diff --git a/model_zoo/official/cv/mobilenetv1/README.md b/model_zoo/official/cv/mobilenetv1/README.md index 75c6faa9102..83228c9a7c9 100644 --- a/model_zoo/official/cv/mobilenetv1/README.md +++ b/model_zoo/official/cv/mobilenetv1/README.md @@ -1,4 +1,4 @@ -# Mobilenet_V1 +# Mobilenet_V1 - [Mobilenet_V1](#mobilenet_v1) - [MobileNetV1 Description](#mobilenetv1-description) @@ -161,6 +161,40 @@ Inference result will be stored in the example path, you can find result like th result: {'top_5_accuracy': 0.9010016025641026, 'top_1_accuracy': 0.7128004807692307} ckpt=./train_parallel0/ckpt_0/mobilenetv1-90_1251.ckpt ``` +## Inference Process + +### [Export MindIR](#contents) + +```shell +python export.py --ckpt_file [CKPT_PATH] --file_name [FILE_NAME] --file_format [FILE_FORMAT] +``` + +The ckpt_file parameter is required, +`EXPORT_FORMAT` should be in ["AIR", "MINDIR"] + +### Infer on Ascend310 + +Before performing inference, the mindir file must be exported by `export.py` script. We only provide an example of inference using MINDIR model. +Current batch_Size for imagenet2012 dataset can only be set to 1. + +```shell +# Ascend310 inference +bash run_infer_310.sh [MINDIR_PATH] [DATASET_PATH] [DEVICE_ID] +``` + +- `MINDIR_PATH` specifies path of used "MINDIR" OR "AIR" model. +- `DATASET_PATH` specifies path of cifar10 datasets +- `DEVICE_ID` is optional, default value is 0. + +### Result + +Inference result is saved in current path, you can find result like this in acc.log file. + +```bash +'top1 acc': 0.71966 +'top5 acc': 0.90424 +``` + ## Model description ### [Performance](#contents) diff --git a/model_zoo/official/cv/mobilenetv1/ascend310_infer/CMakeLists.txt b/model_zoo/official/cv/mobilenetv1/ascend310_infer/CMakeLists.txt new file mode 100644 index 00000000000..ee3c8544734 --- /dev/null +++ b/model_zoo/official/cv/mobilenetv1/ascend310_infer/CMakeLists.txt @@ -0,0 +1,14 @@ +cmake_minimum_required(VERSION 3.14.1) +project(Ascend310Infer) +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 src/main.cc src/utils.cc) +target_link_libraries(main ${MS_LIB} ${MD_LIB} gflags) diff --git a/model_zoo/official/cv/mobilenetv1/ascend310_infer/build.sh b/model_zoo/official/cv/mobilenetv1/ascend310_infer/build.sh new file mode 100644 index 00000000000..285514e19f2 --- /dev/null +++ b/model_zoo/official/cv/mobilenetv1/ascend310_infer/build.sh @@ -0,0 +1,29 @@ +#!/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 [ -d out ]; then + rm -rf out +fi + +mkdir out +cd out || exit + +if [ -f "Makefile" ]; then + make clean +fi + +cmake .. \ + -DMINDSPORE_PATH="`pip3.7 show mindspore-ascend | grep Location | awk '{print $2"/mindspore"}' | xargs realpath`" +make diff --git a/model_zoo/official/cv/mobilenetv1/ascend310_infer/inc/utils.h b/model_zoo/official/cv/mobilenetv1/ascend310_infer/inc/utils.h new file mode 100644 index 00000000000..f8ae1e5b473 --- /dev/null +++ b/model_zoo/official/cv/mobilenetv1/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/mobilenetv1/ascend310_infer/src/main.cc b/model_zoo/official/cv/mobilenetv1/ascend310_infer/src/main.cc new file mode 100644 index 00000000000..d92a9b0cc57 --- /dev/null +++ b/model_zoo/official/cv/mobilenetv1/ascend310_infer/src/main.cc @@ -0,0 +1,181 @@ +/** + * 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 "include/api/model.h" +#include "include/api/context.h" +#include "include/api/types.h" +#include "include/api/serialization.h" +#include "include/dataset/vision_ascend.h" +#include "include/dataset/execute.h" +#include "include/dataset/transforms.h" +#include "include/dataset/vision.h" +#include "inc/utils.h" + +using mindspore::Context; +using mindspore::Serialization; +using