[TIPC] add ptq test shell (#6250)

* [TIPC] add ptq test shell and txt

* [TIPC] alter shell save log, test=document_fix

test_tipc/README.md

@@ -107,6 +107,7 @@ bash test_tipc/test_train_inference_python.sh ./test_tipc/configs/yolov3/yolov3_
 - [test_train_inference_python 使用](docs/test_train_inference_python.md) ：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_train_fleet_inference_python 使用](./docs/test_train_fleet_inference_python.md)：测试基于Python的多机多卡训练与推理等基本功能。
 - [test_inference_cpp 使用](docs/test_inference_cpp.md)：测试基于C++的模型推理。
-- [test_serving 使用](docs/test_serving.md)：测试基于Paddle Serving的服务化部署功能。
-- [test_lite_arm_cpu_cpp 使用](./)：测试基于Paddle-Lite的ARM CPU端c++预测部署功能。
+- [test_serving 使用](docs/test_serving.md)：测试基于Paddle Serving的服务化部署功能，包括Python、C++。
+- test_lite_arm_cpu_cpp 使用（待开发）：测试基于Paddle-Lite的ARM CPU端c++预测部署功能。
 - [test_paddle2onnx 使用](docs/test_paddle2onnx.md)：测试Paddle2ONNX的模型转化功能，并验证正确性。
+- [test_ptq_inference_python 使用](docs/test_ptq_inference_python.md)：测试基于Python的离线量化功能。

test_tipc/configs/keypoint/tinypose_128x96_KL_train_infer_python.txt

@@ -37,7 +37,7 @@ kl_quant_export:tools/post_quant.py -c configs/keypoint/tiny_pose/tinypose_128x9
 ##
 infer_mode:kl_quant
 infer_quant:True
-inference:./deploy/python/infer.py
+inference:./deploy/python/keypoint_infer.py
 --device:gpu|cpu
 --enable_mkldnn:False
 --cpu_threads:4

test_tipc/configs/keypoint/tinypose_128x96_train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt

@@ -37,7 +37,7 @@ kl_quant_export:tools/post_quant.py -c configs/keypoint/tiny_pose/tinypose_128x9
 ##
 infer_mode:norm
 infer_quant:False
-inference:./deploy/python/infer.py
+inference:./deploy/python/keypoint_infer.py
 --device:gpu|cpu
 --enable_mkldnn:False
 --cpu_threads:4

test_tipc/configs/keypoint/tinypose_128x96_train_ptq_infer_python.txt

+===========================ptq_params===========================
+model_name:tinypose_128x96
+python:python3.7
+filename:
+##
+--output_dir:./output_inference
+weights:https://paddledet.bj.bcebos.com/models/keypoint/tinypose_128x96.pdparams
+kl_quant_export:tools/post_quant.py -c configs/keypoint/tiny_pose/tinypose_128x96.yml --slim_config configs/slim/post_quant/yolov3_darknet53_ptq.yml -o
+export_param1:null
+##
+inference:./deploy/python/keypoint_infer.py
+--device:gpu|cpu
+--enable_mkldnn:False
+--cpu_threads:4
+--batch_size:1|2
+--run_mode:paddle
+--model_dir:
+--image_dir:./dataset/coco/test2017/
+--run_benchmark:False
+null:null
\ No newline at end of file

test_tipc/configs/mask_rcnn/mask_rcnn_r50_fpn_1x_coco_train_ptq_infer_python.txt

+===========================ptq_params===========================
+model_name:mask_rcnn_r50_fpn_1x_coco
+python:python3.7
+filename:
+##
+--output_dir:./output_inference
+weights:https://paddledet.bj.bcebos.com/models/mask_rcnn_r50_fpn_1x_coco.pdparams
+kl_quant_export:tools/post_quant.py -c configs/mask_rcnn/mask_rcnn_r50_fpn_1x_coco.yml --slim_config configs/slim/post_quant/yolov3_darknet53_ptq.yml -o
+export_param1:null
+##
+inference:./deploy/python/infer.py
+--device:gpu|cpu
+--enable_mkldnn:False
+--cpu_threads:4
+--batch_size:1|2
+--run_mode:paddle
+--model_dir:
+--image_dir:./dataset/coco/test2017/
+--run_benchmark:False
+null:null
\ No newline at end of file

