diff --git a/model_zoo/official/cv/resnet/ascend310_infer/inc/utils.h b/model_zoo/official/cv/resnet/ascend310_infer/inc/utils.h new file mode 100644 index 0000000000..f8ae1e5b47 --- /dev/null +++ b/model_zoo/official/cv/resnet/ascend310_infer/inc/utils.h @@ -0,0 +1,35 @@ +/** + * 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 +#include +#include +#include +#include +#include "include/api/types.h" + +std::vector GetAllFiles(std::string_view dirName); +DIR *OpenDir(std::string_view dirName); +std::string RealPath(std::string_view path); +mindspore::MSTensor ReadFileToTensor(const std::string &file); +int WriteResult(const std::string& imageFile, const std::vector &outputs); +std::vector GetAllFiles(std::string dir_name); +std::vector> GetAllInputData(std::string dir_name); + +#endif diff --git a/model_zoo/official/cv/resnet/ascend310_infer/src/CMakeLists.txt b/model_zoo/official/cv/resnet/ascend310_infer/src/CMakeLists.txt new file mode 100644 index 0000000000..0397995b0e --- /dev/null +++ b/model_zoo/official/cv/resnet/ascend310_infer/src/CMakeLists.txt @@ -0,0 +1,14 @@ +cmake_minimum_required(VERSION 3.14.1) +project(MindSporeCxxTestcase[CXX]) +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") +set(PROJECT_SRC_ROOT ${CMAKE_CURRENT_LIST_DIR}/) +option(MINDSPORE_PATH "mindspore install path" "") +include_directories(${MINDSPORE_PATH}) +include_directories(${MINDSPORE_PATH}/include) +include_directories(${PROJECT_SRC_ROOT}/../) +find_library(MS_LIB libmindspore.so ${MINDSPORE_PATH}/lib) +file(GLOB_RECURSE MD_LIB ${MINDSPORE_PATH}/_c_dataengine*) + +add_executable(main main.cc utils.cc) +target_link_libraries(main ${MS_LIB} ${MD_LIB} gflags) diff --git a/model_zoo/official/cv/resnet/ascend310_infer/src/build.sh b/model_zoo/official/cv/resnet/ascend310_infer/src/build.sh new file mode 100644 index 0000000000..7fac9cff3a --- /dev/null +++ b/model_zoo/official/cv/resnet/ascend310_infer/src/build.sh @@ -0,0 +1,18 @@ +#!/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. +# ============================================================================ + +cmake . -DMINDSPORE_PATH="`pip3.7 show mindspore-ascend | grep Location | awk '{print $2"/mindspore"}' | xargs realpath`" +make \ No newline at end of file diff --git a/model_zoo/official/cv/resnet/ascend310_infer/src/main.cc b/model_zoo/official/cv/resnet/ascend310_infer/src/main.cc new file mode 100644 index 0000000000..9f3f52356b --- /dev/null +++ b/model_zoo/official/cv/resnet/ascend310_infer/src/main.cc @@ -0,0 +1,147 @@ +/** + * 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 +#include +#include +#include +#include +#include +#include +#include +#include + +#include "include/api/model.h" +#include "include/api/context.h" +#include "include/api/types.h" +#include "include/api/serialization.h" +#include "minddata/dataset/include/vision_ascend.h" +#include "minddata/dataset/include/execute.h" +#include "minddata/dataset/include/transforms.h" +#include "minddata/dataset/include/vision.h" +#include "inc/utils.h" + +using mindspore::dataset::vision::Decode; +using mindspore::dataset::vision::Resize; +using mindspore::dataset::vision::CenterCrop; +using mindspore::dataset::vision::Normalize; +using mindspore::dataset::vision::HWC2CHW; +using mindspore::dataset::TensorTransform; +using mindspore::GlobalContext; +using mindspore::Serialization; +using mindspore::Model; +using mindspore::ModelContext; +using mindspore::Status; +using mindspore::ModelType; +using mindspore::GraphCell; +using mindspore::kSuccess; +using mindspore::MSTensor; +using mindspore::dataset::Execute; + + +DEFINE_string(mindir_path, "", "mindir path"); +DEFINE_string(dataset_path, ".", "dataset path"); +DEFINE_int32(device_id, 0, "device id"); + +int main(int argc, char **argv) { + gflags::ParseCommandLineFlags(&argc, &argv, true); + if (RealPath(FLAGS_mindir_path).empty()) { + std::cout << "Invalid mindir" << std::endl; + return 1; + } + + + GlobalContext::SetGlobalDeviceTarget(mindspore::kDeviceTypeAscend310); + GlobalContext::SetGlobalDeviceID(FLAGS_device_id); + auto