From 79bbc286aaec0ca583bb7b5b2f615529785edf6a Mon Sep 17 00:00:00 2001 From: stephon Date: Wed, 10 Nov 2021 11:38:22 +0000 Subject: [PATCH] add test_tipc --- test_tipc/README.md | 67 ++++ test_tipc/common_func.sh | 65 ++++ .../train_infer_python.txt | 52 +++ ...u_fleet_amp_infer_python_linux_gpu_cpu.txt | 52 +++ ..._normal_amp_infer_python_linux_gpu_cpu.txt | 52 +++ .../config/ResNet50_vd/train_infer_python.txt | 52 +++ ...u_fleet_amp_infer_python_linux_gpu_cpu.txt | 52 +++ ..._normal_amp_infer_python_linux_gpu_cpu.txt | 52 +++ test_tipc/docs/guide.png | Bin 0 -> 141626 bytes test_tipc/docs/test.png | Bin 0 -> 229200 bytes test_tipc/prepare.sh | 153 ++++++++ test_tipc/test_train_inference_python.sh | 326 ++++++++++++++++++ 12 files changed, 923 insertions(+) create mode 100644 test_tipc/README.md create mode 100644 test_tipc/common_func.sh create mode 100644 test_tipc/config/MobileNetV3_large_x1_0/train_infer_python.txt create mode 100644 test_tipc/config/MobileNetV3_large_x1_0/train_linux_gpu_fleet_amp_infer_python_linux_gpu_cpu.txt create mode 100644 test_tipc/config/MobileNetV3_large_x1_0/train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt create mode 100644 test_tipc/config/ResNet50_vd/train_infer_python.txt create mode 100644 test_tipc/config/ResNet50_vd/train_linux_gpu_fleet_amp_infer_python_linux_gpu_cpu.txt create mode 100644 test_tipc/config/ResNet50_vd/train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt create mode 100644 test_tipc/docs/guide.png create mode 100644 test_tipc/docs/test.png create mode 100644 test_tipc/prepare.sh create mode 100644 test_tipc/test_train_inference_python.sh diff --git a/test_tipc/README.md b/test_tipc/README.md new file mode 100644 index 00000000..59391a43 --- /dev/null +++ b/test_tipc/README.md @@ -0,0 +1,67 @@ + +# 飞桨训推一体认证 + +## 1. 简介 + +飞桨除了基本的模型训练和预测,还提供了支持多端多平台的高性能推理部署工具。本文档提供了PaddleOCR中所有模型的飞桨训推一体认证 (Training and Inference Pipeline Certification(TIPC)) 信息和测试工具,方便用户查阅每种模型的训练推理部署打通情况,并可以进行一键测试。 + +
+ +
+ +## 2. 汇总信息 + +打通情况汇总如下,已填写的部分表示可以使用本工具进行一键测试,未填写的表示正在支持中。 + +**字段说明:** +- 基础训练预测:包括模型训练、Paddle Inference Python预测。 +- 更多训练方式:包括多机多卡、混合精度。 +- 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。 + +更详细的mkldnn、Tensorrt等预测加速相关功能的支持情况可以查看各测试工具的[更多教程](#more)。 + +## 3. 一键测试工具使用 +### 目录介绍 +./test_tipc/ +├── common_func.sh +├── config +│ ├── MobileNetV3_large_x1_0 +│ │ ├── train_infer_python.txt +│ │ ├── train_linux_gpu_fleet_amp_infer_python_linux_gpu_cpu.txt +│ │ └── train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt +│ └── ResNet50_vd +│ ├── train_infer_python.txt +│ ├── train_linux_gpu_fleet_amp_infer_python_linux_gpu_cpu.txt +│ └── train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt +├── docs +│ ├── guide.png +│ └── test.png +├── prepare.sh +├── README.md +├── results +└── test_train_inference_python.sh + +### 测试流程 +使用本工具,可以测试不同功能的支持情况,以及预测结果是否对齐,测试流程如下: +
+ +