test_tipc/configs/picodet/picodet_l_640_coco_train_ptq_infer_python.txt

+===========================ptq_params===========================
+model_name:picodet_l_640_coco
+python:python3.7
+filename:
+##
+--output_dir:./output_inference
+weights:https://paddledet.bj.bcebos.com/models/picodet_l_640_coco.pdparams
+kl_quant_export:tools/post_quant.py -c configs/picodet/legacy_model/picodet_l_640_coco.yml --slim_config configs/slim/post_quant/yolov3_darknet53_ptq.yml -o
+export_param1:null
+##
+inference:./deploy/python/infer.py
+--device:gpu|cpu
+--enable_mkldnn:False
+--cpu_threads:4
+--batch_size:1|2
+--run_mode:paddle
+--model_dir:
+--image_dir:./dataset/coco/test2017/
+--run_benchmark:False
+null:null
\ No newline at end of file

test_tipc/configs/picodet/picodet_lcnet_1_5x_416_coco_train_ptq_infer_python.txt

+===========================ptq_params===========================
+model_name:picodet_lcnet_1_5x_416_coco
+python:python3.7
+filename:
+##
+--output_dir:./output_inference
+weights:https://paddledet.bj.bcebos.com/models/picodet_lcnet_1_5x_416_coco.pdparams
+kl_quant_export:tools/post_quant.py -c configs/picodet/legacy_model/more_config/picodet_lcnet_1_5x_416_coco.yml --slim_config configs/slim/post_quant/yolov3_darknet53_ptq.yml -o
+export_param1:null
+##
+inference:./deploy/python/infer.py
+--device:gpu|cpu
+--enable_mkldnn:False
+--cpu_threads:4
+--batch_size:1|2
+--run_mode:paddle
+--model_dir:
+--image_dir:./dataset/coco/test2017/
+--run_benchmark:False
+null:null
\ No newline at end of file

test_tipc/configs/picodet/picodet_m_416_coco_train_ptq_infer_python.txt

+===========================ptq_params===========================
+model_name:picodet_m_416_coco
+python:python3.7
+filename:
+##
+--output_dir:./output_inference
+weights:https://paddledet.bj.bcebos.com/models/picodet_m_416_coco.pdparams
+kl_quant_export:tools/post_quant.py -c configs/picodet/legacy_model/picodet_m_416_coco.yml --slim_config configs/slim/post_quant/yolov3_darknet53_ptq.yml -o
+export_param1:null
+##
+inference:./deploy/python/infer.py
+--device:gpu|cpu
+--enable_mkldnn:False
+--cpu_threads:4
+--batch_size:1|2
+--run_mode:paddle
+--model_dir:
+--image_dir:./dataset/coco/test2017/
+--run_benchmark:False
+null:null
\ No newline at end of file

test_tipc/configs/picodet/picodet_mobilenetv3_large_1x_416_coco_train_ptq_infer_python.txt

+===========================ptq_params===========================
+model_name:picodet_mobilenetv3_large_1x_416_coco
+python:python3.7
+filename:
+##
+--output_dir:./output_inference
+weights:https://paddledet.bj.bcebos.com/models/picodet_mobilenetv3_large_1x_416_coco.pdparams
+kl_quant_export:tools/post_quant.py -c configs/picodet/legacy_model/more_config/picodet_mobilenetv3_large_1x_416_coco.yml --slim_config configs/slim/post_quant/yolov3_darknet53_ptq.yml -o
+export_param1:null
+##
+inference:./deploy/python/infer.py
+--device:gpu|cpu
+--enable_mkldnn:False
+--cpu_threads:4
+--batch_size:1|2
+--run_mode:paddle
+--model_dir:
+--image_dir:./dataset/coco/test2017/
+--run_benchmark:False
+null:null
\ No newline at end of file

test_tipc/configs/picodet/picodet_r18_640_coco_train_ptq_infer_python.txt

+===========================ptq_params===========================
+model_name:picodet_r18_640_coco
+python:python3.7
+filename:
+##
+--output_dir:./output_inference
+weights:https://paddledet.bj.bcebos.com/models/picodet_r18_640_coco.pdparams
+kl_quant_export:tools/post_quant.py -c configs/picodet/legacy_model/more_config/picodet_r18_640_coco.yml --slim_config configs/slim/post_quant/yolov3_darknet53_ptq.yml -o
+export_param1:null
+##
+inference:./deploy/python/infer.py
+--device:gpu|cpu
+--enable_mkldnn:False
+--cpu_threads:4
+--batch_size:1|2
+--run_mode:paddle
+--model_dir:
+--image_dir:./dataset/coco/test2017/
+--run_benchmark:False
+null:null
\ No newline at end of file

test_tipc/configs/picodet/picodet_s_320_coco_train_ptq_infer_python.txt

+===========================ptq_params===========================
+model_name:picodet_s_320_coco
+python:python3.7
+filename:
+##
+--output_dir:./output_inference
+weights:https://paddledet.bj.bcebos.com/models/picodet_s_320_coco.pdparams
+kl_quant_export:tools/post_quant.py -c configs/picodet/legacy_model/picodet_s_320_coco.yml --slim_config configs/slim/post_quant/yolov3_darknet53_ptq.yml -o
+export_param1:null
+##
+inference:./deploy/python/infer.py
+--device:gpu|cpu
+--enable_mkldnn:False
+--cpu_threads:4
+--batch_size:1|2
+--run_mode:paddle
+--model_dir:
+--image_dir:./dataset/coco/test2017/
+--run_benchmark:False
+null:null
\ No newline at end of file

test_tipc/configs/picodet/picodet_shufflenetv2_1x_416_coco_train_ptq_infer_python.txt

