = processSample.InitResource(acljson_path.c_str());
+  if (ret != SUCCESS) {
+    ERROR_LOG("sample init resource failed");
+    return FAILED;
+  }
+
+  ret = processSample.Process(om_path.c_str(), dataset_path.c_str());
+  if (ret != SUCCESS) {
+    ERROR_LOG("sample process failed");
+    return FAILED;
+  }
+
+  INFO_LOG("execute sample success");
+  return SUCCESS;
+}

model_zoo/official/cv/resnet50_quant/ascend310_infer/src/utils.cpp

@@ -0,0 +1,113 @@
+/**
+ * Copyright 2021 Huawei Technologies Co., Ltd
+ * 
+ * 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.
+ */
+
+#include "../inc/utils.h"
+#include <sys/stat.h>
+#include <iostream>
+#include <fstream>
+#include <cstring>
+#include "acl/acl.h"
+
+extern bool g_isDevice;
+
+void* Utils::ReadBinFile(std::string fileName, uint32_t *fileSize) {
+    struct stat sBuf;
+    int fileStatus = stat(fileName.data(), &sBuf);
+    if (fileStatus == -1) {
+        ERROR_LOG("failed to get file");
+        return nullptr;
+    }
+    if (S_ISREG(sBuf.st_mode) == 0) {
+        ERROR_LOG("%s is not a file, please enter a file", fileName.c_str());
+        return nullptr;
+    }
+
+    std::ifstream binFile(fileName, std::ifstream::binary);
+    if (binFile.is_open() == false) {
+        ERROR_LOG("open file %s failed", fileName.c_str());
+        return nullptr;
+    }
+
+    binFile.seekg(0, binFile.end);
+    uint32_t binFileBufferLen = binFile.tellg();
+    if (binFileBufferLen == 0) {
+        ERROR_LOG("binfile is empty, filename is %s", fileName.c_str());
+        binFile.close();
+        return nullptr;
+    }
+
+    binFile.seekg(0, binFile.beg);
+
+    void* binFileBufferData = nullptr;
+    aclError ret = ACL_ERROR_NONE;
+    if (!g_isDevice) {
+        ret = aclrtMallocHost(&binFileBufferData, binFileBufferLen);
+        if (ret != ACL_ERROR_NONE) {
+            ERROR_LOG("malloc for binFileBufferData failed");
+            binFile.close();
+            return nullptr;
+        }
+        if (binFileBufferData == nullptr) {
+            ERROR_LOG("malloc binFileBufferData failed");
+            binFile.close();
+            return nullptr;
+        }
+    } else {
+        ret = aclrtMalloc(&binFileBufferData, binFileBufferLen, ACL_MEM_MALLOC_NORMAL_ONLY);
+        if (ret != ACL_ERROR_NONE) {
+            ERROR_LOG("malloc device buffer failed. size is %u", binFileBufferLen);
+            binFile.close();
+            return nullptr;
+        }
+    }
+    binFile.read(static_cast<char *>(binFileBufferData), binFileBufferLen);
+    binFile.close();
+    *fileSize = binFileBufferLen;
+    return binFileBufferData;
+}
+
+void* Utils::GetDeviceBufferOfFile(std::string fileName, uint32_t *fileSize) {
+    uint32_t inputHostBuffSize = 0;
+    void* inputHostBuff = Utils::ReadBinFile(fileName, &inputHostBuffSize);
+    if (inputHostBuff == nullptr) {
+        return nullptr;
+    }
+    if (!g_isDevice) {
+        void *inBufferDev = nullptr;
+        uint32_t inBufferSize = inputHostBuffSize;
+        aclError ret = aclrtMalloc(&inBufferDev, inBufferSize, ACL_MEM_MALLOC_NORMAL_ONLY);
+        if (ret != ACL_ERROR_NONE) {
+            ERROR_LOG("malloc device buffer failed. size is %u", inBufferSize);
+            aclrtFreeHost(inputHostBuff);
+            return nullptr;
+        }
+
+        ret = aclrtMemcpy(inBufferDev, inBufferSize, inputHostBuff, inputHostBuffSize, ACL_MEMCPY_HOST_TO_DEVICE);
+        if (ret != ACL_ERROR_NONE) {
+            ERROR_LOG("memcpy failed. device buffer size is %u, input host buffer size is %u",
+                inBufferSize, inputHostBuffSize);
+            aclrtFree(inBufferDev);
+            aclrtFreeHost(inputHostBuff);
+            return nullptr;
+        }
+        aclrtFreeHost(inputHostBuff);
+        *fileSize = inBufferSize;
+        return inBufferDev;
+    } else {
+        *fileSize = inputHostBuffSize;
+        return inputHostBuff;
+    }
+}

model_zoo/official/cv/resnet50_quant/export_bin_file.py

@@ -0,0 +1,64 @@
+# Copyright 2021 Huawei Technologies Co., Ltd
+#
+# 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.
+# ============================================================================
+"""
+export imagenet2012 dataset to bin.
+"""
+import os
+import argparse
+from mindspore import context
+from src.dataset import create_dataset
+
+def parse_args():
+    parser = argparse.ArgumentParser(description='ImageNet2012 to bin')
+    parser.add_argument('--device_target', type=str, default="Ascend",
+                        choices=['Ascend', 'GPU'],
+                        help='device where the code will be implemented (default: Ascend)')
+    parser.add_argument('--dataset_dir', type=str, default='', help='dataset path')
+    parser.add_argument('--save_dir', type=str, default='', help='path to save bin file')
+    parser.add_argument('--batch_size', type=int, default=1, help='batch size for bin')
+    args_, _ = parser.parse_known_args()
+    return args_
+
+if __name__ == "__main__":
+    args = parse_args()
+    os.environ["RANK_SIZE"] = '1'
+    os.environ["RANK_ID"] = '0'
+    device_id = int(os.getenv('DEVICE_ID')) if os.getenv('DEVICE_ID') else 0
+    context.set_context(mode=context.GRAPH_MODE, device_target=args.device_target, device_id=device_id)
+    imagenet2012_path = args.dataset_dir
+    batch_size = args.batch_size
+    save_dir = os.path.join(args.save_dir, 'imagenet2012_310_infer_data')
+    folder = os.path.join(save_dir, 'imagenet2012_bs_' + str(batch_size) + '_bin')
+    if not os.path.exists(folder):
+        os.makedirs(folder)
+    ds = create_dataset(imagenet2012_path, do_train=False, repeat_num=1, batch_size=batch_size,
+                        target=args.device_target)
+    iter_num = 0
+    label_file = os.path.join(save_dir, './imagenet2012_bs_' + str(batch_size) + '_label.txt')
+    with open(label_file, 'w') as f:
+        for data in ds.create_dict_iterator():
+            image = data['image']
+            label = data['label']
+            file_name = "imagenet2012_" + str(iter_num) + ".bin"
+            file_path = folder + "/" + file_name
+            image.asnumpy().tofile(file_path)
+            f.write(file_name)
+            for i in label:
+                f.write(',' + str(i))
+            f.write('\n')
+            iter_num += 1
+    print("=====iter_num:{}=====".format(iter_num))
+    print("=====image_data:{}=====".format(image))
+    print("=====label_data:{}=====".format(label))

model_zoo/official/cv/resnet50_quant/postprocess.py

@@ -0,0 +1,57 @@
+# Copyright 2021 Huawei Technologies Co., Ltd
+#
+# 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.
+# ============================================================================
+"""
+post process for 310 inference.
+"""
+import os
+import argparse
+import numpy as np
+
+def parse_args():
+    parser = argparse.ArgumentParser(description='resnet50_quant inference')
+    parser.add_argument('--result_path', type=str, default='', help='result files path')
+    parser.add_argument('--label_path', type=str, default='', help='label file path')
+    args_, _ = parser.parse_known_args()
+    return args_
+
+if __name__ == "__main__":
+    args = parse_args()
+    path = args.result_path
+    label_path = args.label_path
+    files = os.listdir(path)
+    step = 0
+    sum_right = 0
+    label_dict = {}
+    with open(label_path, 'r') as f:
+        for line in f.readlines():
+            batch_label = line.strip().split(',')
+            label_dict[batch_label[0]] = batch_label[1:]
+    for file in files:
+        full_file_path = os.path.join(path, file)
+        if os.path.isfile(full_file_path):
+            label_file = file.split('_0.bin')[0] + '.bin'
+            label_array = np.array(label_dict[label_file])
+            line = np.fromfile(full_file_path, dtype=np.float32)
+            batch_size = label_array.shape[0]
+            line_comp = line.reshape(batch_size, int(line.shape[0] / batch_size))
+        for i in range(0, batch_size):
+            pred = np.argmax(line_comp[i], axis=0)
+            step += 1
+            if pred == label_array[i].astype(np.int64):
+                sum_right += 1
+    print("=====step:{}=====".format(step))
+    print("=====sum_right:{}=====".format(sum_right))
+    accuracy = sum_right * 100.0 / step
+    print("=====accuracy:{}=====".format(accuracy))

