From 7eadaaed1bd3e7ac7bd127acfc230eab35bbc110 Mon Sep 17 00:00:00 2001 From: zdc Date: Thu, 24 Jun 2021 17:12:55 +0800 Subject: [PATCH] ascend 310 inference --- model_zoo/official/cv/simclr/README.md | 31 ++++ .../cv/simclr/ascend310_infer/CMakeLists.txt | 14 ++ .../cv/simclr/ascend310_infer/build.sh | 30 ++++ .../cv/simclr/ascend310_infer/inc/utils.h | 32 +++++ .../cv/simclr/ascend310_infer/src/main.cc | 134 ++++++++++++++++++ .../cv/simclr/ascend310_infer/src/utils.cc | 129 +++++++++++++++++ model_zoo/official/cv/simclr/export.py | 50 ++++--- model_zoo/official/cv/simclr/postprocess.py | 47 ++++++ model_zoo/official/cv/simclr/preprocess.py | 51 +++++++ .../cv/simclr/scripts/run_infer_310.sh | 122 ++++++++++++++++ .../official/cv/simclr/src/simclr_model.py | 15 ++ 11 files changed, 633 insertions(+), 22 deletions(-) create mode 100644 model_zoo/official/cv/simclr/ascend310_infer/CMakeLists.txt create mode 100644 model_zoo/official/cv/simclr/ascend310_infer/build.sh create mode 100644 model_zoo/official/cv/simclr/ascend310_infer/inc/utils.h create mode 100644 model_zoo/official/cv/simclr/ascend310_infer/src/main.cc create mode 100644 model_zoo/official/cv/simclr/ascend310_infer/src/utils.cc create mode 100644 model_zoo/official/cv/simclr/postprocess.py create mode 100644 model_zoo/official/cv/simclr/preprocess.py create mode 100644 model_zoo/official/cv/simclr/scripts/run_infer_310.sh diff --git a/model_zoo/official/cv/simclr/README.md b/model_zoo/official/cv/simclr/README.md index 678f7553807..7c0a38dd618 100644 --- a/model_zoo/official/cv/simclr/README.md +++ b/model_zoo/official/cv/simclr/README.md @@ -175,8 +175,11 @@ Major parameters in linear_eval.py as follows: ``` The model checkpoint will be saved in the outputs directory. + ### [Evaluation Process](#contents) + #### Evaluation + Before running the command below, please check the checkpoint path used for evaluation. - running on Ascend @@ -192,6 +195,34 @@ Before running the command below, please check the checkpoint path used for eval 'Accuracy': 0.84505 ``` +## [Export MindIR](#contents) + +```shell +python export.py --ckpt_simclr_encoder [SIMCLR_CKPT_PATH] --ckpt_linear_classifier [CLASSIFIER_CKPT_PATH] --file_name [FILE_NAME] --file_format [FILE_FORMAT] +``` + +The parameters ckpt_simclr_encoder and ckpt_linear_classifier are required, +`EXPORT_FORMAT` should be in ["AIR", "MINDIR"] + +## [Inference Process](#contents) + +### Usage + +Before performing inference, the mindir file must be exported by export.py. Input files must be in bin format. + +```shell +# Ascend310 inference +bash run_infer_310.sh [SIMCLR_CLASSIFIER_MINDIR_PATH] [DATA_PATH] [NEED_PREPROCESS] [DEVICE_ID] +``` + +`DATA_PATH` is the path to the cifar10 evaluation dataset +`NEED_PREPROCESS` means weather need preprocess or not, it's value is 'y' or 'n' +`DEVICE_ID` is optional, default value is 0. + +#### result + +Inference result is saved in current path, you can find result in acc.log file. + ## [Model Description](#contents) ### [Performance](#contents) diff --git a/model_zoo/official/cv/simclr/ascend310_infer/CMakeLists.txt b/model_zoo/official/cv/simclr/ascend310_infer/CMakeLists.txt new file mode 100644 index 00000000000..ee3c8544734 --- /dev/null +++ b/model_zoo/official/cv/simclr/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/simclr/ascend310_infer/build.sh b/model_zoo/official/cv/simclr/ascend310_infer/build.sh new file mode 100644 index 00000000000..402068723ef --- /dev/null +++ b/model_zoo/official/cv/simclr/ascend310_infer/build.sh @@ -0,0 +1,30 @@ +#!/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/simclr/ascend310_infer/inc/utils.h b/model_zoo/official/cv/simclr/ascend310_infer/inc/utils.h new file mode 100644 index 00000000000..efebe03a8c1 --- /dev/null +++ b/model_zoo/official/cv/simclr/ascend310_infer/inc/utils.h @@ -0,0 +1,32 @@ +/** + * 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); +#endif diff --git a/model_zoo/official/cv/simclr/ascend310_infer/src/main.cc b/model_zoo/official/cv/simclr/ascend310_infer/src/main.cc new file mode 100644 index 00000000000..e9b92db9c12 --- /dev/null +++ b/model_zoo/official/cv/simclr/ascend310_infer/src/main.cc @@ -0,0 +1,134 @@ +/** + * 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/execute.