+ +1. 运行prepare.sh准备测试所需数据和模型; +2. 运行要测试的功能对应的测试脚本`test_*.sh`,产出log,由log可以看到不同配置是否运行成功; +3. 用`compare_results.py`对比log中的预测结果和预存在results目录下的结果,判断预测精度是否符合预期(在误差范围内)。 + +其中,有4个测试主程序,功能如下: +- `test_train_inference_python.sh`:测试基于Python的模型训练、评估、推理等基本功能,包括裁剪、量化、蒸馏。 +- `test_inference_cpp.sh`:测试基于C++的模型推理。 +- `test_serving.sh`:测试基于Paddle Serving的服务化部署功能。 +- `test_lite.sh`:测试基于Paddle-Lite的端侧预测部署功能。 + + +#### 更多教程 +各功能测试中涉及混合精度、裁剪、量化等训练相关,及mkldnn、Tensorrt等多种预测相关参数配置,请点击下方相应链接了解更多细节和使用教程: +[test_train_inference_python 使用](docs/test_train_inference_python.md) +[test_inference_cpp 使用](docs/test_inference_cpp.md) +[test_serving 使用](docs/test_serving.md) +[test_lite 使用](docs/test_lite.md) diff --git a/test_tipc/common_func.sh b/test_tipc/common_func.sh new file mode 100644 index 00000000..3f0fa66b --- /dev/null +++ b/test_tipc/common_func.sh @@ -0,0 +1,65 @@ +#!/bin/bash + +function func_parser_key(){ + strs=$1 + IFS=":" + array=(${strs}) + tmp=${array[0]} + echo ${tmp} +} + +function func_parser_value(){ + strs=$1 + IFS=":" + array=(${strs}) + tmp=${array[1]} + echo ${tmp} +} + +function func_set_params(){ + key=$1 + value=$2 + if [ ${key}x = "null"x ];then + echo " " + elif [[ ${value} = "null" ]] || [[ ${value} = " " ]] || [ ${#value} -le 0 ];then + echo " " + else + echo "${key}=${value}" + fi +} + +function func_parser_params(){ + strs=$1 + IFS=":" + array=(${strs}) + key=${array[0]} + tmp=${array[1]} + IFS="|" + res="" + for _params in ${tmp[*]}; do + IFS="=" + array=(${_params}) + mode=${array[0]} + value=${array[1]} + if [[ ${mode} = ${MODE} ]]; then + IFS="|" + #echo $(func_set_params "${mode}" "${value}") + echo $value + break + fi + IFS="|" + done + echo ${res} +} + +function status_check(){ + last_status=$1 # the exit code + run_command=$2 + run_log=$3 + if [ $last_status -eq 0 ]; then + echo -e "\033[33m Run successfully with command - ${run_command}! \033[0m" | tee -a ${run_log} + else + echo -e "\033[33m Run failed with command - ${run_command}! \033[0m" | tee -a ${run_log} + fi +} + diff --git a/test_tipc/config/MobileNetV3_large_x1_0/train_infer_python.txt b/test_tipc/config/MobileNetV3_large_x1_0/train_infer_python.txt new file mode 100644 index 00000000..b784c84d --- /dev/null +++ b/test_tipc/config/MobileNetV3_large_x1_0/train_infer_python.txt @@ -0,0 +1,52 @@ +===========================train_params=========================== +model_name:MobileNetV3_large_x1_0 +python:python3.7 +gpu_list:0|0,1 +-o Global.device:gpu +-o Global.auto_cast:null +-o Global.epochs:lite_train_infer=2|whole_train_infer=120 +-o Global.output_dir:./output/ +-o DataLoader.Train.sampler.batch_size:8 +-o Global.pretrained_model:null +train_model_name:latest +train_infer_img_dir:./dataset/ILSVRC2012/val +null:null +## +trainer:norm_train|pact_train|fpgm_train +norm_train:tools/train.py -c ppcls/configs/ImageNet/MobileNetV3/MobileNetV3_large_x1_0.yaml -o Global.seed=1234 -o DataLoader.Train.sampler.shuffle=False -o DataLoader.Train.loader.num_workers=0 -o DataLoader.Train.loader.use_shared_memory=False +pact_train:tools/train.py -c ppcls/configs/slim/MobileNetV3_large_x1_0_quantization.yaml -o Global.seed=1234 -o DataLoader.Train.sampler.shuffle=False -o DataLoader.Train.loader.num_workers=0 -o DataLoader.Train.loader.use_shared_memory=False +fpgm_train:tools/train.py -c ppcls/configs/slim/MobileNetV3_large_x1_0_prune.yaml -o Global.seed=1234 -o DataLoader.Train.sampler.shuffle=False -o DataLoader.Train.loader.num_workers=0 -o DataLoader.Train.loader.use_shared_memory=False +distill_train:null +null:null +null:null +## +===========================eval_params=========================== +eval:tools/eval.py -c ppcls/configs/ImageNet/MobileNetV3/MobileNetV3_large_x1_0.yaml +null:null +## +===========================infer_params========================== +-o Global.save_inference_dir:./inference +-o Global.pretrained_model: +norm_export:tools/export_model.py -c ppcls/configs/ImageNet/MobileNetV3/MobileNetV3_large_x1_0.yaml +quant_export:tools/export_model.py -c ppcls/configs/slim/MobileNetV3_large_x1_0_quantization.yaml +fpgm_export:tools/export_model.py -c ppcls/configs/slim/MobileNetV3_large_x1_0_prune.yaml +distill_export:null +kl_quant:deploy/slim/quant_post_static.py -c ppcls/configs/ImageNet/MobileNetV3/MobileNetV3_large_x1_0.yaml -o Global.save_inference_dir=./inference +export2:null +inference_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/whole_chain/MobileNetV3_large_x1_0_inference.tar +infer_model:../inference/ +infer_export:null +infer_quant:Fasle +inference:python/predict_cls.py -c configs/inference_cls.yaml +-o Global.use_gpu:True|False +-o Global.enable_mkldnn:True|False +-o Global.cpu_num_threads:1|6 +-o Global.batch_size:1|16 +-o Global.use_tensorrt:True|False +-o Global.use_fp16:True|False +-o Global.inference_model_dir:../inference +-o Global.infer_imgs:../dataset/ILSVRC2012/val +-o Global.save_log_path:null +-o Global.benchmark:True +null:null +null:null \ No newline at end of file diff --git a/test_tipc/config/MobileNetV3_large_x1_0/train_linux_gpu_fleet_amp_infer_python_linux_gpu_cpu.txt b/test_tipc/config/MobileNetV3_large_x1_0/train_linux_gpu_fleet_amp_infer_python_linux_gpu_cpu.txt new file mode 100644 index 00000000..ade6e3e8 --- /dev/null +++ b/test_tipc/config/MobileNetV3_large_x1_0/train_linux_gpu_fleet_amp_infer_python_linux_gpu_cpu.txt @@ -0,0 +1,52 @@ +===========================train_params=========================== +model_name:MobileNetV3_large_x1_0 +python:python3.7 +gpu_list:10.21.226.181,10.21.226.133;0,1 +-o Global.device:gpu +-o Global.auto_cast:null|amp +-o Global.epochs:lite_train_infer=2|whole_train_infer=120 +-o Global.output_dir:./output/ +-o DataLoader.Train.sampler.batch_size:8 +-o Global.pretrained_model:null +train_model_name:latest +train_infer_img_dir:./dataset/ILSVRC2012/val +null:null +## +trainer:norm_train|pact_train|fpgm_train +norm_train:tools/train.py -c ppcls/configs/ImageNet/MobileNetV3/MobileNetV3_large_x1_0.yaml -o Global.seed=1234 -o DataLoader.Train.sampler.shuffle=False -o DataLoader.Train.loader.num_workers=0 -o DataLoader.Train.loader.use_shared_memory=False +pact_train:tools/train.py -c ppcls/configs/slim/MobileNetV3_large_x1_0_quantization.yaml -o Global.seed=1234 -o DataLoader.Train.sampler.shuffle=False -o DataLoader.Train.loader.num_workers=0 -o DataLoader.Train.loader.use_shared_memory=False +fpgm_train:tools/train.py -c ppcls/configs/slim/MobileNetV3_large_x1_0_prune.yaml -o Global.seed=1234 -o DataLoader.Train.sampler.shuffle=False -o DataLoader.Train.loader.num_workers=0 -o DataLoader.Train.loader.use_shared_memory=False +distill_train:null +null:null +null:null +## +===========================eval_params=========================== +eval:tools/eval.py -c ppcls/configs/ImageNet/MobileNetV3/MobileNetV3_large_x1_0.yaml +null:null +## +===========================infer_params========================== +-o Global.save_inference_dir:./inference +-o Global.pretrained_model: +norm_export:tools/export_model.py -c ppcls/configs/ImageNet/MobileNetV3/MobileNetV3_large_x1_0.yaml +quant_export:tools/export_model.py -c ppcls/configs/slim/MobileNetV3_large_x1_0_quantization.yaml +fpgm_export:tools/export_model.py -c ppcls/configs/slim/MobileNetV3_large_x1_0_prune.yaml +distill_export:null +kl_quant:deploy/slim/quant_post_static.py -c ppcls/configs/ImageNet/MobileNetV3/MobileNetV3_large_x1_0.yaml -o Global.save_inference_dir=./inference +export2:null +inference_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/whole_chain/MobileNetV3_large_x1_0_inference.tar +infer_model:../inference/ +infer_export:null +infer_quant:Fasle +inference:python/predict_cls.py -c configs/inference_cls.yaml +-o Global.use_gpu:True|False +-o Global.enable_mkldnn:True|False +-o Global.cpu_num_threads:1|6 +-o Global.batch_size:1|16 +-o Global.use_tensorrt:True|False +-o Global.use_fp16:True|False +-o Global.inference_model_dir:../inference +-o Global.infer_imgs:../dataset/ILSVRC2012/val +-o Global.save_log_path:null +-o Global.benchmark:True +null:null +null:null \ No newline at end of file diff --git a/test_tipc/config/MobileNetV3_large_x1_0/train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt b/test_tipc/config/MobileNetV3_large_x1_0/train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt new file mode 100644 index 00000000..732edc17 --- /dev/null +++ b/test_tipc/config/MobileNetV3_large_x1_0/train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt @@ -0,0 +1,52 @@ +===========================train_params=========================== +model_name:MobileNetV3_large_x1_0 +python:python3.7 +gpu_list:0|0,1 +-o Global.device:gpu +-o Global.auto_cast:amp +-o Global.epochs:lite_train_infer=2|whole_train_infer=120 +-o Global.output_dir:./output/ +-o DataLoader.Train.sampler.batch_size:8 +-o Global.pretrained_model:null +train_model_name:latest +train_infer_img_dir:./dataset/ILSVRC2012/val +null:null +## +trainer:norm_train|pact_train|fpgm_train +norm_train:tools/train.py -c ppcls/configs/ImageNet/MobileNetV3/MobileNetV3_large_x1_0.yaml -o Global.seed=1234 -o DataLoader.Train.sampler.shuffle=False -o DataLoader.Train.loader.num_workers=0 -o DataLoader.Train.loader.use_shared_memory=False +pact_train:tools/train.py -c ppcls/configs/slim/MobileNetV3_large_x1_0_quantization.yaml -o Global.seed=1234 -o DataLoader.Train.sampler.shuffle=False -o DataLoader.Train.loader.num_workers=0 -o DataLoader.Train.loader.use_shared_memory=False +fpgm_train:tools/train.py -c ppcls/configs/slim/MobileNetV3_large_x1_0_prune.yaml -o Global.seed=1234 -o DataLoader.Train.sampler.shuffle=False -o DataLoader.Train.loader.num_workers=0 -o DataLoader.Train.loader.use_shared_memory=False +distill_train:null +null:null +null:null +## +===========================eval_params=========================== +eval:tools/eval.py -c ppcls/configs/ImageNet/MobileNetV3/MobileNetV3_large_x1_0.yaml +null:null +## +===========================infer_params========================== +-o Global.save_inference_dir:./inference +-o