+===========================ptq_params===========================
+model_name:picodet_shufflenetv2_1x_416_coco
+python:python3.7
+filename:
+##
+--output_dir:./output_inference
+weights:https://paddledet.bj.bcebos.com/models/picodet_shufflenetv2_1x_416_coco.pdparams
+kl_quant_export:tools/post_quant.py -c configs/picodet/legacy_model/more_config/picodet_shufflenetv2_1x_416_coco.yml --slim_config configs/slim/post_quant/yolov3_darknet53_ptq.yml -o
+export_param1:null
+##
+inference:./deploy/python/infer.py
+--device:gpu|cpu
+--enable_mkldnn:False
+--cpu_threads:4
+--batch_size:1|2
+--run_mode:paddle
+--model_dir:
+--image_dir:./dataset/coco/test2017/
+--run_benchmark:False
+null:null
\ No newline at end of file

test_tipc/configs/ppyolo/ppyolo_mbv3_large_coco_train_ptq_infer_python.txt

+===========================ptq_params===========================
+model_name:ppyolo_mbv3_large_coco
+python:python3.7
+filename:
+##
+--output_dir:./output_inference
+weights:https://paddledet.bj.bcebos.com/models/ppyolo_mbv3_large_coco.pdparams
+kl_quant_export:tools/post_quant.py -c configs/ppyolo/ppyolo_mbv3_large_coco.yml --slim_config configs/slim/post_quant/yolov3_darknet53_ptq.yml -o
+export_param1:null
+##
+inference:./deploy/python/infer.py
+--device:gpu|cpu
+--enable_mkldnn:False
+--cpu_threads:4
+--batch_size:1|2
+--run_mode:paddle
+--model_dir:
+--image_dir:./dataset/coco/test2017/
+--run_benchmark:False
+null:null
\ No newline at end of file

test_tipc/configs/ppyolo/ppyolo_mbv3_small_coco_train_ptq_infer_python.txt

+===========================ptq_params===========================
+model_name:ppyolo_mbv3_small_coco
+python:python3.7
+filename:
+##
+--output_dir:./output_inference
+weights:https://paddledet.bj.bcebos.com/models/ppyolo_mbv3_small_coco.pdparams
+kl_quant_export:tools/post_quant.py -c configs/ppyolo/ppyolo_mbv3_small_coco.yml --slim_config configs/slim/post_quant/yolov3_darknet53_ptq.yml -o
+export_param1:null
+##
+inference:./deploy/python/infer.py
+--device:gpu|cpu
+--enable_mkldnn:False
+--cpu_threads:4
+--batch_size:1|2
+--run_mode:paddle
+--model_dir:
+--image_dir:./dataset/coco/test2017/
+--run_benchmark:False
+null:null
\ No newline at end of file

test_tipc/configs/ppyolo/ppyolo_r18vd_coco_train_ptq_infer_python.txt

+===========================ptq_params===========================
+model_name:ppyolo_r18vd_coco
+python:python3.7
+filename:
+##
+--output_dir:./output_inference
+weights:https://paddledet.bj.bcebos.com/models/ppyolo_r18vd_coco.pdparams
+kl_quant_export:tools/post_quant.py -c configs/ppyolo/ppyolo_r18vd_coco.yml --slim_config configs/slim/post_quant/yolov3_darknet53_ptq.yml -o
+export_param1:null
+##
+inference:./deploy/python/infer.py
+--device:gpu|cpu
+--enable_mkldnn:False
+--cpu_threads:4
+--batch_size:1|2
+--run_mode:paddle
+--model_dir:
+--image_dir:./dataset/coco/test2017/
+--run_benchmark:False
+null:null
\ No newline at end of file

test_tipc/configs/ppyolo/ppyolo_r50vd_dcn_1x_coco_train_ptq_infer_python.txt

+===========================ptq_params===========================
+model_name:ppyolo_r50vd_dcn_1x_coco
+python:python3.7
+filename:
+##
+--output_dir:./output_inference
+weights:https://paddledet.bj.bcebos.com/models/ppyolo_r50vd_dcn_1x_coco.pdparams
+kl_quant_export:tools/post_quant.py -c configs/ppyolo/ppyolo_r50vd_dcn_1x_coco.yml --slim_config configs/slim/post_quant/yolov3_darknet53_ptq.yml -o
+export_param1:null
+##
+inference:./deploy/python/infer.py
+--device:gpu|cpu
+--enable_mkldnn:False
+--cpu_threads:4
+--batch_size:1|2
+--run_mode:paddle
+--model_dir:
+--image_dir:./dataset/coco/test2017/
+--run_benchmark:False
+null:null
\ No newline at end of file