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; + + +DEFINE_string(simclr_classifier_mindir_path, "", "simclr_classifier 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_simclr_classifier_mindir_path).empty()) { + std::cout << "Invalid simclr_classifier mindir path" << std::endl; + return 1; + } + + auto context = std::make_shared(); + auto ascend310 = std::make_shared(); + ascend310->SetDeviceID(FLAGS_device_id); + context->MutableDeviceInfo().push_back(ascend310); + mindspore::Graph simclr_classifier_graph; + Serialization::Load(FLAGS_simclr_classifier_mindir_path, ModelType::kMindIR, &simclr_classifier_graph); + + Model simclr_classifier_model; + Status ret = simclr_classifier_model.Build(GraphCell(simclr_classifier_graph), context); + if (ret != kSuccess) { + std::cout << "ERROR: Build simclr_classifier model failed." << std::endl; + return 1; + } + + std::vector simclr_classifier_model_inputs = simclr_classifier_model.GetInputs(); + if (simclr_classifier_model_inputs.empty()) { + std::cout << "Invalid model, inputs is empty." << std::endl; + return 1; + } + + auto input0_files = GetAllFiles(FLAGS_dataset_path); + if (input0_files.empty()) { + std::cout << "ERROR: no input data." << std::endl; + return 1; + } + + std::map costTime_map; + size_t size = input0_files.size(); + std::cout << "sizeļ¼š" << size << std::endl; + + for (size_t i = 0; i < size; ++i) { + struct timeval start = {0}; + struct timeval end = {0}; + double startTimeMs; + double endTimeMs; + std::vector model_inputs; + std::vector model_outputs; + std::cout << "Start predict input files:" << input0_files[i] << std::endl; + + auto input0 = ReadFileToTensor(input0_files[i]); + model_inputs.emplace_back(simclr_classifier_model_inputs[0].Name(), + simclr_classifier_model_inputs[0].DataType(), + simclr_classifier_model_inputs[0].Shape(), + input0.Data().get(), input0.DataSize()); + gettimeofday(&start, nullptr); + ret = simclr_classifier_model.Predict(model_inputs, &model_outputs); + if (ret != kSuccess) { + std::cout << "Predict" << input0_files[i] << "failed." << std::endl; + return 1; + } + + gettimeofday(&end, nullptr); + 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], model_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/simclr/ascend310_infer/src/utils.cc b/model_zoo/official/cv/simclr/ascend310_infer/src/utils.cc new file mode 100644 index 00000000000..c947e4d5f45 --- /dev/null +++ b/model_zoo/official/cv/simclr/ascend310_infer/src/utils.cc @@ -0,0 +1,129 @@ +/** + * 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 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/simclr/export.py b/model_zoo/official/cv/simclr/export.py index 268b7e55425..53984a39f9f 100644 --- a/model_zoo/official/cv/simclr/export.py +++ b/model_zoo/official/cv/simclr/export.py @@ -18,45 +18,51 @@ python export.py """ import argparse import numpy as np - -import mindspore as ms -from mindspore import context, Tensor, load_checkpoint, load_param_into_net, export - -from src.simclr_model import SimCLR +import mindspore.common.dtype as mstype +from mindspore import context, Tensor, nn, load_checkpoint, load_param_into_net, export +from src.simclr_model import SimCLR, SimCLR_Classifier from src.resnet import resnet50 as resnet parser = argparse.ArgumentParser(description='SimCLR') parser.add_argument("--device_id", type=int, default=0, help="Device id") -parser.add_argument("--batch_size", type=int, default=128, help="batch size") +parser.add_argument("--batch_size", type=int, default=1, help="batch size") parser.add_argument('--dataset_name', type=str, default='cifar10', choices=['cifar10'], help='Dataset, Currently only cifar10 is supported.') parser.add_argument('--device_target', type=str, default="Ascend", choices=['Ascend'], help='Device target, Currently only Ascend is supported.') -parser.add_argument("--ckpt_file", type=str, required=True, help="Checkpoint file path.") -parser.add_argument("--file_name", type=str, default="simclr", help="output file name.") -parser.add_argument("--file_format", type=str, choices=["AIR", "ONNX", "MINDIR"], default="AIR", help="file