model_zoo/official/cv/resnet50_quant/scripts/run_infer_310.sh

@@ -0,0 +1,107 @@
+#!/bin/bash
+# Copyright 2021 Huawei Technologies Co., Ltd
+#
+# 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.
+# ============================================================================
+
+if [[ $# -lt 3 || $# -gt 4 ]]; then
+    echo "Usage: bash run_infer_310.sh [AIR_PATH] [DATA_PATH] [LABEL_PATH] [DEVICE_ID]
+    DEVICE_ID is optional, it can be set by environment variable device_id, otherwise the value is zero"
+exit 1
+fi
+
+get_real_path(){
+    if [ "${1:0:1}" == "/" ]; then
+        echo "$1"
+    else
+        echo "$(realpath -m $PWD/$1)"
+    fi
+}
+model=$(get_real_path $1)
+data_path=$(get_real_path $2)
+label_path=$(get_real_path $3)
+
+device_id=0
+if [ $# == 4 ]; then
+    device_id=$4
+fi
+
+echo "mindir name: "$model
+echo "dataset path: "$data_path
+echo "label path: "$label_path
+echo "device id: "$device_id
+
+export ASCEND_HOME=/usr/local/Ascend/
+if [ -d ${ASCEND_HOME}/ascend-toolkit ]; then
+    export PATH=$ASCEND_HOME/ascend-toolkit/latest/fwkacllib/ccec_compiler/bin:$ASCEND_HOME/ascend-toolkit/latest/atc/bin:$PATH
+    export LD_LIBRARY_PATH=/usr/local/lib:$ASCEND_HOME/ascend-toolkit/latest/atc/lib64:$ASCEND_HOME/ascend-toolkit/latest/fwkacllib/lib64:$ASCEND_HOME/driver/lib64:$ASCEND_HOME/add-ons:$LD_LIBRARY_PATH
+    export TBE_IMPL_PATH=$ASCEND_HOME/ascend-toolkit/latest/opp/op_impl/built-in/ai_core/tbe
+    export PYTHONPATH=${TBE_IMPL_PATH}:$ASCEND_HOME/ascend-toolkit/latest/fwkacllib/python/site-packages:$PYTHONPATH
+    export ASCEND_OPP_PATH=$ASCEND_HOME/ascend-toolkit/latest/opp
+else
+    export PATH=$ASCEND_HOME/atc/ccec_compiler/bin:$ASCEND_HOME/atc/bin:$PATH
+    export LD_LIBRARY_PATH=/usr/local/lib:$ASCEND_HOME/atc/lib64:$ASCEND_HOME/acllib/lib64:$ASCEND_HOME/driver/lib64:$ASCEND_HOME/add-ons:$LD_LIBRARY_PATH
+    export PYTHONPATH=$ASCEND_HOME/atc/python/site-packages:$PYTHONPATH
+    export ASCEND_OPP_PATH=$ASCEND_HOME/opp
+fi
+
+function air_to_om()
+{
+    atc --input_format=NCHW --framework=1 --model=$model --output=resnet50_quant --soc_version=Ascend310 &> atc.log
+}
+
+function compile_app()
+{
+    cd ../ascend310_infer/src || exit
+    bash build.sh &> build.log
+}
+
+function infer()
+{
+    cd - || exit
+    if [ -d result_Files ]; then
+        rm -rf ./result_Files
+    fi
+    if [ -d time_Result ]; then
+        rm -rf ./time_Result
+    fi
+    mkdir result_Files
+    mkdir time_Result
+    ../ascend310_infer/src/out/main --om_path=./resnet50_quant.om --dataset_path=$data_path --acljson_path=../ascend310_infer/src/acl.json --device_id=$device_id &> infer.log
+}
+
+function cal_acc()
+{
+    python3.7 ../postprocess.py --result_path=./result_Files --label_path=$label_path  &> acc.log
+}
+
+air_to_om
+if [ $? -ne 0 ]; then
+    echo " air to om failed"
+    exit 1
+fi
+compile_app
+if [ $? -ne 0 ]; then
+    echo "compile app code failed"
+    exit 1
+fi
+infer
+if [ $? -ne 0 ]; then
+    echo " execute inference failed"
+    exit 1
+fi
+cal_acc
+if [ $? -ne 0 ]; then
+    echo "calculate accuracy failed"
+    exit 1
+fi

model_zoo/official/cv/yolov3_darknet53_quant/README.md

@@ -106,11 +106,13 @@ sh run_eval.sh dataset/coco2014/ checkpoint/yolov3_quant.ckpt 0
 .
 └─yolov3_darknet53_quant
   ├─README.md
+  ├─ascend310_infer   # application for 310 inference
   ├─mindspore_hub_conf.md             # config for mindspore hub
   ├─scripts
     ├─run_standalone_train.sh         # launch standalone training(1p) in ascend
     ├─run_distribute_train.sh         # launch distributed training(8p) in ascend
     └─run_eval.sh                     # launch evaluating in ascend
+    └─run_infer_310.sh                # shell script for 310 inference
   ├─src
     ├─__init__.py                     # python init file
     ├─config.py                       # parameter configuration
@@ -126,6 +128,8 @@ sh run_eval.sh dataset/coco2014/ checkpoint/yolov3_quant.ckpt 0
     ├─yolo_dataset.py                 # create dataset for YOLOV3
   ├─eval.py                           # eval net
   └─train.py                          # train net
+  └─export_bin_file.py                # export bin file of coco2014 for 310 inference
+  └─postprocess.py                    # post process for 310 inference
 ```
 
 ### [Script Parameters](#contents)
@@ -257,6 +261,48 @@ Average Recall     (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.450
 Average Recall     (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.558
 ```
 
+## [Model Export](#contents)
+
+```shell
+python export.py --ckpt_file [CKPT_PATH] --file_format [EXPORT_FORMAT]
+```
+
+`EXPORT_FORMAT` should be in ["AIR", "MINDIR"].
+
+## [Ascend 310 inference](#contents)
+
+You should export AIR model at Ascend 910 before  running the command below.
+You can use export_bin_file.py to export coco2014 bin, image_shape.npy and image_id.npy for 310 inference.
+
+```shell
+python export_bin_file.py --data_dir [DATASET_PATH] --save_path [SAVE_PATH]
+```
+
+Run run_infer_310.sh and get the accuracy：
+
+```shell
+# Ascend310 inference
+bash run_infer_310.sh [AIR_PATH] [DATA_PATH] [ANNO_PATH] [IMAGESHAPE_PATH] [IMAGEID_PATH] [DEVICE_ID]
+```
+
+You can view the results through the file "acc.log". The accuracy of the test dataset will be as follows:
+
+```bash
+=============coco eval reulst=========
+Average Precision  (AP) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.306
+Average Precision  (AP) @[ IoU=0.50      | area=   all | maxDets=100 ] = 0.528
+Average Precision  (AP) @[ IoU=0.75      | area=   all | maxDets=100 ] = 0.315
+Average Precision  (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.122
+Average Precision  (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.322
+Average Precision  (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.426
+Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=  1 ] = 0.259
+Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets= 10 ] = 0.398
+Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.423
+Average Recall     (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.226
+Average Recall     (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.442
+Average Recall     (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.555
+```
+
 ## [Model Description](#contents)
 