Global.pretrained_model: +norm_export:tools/export_model.py -c ppcls/configs/ImageNet/MobileNetV3/MobileNetV3_large_x1_0.yaml +quant_export:tools/export_model.py -c ppcls/configs/slim/MobileNetV3_large_x1_0_quantization.yaml +fpgm_export:tools/export_model.py -c ppcls/configs/slim/MobileNetV3_large_x1_0_prune.yaml +distill_export:null +kl_quant:deploy/slim/quant_post_static.py -c ppcls/configs/ImageNet/MobileNetV3/MobileNetV3_large_x1_0.yaml -o Global.save_inference_dir=./inference +export2:null +inference_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/whole_chain/MobileNetV3_large_x1_0_inference.tar +infer_model:../inference/ +infer_export:null +infer_quant:Fasle +inference:python/predict_cls.py -c configs/inference_cls.yaml +-o Global.use_gpu:True|False +-o Global.enable_mkldnn:True|False +-o Global.cpu_num_threads:1|6 +-o Global.batch_size:1|16 +-o Global.use_tensorrt:True|False +-o Global.use_fp16:True|False +-o Global.inference_model_dir:../inference +-o Global.infer_imgs:../dataset/ILSVRC2012/val +-o Global.save_log_path:null +-o Global.benchmark:True +null:null +null:null \ No newline at end of file diff --git a/test_tipc/config/ResNet50_vd/train_infer_python.txt b/test_tipc/config/ResNet50_vd/train_infer_python.txt new file mode 100644 index 00000000..69bfae9a --- /dev/null +++ b/test_tipc/config/ResNet50_vd/train_infer_python.txt @@ -0,0 +1,52 @@ +===========================train_params=========================== +model_name:ResNet50_vd +python:python3.7 +gpu_list:0|0,1 +-o Global.device:gpu +-o Global.auto_cast:null +-o Global.epochs:lite_train_lite_infer=2|whole_train_whole_infer=120 +-o Global.output_dir:./output/ +-o DataLoader.Train.sampler.batch_size:8 +-o Global.pretrained_model:null +train_model_name:latest +train_infer_img_dir:./dataset/ILSVRC2012/val +null:null +## +trainer:norm_train|pact_train|fpgm_train +norm_train:tools/train.py -c ppcls/configs/ImageNet/ResNet/ResNet50_vd.yaml -o Global.seed=1234 -o DataLoader.Train.sampler.shuffle=False -o DataLoader.Train.loader.num_workers=0 -o DataLoader.Train.loader.use_shared_memory=False +pact_train:tools/train.py -c ppcls/configs/slim/ResNet50_vd_quantization.yaml -o Global.seed=1234 -o DataLoader.Train.sampler.shuffle=False -o DataLoader.Train.loader.num_workers=0 -o DataLoader.Train.loader.use_shared_memory=False +fpgm_train:tools/train.py -c ppcls/configs/slim/ResNet50_vd_prune.yaml -o Global.seed=1234 -o DataLoader.Train.sampler.shuffle=False -o DataLoader.Train.loader.num_workers=0 -o DataLoader.Train.loader.use_shared_memory=False +distill_train:null +null:null +null:null +## +===========================eval_params=========================== +eval:tools/eval.py -c ppcls/configs/ImageNet/ResNet/ResNet50_vd.yaml +null:null +## +===========================infer_params========================== +-o Global.save_inference_dir:./inference +-o Global.pretrained_model: +norm_export:tools/export_model.py -c ppcls/configs/ImageNet/ResNet/ResNet50_vd.yaml +quant_export:tools/export_model.py -c ppcls/configs/slim/ResNet50_vd_quantization.yaml +fpgm_export:tools/export_model.py -c ppcls/configs/slim/ResNet50_vd_prune.yaml +distill_export:null +kl_quant:deploy/slim/quant_post_static.py -c