format") +parser.add_argument("--ckpt_simclr_encoder", type=str, required=True, help="Simclr encoder checkpoint file path.") +parser.add_argument("--ckpt_linear_classifier", type=str, required=True, help="Linear classifier checkpoint file path.") +parser.add_argument("--file_name", type=str, default="simclr_classifier", help="output file name.") +parser.add_argument("--file_format", type=str, choices=["AIR", "MINDIR"], default="MINDIR", help="file format") args_opt = parser.parse_args() context.set_context(mode=context.GRAPH_MODE, device_target=args_opt.device_target) if args_opt.device_target == "Ascend": context.set_context(device_id=args_opt.device_id) + if __name__ == '__main__': - if args_opt.dataset_name == 'cifar10': - width_multiplier = 1 - cifar_stem = True - projection_dimension = 128 - image_height = 32 - image_width = 32 - else: + if args_opt.dataset_name != 'cifar10': raise ValueError("dataset is not support.") + width_multiplier = 1 + cifar_stem = True + projection_dimension = 128 + class_num = 10 + image_height = 32 + image_width = 32 - base_net = resnet(1, width_multiplier=width_multiplier, cifar_stem=cifar_stem) - net = SimCLR(base_net, projection_dimension, base_net.end_point.in_channels) + encoder = resnet(1, width_multiplier=width_multiplier, cifar_stem=cifar_stem) + classifier = nn.Dense(encoder.end_point.in_channels, class_num) - param_dict = load_checkpoint(args_opt.ckpt_file) - load_param_into_net(net, param_dict) + simclr = SimCLR(encoder, projection_dimension, encoder.end_point.in_channels) + param_simclr = load_checkpoint(args_opt.ckpt_simclr_encoder) + load_param_into_net(simclr, param_simclr) - input_arr = Tensor(np.zeros([args_opt.batch_size, 3, image_height, image_width]), ms.float32) - export(net, input_arr, file_name=args_opt.file_name, file_format=args_opt.file_format) + param_classifier = load_checkpoint(args_opt.ckpt_linear_classifier) + load_param_into_net(classifier, param_classifier) + + # export SimCLR_Classifier network + simclr_classifier = SimCLR_Classifier(simclr.encoder, classifier) + input_data = Tensor(np.zeros([args_opt.batch_size, 3, image_height, image_width]), mstype.float32) + export(simclr_classifier, input_data, file_name=args_opt.file_name, file_format=args_opt.file_format) diff --git a/model_zoo/official/cv/simclr/postprocess.py b/model_zoo/official/cv/simclr/postprocess.py new file mode 100644 index 00000000000..5636c78a473 --- /dev/null +++ b/model_zoo/official/cv/simclr/postprocess.py @@ -0,0 +1,47 @@ +# 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. +# ============================================================================ +""" +#################SimCLR postprocess######################## +""" +import argparse +import os +import numpy as np + +parser = argparse.ArgumentParser(description='SimCLR Postprocess') +parser.add_argument('--label_dir', type=str, default='', help='label data directory.') +parser.add_argument('--result_dir', type=str, default="./result_Files", + help='infer result dir.') +parser.add_argument("--batch_size", type=int, default=1, help="batch size") +parser.add_argument('--class_num', type=int, default=10, help='dataset classification number, default is 10.') +args, _ = parser.parse_known_args() + + +if __name__ == '__main__': + + rst_path = args.result_dir + labels = np.load(args.label_dir) + top1 = 0 + total_data = len(os.listdir(rst_path)) + + for i in range(total_data): + file_name = os.path.join(rst_path, "cifar10_data_bs" + str(args.batch_size) + '_' + str(i) + '_0.bin') + output = np.fromfile(file_name, dtype=np.float32).reshape(args.batch_size, args.class_num) + for j in range(args.batch_size): + predict = np.argmax(output[j], axis=0) + y = labels[i][j] + if predict == y: + top1 += 1 + + print("result of Accuracy is: ", top1 / (total_data * args.batch_size)) diff --git a/model_zoo/official/cv/simclr/preprocess.py b/model_zoo/official/cv/simclr/preprocess.py new file mode 100644 index 00000000000..d457838171b --- /dev/null +++ b/model_zoo/official/cv/simclr/preprocess.