 ### [Performance](#contents)

model_zoo/official/cv/yolov3_darknet53_quant/README_CN.md

@@ -116,11 +116,13 @@ sh run_eval.sh dataset/coco2014/ checkpoint/yolov3_quant.ckpt 0
 .
 └─yolov3_darknet53_quant
   ├─README.md
+  ├─ascend310_infer                   # 实现310推理源代码
   ├─mindspore_hub_conf.md             # Mindspore Hub配置
   ├─scripts
     ├─run_standalone_train.sh         # 在Ascend中启动单机训练(1卡)
     ├─run_distribute_train.sh         # 在Ascend中启动分布式训练(8卡)
-    └─run_eval.sh                     # 在Ascend中启动评估
+    ├─run_eval.sh                     # 在Ascend中启动评估
+    ├─run_infer_310.sh                # Ascend 310 推理shell脚本
   ├─src
     ├─__init__.py                     # python初始化文件
     ├─config.py                       # 参数配置
@@ -136,6 +138,8 @@ sh run_eval.sh dataset/coco2014/ checkpoint/yolov3_quant.ckpt 0
     ├─yolo_dataset.py                 # 为YOLOV3创建数据集
   ├─eval.py                           # 评估网络
   └─train.py                          # 训练网络
+  ├─export_bin_file.py                # 导出coco2014数据集的bin文件用于310推理
+  ├─postprocess.py                    # 310推理后处理脚本
 ```
 
 ### 脚本参数
@@ -266,6 +270,48 @@ Average Recall     (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.450
 Average Recall     (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.558
 ```
 
+## 模型导出
+
+```shell
+python export.py --ckpt_file [CKPT_PATH] --file_format [EXPORT_FORMAT]
+```
+
+`EXPORT_FORMAT` 可选 ["AIR", "MINDIR"].
+
+## Ascend 310 推理
+
+在推理之前需要在昇腾910环境上完成AIR模型的导出。
+并使用export_bin_file.py导出coco2014数据集的bin文件和对应的image_shape, image_id文件：
+
+```shell
+python export_bin_file.py --data_dir [DATASET_PATH] --save_path [SAVE_PATH]
+```
+
+执行推理并得到推理精度：
+
+```shell
+# Ascend310 inference
+bash run_infer_310.sh [AIR_PATH] [DATA_PATH] [ANNO_PATH] [IMAGESHAPE_PATH] [IMAGEID_PATH] [DEVICE_ID]
+```
+
+您可以通过acc.log文件查看结果。推理准确性如下：
+
+```bash
+=============coco eval reulst=========
+Average Precision  (AP) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.306
+Average Precision  (AP) @[ IoU=0.50      | area=   all | maxDets=100 ] = 0.528
+Average Precision  (AP) @[ IoU=0.75      | area=   all | maxDets=100 ] = 0.315
+Average Precision  (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.122
+Average Precision  (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.322
+Average Precision  (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.426
+Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=  1 ] = 0.259
+Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets= 10 ] = 0.398
+Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.423
+Average Recall     (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.226
+Average Recall     (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.442
+Average Recall     (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.555
+```
+
 ## 模型描述
 
 ### 性能

model_zoo/official/cv/yolov3_darknet53_quant/ascend310_infer/inc/ModelProcess.h

@@ -0,0 +1,114 @@
+/**
+ * Copyright 2021 Huawei Technologies Co., Ltd
+ * 
+ * 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 MODELPROCESS_H
+#define MODELPROCESS_H
+
+#include <iostream>
+#include <vector>
+#include "acl/acl.h"
+#include "../inc/utils.h"
+
+/**
+* ModelProcess
+*/
+class ModelProcess {
+ public:
+    /**
+    * @brief Constructor
+    */
+    ModelProcess();
+
+    /**
+    * @brief Destructor
+    */
+    ~ModelProcess();
+
+    /**
+    * @brief load model from file with mem
+    * @param [in] modelPath: model path
+    * @return result
+    */
+    Result LoadModelFromFileWithMem(const char *modelPath);
+
+    /**
+    * @brief unload model
+    */
+    void Unload();
+
+    /**
+    * @brief create model desc
+    * @return result
+    */
+    Result CreateDesc();
+
+    /**
+    * @brief destroy desc
+    */
+    void DestroyDesc();
+
+    /**
+    * @brief create model input
+    * @param [in] inputDataBuffer: input buffer
+    * @param [in] bufferSize: input buffer size
+    * @return result
+    */
+    Result CreateInput(const std::vector<void *> &inputDataBuffer, const std::vector<size_t> &bufferSize);
+
+    /**
+    * @brief destroy input resource
+    */
+    void DestroyInput();
+
+    /**
+    * @brief create output buffer
+    * @return result
+    */
+    Result CreateOutput();
+
+    /**
+    * @brief destroy output resource
+    */
+    void DestroyOutput();
+
+    /**
+    * @brief model execute
+    * @return result
+    */
+    Result Execute();
+
+    /**
+    * @brief dump model output result to file
+    */
+    void DumpModelOutputResult(char *output_name);
+
+    /**
+    * @brief get model output result
+    */
+    void OutputModelResult();
+
+ private:
+    uint32_t modelId_;
+    size_t modelMemSize_;
+    size_t modelWeightSize_;
+    void *modelMemPtr_;
+    void *modelWeightPtr_;
+    bool loadFlag_;  // model load flag
+    aclmdlDesc *modelDesc_;
+    aclmdlDataset *input_;
+    aclmdlDataset *output_;
+};
+#endif

model_zoo/official/cv/yolov3_darknet53_quant/ascend310_infer/inc/SampleProcess.h

@@ -0,0 +1,62 @@
+/**
+ * Copyright 2021 Huawei Technologies Co., Ltd
+ * 
+ * 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 SAMPLEPROCESS_H
+#define SAMPLEPROCESS_H
+
+#include <string>
+#include <vector>
+#include "acl/acl.h"
+#include "../inc/utils.h"
+
+/**
+* SampleProcess
+*/
+class SampleProcess {
+ public:
+    /**
+    * @brief Constructor
+    */
+    explicit SampleProcess(int32_t deviceId);
+
+    /**
+    * @brief Destructor
+    */
+    ~SampleProcess();
+
+    /**
+    * @brief init reousce
+    * @return result
+    */
+    Result InitResource(const char *acl_config_path);
+
+    /**
+    * @brief sample process
+    * @return result
+    */
+    Result Process(const char *om_path, const char *input_folder);
+
+    void GetAllFiles(std::string path, std::vector<std::string> *files);
+
+ private:
+    void DestroyResource();
+
+    int32_t deviceId_;
+    aclrtContext context_;
+    aclrtStream stream_;
+};
+
+#endif

model_zoo/official/cv/yolov3_darknet53_quant/ascend310_infer/inc/utils.h

@@ -0,0 +1,53 @@
+/**
+ * Copyright 2021 Huawei Technologies Co., Ltd
+ * 
+ * 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 MINDSPORE_INFERENCE_UTILS_H_
+#define MINDSPORE_INFERENCE_UTILS_H_
+
+#include <iostream>
+#include <string>
+
+#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)
+
+typedef enum Result {
+    SUCCESS = 0,
+    FAILED = 1
+} Result;
+
+/**
+* Utils
+*/
+class Utils {
+ public:
+    /**
+    * @brief create device buffer of file
+    * @param [in] fileName: file name
+    * @param [out] fileSize: size of file
+    * @return device buffer of file
+    */
+    static void *GetDeviceBufferOfFile(std::string fileName, uint32_t *fileSize);
+
+    /**
+    * @brief Read bin file
+    * @param [in] fileName: file name
+    * @param [out] fileSize: size of file
+    * @return buffer of pic
+    */
+    static void* ReadBinFile(std::string fileName, uint32_t *fileSize);
+};
+#endif