ppcls/configs/ImageNet/ResNet/ResNet50_vd.yaml -o Global.save_inference_dir=./inference +export2:null +inference_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/whole_chain/ResNet50_vd_inference.tar +infer_model:../inference/ +infer_export:null +infer_quant:Fasle +inference:python/predict_cls.py -c configs/inference_cls.yaml +-o Global.use_gpu:True|False +-o Global.enable_mkldnn:True|False +-o Global.cpu_num_threads:1|6 +-o Global.batch_size:1|16 +-o Global.use_tensorrt:True|False +-o Global.use_fp16:True|False +-o Global.inference_model_dir:../inference +-o Global.infer_imgs:../dataset/ILSVRC2012/val +-o Global.save_log_path:null +-o Global.benchmark:True +null:null +null:null diff --git a/test_tipc/config/ResNet50_vd/train_linux_gpu_fleet_amp_infer_python_linux_gpu_cpu.txt b/test_tipc/config/ResNet50_vd/train_linux_gpu_fleet_amp_infer_python_linux_gpu_cpu.txt new file mode 100644 index 00000000..5c65db74 --- /dev/null +++ b/test_tipc/config/ResNet50_vd/train_linux_gpu_fleet_amp_infer_python_linux_gpu_cpu.txt @@ -0,0 +1,52 @@ +===========================train_params=========================== +model_name:ResNet50_vd +python:python3.7 +gpu_list:10.21.226.181,10.21.226.133;0,1 +-o Global.device:gpu +-o Global.auto_cast:null|amp +-o Global.epochs:lite_train_infer=2|whole_train_infer=120 +-o Global.output_dir:./output/ +-o DataLoader.Train.sampler.batch_size:8 +-o Global.pretrained_model:null +train_model_name:latest +train_infer_img_dir:./dataset/ILSVRC2012/val +null:null +## +trainer:norm_train|pact_train|fpgm_train +norm_train:tools/train.py -c ppcls/configs/ImageNet/ResNet/ResNet50_vd.yaml -o Global.seed=1234 -o DataLoader.Train.sampler.shuffle=False -o DataLoader.Train.loader.num_workers=0 -o DataLoader.Train.loader.use_shared_memory=False +pact_train:tools/train.py -c ppcls/configs/slim/ResNet50_vd_quantization.yaml -o Global.seed=1234 -o DataLoader.Train.sampler.shuffle=False -o DataLoader.Train.loader.num_workers=0 -o DataLoader.Train.loader.use_shared_memory=False +fpgm_train:tools/train.py -c ppcls/configs/slim/ResNet50_vd_prune.yaml -o Global.seed=1234 -o DataLoader.Train.sampler.shuffle=False -o DataLoader.Train.loader.num_workers=0 -o DataLoader.Train.loader.use_shared_memory=False +distill_train:null +null:null +null:null +## +===========================eval_params=========================== +eval:tools/eval.py -c ppcls/configs/ImageNet/ResNet/ResNet50_vd.yaml +null:null +## +===========================infer_params========================== +-o Global.save_inference_dir:./inference +-o Global.pretrained_model: +norm_export:tools/export_model.py -c ppcls/configs/ImageNet/ResNet/ResNet50_vd.yaml +quant_export:tools/export_model.py -c ppcls/configs/slim/ResNet50_vd_quantization.yaml +fpgm_export:tools/export_model.py -c ppcls/configs/slim/ResNet50_vd_prune.yaml +distill_export:null +kl_quant:deploy/slim/quant_post_static.py -c ppcls/configs/ImageNet/ResNet/ResNet50_vd.yaml -o Global.save_inference_dir=./inference +export2:null +inference_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/whole_chain/ResNet50_vd_inference.tar +infer_model:../inference/ +infer_export:null +infer_quant:Fasle +inference:python/predict_cls.py -c configs/inference_cls.yaml +-o Global.use_gpu:True|False +-o Global.enable_mkldnn:True|False +-o Global.cpu_num_threads:1|6 +-o Global.batch_size:1|16 +-o Global.use_tensorrt:True|False +-o Global.use_fp16:True|False +-o Global.inference_model_dir:../inference +-o Global.infer_imgs:../dataset/ILSVRC2012/val +-o Global.save_log_path:null +-o Global.benchmark:True +null:null +null:null diff --git a/test_tipc/config/ResNet50_vd/train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt b/test_tipc/config/ResNet50_vd/train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt new file mode 100644 index 00000000..1a379217 --- /dev/null +++ b/test_tipc/config/ResNet50_vd/train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt @@ -0,0 +1,52 @@ +===========================train_params=========================== +model_name:ResNet50_vd +python:python3.7 +gpu_list:0|0,1 +-o Global.device:gpu +-o Global.auto_cast:amp +-o Global.epochs:lite_train_infer=2|whole_train_infer=120 +-o Global.output_dir:./output/ +-o DataLoader.Train.sampler.batch_size:8 +-o Global.pretrained_model:null +train_model_name:latest +train_infer_img_dir:./dataset/ILSVRC2012/val +null:null +## +trainer:norm_train|pact_train|fpgm_train +norm_train:tools/train.py -c ppcls/configs/ImageNet/ResNet/ResNet50_vd.yaml -o Global.seed=1234 -o DataLoader.Train.sampler.shuffle=False -o DataLoader.Train.loader.num_workers=0 -o DataLoader.Train.loader.use_shared_memory=False +pact_train:tools/train.py -c ppcls/configs/slim/ResNet50_vd_quantization.yaml -o Global.seed=1234 -o DataLoader.Train.sampler.shuffle=False -o DataLoader.Train.loader.num_workers=0 -o DataLoader.Train.loader.use_shared_memory=False +fpgm_train:tools/train.py -c ppcls/configs/slim/ResNet50_vd_prune.yaml -o Global.seed=1234 -o DataLoader.Train.sampler.shuffle=False -o DataLoader.Train.loader.num_workers=0 -o DataLoader.Train.loader.use_shared_memory=False +distill_train:null +null:null +null:null +## +===========================eval_params=========================== +eval:tools/eval.py -c ppcls/configs/ImageNet/ResNet/ResNet50_vd.yaml +null:null +## +===========================infer_params========================== +-o Global.save_inference_dir:./inference +-o Global.pretrained_model: +norm_export:tools/export_model.py -c ppcls/configs/ImageNet/ResNet/ResNet50_vd.yaml +quant_export:tools/export_model.py -c ppcls/configs/slim/ResNet50_vd_quantization.yaml +fpgm_export:tools/export_model.py -c ppcls/configs/slim/ResNet50_vd_prune.yaml +distill_export:null +kl_quant:deploy/slim/quant_post_static.py -c ppcls/configs/ImageNet/ResNet/ResNet50_vd.yaml -o Global.save_inference_dir=./inference +export2:null +inference_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/whole_chain/ResNet50_vd_inference.tar +infer_model:../inference/ +infer_export:null +infer_quant:Fasle +inference:python/predict_cls.py -c configs/inference_cls.yaml +-o Global.use_gpu:True|False +-o Global.enable_mkldnn:True|False +-o Global.cpu_num_threads:1|6 +-o Global.batch_size:1|16 +-o Global.use_tensorrt:True|False +-o Global.use_fp16:True|False +-o Global.inference_model_dir:../inference +-o Global.infer_imgs:../dataset/ILSVRC2012/val +-o Global.save_log_path:null +-o 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