test_tipc/configs/ppyolo/ppyolo_tiny_650e_coco_train_ptq_infer_python.txt

+===========================ptq_params===========================
+model_name:ppyolo_tiny_650e_coco
+python:python3.7
+filename:
+##
+--output_dir:./output_inference
+weights:https://paddledet.bj.bcebos.com/models/ppyolo_tiny_650e_coco.pdparams
+kl_quant_export:tools/post_quant.py -c configs/ppyolo/ppyolo_tiny_650e_coco.yml --slim_config configs/slim/post_quant/yolov3_darknet53_ptq.yml -o
+export_param1:null
+##
+inference:./deploy/python/infer.py
+--device:gpu|cpu
+--enable_mkldnn:False
+--cpu_threads:4
+--batch_size:1|2
+--run_mode:paddle
+--model_dir:
+--image_dir:./dataset/coco/test2017/
+--run_benchmark:False
+null:null
\ No newline at end of file

test_tipc/configs/ppyolo/ppyolov2_r101vd_dcn_365e_coco_train_ptq_infer_python.txt

+===========================ptq_params===========================
+model_name:ppyolov2_r101vd_dcn_365e_coco
+python:python3.7
+filename:
+##
+--output_dir:./output_inference
+weights:https://paddledet.bj.bcebos.com/models/ppyolov2_r101vd_dcn_365e_coco.pdparams
+kl_quant_export:tools/post_quant.py -c configs/ppyolo/ppyolov2_r101vd_dcn_365e_coco.yml --slim_config configs/slim/post_quant/yolov3_darknet53_ptq.yml -o
+export_param1:null
+##
+inference:./deploy/python/infer.py
+--device:gpu|cpu
+--enable_mkldnn:False
+--cpu_threads:4
+--batch_size:1|2
+--run_mode:paddle
+--model_dir:
+--image_dir:./dataset/coco/test2017/
+--run_benchmark:False
+null:null
\ No newline at end of file

test_tipc/configs/ppyolo/ppyolov2_r50vd_dcn_365e_coco_train_ptq_infer_python.txt

+===========================ptq_params===========================
+model_name:ppyolov2_r50vd_dcn_365e_coco
+python:python3.7
+filename:
+##
+--output_dir:./output_inference
+weights:https://paddledet.bj.bcebos.com/models/ppyolov2_r50vd_dcn_365e_coco.pdparams
+kl_quant_export:tools/post_quant.py -c configs/ppyolo/ppyolov2_r50vd_dcn_365e_coco.yml --slim_config configs/slim/post_quant/yolov3_darknet53_ptq.yml -o
+export_param1:null
+##
+inference:./deploy/python/infer.py
+--device:gpu|cpu
+--enable_mkldnn:False
+--cpu_threads:4
+--batch_size:1|2
+--run_mode:paddle
+--model_dir:
+--image_dir:./dataset/coco/test2017/
+--run_benchmark:False
+null:null
\ No newline at end of file

test_tipc/configs/ppyoloe/ppyoloe_crn_l_300e_coco_train_ptq_infer_python.txt

+===========================ptq_params===========================
+model_name:ppyoloe_crn_l_300e_coco
+python:python3.7
+filename:
+##
+--output_dir:./output_inference
+weights:https://paddledet.bj.bcebos.com/models/ppyoloe_crn_l_300e_coco.pdparams
+kl_quant_export:tools/post_quant.py -c configs/ppyoloe/ppyoloe_crn_l_300e_coco.yml --slim_config configs/slim/post_quant/yolov3_darknet53_ptq.yml -o
+export_param1:null
+##
+inference:./deploy/python/infer.py
+--device:gpu|cpu
+--enable_mkldnn:False
+--cpu_threads:4
+--batch_size:1|2
+--run_mode:paddle
+--model_dir:
+--image_dir:./dataset/coco/test2017/
+--run_benchmark:False
+null:null
\ No newline at end of file