model_zoo/official/cv/yolov3_darknet53_quant/ascend310_infer/src/CMakeLists.txt

@@ -0,0 +1,42 @@
+# Copyright (c) Huawei Technologies Co., Ltd. 2021. All rights reserved.
+
+# CMake lowest version requirement
+cmake_minimum_required(VERSION 3.5.1)
+# project information
+project(InferClassification)
+# Check environment variable
+if(NOT DEFINED ENV{ASCEND_HOME})
+    message(FATAL_ERROR "please define environment variable:ASCEND_HOME")
+endif()
+
+# Compile options
+add_compile_definitions(_GLIBCXX_USE_CXX11_ABI=0)
+set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -O0 -g -std=c++17 -Werror -Wall -fPIE -Wl,--allow-shlib-undefined")
+
+# Skip build rpath
+set(CMAKE_SKIP_BUILD_RPATH True)
+
+# Set output directory
+set(PROJECT_SRC_ROOT ${CMAKE_CURRENT_LIST_DIR}/)
+set(CMAKE_RUNTIME_OUTPUT_DIRECTORY ${PROJECT_SRC_ROOT}/out)
+
+# Set include directory and library directory
+set(ACL_LIB_DIR $ENV{ASCEND_HOME}/acllib)
+set(ATLAS_ACL_LIB_DIR $ENV{ASCEND_HOME}/ascend-toolkit/latest/acllib)
+
+# Header path
+include_directories(${ACL_LIB_DIR}/include/)
+include_directories(${ATLAS_ACL_LIB_DIR}/include/)
+include_directories(${PROJECT_SRC_ROOT}/../inc)
+
+# add host lib path
+link_directories(${ACL_LIB_DIR})
+find_library(acl libascendcl.so ${ACL_LIB_DIR}/lib64 ${ATLAS_ACL_LIB_DIR}/lib64)
+
+add_executable(main utils.cpp
+        SampleProcess.cpp
+        ModelProcess.cpp
+        main.cpp)
+
+target_link_libraries(main ${acl} gflags pthread)
+

model_zoo/official/cv/yolov3_darknet53_quant/ascend310_infer/src/ModelProcess.cpp

@@ -0,0 +1,337 @@
+/**
+ * Copyright 2021 Huawei Technologies Co., Ltd
+ * 
+ * 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.
+ */
+
+#include "../inc/ModelProcess.h"
+#include <iostream>
+#include <map>
+#include <sstream>
+#include <algorithm>
+#include "../inc/utils.h"
+
+extern bool g_isDevice;
+
+ModelProcess::ModelProcess() :modelId_(0), modelMemSize_(0), modelWeightSize_(0), modelMemPtr_(nullptr),
+modelWeightPtr_(nullptr), loadFlag_(false), modelDesc_(nullptr), input_(nullptr), output_(nullptr) {
+}
+
+ModelProcess::~ModelProcess() {
+    Unload();
+    DestroyDesc();
+    DestroyInput();
+    DestroyOutput();
+}
+
+Result ModelProcess::LoadModelFromFileWithMem(const char *modelPath) {
+    if (loadFlag_) {
+        ERROR_LOG("has already loaded a model");
+        return FAILED;
+    }
+
+    aclError ret = aclmdlQuerySize(modelPath, &modelMemSize_, &modelWeightSize_);
+    if (ret != ACL_ERROR_NONE) {
+        ERROR_LOG("query model failed, model file is %s", modelPath);
+        return FAILED;
+    }
+
+    ret = aclrtMalloc(&modelMemPtr_, modelMemSize_, ACL_MEM_MALLOC_HUGE_FIRST);
+    if (ret != ACL_ERROR_NONE) {
+        ERROR_LOG("malloc buffer for mem failed, require size is %zu", modelMemSize_);
+        return FAILED;
+    }
+
+    ret = aclrtMalloc(&modelWeightPtr_, modelWeightSize_, ACL_MEM_MALLOC_HUGE_FIRST);
+    if (ret != ACL_ERROR_NONE) {
+        ERROR_LOG("malloc buffer for weight failed, require size is %zu", modelWeightSize_);
+        return FAILED;
+    }
+
+    ret = aclmdlLoadFromFileWithMem(modelPath, &modelId_, modelMemPtr_,
+        modelMemSize_, modelWeightPtr_, modelWeightSize_);
+    if (ret != ACL_ERROR_NONE) {
+        ERROR_LOG("load model from file failed, model file is %s", modelPath);
+        return FAILED;
+    }
+
+    loadFlag_ = true;
+    INFO_LOG("load model %s success", modelPath);
+    return SUCCESS;
+}
+
+Result ModelProcess::CreateDesc() {
+    modelDesc_ = aclmdlCreateDesc();
+    if (modelDesc_ == nullptr) {
+        ERROR_LOG("create model description failed");
+        return FAILED;
+    }
+
+    aclError ret = aclmdlGetDesc(modelDesc_, modelId_);
+    if (ret != ACL_ERROR_NONE) {
+        ERROR_LOG("get model description failed");
+        return FAILED;
+    }
+
+    INFO_LOG("create model description success");
+
+    return SUCCESS;
+}
+
+void ModelProcess::DestroyDesc() {
+    if (modelDesc_ != nullptr) {
+        (void)aclmdlDestroyDesc(modelDesc_);
+        modelDesc_ = nullptr;
+    }
+}
+
+Result ModelProcess::CreateInput(const std::vector<void *> &inputDataBuffer, const std::vector<size_t> &bufferSize) {
+    input_ = aclmdlCreateDataset();
+    if (input_ == nullptr) {
+        ERROR_LOG("can't create dataset, create input failed");
+        return FAILED;
+    }
+    for (size_t i = 0; i < inputDataBuffer.size(); ++i) {
+        aclDataBuffer* inputData = aclCreateDataBuffer(inputDataBuffer[i], bufferSize[i]);
+        if (inputData == nullptr) {
+            ERROR_LOG("can't create data buffer, create input failed");
+            return FAILED;
+        }
+        aclError ret = aclmdlAddDatasetBuffer(input_, inputData);
+        if (ret != ACL_ERROR_NONE) {
+            ERROR_LOG("add input dataset buffer failed");
+            aclDestroyDataBuffer(inputData);
+            inputData = nullptr;
+            return FAILED;
+        }
+    }
+    return SUCCESS;
+}
+
+void ModelProcess::DestroyInput() {
+    if (input_ == nullptr) {
+        return;
+    }
+
+    for (size_t i = 0; i < aclmdlGetDatasetNumBuffers(input_); ++i) {
+        aclDataBuffer* dataBuffer = aclmdlGetDatasetBuffer(input_, i);
+        aclDestroyDataBuffer(dataBuffer);
+    }
+    aclmdlDestroyDataset(input_);
+    input_ = nullptr;
+}
+
+Result ModelProcess::CreateOutput() {
+    if (modelDesc_ == nullptr) {
+        ERROR_LOG("no model description, create output failed");
+        return FAILED;
+    }
+
+    output_ = aclmdlCreateDataset();
+    if (output_ == nullptr) {
+        ERROR_LOG("can't create dataset, create output failed");
+        return FAILED;
+    }
+
+    size_t outputSize = aclmdlGetNumOutputs(modelDesc_);
+    for (size_t i = 0; i < outputSize; ++i) {
+        size_t buffer_size = aclmdlGetOutputSizeByIndex(modelDesc_, i);
+
+        void *outputBuffer = nullptr;
+        aclError ret = aclrtMalloc(&outputBuffer, buffer_size, ACL_MEM_MALLOC_NORMAL_ONLY);
+        if (ret != ACL_ERROR_NONE) {
+            ERROR_LOG("can't malloc buffer, size is %zu, create output failed", buffer_size);