graph = Serialization::LoadModel(FLAGS_mindir_path, ModelType::kMindIR); + auto model_context = std::make_shared(); + + Model model(GraphCell(graph), model_context); + Status ret = model.Build(); + if (ret != kSuccess) { + std::cout << "ERROR: Build failed." << std::endl; + return 1; + } + + auto all_files = GetAllInputData(FLAGS_dataset_path); + if (all_files.empty()) { + std::cout << "ERROR: no input data." << std::endl; + return 1; + } + + std::map costTime_map; + size_t size = all_files.size(); + // Define transform + std::vector crop_paras = {224}; + std::vector resize_paras = {256}; + std::vector mean = {0.485 * 255, 0.456 * 255, 0.406 * 255}; + std::vector std = {0.229 * 255, 0.224 * 255, 0.225 * 255}; + + std::shared_ptr decode(new Decode()); + std::shared_ptr resize(new Resize(resize_paras)); + std::shared_ptr centercrop(new CenterCrop(crop_paras)); + std::shared_ptr normalize(new Normalize(mean, std)); + std::shared_ptr hwc2chw(new HWC2CHW()); + + std::vector> trans_list = {decode, resize, centercrop, normalize, hwc2chw}; + mindspore::dataset::Execute SingleOp(trans_list); + + for (size_t i = 0; i < size; ++i) { + for (size_t j = 0; j < all_files[i].size(); ++j) { + struct timeval start = {0}; + struct timeval end = {0}; + double startTimeMs; + double endTimeMs; + std::vector inputs; + std::vector outputs; + std::cout << "Start predict input files:" << all_files[i][j] <(); + SingleOp(ReadFileToTensor(all_files[i][j]), imgDvpp.get()); + + inputs.emplace_back(imgDvpp->Name(), imgDvpp->DataType(), imgDvpp->Shape(), + imgDvpp->Data().get(), imgDvpp->DataSize()); + gettimeofday(&start, nullptr); + ret = model.Predict(inputs, &outputs); + gettimeofday(&end, nullptr); + if (ret != kSuccess) { + std::cout << "Predict " << all_files[i][j] << " failed." << std::endl; + return 1; + } + startTimeMs = (1.0 * start.tv_sec * 1000000 + start.tv_usec) / 1000; + endTimeMs = (1.0 * end.tv_sec * 1000000 + end.tv_usec) / 1000; + costTime_map.insert(std::pair(startTimeMs, endTimeMs)); + WriteResult(all_files[i][j], outputs); + } + } + double average = 0.0; + int inferCount = 0; + char tmpCh[256] = {0}; + for (auto iter = costTime_map.begin(); iter != costTime_map.end(); iter++) { + double diff = 0.0; + diff = iter->second - iter->first; + average += diff; + inferCount++; + } + average = average / inferCount; + snprintf(tmpCh, sizeof(tmpCh), \ + "NN inference cost average time: %4.3f ms of infer_count %d \n", average, inferCount); + std::cout << "NN inference cost average time: "<< average << "ms of infer_count " << inferCount << std::endl; + std::string fileName = "./time_Result" + std::string("/test_perform_static.txt"); + std::ofstream fileStream(fileName.c_str(), std::ios::trunc); + fileStream << tmpCh; + fileStream.close(); + costTime_map.clear(); + return 0; +} diff --git a/model_zoo/official/cv/resnet/ascend310_infer/src/utils.cc b/model_zoo/official/cv/resnet/ascend310_infer/src/utils.cc new file mode 100644 index 0000000000..ac07be3cb7 --- /dev/null +++ b/model_zoo/official/cv/resnet/ascend310_infer/src/utils.cc @@ -0,0 +1,186 @@ +/** + * 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 +#include +#include +#include "inc/utils.h" + +using mindspore::MSTensor; +using mindspore::DataType; + + +std::vector> GetAllInputData(std::string dir_name) { + std::vector> ret; + + DIR *dir = OpenDir(dir_name); + if (dir == nullptr) { + return {}; + } + struct dirent *filename; + /* read all the files in the dir ~ */ + std::vector sub_dirs; + while ((filename = readdir(dir)) != nullptr) { + std::string d_name = std::string(filename->d_name); + // get rid of "." and ".." + if (d_name == "." || d_name == ".." || d_name.empty()) { + continue; + } + std::string dir_path = RealPath(std::string(dir_name) + "/" + filename->d_name); + struct stat s; + lstat(dir_path.c_str(), &s); + if (!S_ISDIR(s.st_mode)) { + continue; + } + + sub_dirs.emplace_back(dir_path); + } + std::sort(sub_dirs.begin(), sub_dirs.end()); + + (void)std::transform(sub_dirs.begin(), sub_dirs.end(), std::back_inserter(ret), + [](const