test_tipc/configs/ppyoloe/ppyoloe_crn_m_300e_coco_train_ptq_infer_python.txt

+===========================ptq_params===========================
+model_name:ppyoloe_crn_m_300e_coco
+python:python3.7
+filename:
+##
+--output_dir:./output_inference
+weights:https://paddledet.bj.bcebos.com/models/ppyoloe_crn_m_300e_coco.pdparams
+kl_quant_export:tools/post_quant.py -c configs/ppyoloe/ppyoloe_crn_m_300e_coco.yml --slim_config configs/slim/post_quant/yolov3_darknet53_ptq.yml -o
+export_param1:null
+##
+inference:./deploy/python/infer.py
+--device:gpu|cpu
+--enable_mkldnn:False
+--cpu_threads:4
+--batch_size:1|2
+--run_mode:paddle
+--model_dir:
+--image_dir:./dataset/coco/test2017/
+--run_benchmark:False
+null:null
\ No newline at end of file

test_tipc/configs/ppyoloe/ppyoloe_crn_s_300e_coco_train_ptq_infer_python.txt

+===========================ptq_params===========================
+model_name:ppyoloe_crn_s_300e_coco
+python:python3.7
+filename:
+##
+--output_dir:./output_inference
+weights:https://paddledet.bj.bcebos.com/models/ppyoloe_crn_s_300e_coco.pdparams
+kl_quant_export:tools/post_quant.py -c configs/ppyoloe/ppyoloe_crn_s_300e_coco.yml --slim_config configs/slim/post_quant/yolov3_darknet53_ptq.yml -o
+export_param1:null
+##
+inference:./deploy/python/infer.py
+--device:gpu|cpu
+--enable_mkldnn:False
+--cpu_threads:4
+--batch_size:1|2
+--run_mode:paddle
+--model_dir:
+--image_dir:./dataset/coco/test2017/
+--run_benchmark:False
+null:null
\ No newline at end of file

test_tipc/configs/ppyoloe/ppyoloe_crn_x_300e_coco_train_ptq_infer_python.txt

+===========================ptq_params===========================
+model_name:ppyoloe_crn_x_300e_coco
+python:python3.7
+filename:
+##
+--output_dir:./output_inference
+weights:https://paddledet.bj.bcebos.com/models/ppyoloe_crn_x_300e_coco.pdparams
+kl_quant_export:tools/post_quant.py -c configs/ppyoloe/ppyoloe_crn_x_300e_coco.yml --slim_config configs/slim/post_quant/yolov3_darknet53_ptq.yml -o
+export_param1:null
+##
+inference:./deploy/python/infer.py
+--device:gpu|cpu
+--enable_mkldnn:False
+--cpu_threads:4
+--batch_size:1|2
+--run_mode:paddle
+--model_dir:
+--image_dir:./dataset/coco/test2017/
+--run_benchmark:False
+null:null
\ No newline at end of file

test_tipc/configs/yolov3/yolov3_darknet53_270e_coco_train_ptq_infer_python.txt

+===========================ptq_params===========================
+model_name:yolov3_darknet53_270e_coco
+python:python3.7
+filename:
+##
+--output_dir:./output_inference
+weights:https://paddledet.bj.bcebos.com/models/yolov3_darknet53_270e_coco.pdparams
+kl_quant_export:tools/post_quant.py -c configs/yolov3/yolov3_darknet53_270e_coco.yml --slim_config configs/slim/post_quant/yolov3_darknet53_ptq.yml -o
+export_param1:null
+##
+inference:./deploy/python/infer.py
+--device:gpu|cpu
+--enable_mkldnn:False
+--cpu_threads:4
+--batch_size:1|2
+--run_mode:paddle
+--model_dir:
+--image_dir:./dataset/coco/test2017/
+--run_benchmark:False
+null:null
\ No newline at end of file

