From e063925b9c903faad4f78fe6cf49d553ba51a231 Mon Sep 17 00:00:00 2001 From: unknown Date: Tue, 23 Mar 2021 11:17:32 +0800 Subject: [PATCH] deeplabv3 & ssd & lstm new interface modified: model_zoo/official/cv/ssd/README_CN.md --- .../cv/deeplabv3/ascend310_infer/build.sh | 6 +-- .../cv/deeplabv3/ascend310_infer/src/main.cc | 26 +++++----- .../cv/deeplabv3/scripts/run_infer_310.sh | 2 +- model_zoo/official/cv/ssd/README.md | 2 +- model_zoo/official/cv/ssd/README_CN.md | 47 +++++++++++++++++++ .../official/cv/ssd/ascend310_infer/build.sh | 6 +-- .../cv/ssd/ascend310_infer/src/main.cc | 19 ++++---- .../official/cv/ssd/scripts/run_infer_310.sh | 4 +- model_zoo/official/nlp/lstm/export.py | 33 +++++++++++-- 9 files changed, 109 insertions(+), 36 deletions(-) diff --git a/model_zoo/official/cv/deeplabv3/ascend310_infer/build.sh b/model_zoo/official/cv/deeplabv3/ascend310_infer/build.sh index 6825591942..76edaa8ac3 100644 --- a/model_zoo/official/cv/deeplabv3/ascend310_infer/build.sh +++ b/model_zoo/official/cv/deeplabv3/ascend310_infer/build.sh @@ -13,11 +13,11 @@ # See the License for the specific language governing permissions and # limitations under the License. # ============================================================================ -if [ ! -d out ]; then - mkdir out +if [ -d out ]; then + rm -rf out fi -cd out +mkdir out && cd out if [ -f "Makefile" ]; then make clean diff --git a/model_zoo/official/cv/deeplabv3/ascend310_infer/src/main.cc b/model_zoo/official/cv/deeplabv3/ascend310_infer/src/main.cc index cc2c65877a..b732159c3f 100644 --- a/model_zoo/official/cv/deeplabv3/ascend310_infer/src/main.cc +++ b/model_zoo/official/cv/deeplabv3/ascend310_infer/src/main.cc @@ -1,12 +1,12 @@ /** * 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. @@ -31,10 +31,9 @@ #include "include/minddata/dataset/include/execute.h" #include "../inc/utils.h" -using mindspore::GlobalContext; +using mindspore::Context; using mindspore::Serialization; using mindspore::Model; -using mindspore::ModelContext; using mindspore::Status; using mindspore::ModelType; using mindspore::GraphCell; @@ -127,15 +126,18 @@ int main(int argc, char **argv) { std::cout << "Invalid fusion switch path" << 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(); + auto context = std::make_shared(); + auto ascend310 = std::make_shared(); + ascend310->SetDeviceID(FLAGS_device_id); + context->MutableDeviceInfo().push_back(ascend310); + mindspore::Graph graph; + Serialization::Load(FLAGS_mindir_path, ModelType::kMindIR, &graph); + if (!FLAGS_fusion_switch_path.empty()) { - ModelContext::SetFusionSwitchConfigPath(model_context, FLAGS_fusion_switch_path); + ascend310->SetFusionSwitchConfigPath(FLAGS_fusion_switch_path); } - Model model(GraphCell(graph), model_context); - Status ret = model.Build(); + Model model; + Status ret = model.Build(GraphCell(graph), context); if (ret != kSuccess) { std::cout << "ERROR: Build failed." << std::endl; return 1; diff --git a/model_zoo/official/cv/deeplabv3/scripts/run_infer_310.sh b/model_zoo/official/cv/deeplabv3/scripts/run_infer_310.sh index fd379a47ca..3b7c47a7bb 100644 --- a/model_zoo/official/cv/deeplabv3/scripts/run_infer_310.sh +++ b/model_zoo/official/cv/deeplabv3/scripts/run_infer_310.sh @@ -15,7 +15,7 @@ # ============================================================================ if [[ $# -lt 4 || $# -gt 5 ]]; then - echo "Usage: sh run_infer_310.sh [MINDIR_PATH] [DATA_PATH] [DATA_ROOT] [DATA_LIST] [DEVICE_ID] + echo "Usage: bash run_infer_310.sh [MINDIR_PATH] [DATA_PATH] [DATA_ROOT] [DATA_LIST] [DEVICE_ID] DEVICE_ID is optional, it can be set by environment variable device_id, otherwise the value is zero" exit 1 fi diff --git a/model_zoo/official/cv/ssd/README.md b/model_zoo/official/cv/ssd/README.md index 31525f3214..3e30df696e 100644 --- a/model_zoo/official/cv/ssd/README.md +++ b/model_zoo/official/cv/ssd/README.md @@ -406,7 +406,7 @@ The ckpt_file parameter is required, ### Infer on Ascend310 -Before performing