From 976123fad219a37b66aaf302834f0d21659c69fb Mon Sep 17 00:00:00 2001 From: andyjpaddle <87074272+andyjpaddle@users.noreply.github.com> Date: Tue, 8 Mar 2022 10:22:50 +0800 Subject: [PATCH] add Windows TIPC (#5484) * add windows tipc * add windows tipc * update win tipc doc Co-authored-by: MissPenguin --- .../Step6/test_tipc/README.md | 11 +- .../win_train_infer_python.txt | 32 ++ .../test_windows_train_inference_python.md | 96 +++++ .../test_train_infer_python.md | 12 +- .../images/autolog_win_demo.png | Bin 0 -> 1082372 bytes .../test_windows_train_infer_python.md | 354 +++++++++++++++++- 6 files changed, 489 insertions(+), 16 deletions(-) create mode 100644 tutorials/mobilenetv3_prod/Step6/test_tipc/configs/mobilenet_v3_small/win_train_infer_python.txt create mode 100644 tutorials/mobilenetv3_prod/Step6/test_tipc/docs/test_windows_train_inference_python.md create mode 100644 tutorials/tipc/windows_train_infer_python/images/autolog_win_demo.png diff --git a/tutorials/mobilenetv3_prod/Step6/test_tipc/README.md b/tutorials/mobilenetv3_prod/Step6/test_tipc/README.md index e80dc3ab..7250217a 100644 --- a/tutorials/mobilenetv3_prod/Step6/test_tipc/README.md +++ b/tutorials/mobilenetv3_prod/Step6/test_tipc/README.md @@ -15,11 +15,10 @@ - 模型压缩:包括裁剪、离线/在线量化、蒸馏。 - 其他预测部署:包括Paddle Inference C++预测、Paddle Serving部署、Paddle-Lite部署等。 -| 算法论文 | 模型名称 | 模型类型 | 基础
训练预测 | 更多
训练方式 | 模型压缩 | 其他预测部署 | -| :--- | :--- | :----: | :--------: | :---- | :---- | :---- | -| MobileNetV3 | mobilenet_v3_small | 分类 | 支持 | 混合精度
| - | - | -| MobileNetV3 | mobilenet_v3_small | 分类 | 支持 | - | PACT量化训练
| - | -| MobileNetV3 | mobilenet_v3_small | 分类 | 支持 | - | 离线量化训练
| - | +| 算法论文 | 模型名称 | 模型类型 | 基础
训练预测 | 更多
训练方式 | 更多
部署方式 | Slim训练部署 | 更多
训练环境 | +| :--- | :--- | :----: | :--------: | :---- | :---- | :---- | :---- | +| MobileNetV3 | mobilenet_v3_small | 分类 | 支持 | 混合精度 | | PACT量化
离线量化 | Windows | + ## 3. 测试工具简介 @@ -77,4 +76,4 @@ test_tipc - [Linux XPU2 基础训练推理测试] - [Linux DCU 基础训练推理测试] - [Linux NPU 基础训练推理测试] - - [Windows GPU/CPU 基础训练推理测试] + - [Windows GPU/CPU 基础训练推理测试](docs/test_windows_train_inference_python.md) diff --git a/tutorials/mobilenetv3_prod/Step6/test_tipc/configs/mobilenet_v3_small/win_train_infer_python.txt b/tutorials/mobilenetv3_prod/Step6/test_tipc/configs/mobilenet_v3_small/win_train_infer_python.txt new file mode 100644 index 00000000..144a632e --- /dev/null +++ b/tutorials/mobilenetv3_prod/Step6/test_tipc/configs/mobilenet_v3_small/win_train_infer_python.txt @@ -0,0 +1,32 @@ +===========================train_params=========================== +model_name:mobilenet_v3_small +python:python +gpu_list:0 +use-gpu:True +--epochs:lite_train_lite_infer=5|whole_train_whole_infer=90 +--output-dir:./output/ +--batch-size:lite_train_lite_infer=4|whole_train_whole_infer=128 +--pretrained:null +train_model_name:latest.pdparams +--data-path:./lite_data +## +trainer:norm_train +norm_train:train.py --workers=0 +## +===========================eval_params=========================== +eval:train.py --test-only --workers=0 +## +===========================infer_params=========================== +--save-inference-dir:./output/mobilenet_v3_small_infer/ +--pretrained: +norm_export:tools/export_model.py --model=mobilenet_v3_small +## +train_model:./mobilenet_v3_small_pretrained.pdparams +infer_export:tools/export_model.py --model=mobilenet_v3_small +## +inference:deploy/inference_python/infer.py +--use-gpu:True|False +--batch-size:1 +--model-dir:./output/mobilenet_v3_small_infer/ +--img-path:./images/demo.jpg +--benchmark:True \ No newline at end of file diff --git a/tutorials/mobilenetv3_prod/Step6/test_tipc/docs/test_windows_train_inference_python.md b/tutorials/mobilenetv3_prod/Step6/test_tipc/docs/test_windows_train_inference_python.md new file mode 100644 index 00000000..e1e7631d --- /dev/null +++ b/tutorials/mobilenetv3_prod/Step6/test_tipc/docs/test_windows_train_inference_python.md @@ -0,0 +1,96 @@ +# Windows GPU/CPU 基础训练推理测试 + +Windows GPU/CPU 基础训练推理测试的主程序为`test_train_inference_python.sh`,可以测试基于Python的模型训练、评估、推理等基本功能。 +在Windows平台上执行命令和Linux平台略有不同,主要体现在:下载与解压数据、设置环境变量、数据加载等方面。此外Windows平台只支持单卡的训练与预测,DataLoader只支持单进程模式,因此需要设置 workers 为0。 + +## 1. 测试结论汇总 + +- 训练相关: + +| 算法名称 | 模型名称 | 单机单卡 | 单机多卡 | +| :----: | :----: | :----: | :----: | +| MobileNetV3 | mobilenet_v3_small | 正常训练 | 不支持 | + + +- 推理相关: + +| 算法名称 | 模型名称 | device_CPU | device_GPU | batchsize | +| :----: | :----: | :----: | :----: | :----: | +| MobileNetV3 | mobilenet_v3_small | 支持 | 支持 | 1 | + + +## 2. 测试流程 + +### 2.1 准备数据 + +用于基础训练推理测试的数据位于`test_images/lite_data.tar`,直接解压即可(如果已经解压完成,则无需运行下面的命令)。 + +```bash +python -c "import shutil;shutil.unpack_archive('test_images/lite_data.tar', extract_dir='./',format='tar')" +``` + +执行该命令后,会在当前路径下解压出对应的数据集文件夹`lite_data` + +### 2.2 准备预训练模型 + +使用下面的命令下载 MobileNetV3 预训练模型,便于后续测试模型评估、预测、推理部署等功能。 + +```bash +pip install wget +python -c "import wget;wget.download('https://paddle-model-ecology.bj.bcebos.com/model/mobilenetv3_reprod/mobilenet_v3_small_pretrained.pdparams')" +``` + +### 2.3 准备环境 + +- 安装PaddlePaddle:如果您已经安装了2.2或者以上版本的paddlepaddle,那么无需运行下面的命令安装paddlepaddle。 + ``` + # 需要安装2.2及以上版本的Paddle + # 安装GPU版本的Paddle + pip install paddlepaddle-gpu==2.2.0 + # 安装CPU版本的Paddle + pip install paddlepaddle==2.2.0 + ``` + +- 安装依赖 + ``` + pip install -r requirements.txt + ``` + +- 安装AutoLog(规范化日志输出工具) + ``` + pip install https://paddleocr.bj.bcebos.com/libs/auto_log-1.2.0-py3-none-any.whl + ``` +- 安装 Git + 在windows下想要执行shell脚本,需要使用到"Git Bash",所以需要先安装Git,具体可百度搜索安装方法。 + +### 2.4 功能测试 + +测试方法如下所示,希望测试不同的模型文件,只需更换为自己的参数配置文件,即可完成对应模型的测试。 + +```bash +bash test_tipc/test_train_inference_python.sh ${your_params_file} lite_train_lite_infer +``` + +以`mobilenet_v3_small`的`Windows GPU/CPU 基础训练推理测试`为例,命令如下所示。 + +```bash +bash test_tipc/test_train_inference_python.sh test_tipc/configs/mobilenet_v3_small/win_train_infer_python.txt lite_train_lite_infer +``` + +输出结果如下,表示命令运行成功。 + +```bash +Run successfully with command - python train.py --workers=0 --output-dir=./log/mobilenet_v3_small/lite_train_lite_infer/norm_train_gpus_0 --epochs=5 --batch-size=4! +...... +Run successfully with command - python deploy/inference_python/infer.py --use-gpu=False --model-dir=./log/mobilenet_v3_small/lite_train_lite_infer/norm_train_gpus_0 --batch-size=1 --benchmark=True > ./log/mobilenet_v3_small/lite_train_lite_infer/python_infer_cpu_batchsize_1.log 2>&1 ! +``` + +在开启benchmark参数时,可以得到测试的详细数据,包含运行环境信息(系统版本、CUDA版本、CUDNN版本、驱动版本),Paddle版本信息,参数设置信息(运行设备、线程数、是否开启内存优化等),模型信息(模型名称、精度),数据信息(batchsize、是否为动态shape等),性能信息(CPU,GPU的占用、运行耗时、预处理耗时、推理耗时、后处理耗时),如下图所示 + +
+ +
+ +该信息可以在运行log中查看,以`mobilenet_v3_small`为例,log位置在`./log/mobilenet_v3_small/lite_train_lite_infer/python_infer_cpu_batchsize_1.log`。 + +如果运行失败,也会在终端中输出运行失败的日志信息以及对应的运行命令。可以基于该命令,分析运行失败的原因。 diff --git a/tutorials/tipc/train_infer_python/test_train_infer_python.md b/tutorials/tipc/train_infer_python/test_train_infer_python.md index 7abb4e86..0253e9f8 100644 --- a/tutorials/tipc/train_infer_python/test_train_infer_python.md +++ b/tutorials/tipc/train_infer_python/test_train_infer_python.md @@ -7,12 +7,12 @@ - [2.1 命令解析](#2.1) - [2.2 配置文件和运行命令映射解析](#2.2) - [3. 基本训练推理功能测试开发](#3) - - [2.1 准备待测试的命令](#3.1) - - [2.2 准备数据与环境](#3.2) - - [2.3 准备开发所需脚本](#3.3) - - [2.4 填写配置文件](#3.4) - - [2.5 验证配置正确性](#3.5) - - [2.6 撰写说明文档](#3.6) + - [3.1 准备待测试的命令](#3.1) + - [3.2 准备数据与环境](#3.2) + - [3.3 准备开发所需脚本](#3.3) + - [3.4 填写配置文件](#3.4) + - [3.5 验证配置正确性](#3.5) + - [3.6 撰写说明文档](#3.6) - [4. 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