+            return FAILED;
+        }
+
+        aclDataBuffer* outputData = aclCreateDataBuffer(outputBuffer, buffer_size);
+        if (ret != ACL_ERROR_NONE) {
+            ERROR_LOG("can't create data buffer, create output failed");
+            aclrtFree(outputBuffer);
+            return FAILED;
+        }
+
+        ret = aclmdlAddDatasetBuffer(output_, outputData);
+        if (ret != ACL_ERROR_NONE) {
+            ERROR_LOG("can't add data buffer, create output failed");
+            aclrtFree(outputBuffer);
+            aclDestroyDataBuffer(outputData);
+            return FAILED;
+        }
+    }
+
+    INFO_LOG("create model output success");
+    return SUCCESS;
+}
+
+void ModelProcess::DumpModelOutputResult(char *output_name) {
+    size_t outputNum = aclmdlGetDatasetNumBuffers(output_);
+    std::string homePath = "./result_Files";
+    for (size_t i = 0; i < outputNum; ++i) {
+        std::string fileName = std::string(output_name) +  '_' + std::to_string(i) + ".bin";
+        std::string outputFileName = homePath + "/" + fileName;
+        FILE *outputFile = fopen(outputFileName.c_str(), "wb");
+        if (outputFile) {
+            aclDataBuffer* dataBuffer = aclmdlGetDatasetBuffer(output_, i);
+            void* data = aclGetDataBufferAddr(dataBuffer);
+            uint32_t len = aclGetDataBufferSizeV2(dataBuffer);
+            void* outHostData = NULL;
+            aclError ret = ACL_ERROR_NONE;
+            if (!g_isDevice) {
+                ret = aclrtMallocHost(&outHostData, len);
+                if (ret != ACL_ERROR_NONE) {
+                    ERROR_LOG("aclrtMallocHost failed, ret[%d]", ret);
+                    return;
+                }
+
+                ret = aclrtMemcpy(outHostData, len, data, len, ACL_MEMCPY_DEVICE_TO_HOST);
+                if (ret != ACL_ERROR_NONE) {
+                    ERROR_LOG("aclrtMemcpy failed, ret[%d]", ret);
+                    (void)aclrtFreeHost(outHostData);
+                    return;
+                }
+
+                fwrite(outHostData, len, sizeof(char), outputFile);
+
+                ret = aclrtFreeHost(outHostData);
+                if (ret != ACL_ERROR_NONE) {
+                    ERROR_LOG("aclrtFreeHost failed, ret[%d]", ret);
+                    return;
+                }
+            } else {
+                fwrite(data, len, sizeof(char), outputFile);
+            }
+            fclose(outputFile);
+            outputFile = nullptr;
+        } else {
+            ERROR_LOG("create output file [%s] failed", outputFileName.c_str());
+            return;
+        }
+    }
+
+    INFO_LOG("dump data success");
+    return;
+}
+
+void ModelProcess::OutputModelResult() {
+    for (size_t i = 0; i < aclmdlGetDatasetNumBuffers(output_); ++i) {
+        aclDataBuffer* dataBuffer = aclmdlGetDatasetBuffer(output_, i);
+        void* data = aclGetDataBufferAddr(dataBuffer);
+        uint32_t len = aclGetDataBufferSizeV2(dataBuffer);
+
+        void *outHostData = NULL;
+        aclError ret = ACL_ERROR_NONE;
+        float *outData = NULL;
+        if (!g_isDevice) {
+            ret = aclrtMallocHost(&outHostData, len);
+            if (ret != ACL_ERROR_NONE) {
+                ERROR_LOG("aclrtMallocHost failed, ret[%d]", ret);
+                return;
+            }
+
+            ret = aclrtMemcpy(outHostData, len, data, len, ACL_MEMCPY_DEVICE_TO_HOST);
+            if (ret != ACL_ERROR_NONE) {
+                ERROR_LOG("aclrtMemcpy failed, ret[%d]", ret);
+                return;
+            }
+
+            outData = reinterpret_cast<float*>(outHostData);
+        } else {
+            outData = reinterpret_cast<float*>(data);
+        }
+        std::map<float, unsigned int, std::greater<float> > resultMap;
+        for (unsigned int j = 0; j < len / sizeof(float); ++j) {
+            resultMap[*outData] = j;
+            outData++;
+        }
+
+        int cnt = 0;
+        for (auto it = resultMap.begin(); it != resultMap.end(); ++it) {
+            // print top 5
+            if (++cnt > 5) {
+                break;
+            }
+
+            INFO_LOG("top %d: index[%d] value[%lf]", cnt, it->second, it->first);
+        }
+        if (!g_isDevice) {
+            ret = aclrtFreeHost(outHostData);
+            if (ret != ACL_ERROR_NONE) {
+                ERROR_LOG("aclrtFreeHost failed, ret[%d]", ret);
+                return;
+            }
+        }
+    }
+
+    INFO_LOG("output data success");
+    return;
+}
+
+void ModelProcess::DestroyOutput() {
+    if (output_ == nullptr) {
+        return;
+    }
+
+    for (size_t i = 0; i < aclmdlGetDatasetNumBuffers(output_); ++i) {
+        aclDataBuffer* dataBuffer = aclmdlGetDatasetBuffer(output_, i);
+        void* data = aclGetDataBufferAddr(dataBuffer);
+        (void)aclrtFree(data);
+        (void)aclDestroyDataBuffer(dataBuffer);
+    }
+
+    (void)aclmdlDestroyDataset(output_);
+    output_ = nullptr;
+}
+
+Result ModelProcess::Execute() {
+    aclError ret = aclmdlExecute(modelId_, input_, output_);
+    if (ret != ACL_ERROR_NONE) {
+        ERROR_LOG("execute model failed, modelId is %u", modelId_);
+        return FAILED;
+    }
+
+    INFO_LOG("model execute success");
+    return SUCCESS;
+}
+
+void ModelProcess::Unload() {
+    if (!loadFlag_) {
+        WARN_LOG("no model had been loaded, unload failed");
+        return;
+    }
+
+    aclError ret = aclmdlUnload(modelId_);
+    if (ret != ACL_ERROR_NONE) {
+        ERROR_LOG("unload model failed, modelId is %u", modelId_);
+    }
+
+    if (modelDesc_ != nullptr) {
+        (void)aclmdlDestroyDesc(modelDesc_);
+        modelDesc_ = nullptr;
+    }
+
+    if (modelMemPtr_ != nullptr) {
+        aclrtFree(modelMemPtr_);
+        modelMemPtr_ = nullptr;
+        modelMemSize_ = 0;
+    }
+
+    if (modelWeightPtr_ != nullptr) {
+        aclrtFree(modelWeightPtr_);
+        modelWeightPtr_ = nullptr;
+        modelWeightSize_ = 0;
+    }
+
+    loadFlag_ = false;
+    INFO_LOG("unload model success, modelId is %u", modelId_);
+}