test_tipc/docs/test_ptq_inference_python.md

+# Linux GPU/CPU 离线量化功能测试
+
+Linux GPU/CPU 离线量化功能测试的主程序为`test_ptq_inference_python.sh`，可以测试基于Python的离线量化功能。
+
+## 1. 测试结论汇总
+
+| 模型类型 |device | batchsize | tensorrt | mkldnn | cpu多线程 |
+|  ----   |  ---- |-----------|  :----:  |   :----:   |  :----:  |
+| 量化模型 | GPU | 1/2       | int8 | - | - |
+| 量化模型 | CPU | 1/2       | - | int8 | 支持 |
+
+## 2. 测试流程
+### 2.1 功能测试
+先运行`prepare.sh`准备数据和模型，然后运行`test_ptq_inference_python.sh`进行测试，最终在```test_tipc/output```目录下生成`python_infer_*.log`后缀的日志文件。
+
+```shell
+bash test_tipc/prepare.sh ./test_tipc/configs/yolov3/yolov3_darknet53_270e_coco_train_ptq_infer_python.txt "whole_infer"
+
+# 用法:
+bash test_tipc/test_ptq_inference_python.sh ./test_tipc/configs/yolov3/yolov3_darknet53_270e_coco_train_ptq_infer_python.txt
+```  
+
+#### 运行结果
+
+各测试的运行情况会打印在 `test_tipc/output/results_ptq_python.log` 中：
+运行成功时会输出：
+
+```
+Run successfully with command - yolov3_darknet53_270e_coco - python3.7 tools/post_quant.py -c configs/yolov3/yolov3_darknet53_270e_coco.yml --slim_config configs/slim/post_quant/yolov3_darknet53_ptq.yml -o weights=https://paddledet.bj.bcebos.com/models/yolov3_darknet53_270e_coco.pdparams filename=yolov3_darknet53_270e_coco --output_dir=./output_inference !
+Run successfully with command - yolov3_darknet53_270e_coco - python3.7 ./deploy/python/infer.py --device=gpu --run_mode=paddle --model_dir=./output_inference/yolov3_darknet53_270e_coco --batch_size=2 --image_dir=./dataset/coco/test2017/ --run_benchmark=False   > ./test_tipc/output/yolov3_darknet53_270e_coco/whole_infer/python_infer_gpu_mode_paddle_batchsize_2.log 2>&1 !
+...
+```
+
+运行失败时会输出：
+
+```
+Run failed with command - yolov3_darknet53_270e_coco - python3.7 tools/post_quant.py -c configs/yolov3/yolov3_darknet53_270e_coco.yml --slim_config configs/slim/post_quant/yolov3_darknet53_ptq.yml -o weights=https://paddledet.bj.bcebos.com/models/yolov3_darknet53_270e_coco.pdparams filename=yolov3_darknet53_270e_coco --output_dir=./output_inference!
+...
+```
+
+
+## 3. 更多教程
+
+本文档为功能测试用，更详细的离线量化功能使用教程请参考：[Paddle 离线量化官网教程](https://github.com/PaddlePaddle/PaddleSlim/blob/develop/docs/zh_cn/api_cn/static/quant/quantization_api.rst#quant_post_static)

test_tipc/test_inference_cpp.sh

@@ -2,6 +2,7 @@
 source test_tipc/utils_func.sh
 
 FILENAME=$1
+MODE="cpp_infer"
 
 # parser model_name
 dataline=$(cat ${FILENAME})
@@ -54,7 +55,7 @@ cpp_benchmark_value=$(func_parser_value "${lines[27]}")
 cpp_infer_key1=$(func_parser_key "${lines[28]}")
 cpp_infer_value1=$(func_parser_value "${lines[28]}")
 
-LOG_PATH="./test_tipc/output"
+LOG_PATH="./test_tipc/output/${model_name}/${MODE}"
 mkdir -p ${LOG_PATH}
 status_log="${LOG_PATH}/results_cpp.log"
 
@@ -74,7 +75,7 @@ function func_cpp_inference(){
                 fi
                 for threads in ${cpp_cpu_threads_list[*]}; do
                     for batch_size in ${cpp_batch_size_list[*]}; do
-                        _save_log_path="${_log_path}/cpp_infer_cpu_usemkldnn_${use_mkldnn}_threads_${threads}_precision_fluid_batchsize_${batch_size}.log"
+                        _save_log_path="${_log_path}/cpp_infer_cpu_usemkldnn_${use_mkldnn}_threads_${threads}_mode_paddle_batchsize_${batch_size}.log"
                         set_infer_data=$(func_set_params "${cpp_image_dir_key}" "${_img_dir}")
                         set_benchmark=$(func_set_params "${cpp_benchmark_key}" "${cpp_benchmark_value}")
                         set_batchsize=$(func_set_params "${cpp_batch_size_key}" "${batch_size}")
@@ -91,7 +92,7 @@ function func_cpp_inference(){
             done
         elif [ ${use_gpu} = "True" ] || [ ${use_gpu} = "gpu" ]; then
             for precision in ${cpp_precision_list[*]}; do
-                if [[ ${precision} != "fluid" ]]; then
+                if [[ ${precision} != "paddle" ]]; then
                     if [[ ${_flag_quant} = "False" ]] && [[ ${precision} = "trt_int8" ]]; then
                         continue
                     fi
@@ -100,7 +101,7 @@ function func_cpp_inference(){
                     fi
                 fi
                 for batch_size in ${cpp_batch_size_list[*]}; do
-                    _save_log_path="${_log_path}/cpp_infer_gpu_precision_${precision}_batchsize_${batch_size}.log"
+                    _save_log_path="${_log_path}/cpp_infer_gpu_mode_${precision}_batchsize_${batch_size}.log"
                     set_infer_data=$(func_set_params "${cpp_image_dir_key}" "${_img_dir}")
                     set_benchmark=$(func_set_params "${cpp_benchmark_key}" "${cpp_benchmark_value}")
                     set_batchsize=$(func_set_params "${cpp_batch_size_key}" "${batch_size}")
@@ -183,6 +184,7 @@ else
     env="export CUDA_VISIBLE_DEVICES=${GPUID}"
 fi
 eval $env
+
 # run cpp infer
 Count=0
 IFS="|"
@@ -201,9 +203,10 @@ for infer_mode in ${cpp_infer_mode_list[*]}; do
         set_export_weight=$(func_set_params "${export_weight_key}" "${export_weight_value}")
         set_save_export_dir=$(func_set_params "${save_export_key}" "${save_export_value}")
         set_filename=$(func_set_params "${filename_key}" "${model_name}")
+        export_log_path="${LOG_PATH}/export.log"
         export_cmd="${python} ${run_export} ${set_export_weight} ${set_filename} ${set_save_export_dir} "
         echo  $export_cmd
-        eval $export_cmd
+        eval "${export_cmd} > ${export_log_path} 2>&1"
         status_export=$?
         status_check $status_export "${export_cmd}" "${status_log}" "${model_name}"
     fi