mindspore::Model; +using mindspore::Status; +using mindspore::ModelType; +using mindspore::GraphCell; +using mindspore::kSuccess; +using mindspore::MSTensor; +using mindspore::dataset::Execute; +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; + + +DEFINE_string(mindir_path, "", "mindir path"); +DEFINE_string(dataset_name, "imagenet2012", "['cifar10', 'imagenet2012']"); +DEFINE_string(input0_path, ".", "input0 path"); +DEFINE_int32(device_id, 0, "device id"); + +int load_model(Model *model, std::vector *model_inputs, std::string mindir_path, int device_id) { + if (RealPath(mindir_path).empty()) { + std::cout << "Invalid mindir" << std::endl; + return 1; + } + + auto context = std::make_shared(); + auto ascend310 = std::make_shared(); + ascend310->SetDeviceID(device_id); + context->MutableDeviceInfo().push_back(ascend310); + mindspore::Graph graph; + Serialization::Load(mindir_path, ModelType::kMindIR, &graph); + + Status ret = model->Build(GraphCell(graph), context); + if (ret != kSuccess) { + std::cout << "ERROR: Build failed." << std::endl; + return 1; + } + + *model_inputs = model->GetInputs(); + if (model_inputs->empty()) { + std::cout << "Invalid model, inputs is empty." << std::endl; + return 1; + } + return 0; +} + +int main(int argc, char **argv) { + gflags::ParseCommandLineFlags(&argc, &argv, true); + + Model model; + std::vector model_inputs; + load_model(&model, &model_inputs, FLAGS_mindir_path, FLAGS_device_id); + + std::map costTime_map; + struct timeval start = {0}; + struct timeval end = {0}; + double startTimeMs; + double endTimeMs; + + if (FLAGS_dataset_name == "cifar10") { + auto input0_files = GetAllFiles(FLAGS_input0_path); + if (input0_files.empty()) { + std::cout << "ERROR: no input data." << std::endl; + return 1; + } + size_t size = input0_files.size(); + for (size_t i = 0; i < size; ++i) { + std::vector inputs; + std::vector outputs; + std::cout << "Start predict input files:" << input0_files[i] <(startTimeMs, endTimeMs)); + WriteResult(input0_files[i], outputs); + } + } else { + auto input0_files = GetAllInputData(FLAGS_input0_path); + if (input0_files.empty()) { + std::cout << "ERROR: no input data." << std::endl; + return 1; + } + size_t size = input0_files.size(); + for (size_t i = 0; i < size; ++i) { + for (size_t j = 0; j < input0_files[i].size(); ++j) { + std::vector inputs; + std::vector outputs; + std::cout << "Start predict input files:" << input0_files[i][j] <(); + SingleOp(ReadFileToTensor(input0_files[i][j]), imgDvpp.get()); + inputs.emplace_back(model_inputs[0].Name(), model_inputs[0].DataType(), model_inputs[0].Shape(), + imgDvpp->Data().get(), imgDvpp->DataSize()); + gettimeofday(&start, nullptr); + Status ret = model.Predict(inputs, &outputs); + gettimeofday(&end, nullptr); + if (ret != kSuccess) { + std::cout << "Predict " << input0_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(input0_files[i][j], outputs); + } + } + } + double average = 0.0; + int inferCount = 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; + std::stringstream timeCost; + timeCost << "NN inference cost average time: "<< average << " ms of infer_count " << inferCount << std::endl; + 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 << timeCost.str(); + fileStream.close(); + costTime_map.clear(); + return 0; +} diff --git a/model_zoo/official/cv/mobilenetv1/ascend310_infer/src/utils.cc b/model_zoo/official/cv/mobilenetv1/ascend310_infer/src/utils.cc new file mode 100644 index 00000000000..d71f388b83d --- /dev/null +++ b/model_zoo/official/cv/mobilenetv1/ascend310_infer/src/utils.cc @@ -0,0 +1,185 @@ +/** + * 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/mobilenetv1/postprocess.py