model_zoo/official/cv/yolov3_darknet53_quant/ascend310_infer/src/SampleProcess.cpp

@@ -0,0 +1,214 @@
+/**
+ * Copyright 2021 Huawei Technologies Co., Ltd
+ * 
+ * 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.
+ */
+
+#include "../inc/SampleProcess.h"
+#include <sys/types.h>
+#include <dirent.h>
+#include <string.h>
+#include <iostream>
+#include <fstream>
+#include "../inc/utils.h"
+#include "../inc/ModelProcess.h"
+#include "acl/acl.h"
+
+extern bool g_isDevice;
+using std::string;
+using std::vector;
+
+SampleProcess::SampleProcess(int32_t deviceId) : context_(nullptr), stream_(nullptr) {
+    deviceId_ = deviceId;
+}
+
+SampleProcess::~SampleProcess() {
+    DestroyResource();
+}
+
+Result SampleProcess::InitResource(const char *aclConfigPath) {
+    // ACL init
+    aclError ret = aclInit(aclConfigPath);
+    if (ret != ACL_ERROR_NONE) {
+        ERROR_LOG("acl init failed");
+        return FAILED;
+    }
+    INFO_LOG("acl init success");
+
+    // open device
+    ret = aclrtSetDevice(deviceId_);
+    if (ret != ACL_ERROR_NONE) {
+        ERROR_LOG("acl open device %d failed", deviceId_);
+        return FAILED;
+    }
+    INFO_LOG("open device %d success", deviceId_);
+
+    // create context (set current)
+    ret = aclrtCreateContext(&context_, deviceId_);
+    if (ret != ACL_ERROR_NONE) {
+        ERROR_LOG("acl create context failed");
+        return FAILED;
+    }
+    INFO_LOG("create context success");
+
+    // create stream
+    ret = aclrtCreateStream(&stream_);
+    if (ret != ACL_ERROR_NONE) {
+        ERROR_LOG("acl create stream failed");
+        return FAILED;
+    }
+    INFO_LOG("create stream success");
+
+    // get run mode
+    aclrtRunMode runMode;
+    ret = aclrtGetRunMode(&runMode);
+    if (ret != ACL_ERROR_NONE) {
+        ERROR_LOG("acl get run mode failed");
+        return FAILED;
+    }
+    g_isDevice = (runMode == ACL_DEVICE);
+    INFO_LOG("get run mode success");
+    return SUCCESS;
+}
+
+void SampleProcess::GetAllFiles(std::string path, std::vector<string> *files) {
+    DIR *pDir;
+    struct dirent* ptr;
+    if (!(pDir = opendir(path.c_str())))
+        return;
+    while ((ptr = readdir(pDir)) != 0) {
+        if (strcmp(ptr->d_name, ".") != 0 && strcmp(ptr->d_name, "..") != 0)
+            files->push_back(path + "/" + ptr->d_name);
+    }
+    closedir(pDir);
+}
+
+Result SampleProcess::Process(const char *om_path, const char *input_folder) {
+    // model init
+    ModelProcess processModel;
+
+    Result ret = processModel.LoadModelFromFileWithMem(om_path);
+    if (ret != SUCCESS) {
+        ERROR_LOG("execute LoadModelFromFileWithMem failed");
+        return FAILED;
+    }
+
+    ret = processModel.CreateDesc();
+    if (ret != SUCCESS) {
+        ERROR_LOG("execute CreateDesc failed");
+        return FAILED;
+    }
+
+    ret = processModel.CreateOutput();
+    if (ret != SUCCESS) {
+        ERROR_LOG("execute CreateOutput failed");
+        return FAILED;
+    }
+
+    std::vector<string> testFile;
+    GetAllFiles(input_folder, &testFile);
+
+    if (testFile.size() == 0) {
+        WARN_LOG("no input data under folder");
+    }
+    float *inputShape = reinterpret_cast<float *>(malloc(sizeof(float) * 2));
+    inputShape[0] = 416;
+    inputShape[1] = 416;
+    void *inputShapeBuffer = nullptr;
+    int mret = aclrtMalloc(&inputShapeBuffer, 8, ACL_MEM_MALLOC_NORMAL_ONLY);
+    if (mret != ACL_ERROR_NONE) {
+        aclrtFree(inputShapeBuffer);
+        return FAILED;
+    }
+    mret = aclrtMemcpy(reinterpret_cast<uint8_t *>(inputShapeBuffer), 8, inputShape, 8, ACL_MEMCPY_HOST_TO_DEVICE);
+    if (mret != ACL_ERROR_NONE) {
+        aclrtFree(inputShapeBuffer);
+        return FAILED;
+    }
+    // loop begin
+    for (size_t index = 0; index < testFile.size(); ++index) {
+        INFO_LOG("start to process file:%s", testFile[index].c_str());
+        // model process
+        uint32_t devBufferSize;
+        void *picDevBuffer = Utils::GetDeviceBufferOfFile(testFile[index], &devBufferSize);
+        if (picDevBuffer == nullptr) {
+            ERROR_LOG("get pic device buffer failed,index is %zu", index);
+            return FAILED;
+        }
+        std::vector<void *> inputBuffers({picDevBuffer, inputShapeBuffer});
+        std::vector<size_t> inputSizes({devBufferSize, 8});
+        ret = processModel.CreateInput(inputBuffers, inputSizes);
+        if (ret != SUCCESS) {
+            ERROR_LOG("execute CreateInput failed");
+            aclrtFree(picDevBuffer);
+            return FAILED;
+        }
+
+        ret = processModel.Execute();
+        if (ret != SUCCESS) {
+            ERROR_LOG("execute inference failed");
+            aclrtFree(picDevBuffer);
+            return FAILED;
+        }
+
+        int pos = testFile[index].find_last_of('/');
+        std::string name = testFile[index].substr(pos+1);
+        std::string outputname = name.substr(0, name.rfind("."));
+
+        // print the top 5 confidence values
+        processModel.OutputModelResult();
+        // dump output result to file in the current directory
+        processModel.DumpModelOutputResult(const_cast<char *>(outputname.c_str()));
+
+        // release model input buffer
+        aclrtFree(picDevBuffer);
+        processModel.DestroyInput();
+    }
+    // loop end
+
+    return SUCCESS;
+}
+
+void SampleProcess::DestroyResource() {
+    aclError ret;
+    if (stream_ != nullptr) {
+        ret = aclrtDestroyStream(stream_);
+        if (ret != ACL_ERROR_NONE) {
+            ERROR_LOG("destroy stream failed");
+        }
+        stream_ = nullptr;
+    }
+    INFO_LOG("end to destroy stream");
+
+    if (context_ != nullptr) {
+        ret = aclrtDestroyContext(context_);
+        if (ret != ACL_ERROR_NONE) {
+            ERROR_LOG("destroy context failed");
+        }
+        context_ = nullptr;
+    }
+    INFO_LOG("end to destroy context");
+
+    ret = aclrtResetDevice(deviceId_);
+    if (ret != ACL_ERROR_NONE) {
+        ERROR_LOG("reset device failed");
+    }
+    INFO_LOG("end to reset device is %d", deviceId_);
+
+    ret = aclFinalize();
+    if (ret != ACL_ERROR_NONE) {
+        ERROR_LOG("finalize acl failed");
+    }
+    INFO_LOG("end to finalize acl");
+}
+

model_zoo/official/cv/yolov3_darknet53_quant/ascend310_infer/src/acl.json

@@ -0,0 +1 @@
+{}

model_zoo/official/cv/yolov3_darknet53_quant/ascend310_infer/src/build.sh

@@ -0,0 +1,55 @@
+#!/bin/bash
+# Copyright 2021 Huawei Technologies Co., Ltd
+#
+# 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.
+# ============================================================================
+path_cur=$(cd "`dirname $0`" || exit; pwd)
+
+function preparePath() {
+    rm -rf $1
+    mkdir -p $1
+    cd $1 || exit
+}
+
+function buildA300() {
+    if [ ! "${ARCH_PATTERN}" ]; then
+        # set ARCH_PATTERN to acllib when it was not specified by user
+        export ARCH_PATTERN=acllib
+        echo "ARCH_PATTERN is set to the default value: ${ARCH_PATTERN}"
+    else
+        echo "ARCH_PATTERN is set to ${ARCH_PATTERN} by user, reset it to ${ARCH_PATTERN}/acllib"
+        export ARCH_PATTERN=${ARCH_PATTERN}/acllib
+    fi
+
+    path_build=$path_cur/build
+    preparePath $path_build
+    cmake ..
+    make -j
+    ret=$?
+    cd ..
+    return ${ret}
+}
+
+# set ASCEND_VERSION to ascend-toolkit/latest when it was not specified by user
+if [ ! "${ASCEND_VERSION}" ]; then
+    export ASCEND_VERSION=ascend-toolkit/latest
+    echo "Set ASCEND_VERSION to the default value: ${ASCEND_VERSION}"
+else
+    echo "ASCEND_VERSION is set to ${ASCEND_VERSION} by user"
+fi
+
+buildA300
+
+if [ $? -ne 0 ]; then
+    exit 1
+fi

model_zoo/official/cv/yolov3_darknet53_quant/ascend310_infer/src/main.cpp

@@ -0,0 +1,58 @@
+/**
+ * Copyright 2021 Huawei Technologies Co., Ltd
+ *
+ * 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.
+ */
+
+#include <gflags/gflags.h>
+#include <iostream>
+#include <fstream>
+#include <memory>
+#include "../inc/SampleProcess.h"
+#include "../inc/utils.h"
+
+bool g_isDevice = false;
+
+DEFINE_string(om_path, "", "om path");
+DEFINE_string(dataset_path, "", "dataset path");
+DEFINE_string(acljson_path, "", "acl json path");
+DEFINE_int32(device_id, 0, "device id");
+
+int main(int argc, char **argv) {
+  gflags::ParseCommandLineFlags(&argc, &argv, true);
+  std::string om_path = FLAGS_om_path;
+  std::string dataset_path = FLAGS_dataset_path;
+  std::string acljson_path = FLAGS_acljson_path;
+  int32_t device_id = FLAGS_device_id;
+  std::ifstream fin(om_path);
+  if (!fin) {
+    std::cout << "Invalid om path." << std::endl;
+    return FAILED;
+  }
+  SampleProcess processSample(device_id);
+  // acl.json is deployed for dump data.
+  Result ret = processSample.InitResource(acljson_path.c_str());
+  if (ret != SUCCESS) {
+    ERROR_LOG("sample init resource failed");
+    return FAILED;
+  }
+
+  ret = processSample.Process(om_path.c_str(), dataset_path.c_str());
+  if (ret != SUCCESS) {
+    ERROR_LOG("sample process failed");
+    return FAILED;
+  }
+
+  INFO_LOG("execute sample success");
+  return SUCCESS;
+}