test_tipc/test_paddle2onnx.sh

@@ -2,6 +2,7 @@
 source test_tipc/utils_func.sh
 
 FILENAME=$1
+MODE="paddle2onnx_infer"
 
 # parser model_name
 dataline=$(cat ${FILENAME})
@@ -56,7 +57,7 @@ infer_image_value=$(func_parser_value "${lines[28]}")
 infer_param1_key=$(func_parser_key "${lines[29]}")
 infer_param1_value=$(func_parser_value "${lines[29]}")
 
-LOG_PATH="./test_tipc/output"
+LOG_PATH="./test_tipc/output/${model_name}/${MODE}"
 mkdir -p ${LOG_PATH}
 status_log="${LOG_PATH}/results_paddle2onnx.log"
 
@@ -68,7 +69,6 @@ function func_paddle2onnx_inference(){
 
     # paddle2onnx
     echo "################### run paddle2onnx ###################"
-    _save_log_path="${LOG_PATH}/paddle2onnx_infer_cpu.log"
     set_dirname=$(func_set_params "${model_dir_key}" "${_export_model_dir}")
     set_model_filename=$(func_set_params "${model_filename_key}" "${model_filename_value}")
     set_params_filename=$(func_set_params "${params_filename_key}" "${params_filename_value}")
@@ -76,8 +76,9 @@ function func_paddle2onnx_inference(){
     set_opset_version=$(func_set_params "${opset_version_key}" "${opset_version_value}")
     set_enable_onnx_checker=$(func_set_params "${enable_onnx_checker_key}" "${enable_onnx_checker_value}")
     set_paddle2onnx_params1=$(func_set_params "${paddle2onnx_params1_key}" "${paddle2onnx_params1_value}")
+    trans_log_path="${_log_path}/trans_model.log"
     trans_model_cmd="${padlle2onnx_cmd} ${set_dirname} ${set_model_filename} ${set_params_filename} ${set_save_model} ${set_opset_version} ${set_enable_onnx_checker} ${set_paddle2onnx_params1}"
-    eval $trans_model_cmd
+    eval "${trans_model_cmd} > ${trans_log_path} 2>&1"
     last_status=${PIPESTATUS[0]}
     status_check $last_status "${trans_model_cmd}" "${status_log}" "${model_name}"
 
@@ -87,8 +88,9 @@ function func_paddle2onnx_inference(){
     set_onnx_file=$(func_set_params "${onnx_file_key}" "${_export_model_dir}/${save_file_value}")
     set_infer_image_file=$(func_set_params "${infer_image_key}" "${infer_image_value}")
     set_infer_param1=$(func_set_params "${infer_param1_key}" "${infer_param1_value}")
-    infer_model_cmd="${python} ${inference_py} ${set_infer_cfg} ${set_onnx_file} ${set_infer_image_file} ${set_infer_param1} > ${_save_log_path} 2>&1 "
-    eval $infer_model_cmd
+    _save_log_path="${_log_path}/paddle2onnx_infer_cpu.log"
+    infer_model_cmd="${python} ${inference_py} ${set_infer_cfg} ${set_onnx_file} ${set_infer_image_file} ${set_infer_param1}"
+    eval "${infer_model_cmd} > ${_save_log_path} 2>&1"
     last_status=${PIPESTATUS[0]}
     status_check $last_status "${infer_model_cmd}" "${status_log}" "${model_name}"
 }
@@ -110,9 +112,10 @@ for infer_mode in ${infer_mode_list[*]}; do
         set_save_export_dir=$(func_set_params "${save_export_key}" "${save_export_value}")
         set_filename=$(func_set_params "${filename_key}" "${model_name}")
         set_export_param=$(func_set_params "${export_param_key}" "${export_param_value}")
+        export_log_path="${LOG_PATH}/export.log"
         export_cmd="${python} ${run_export} ${set_export_weight} ${set_filename} ${set_export_param} ${set_save_export_dir} "
         echo  $export_cmd
-        eval $export_cmd
+        eval "${export_cmd} > ${export_log_path} 2>&1"
         status_export=$?
         status_check $status_export "${export_cmd}" "${status_log}" "${model_name}"
     fi