b/model_zoo/official/cv/mobilenetv1/postprocess.py new file mode 100644 index 00000000000..10a4b97b749 --- /dev/null +++ b/model_zoo/official/cv/mobilenetv1/postprocess.py @@ -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 +# +# 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. +# ============================================================================ +"""postprocess for 310 inference""" +import os +import json +import argparse +import numpy as np +from mindspore.nn import Top1CategoricalAccuracy, Top5CategoricalAccuracy + + +parser = argparse.ArgumentParser(description="postprocess") +parser.add_argument("--result_dir", type=str, required=True, help="result files path.") +parser.add_argument("--label_dir", type=str, required=True, help="image file path.") +parser.add_argument('--dataset_name', type=str, choices=["cifar10", "imagenet2012"], default="imagenet2012") +args = parser.parse_args() + +def calcul_acc(lab, preds): + return sum(1 for x, y in zip(lab, preds) if x == y) / len(lab) + +if __name__ == '__main__': + batch_size = 1 + top1_acc = Top1CategoricalAccuracy() + rst_path = args.result_dir + label_list = [] + pred_list = [] + + if args.dataset_name == "cifar10": + from src.config import config1 as cfg + labels = np.load(args.label_dir, allow_pickle=True) + for idx, label in enumerate(labels): + f_name = os.path.join(rst_path, "mobilenetv1_data_bs" + str(cfg.batch_size) + "_" + str(idx) + "_0.bin") + pred = np.fromfile(f_name, np.float32) + pred = pred.reshape(cfg.batch_size, int(pred.shape[0] / cfg.batch_size)) + top1_acc.update(pred, labels[idx]) + print("acc: ", top1_acc.eval()) + else: + from src.config import config2 as cfg + top5_acc = Top5CategoricalAccuracy() + file_list = os.listdir(rst_path) + with open(args.label_dir, "r") as label: + labels = json.load(label) + for f in file_list: + label = f.split("_0.bin")[0] + ".JPEG" + label_list.append(labels[label]) + pred = np.fromfile(os.path.join(rst_path, f), np.float32) + pred = pred.reshape(batch_size, int(pred.shape[0] / batch_size)) + top1_acc.update(pred, [labels[label],]) + top5_acc.update(pred, [labels[label],]) + print("Top1 acc: ", top1_acc.eval()) + print("Top5 acc: ", top5_acc.eval()) diff --git a/model_zoo/official/cv/mobilenetv1/preprocess.py b/model_zoo/official/cv/mobilenetv1/preprocess.py new file mode 100644 index 00000000000..41ea01f235a --- /dev/null +++ b/model_zoo/official/cv/mobilenetv1/preprocess.py @@ -0,0 +1,73 @@ +# 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. +# ============================================================================ +"""preprocess""" +import os +import argparse +import json +import numpy as np +from src.dataset import create_dataset1 + +def create_label(result_path, dir_path): + print("[WARNING] Create imagenet label. Currently only use for Imagenet2012!") + dirs = os.listdir(dir_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(dir_path, file_dir)) + for f in files: + img_label[f] = i + total += len(files) + + json_file = os.path.join(result_path, "imagenet_label.json") + with open(json_file, "w+") as label: + json.dump(img_label, label) + + print("[INFO] Completed! Total {} data.".format(total)) + +parser = argparse.ArgumentParser('preprocess') +parser.add_argument('--dataset', type=str, choices=["cifar10", "imagenet2012"], default="imagenet2012") +parser.add_argument('--data_path', type=str, default='', help='eval data dir') +parser.add_argument('--result_path', type=str, default='./preprocess_Result/', help='result path') +args = parser.parse_args() + +if args.dataset == "cifar10": + from src.config import config1 as cfg +else: + from src.config import config2 as cfg + +args.per_batch_size = cfg.batch_size +#args.image_size = list(map(int, cfg.image_size.split(','))) + + +if __name__ == "__main__": + if args.dataset == "cifar10": + dataset = create_dataset1(args.data_path, False, args.per_batch_size) + img_path = os.path.join(args.result_path, "00_data") + os.makedirs(img_path) + label_list = [] + for idx, data in enumerate(dataset.create_dict_iterator(output_numpy=True)): + file_name = "mobilenetv1_data_bs" + str(args.per_batch_size) + "_" + str(idx) + ".bin" + file_path = os.path.join(img_path, file_name) + data["image"].tofile(file_path) + label_list.append(data["label"]) + np.save(os.path.join(args.result_path, "cifar10_label_ids.npy"), label_list) + print("=" * 20, "export bin files finished", "=" * 20) + else: + create_label(args.result_path, args.data_path) diff --git a/model_zoo/official/cv/mobilenetv1/scripts/run_infer_310.sh b/model_zoo/official/cv/mobilenetv1/scripts/run_infer_310.sh new file mode 100644 index 00000000000..46ce380f5e7 --- /dev/null +++ b/model_zoo/official/cv/mobilenetv1/scripts/run_infer_310.sh @@ -0,0 +1,140 @@ +#!/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 || $# -gt 3 ]]; then + echo "Usage: bash run_infer_310.sh [MINDIR_PATH] [DATASET_PATH] [DEVICE_ID] + DEVICE_ID is optional, it can be set by environment variable device_id, otherwise the value is zero" +exit 1 +fi + +get_real_path(){ + if [ "${1:0:1}" == "/" ]; then + echo "$1" + else + echo "$(realpath -m $PWD/$1)" + fi +} +model=$(get_real_path $1) + +dataset_path=$(get_real_path $2) +dataset_name="imagenet2012" +DVPP="CPU" + +device_id=0 +if [ $# == 3 ]; then + device_id=$3 +fi + +echo "mindir name: "$model +echo "dataset path: "$dataset_path +echo "device id: "$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=$ASCEND_HOME/opp +fi + +export SLOG_PRINT_to_STDOUT=0 +export GLOG_v=2 +export DUMP_GE_GRAPH=2 + + +export ASCEND_HOME=/usr/local/Ascend + +export PATH=$ASCEND_HOME/fwkacllib/ccec_compiler/bin:$ASCEND_HOME/fwkacllib/bin:$ASCEND_HOME/toolkit/bin:$PATH + +export LD_LIBRARY_PATH=/usr/local/lib/:/usr/local/fwkacllib/lib64:$ASCEND_HOME/driver/lib64:$ASCEND_HOME/add-ons:/usr/local/Ascend/toolkit/lib64:$LD_LIBRARY_PATH + +export PYTHONPATH=$ASCEND_HOME/fwkacllib/python/site-packages + +export PATH=/usr/local/python375/bin:$PATH +export NPU_HOST_LIB=/usr/local/Ascend/acllib/lib64/stub +export ASCEND_OPP_PATH=/usr/local/Ascend/opp +export ASCEND_AICPU_PATH=/usr/local/Ascend +export LD_LIBRARY_PATH=/usr/local/lib64/:$LD_LIBRARY_PATH + +function preprocess_data() +{ + if [ -d preprocess_Result ]; then + rm -rf ./preprocess_Result + fi + mkdir preprocess_Result + python3.7 ../preprocess.py --dataset=$dataset_name --data_path=$dataset_path --result_path=./preprocess_Result/ +} + +function compile_app() +{ + cd ../ascend310_infer/ || exit + bash build.sh &> build.log +} + +function infer() +{ + cd - || exit + if [ -d result_Files ]; then + rm -rf ./result_Files + fi + if [ -d time_Result ]; then + rm -rf ./time_Result + fi + mkdir result_Files + mkdir time_Result + + if [ "$DVPP" == "DVPP" ]; then + ../ascend310_infer/out/main --mindir_path=$model --dataset_name=$dataset_name --input0_path=$dataset_path --device_id=$device_id --cpu_dvpp=../ascend310_infer/aipp.cfg --image_height=256 --image_width=256 &> infer.log + else + ../ascend310_infer/out/main --mindir_path=$model --dataset_name=$dataset_name --input0_path=$dataset_path --device_id=$device_id &> infer.log + fi +} + +function cal_acc() +{ + + python3.7 ../postprocess.py --result_dir=./result_Files --label_dir=./preprocess_Result/imagenet_label.json &> acc.log + +} + + +preprocess_data +if [ $? -ne 0 ]; then + echo "preprocess dataset 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