model_zoo/official/cv/yolov3_darknet53_quant/ascend310_infer/src/utils.cpp

@@ -0,0 +1,113 @@
+/**
+ * Copyright 2021 Huawei Technologies Co., Ltd
+ * 
+ * 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.
+ */
+
+#include "../inc/utils.h"
+#include <sys/stat.h>
+#include <iostream>
+#include <fstream>
+#include <cstring>
+#include "acl/acl.h"
+
+extern bool g_isDevice;
+
+void* Utils::ReadBinFile(std::string fileName, uint32_t *fileSize) {
+    struct stat sBuf;
+    int fileStatus = stat(fileName.data(), &sBuf);
+    if (fileStatus == -1) {
+        ERROR_LOG("failed to get file");
+        return nullptr;
+    }
+    if (S_ISREG(sBuf.st_mode) == 0) {
+        ERROR_LOG("%s is not a file, please enter a file", fileName.c_str());
+        return nullptr;
+    }
+
+    std::ifstream binFile(fileName, std::ifstream::binary);
+    if (binFile.is_open() == false) {
+        ERROR_LOG("open file %s failed", fileName.c_str());
+        return nullptr;
+    }
+
+    binFile.seekg(0, binFile.end);
+    uint32_t binFileBufferLen = binFile.tellg();
+    if (binFileBufferLen == 0) {
+        ERROR_LOG("binfile is empty, filename is %s", fileName.c_str());
+        binFile.close();
+        return nullptr;
+    }
+
+    binFile.seekg(0, binFile.beg);
+
+    void* binFileBufferData = nullptr;
+    aclError ret = ACL_ERROR_NONE;
+    if (!g_isDevice) {
+        ret = aclrtMallocHost(&binFileBufferData, binFileBufferLen);
+        if (ret != ACL_ERROR_NONE) {
+            ERROR_LOG("malloc for binFileBufferData failed");
+            binFile.close();
+            return nullptr;
+        }
+        if (binFileBufferData == nullptr) {
+            ERROR_LOG("malloc binFileBufferData failed");
+            binFile.close();
+            return nullptr;
+        }
+    } else {
+        ret = aclrtMalloc(&binFileBufferData, binFileBufferLen, ACL_MEM_MALLOC_NORMAL_ONLY);
+        if (ret != ACL_ERROR_NONE) {
+            ERROR_LOG("malloc device buffer failed. size is %u", binFileBufferLen);
+            binFile.close();
+            return nullptr;
+        }
+    }
+    binFile.read(static_cast<char *>(binFileBufferData), binFileBufferLen);
+    binFile.close();
+    *fileSize = binFileBufferLen;
+    return binFileBufferData;
+}
+
+void* Utils::GetDeviceBufferOfFile(std::string fileName, uint32_t *fileSize) {
+    uint32_t inputHostBuffSize = 0;
+    void* inputHostBuff = Utils::ReadBinFile(fileName, &inputHostBuffSize);
+    if (inputHostBuff == nullptr) {
+        return nullptr;
+    }
+    if (!g_isDevice) {
+        void *inBufferDev = nullptr;
+        uint32_t inBufferSize = inputHostBuffSize;
+        aclError ret = aclrtMalloc(&inBufferDev, inBufferSize, ACL_MEM_MALLOC_NORMAL_ONLY);
+        if (ret != ACL_ERROR_NONE) {
+            ERROR_LOG("malloc device buffer failed. size is %u", inBufferSize);
+            aclrtFreeHost(inputHostBuff);
+            return nullptr;
+        }
+
+        ret = aclrtMemcpy(inBufferDev, inBufferSize, inputHostBuff, inputHostBuffSize, ACL_MEMCPY_HOST_TO_DEVICE);
+        if (ret != ACL_ERROR_NONE) {
+            ERROR_LOG("memcpy failed. device buffer size is %u, input host buffer size is %u",
+                inBufferSize, inputHostBuffSize);
+            aclrtFree(inBufferDev);
+            aclrtFreeHost(inputHostBuff);
+            return nullptr;
+        }
+        aclrtFreeHost(inputHostBuff);
+        *fileSize = inBufferSize;
+        return inBufferDev;
+    } else {
+        *fileSize = inputHostBuffSize;
+        return inputHostBuff;
+    }
+}

model_zoo/official/cv/yolov3_darknet53_quant/export_bin_file.py

@@ -0,0 +1,111 @@
+# Copyright 2021 Huawei Technologies Co., Ltd
+#
+# 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.
+# ============================================================================
+"""YoloV3_quant export coco bin."""
+import os
+import argparse
+import datetime
+import numpy as np
+import mindspore as ms
+from mindspore import Tensor
+from mindspore.context import ParallelMode
+from mindspore import context
+
+from src.logger import get_logger
+from src.yolo_dataset import create_yolo_dataset
+from src.config import ConfigYOLOV3DarkNet53
+
+def parse_args():
+    """Parse arguments."""
+    parser = argparse.ArgumentParser('mindspore coco export bin')
+    parser.add_argument('--device_target', type=str, default="Ascend",
+                        choices=['Ascend', 'GPU'],
+                        help='device where the code will be implemented (default: Ascend)')
+    # dataset related
+    parser.add_argument('--data_dir', type=str, default="", help='Eval data dir. Default: ""')
+    parser.add_argument('--per_batch_size', default=1, type=int, help='Batch size for per device, Default: 1')
+
+    # logging related
+    parser.add_argument('--log_path', type=str, default="outputs/", help='Log save location, Default: "outputs/"')
+    parser.add_argument('--save_path', type=str, default="", help='Bin file save location')
+
+    # detect_related
+    parser.add_argument('--nms_thresh', type=float, default=0.5, help='Threshold for NMS. Default: 0.5')
+    parser.add_argument('--annFile', type=str, default="", help='The path to annotation. Default: ""')
+    parser.add_argument('--testing_shape', type=str, default="", help='Shape for test. Default: ""')
+
+    args_, _ = parser.parse_known_args()
+
+    args_.data_root = os.path.join(args_.data_dir, 'val2014')
+    args_.annFile = os.path.join(args_.data_dir, 'annotations/instances_val2014.json')
+
+    return args_
+
+def conver_testing_shape(args_org):
+    """Convert testing shape to list."""
+    testing_shape = [int(args_org.testing_shape), int(args_org.testing_shape)]
+    return testing_shape
+
+if __name__ == "__main__":
+    args = parse_args()
+    devid = int(os.getenv('DEVICE_ID')) if os.getenv('DEVICE_ID') else 0
+    context.set_context(mode=context.GRAPH_MODE, device_target=args.device_target, device_id=devid)
+
+    # logger
+    args.outputs_dir = os.path.join(args.log_path,
+                                    datetime.datetime.now().strftime('%Y-%m-%d_time_%H_%M_%S'))
+    rank_id = int(os.environ.get('RANK_ID')) if os.environ.get('RANK_ID') else 0
+    args.logger = get_logger(args.outputs_dir, rank_id)
+
+    context.reset_auto_parallel_context()
+    parallel_mode = ParallelMode.STAND_ALONE
+    context.set_auto_parallel_context(parallel_mode=parallel_mode, gradients_mean=True, device_num=1)
+
+    config = ConfigYOLOV3DarkNet53()
+    if args.testing_shape:
+        config.test_img_shape = conver_testing_shape(args)
+    data_root = args.data_root
+    ann_file = args.annFile
+
+    ds, data_size = create_yolo_dataset(data_root, ann_file, is_training=False, batch_size=args.per_batch_size,
+                                        max_epoch=1, device_num=1, rank=rank_id, shuffle=False,
+                                        config=config)
+
+    args.logger.info('testing shape : {}'.format(config.test_img_shape))
+    args.logger.info('totol {} images to eval'.format(data_size))
+
+    cur_dir = args.save_path
+    save_folder = os.path.join(cur_dir, "yolov3_quant_coco_310_infer_data")
+    image_folder = os.path.join(save_folder, "image_bin")
+    if not os.path.exists(image_folder):
+        os.makedirs(image_folder)
+
+    list_image_shape = []
+    list_image_id = []
+
+    input_shape = Tensor(tuple(config.test_img_shape), ms.float32)
+    args.logger.info('Start inference....')
+    for i, data in enumerate(ds.create_dict_iterator()):
+        image = data["image"].asnumpy()
+        image_shape = data["image_shape"]
+        image_id = data["img_id"]
+        file_name = "YoloV3-DarkNet_coco_bs_" + str(args.per_batch_size) + "_" + str(i) + ".bin"
+        file_path = image_folder + "/" + file_name
+        image.tofile(file_path)
+        list_image_shape.append(image_shape.asnumpy())
+        list_image_id.append(image_id.asnumpy())
+    shapes = np.array(list_image_shape)
+    ids = np.array(list_image_id)
+    np.save(save_folder + "/image_shape.npy", shapes)
+    np.save(save_folder + "/image_id.npy", ids)