std::string &d) { return GetAllFiles(d); }); + + return ret; +} + + +std::vector GetAllFiles(std::string dir_name) { + struct dirent *filename; + DIR *dir = OpenDir(dir_name); + if (dir == nullptr) { + return {}; + } + + std::vector res; + while ((filename = readdir(dir)) != nullptr) { + std::string d_name = std::string(filename->d_name); + if (d_name == "." || d_name == ".." || d_name.size() <= 3) { + continue; + } + res.emplace_back(std::string(dir_name) + "/" + filename->d_name); + } + std::sort(res.begin(), res.end()); + + return res; +} + + +std::vector GetAllFiles(std::string_view dirName) { + struct dirent *filename; + DIR *dir = OpenDir(dirName); + if (dir == nullptr) { + return {}; + } + std::vector res; + while ((filename = readdir(dir)) != nullptr) { + std::string dName = std::string(filename->d_name); + if (dName == "." || dName == ".." || filename->d_type != DT_REG) { + continue; + } + res.emplace_back(std::string(dirName) + "/" + filename->d_name); + } + std::sort(res.begin(), res.end()); + for (auto &f : res) { + std::cout << "image file: " << f << std::endl; + } + return res; +} + + +int WriteResult(const std::string& imageFile, const std::vector &outputs) { + std::string homePath = "./result_Files"; + for (size_t i = 0; i < outputs.size(); ++i) { + size_t outputSize; + std::shared_ptr netOutput; + netOutput = outputs[i].Data(); + outputSize = outputs[i].DataSize(); + int pos = imageFile.rfind('/'); + std::string fileName(imageFile, pos + 1); + fileName.replace(fileName.find('.'), fileName.size() - fileName.find('.'), '_' + std::to_string(i) + ".bin"); + std::string outFileName = homePath + "/" + fileName; + FILE * outputFile = fopen(outFileName.c_str(), "wb"); + fwrite(netOutput.get(), outputSize, sizeof(char), outputFile); + fclose(outputFile); + outputFile = nullptr; + } + return 0; +} + +mindspore::MSTensor ReadFileToTensor(const std::string &file) { + if (file.empty()) { + std::cout << "Pointer file is nullptr" << std::endl; + return mindspore::MSTensor(); + } + + std::ifstream ifs(file); + if (!ifs.good()) { + std::cout << "File: " << file << " is not exist" << std::endl; + return mindspore::MSTensor(); + } + + if (!ifs.is_open()) { + std::cout << "File: " << file << "open failed" << std::endl; + return mindspore::MSTensor(); + } + + ifs.seekg(0, std::ios::end); + size_t size = ifs.tellg(); + mindspore::MSTensor buffer(file, mindspore::DataType::kNumberTypeUInt8, {static_cast(size)}, nullptr, size); + + ifs.seekg(0, std::ios::beg); + ifs.read(reinterpret_cast(buffer.MutableData()), size); + ifs.close(); + + return buffer; +} + + +DIR *OpenDir(std::string_view dirName) { + if (dirName.empty()) { + std::cout << " dirName is null ! " << std::endl; + return nullptr; + } + std::string realPath = RealPath(dirName); + struct stat s; + lstat(realPath.c_str(), &s); + if (!S_ISDIR(s.st_mode)) { + std::cout << "dirName is not a valid directory !" << std::endl; + return nullptr; + } + DIR *dir; + dir = opendir(realPath.c_str()); + if (dir == nullptr) { + std::cout << "Can not open dir " << dirName << std::endl; + return nullptr; + } + std::cout << "Successfully opened the dir " << dirName << std::endl; + return dir; +} + +std::string RealPath(std::string_view path) { + char realPathMem[PATH_MAX] = {0}; + char *realPathRet = nullptr; + realPathRet = realpath(path.data(), realPathMem); + + if (realPathRet == nullptr) { + std::cout << "File: " << path << " is not exist."; + return ""; + } + + std::string realPath(realPathMem); + std::cout << path << " realpath is: " << realPath << std::endl; + return realPath; +} diff --git a/model_zoo/official/cv/resnet/create_imagenet2012_label.py b/model_zoo/official/cv/resnet/create_imagenet2012_label.py new file mode 100644 index 0000000000..38f6ee9428 --- /dev/null +++ b/model_zoo/official/cv/resnet/create_imagenet2012_label.py @@ -0,0 +1,48 @@ +# 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 +# +# less 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. +# ============================================================================ +"""create_imagenet2012_label""" +import os +import json +import argparse + +parser = argparse.ArgumentParser(description="resnet imagenet2012 label") +parser.add_argument("--img_path", type=str, required=True, help="imagenet2012 file path.") +args = parser.parse_args() + + +def create_label(file_path): + print("[WARNING] Create imagenet label. Currently only use for Imagenet2012!") + dirs = os.listdir(file_path) + file_list = [] + for file in dirs: + file_list.append(file) + file_list = sorted(file_list) + + total = 0 + img_label = {} + for i, file_dir in enumerate(file_list): + files = os.listdir(os.path.join(file_path, file_dir)) + for f in files: + img_label[f] = i + total += len(files) + + with open("imagenet_label.json", "w+") as label: + json.dump(img_label, label) + + print("[INFO] Completed! Total {} data.".format(total)) + + +if __name__ == '__main__': + create_label(args.img_path) diff --git a/model_zoo/official/cv/resnet/postprocess.py b/model_zoo/official/cv/resnet/postprocess.py new file mode 100644 index 0000000000..f7fa6d040b --- /dev/null +++ b/model_zoo/official/cv/resnet/postprocess.py @@ -0,0 +1,51 @@ +# 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 +# +# less 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 json +import argparse +import numpy as np +from src.config import config2 as config + +batch_size = 1 +parser = argparse.ArgumentParser(description="resnet inference") +parser.add_argument("--result_path", type=str, required=True, help="result files path.") +parser.add_argument("--label_path", type=str, required=True, help="image file path.") +args = parser.parse_args() + + +def get_result(result_path, label_path): + files = os.listdir(result_path) + with open(label_path, "r") as label: + labels = json.load(label) + + top1 = 0 + top5 = 0 + total_data = len(files) + for file in files: + img_ids_name = file.split('_0.')[0] + data_path = os.path.join(result_path, img_ids_name + "_0.bin") + result = np.fromfile(data_path, dtype=np.float32).reshape(batch_size, config.class_num) + for batch in range(batch_size): + predict = np.argsort(-result[batch], axis=-1) + if labels[img_ids_name+".JPEG"] == predict[0]: + top1 += 1 + if labels[img_ids_name+".JPEG"] in predict[:5]: + top5 += 1 + print(f"Total data: {total_data}, top1 accuracy: {top1/total_data}, top5 accuracy: {top5/total_data}.") + + +if __name__ == '__main__': + get_result(args.result_path, args.label_path) diff --git a/model_zoo/official/cv/resnet/scripts/run_infer_310.sh b/model_zoo/official/cv/resnet/scripts/run_infer_310.sh new file mode 100644 index 0000000000..f6c0660251 --- /dev/null +++ b/model_zoo/official/cv/resnet/scripts/run_infer_310.sh @@ -0,0 +1,99 @@ +#!/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 2 || $# -gt 3 ]]; then + echo "Usage: sh run_infer_310.sh [MINDIR_PATH] [DATA_PATH] [DEVICE_ID] + DEVICE_ID is optional, it can be set by environment variable device_id, otherwise the value is zero" +exit 1 +fi + +get_real_path(){ + if [ "${1:0:1}" == "/" ]; then + echo "$1" + else + echo "$(realpath -m $PWD/$1)" + fi +} +model=$(get_real_path $1) +data_path=$(get_real_path $2) + +device_id=0 +if [ $# == 3 ]; then + device_id=$3 +fi + +echo "mindir name: "$model +echo "dataset path: "$data_path +echo "device id: "$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=$ASCEND_HOME/opp +fi + +function compile_app() +{ + cd ../ascend310_infer/src/ + if [ -f "Makefile" ]; then + make clean + fi + sh build.sh &> build.log +} + +function infer() +{ + cd - + if [ -d result_Files ]; then + rm -rf ./result_Files + fi + if [ -d time_Result ]; then + rm -rf ./time_Result + fi + mkdir result_Files + mkdir time_Result + ../ascend310_infer/src/main --mindir_path=$model --dataset_path=$data_path --device_id=$device_id &> infer.log +} + +function cal_acc() +{ + python3.7 ../create_imagenet2012_label.py --img_path=$data_path + python3.7 ../postprocess.py --result_path=./result_Files --label_path=./imagenet_label.json &> acc.log & +} + +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 \ No newline at end of file