inference, the mindir file must bu exported by export script on the 910 environment. We only provide an example of inference using MINDIR model. +Before performing inference, the mindir file must bu exported by `export.py` script. We only provide an example of inference using MINDIR model. Current batch_Size can only be set to 1. The precision calculation process needs about 70G+ memory space, otherwise the process will be killed for execeeding memory limits. ```shell diff --git a/model_zoo/official/cv/ssd/README_CN.md b/model_zoo/official/cv/ssd/README_CN.md index 48527dfd35..ed66491981 100644 --- a/model_zoo/official/cv/ssd/README_CN.md +++ b/model_zoo/official/cv/ssd/README_CN.md @@ -17,6 +17,10 @@ - [评估过程](#评估过程) - [Ascend处理器环境评估](#ascend处理器环境评估) - [GPU处理器环境评估](#gpu处理器环境评估) + - [推理过程](#推理过程) + - [导出MindIR](#导出mindir) + - [在Ascend310执行推理](#在ascend310执行推理) + - [结果](#结果) - [模型描述](#模型描述) - [性能](#性能) - [评估性能](#评估性能) @@ -312,6 +316,49 @@ Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.686 mAP: 0.2244936111705981 ``` +## 推理过程 + +### [导出MindIR](#contents) + +```shell +python export.py --ckpt_file [CKPT_PATH] --file_name [FILE_NAME] --file_format [FILE_FORMAT] +``` + +参数ckpt_file为必填项， +`EXPORT_FORMAT` 必须在 ["AIR", "MINDIR"]中选择。 + +### 在Ascend310执行推理 + +在执行推理前，mindir文件必须通过`export.py`脚本导出。以下展示了使用minir模型执行推理的示例。 +目前仅支持batch_Size为1的推理。精度计算过程需要70G+的内存，否则进程将会因为超出内存被系统终止。 + +```shell +# Ascend310 inference +bash run_infer_310.sh [MINDIR_PATH] [DATA_PATH] [DVPP] [DEVICE_ID] +``` + +- `DVPP` 为必填项，需要在["DVPP", "CPU"]选择，大小写均可。需要注意的是ssd_vgg16执行推理的图片尺寸为[300, 300]，由于DVPP硬件限制宽为16整除，高为2整除，因此，这个网络需要通过CPU算子对图像进行前处理。 +- `DEVICE_ID` 可选，默认值为0。 + +### 结果 + +推理结果保存在脚本执行的当前路径，你可以在acc.log中看到以下精度计算结果。 + +```bash +Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.339 +Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.521 +Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.370 +Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.168 +Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.386 +Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.461 +Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.310 +Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.481 +Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.515 +Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.293 +Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.659 +mAP: 0.33880018942412393 +``` + # 模型描述 ## 性能 diff --git a/model_zoo/official/cv/ssd/ascend310_infer/build.sh b/model_zoo/official/cv/ssd/ascend310_infer/build.sh index 6825591942..76edaa8ac3 100644 --- a/model_zoo/official/cv/ssd/ascend310_infer/build.sh +++ b/model_zoo/official/cv/ssd/ascend310_infer/build.sh @@ -13,11 +13,11 @@ # See the License for the specific language governing permissions and # limitations under the License. # ============================================================================ -if [ ! -d out ]; then - mkdir out +if [ -d out ]; then + rm -rf out fi -cd out +mkdir out && cd out if [ -f "Makefile" ]; then make clean diff --git a/model_zoo/official/cv/ssd/ascend310_infer/src/main.cc b/model_zoo/official/cv/ssd/ascend310_infer/src/main.cc index b696d79f8f..ca67ddb314 100644 --- a/model_zoo/official/cv/ssd/ascend310_infer/src/main.cc +++ b/model_zoo/official/cv/ssd/ascend310_infer/src/main.cc @@ -32,10 +32,9 @@ #include "include/minddata/dataset/include/vision.h" #include "inc/utils.h" -using mindspore::GlobalContext; +using mindspore::Context; using mindspore::Serialization; using mindspore::Model; -using mindspore::ModelContext; using mindspore::Status; using mindspore::ModelType; using mindspore::GraphCell; @@ -64,21 +63,23 @@ int main(int argc, char **argv) { 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(); + auto context = std::make_shared(); + auto ascend310 = std::make_shared(); + ascend310->SetDeviceID(FLAGS_device_id); + context->MutableDeviceInfo().push_back(ascend310); + mindspore::Graph graph; + Serialization::Load(FLAGS_mindir_path, ModelType::kMindIR, &graph); if (FLAGS_cpu_dvpp == "DVPP") { if (RealPath(FLAGS_aipp_path).empty()) { std::cout << "Invalid aipp path" << std::endl; return 1; } else { - ModelContext::SetInsertOpConfigPath(model_context, FLAGS_aipp_path); + ascend310->SetInsertOpConfigPath(FLAGS_aipp_path); } } - Model model(GraphCell(graph), model_context); - Status ret = model.Build(); + Model model; + Status ret = model.Build(GraphCell(graph), context); if (ret != kSuccess) { std::cout << "ERROR: Build failed." << std::endl; return 1; diff --git a/model_zoo/official/cv/ssd/scripts/run_infer_310.sh b/model_zoo/official/cv/ssd/scripts/run_infer_310.sh index 2cc265ca7a..998a16140f 100644 --- a/model_zoo/official/cv/ssd/scripts/run_infer_310.sh +++ b/model_zoo/official/cv/ssd/scripts/run_infer_310.sh @@ -15,7 +15,7 @@ # ============================================================================ if [[ $# -lt 3 || $# -gt 4 ]]; then - echo "Usage: sh run_infer_310.sh [MINDIR_PATH] [DATA_PATH] [DVPP] [DEVICE_ID] + echo "Usage: bash run_infer_310.sh [MINDIR_PATH] [DATA_PATH] [DVPP] [DEVICE_ID] DVPP is mandatory, and must choose from [DVPP|CPU], it's case-insensitive DEVICE_ID is optional, it can be set by environment variable device_id, otherwise the value is zero" exit 1 @@ -59,7 +59,7 @@ fi function compile_app() { cd ../ascend310_infer - sh build.sh &> build.log + bash build.sh &> build.log } function infer() diff --git a/model_zoo/official/nlp/lstm/export.py b/model_zoo/official/nlp/lstm/export.py index 17c741c968..2768a386fd 100644 --- a/model_zoo/official/nlp/lstm/export.py +++ b/model_zoo/official/nlp/lstm/export.py @@ -1,4 +1,4 @@ -# Copyright 2020 Huawei Technologies Co., Ltd +# Copyright 2020-2021 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. @@ -21,9 +21,9 @@ import os import numpy as np -from mindspore import Tensor +from mindspore import Tensor, context from mindspore import export, load_checkpoint, load_param_into_net -from src.config import lstm_cfg as cfg +from src.config import lstm_cfg, lstm_cfg_ascend from src.lstm import SentimentNet if __name__ == '__main__': @@ -31,9 +31,32 @@ if __name__ == '__main__': parser.add_argument('--preprocess_path', type=str, default='./preprocess', help='path where the pre-process data is stored.') parser.add_argument('--ckpt_file', type=str, required=True, help='lstm ckpt file.') + parser.add_argument("--device_id", type=int, default=0, help="Device id") + parser.add_argument("--file_name", type=str, default="lstm", help="output file name.") + parser.add_argument('--file_format', type=str, choices=["AIR", "MINDIR"], default='AIR', help='file format') + parser.add_argument('--device_target', type=str, default="Ascend", choices=['GPU', 'CPU', 'Ascend'], + help='the target device to run, support "GPU", "CPU". Default: "Ascend".') args = parser.parse_args() + context.set_context( + mode=context.GRAPH_MODE, + save_graphs=False, + device_target=args.device_target, + device_id=args.device_id) + + if args.device_target == 'Ascend': + cfg = lstm_cfg_ascend + else: + cfg = lstm_cfg + embedding_table = np.loadtxt(os.path.join(args.preprocess_path, "weight.txt")).astype(np.float32) + + if args.device_target == 'Ascend': + pad_num = int(np.ceil(cfg.embed_size / 16) * 16 - cfg.embed_size) + if pad_num > 0: + embedding_table = np.pad(embedding_table, [(0, 0), (0, pad_num)], 'constant') + cfg.embed_size = int(np.ceil(cfg.embed_size / 16) * 16) + network = SentimentNet(vocab_size=embedding_table.shape[0], embed_size=cfg.embed_size, num_hiddens=cfg.num_hiddens, @@ -46,5 +69,5 @@ if __name__ == '__main__': param_dict = load_checkpoint(args.ckpt_file) load_param_into_net(network, param_dict) - input_arr = Tensor(np.random.uniform(0.0, 1e5, size=[64, 500]).astype(np.int32)) - export(network, input_arr, file_name="lstm", file_format="MINDIR") + input_arr = Tensor(np.random.uniform(0.0, 1e5, size=[cfg.batch_size, 500]).astype(np.int32)) + export(network, input_arr, file_name=args.file_name, file_format=args.file_format)