model_zoo/official/cv/yolov3_darknet53_quant/postprocess.py

@@ -0,0 +1,66 @@
+# Copyright 2021 Huawei Technologies Co., Ltd
+#
+# 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.
+# ============================================================================
+"""YoloV3 postprocess."""
+import os
+import argparse
+import datetime
+import numpy as np
+from eval import DetectionEngine
+
+parser = argparse.ArgumentParser('YoloV3_quant postprocess')
+parser.add_argument('--result_path', type=str, required=True, help='result files path.')
+parser.add_argument('--per_batch_size', default=1, type=int, help='batch size for per gpu')
+parser.add_argument('--nms_thresh', type=float, default=0.5, help='threshold for NMS')
+parser.add_argument('--annFile', type=str, default='', help='path to annotation')
+parser.add_argument('--image_shape', type=str, default='./image_shape.npy', help='path to image_shape.npy')
+parser.add_argument('--image_id', type=str, default='./image_id.npy', help='path to image_id.npy')
+parser.add_argument('--ignore_threshold', type=float, default=0.001, help='threshold to throw low quality boxes')
+parser.add_argument('--log_path', type=str, default='outputs/', help='inference result save location')
+
+args, _ = parser.parse_known_args()
+
+if __name__ == "__main__":
+    args.outputs_dir = os.path.join(args.log_path,
+                                    datetime.datetime.now().strftime('%Y-%m-%d_time_%H_%M_%S'))
+    if not os.path.exists(args.outputs_dir):
+        os.makedirs(args.outputs_dir)
+
+    detection = DetectionEngine(args)
+    bs = args.per_batch_size
+
+    f_list = os.listdir(args.result_path)
+    shape_list = np.load(args.image_shape)
+    id_list = np.load(args.image_id)
+    prefix = "YoloV3-DarkNet_coco_bs_" + str(bs) + "_"
+    iter_num = 0
+    for image_id in id_list:
+        image_shape = shape_list[iter_num]
+        path_small = os.path.join(args.result_path, prefix + str(iter_num) + '_0.bin')
+        path_medium = os.path.join(args.result_path, prefix + str(iter_num) + '_1.bin')
+        path_big = os.path.join(args.result_path, prefix + str(iter_num) + '_2.bin')
+        if os.path.exists(path_small) and os.path.exists(path_medium) and os.path.exists(path_big):
+            output_small = np.fromfile(path_small, np.float32).reshape(bs, 13, 13, 3, 85)
+            output_medium = np.fromfile(path_medium, np.float32).reshape(bs, 26, 26, 3, 85)
+            output_big = np.fromfile(path_big, np.float32).reshape(bs, 52, 52, 3, 85)
+            detection.detect([output_small, output_medium, output_big], bs, image_shape, image_id)
+        else:
+            print("Error: Image ", iter_num, " is not exist.")
+        iter_num += 1
+
+    detection.do_nms_for_results()
+    result_file_path = detection.write_result()
+    eval_result = detection.get_eval_result()
+
+    print('\n=============coco eval result=========\n' + eval_result)

model_zoo/official/cv/yolov3_darknet53_quant/scripts/run_infer_310.sh

@@ -0,0 +1,114 @@
+#!/bin/bash
+# Copyright 2021 Huawei Technologies Co., Ltd
+#
+# 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.
+# ============================================================================
+
+if [[ $# -lt 5 || $# -gt 6 ]]; then
+    echo "Usage: bash run_infer_310.sh [AIR_PATH] [DATA_PATH] [ANNO_PATH] [IMAGESHAPE_PATH] [IMAGEID_PATH] [DEVICE_ID]
+    DEVICE_ID is optional, it can be set by environment variable device_id, otherwise the value is zero"
+exit 1
+fi
+
+get_real_path(){
+    if [ "${1:0:1}" == "/" ]; then
+        echo "$1"
+    else
+        echo "$(realpath -m $PWD/$1)"
+    fi
+}
+model=$(get_real_path $1)
+data_path=$(get_real_path $2)
+anno_path=$(get_real_path $3)
+image_shape_path=$(get_real_path $4)
+image_id_path=$(get_real_path $5)
+
+device_id=0
+if [ $# == 6 ]; then
+    device_id=$6
+fi
+
+echo "mindir name: "$model
+echo "dataset path: "$data_path
+echo "annotation path: "$anno_path
+echo "image shape path: "$image_shape_path
+echo "image id path: "$image_id_path
+echo "device id: "$device_id
+
+export ASCEND_HOME=/usr/local/Ascend/
+if [ -d ${ASCEND_HOME}/ascend-toolkit ]; then
+    export PATH=$ASCEND_HOME/ascend-toolkit/latest/fwkacllib/ccec_compiler/bin:$ASCEND_HOME/ascend-toolkit/latest/atc/bin:$PATH
+    export LD_LIBRARY_PATH=/usr/local/lib:$ASCEND_HOME/ascend-toolkit/latest/atc/lib64:$ASCEND_HOME/ascend-toolkit/latest/fwkacllib/lib64:$ASCEND_HOME/driver/lib64:$ASCEND_HOME/add-ons:$LD_LIBRARY_PATH
+    export TBE_IMPL_PATH=$ASCEND_HOME/ascend-toolkit/latest/opp/op_impl/built-in/ai_core/tbe
+    export PYTHONPATH=${TBE_IMPL_PATH}:$ASCEND_HOME/ascend-toolkit/latest/fwkacllib/python/site-packages:$PYTHONPATH
+    export ASCEND_OPP_PATH=$ASCEND_HOME/ascend-toolkit/latest/opp
+else
+    export PATH=$ASCEND_HOME/atc/ccec_compiler/bin:$ASCEND_HOME/atc/bin:$PATH
+    export LD_LIBRARY_PATH=/usr/local/lib:$ASCEND_HOME/atc/lib64:$ASCEND_HOME/acllib/lib64:$ASCEND_HOME/driver/lib64:$ASCEND_HOME/add-ons:$LD_LIBRARY_PATH
+    export PYTHONPATH=$ASCEND_HOME/atc/python/site-packages:$PYTHONPATH
+    export ASCEND_OPP_PATH=$ASCEND_HOME/opp
+fi
+
+function air_to_om()
+{
+    atc --input_format=NCHW --framework=1 --model=$model --output=yolov3_darknet53_quant --soc_version=Ascend310 &> atc.log
+}
+
+function compile_app()
+{
+    cd ../ascend310_infer/src || exit
+    bash build.sh &> build.log
+}
+
+function infer()
+{
+    cd - || exit
+    if [ -d result_Files ]; then
+        rm -rf ./result_Files
+    fi
+    if [ -d time_Result ]; then
+        rm -rf ./time_Result
+    fi
+    mkdir result_Files
+    mkdir time_Result
+
+    ../ascend310_infer/src/out/main --om_path=./yolov3_darknet53_quant.om --dataset_path=$data_path --acljson_path=../ascend310_infer/src/acl.json --device_id=$device_id &> infer.log
+
+}
+
+function cal_acc()
+{
+    python3.7 ../postprocess.py --result_path=./result_Files --img_path=$data_path --annFile=$anno_path --image_shape=$image_shape_path --image_id=$image_id_path &> acc.log
+}
+
+air_to_om
+if [ $? -ne 0 ]; then
+    echo "air to om code failed"
+    exit 1
+fi
+
+compile_app
+if [ $? -ne 0 ]; then
+    echo "compile app code failed"
+    exit 1
+fi
+infer
+if [ $? -ne 0 ]; then
+    echo " execute inference failed"
+    exit 1
+fi
+cal_acc
+if [ $? -ne 0 ]; then
+    echo "calculate accuracy failed"
+    exit 1
+fi