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 +# +# 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 cifar-10################# +""" +import ast +import argparse +import os +import numpy as np +from src.dataset import create_dataset + +parser = argparse.ArgumentParser(description='preprocess cifar10') +parser.add_argument('--run_distribute', type=ast.literal_eval, default=False, help='Running distributed evaluation.') +parser.add_argument('--dataset_name', type=str, default='cifar10', help='Dataset, Currently only cifar10 is supported.') +parser.add_argument('--eval_dataset_path', type=str, default='./cifar/eval',\ + help='Dataset path for evaluating SimCLR.') +parser.add_argument('--result_path', type=str, default='./preprocess_Result/', help='result path') +parser.add_argument("--batch_size", type=int, default=1, help="batch size") +parser.add_argument('--use_norm', type=ast.literal_eval, default=False, help='Dataset normalize.') +args = parser.parse_args() + +if __name__ == '__main__': + + dataset = create_dataset(args, dataset_mode="eval_classifier") + img_path = os.path.join(args.result_path, "00_data") + if os.path.exists(img_path): + os.rmtree(img_path) + os.makedirs(img_path) + label_list = [] + + for idx, data in enumerate(dataset, start=0): + _, images, labels = data + file_name = "cifar10_data_bs" + str(args.batch_size) + "_" + str(idx) + ".bin" + file_path = img_path + "/" + file_name + images.asnumpy().tofile(file_path) + label_list.append(labels.asnumpy()) + + np.save(args.result_path + "label_ids.npy", label_list) + print("="*20, "export bin files finished", "="*20) diff --git a/model_zoo/official/cv/simclr/scripts/run_infer_310.sh b/model_zoo/official/cv/simclr/scripts/run_infer_310.sh new file mode 100644 index 00000000000..96981a1aa2f --- /dev/null +++ b/model_zoo/official/cv/simclr/scripts/run_infer_310.sh @@ -0,0 +1,122 @@ +#!/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 || $# -gt 4 ]]; then + echo "Usage: bash run_infer_310.sh [SIMCLR_CLASSIFIER_MINDIR_PATH] [DATA_PATH] [NEED_PREPROCESS] [DEVICE_ID] + NEED_PREPROCESS means weather need preprocess or not, it's value is 'y' or 'n'. + DEVICE_ID is optional, it can be set by environment variable device_id, otherwise the value is zero" +exit 1 +fi + +get_real_path(){ + if [ "${1:0:1}" == "/" ]; then + echo "$1" + else + echo "$(realpath -m $PWD/$1)" + fi +} + +model=$(get_real_path $1) + +data_path=$(get_real_path $2) + +if [ "$3" == "y" ] || [ "$3" == "n" ];then + need_preprocess=$3 +else + echo "weather need preprocess or not, it's value must be in [y, n]" + exit 1 +fi + +device_id=0 +if [ $# == 4 ]; then + device_id=$4 +fi + +echo "simclr_classifier mindir: "$model +echo "dataset path: "$data_path +echo "need preprocess: "$need_preprocess +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=$ASCEND_HOME/opp +fi + +function preprocess_data() +{ + if [ -d preprocess_Result ]; then + rm -rf ./preprocess_Result + fi + mkdir preprocess_Result + python3.7 ../preprocess.py --eval_dataset_path=$data_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 + ../ascend310_infer/out/main --simclr_classifier_mindir_path=$model --dataset_path=./preprocess_Result/00_data --device_id=$device_id &> infer.log +} + +function cal_acc() +{ + python3.7 ../postprocess.py --result_dir=./result_Files --label_dir=./preprocess_Result/label_ids.npy &> acc.log +} + +if [ $need_preprocess == "y" ]; then + preprocess_data + if [ $? -ne 0 ]; then + echo "preprocess dataset failed" + exit 1 + fi +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 \ No newline at end of file diff --git a/model_zoo/official/cv/simclr/src/simclr_model.py b/model_zoo/official/cv/simclr/src/simclr_model.py index 0475eb7de63..5d6c7585740 100644 --- a/model_zoo/official/cv/simclr/src/simclr_model.py +++ b/model_zoo/official/cv/simclr/src/simclr_model.py @@ -51,3 +51,18 @@ class SimCLR(nn.Cell): def inference(self, x): h = self.encoder(x) return h + +class SimCLR_Classifier(nn.Cell): + """ + SimCLR with Classifier. + """ + def __init__(self, encoder, classifier): + super(SimCLR_Classifier, self).__init__() + self.encoder = encoder + self.classifier = classifier + self.softmax = nn.Softmax() + + def construct(self, x): + y = self.encoder(x) + z = self.classifier(y) + return self.softmax(z)