test_tipc/test_ptq_inference_python.sh

+#!/bin/bash
+source test_tipc/utils_func.sh
+
+FILENAME=$1
+MODE="whole_infer"
+
+# parser model_name
+dataline=$(cat ${FILENAME})
+IFS=$'\n'
+lines=(${dataline})
+model_name=$(func_parser_value "${lines[1]}")
+echo "ppdet ptq: ${model_name}"
+python=$(func_parser_value "${lines[2]}")
+filename_key=$(func_parser_key "${lines[3]}")
+
+# parser export params
+save_export_key=$(func_parser_key "${lines[5]}")
+save_export_value=$(func_parser_value "${lines[5]}")
+export_weight_key=$(func_parser_key "${lines[6]}")
+export_weight_value=$(func_parser_value "${lines[6]}")
+kl_quant_export=$(func_parser_value "${lines[7]}")
+export_param1_key=$(func_parser_key "${lines[8]}")
+export_param1_value=$(func_parser_value "${lines[8]}")
+
+# parser infer params
+inference_py=$(func_parser_value "${lines[10]}")
+device_key=$(func_parser_key "${lines[11]}")
+device_list=$(func_parser_value "${lines[11]}")
+use_mkldnn_key=$(func_parser_key "${lines[12]}")
+use_mkldnn_list=$(func_parser_value "${lines[12]}")
+cpu_threads_key=$(func_parser_key "${lines[13]}")
+cpu_threads_list=$(func_parser_value "${lines[13]}")
+batch_size_key=$(func_parser_key "${lines[14]}")
+batch_size_list=$(func_parser_value "${lines[14]}")
+run_mode_key=$(func_parser_key "${lines[15]}")
+run_mode_list=$(func_parser_value "${lines[15]}")
+model_dir_key=$(func_parser_key "${lines[16]}")
+image_dir_key=$(func_parser_key "${lines[17]}")
+image_dir_value=$(func_parser_value "${lines[17]}")
+run_benchmark_key=$(func_parser_key "${lines[18]}")
+run_benchmark_value=$(func_parser_value "${lines[18]}")
+infer_param1_key=$(func_parser_key "${lines[19]}")
+infer_param1_value=$(func_parser_value "${lines[19]}")
+
+
+LOG_PATH="./test_tipc/output/${model_name}/${MODE}"
+mkdir -p ${LOG_PATH}
+status_log="${LOG_PATH}/results_ptq_python.log"
+
+function func_ptq_inference(){
+    IFS='|'
+    _python=$1
+    _log_path=$2
+    _script=$3
+    _set_model_dir=$4
+
+    set_image_dir=$(func_set_params "${image_dir_key}" "${image_dir_value}")
+    set_run_benchmark=$(func_set_params "${run_benchmark_key}" "${run_benchmark_value}")
+    set_infer_param1=$(func_set_params "${infer_param1_key}" "${infer_param1_value}")
+    # inference
+    for device in ${device_list[*]}; do
+        set_device=$(func_set_params "${device_key}" "${device}")
+        if [ ${device} = "cpu" ]; then
+            for use_mkldnn in ${use_mkldnn_list[*]}; do
+                set_use_mkldnn=$(func_set_params "${use_mkldnn_key}" "${use_mkldnn}")
+                for threads in ${cpu_threads_list[*]}; do
+                    set_cpu_threads=$(func_set_params "${cpu_threads_key}" "${threads}")
+                    for batch_size in ${batch_size_list[*]}; do
+                        _save_log_path="${_log_path}/python_infer_cpu_usemkldnn_${use_mkldnn}_threads_${threads}_mode_paddle_batchsize_${batch_size}.log"
+                        set_batchsize=$(func_set_params "${batch_size_key}" "${batch_size}")
+                        command="${_python} ${_script} ${set_device} ${set_use_mkldnn} ${set_cpu_threads} ${_set_model_dir} ${set_batchsize} ${set_image_dir} ${set_run_benchmark} ${set_infer_param1} > ${_save_log_path} 2>&1 "
+                        eval $command
+                        last_status=${PIPESTATUS[0]}
+                        eval "cat ${_save_log_path}"
+                        status_check $last_status "${command}" "${status_log}" "${model_name}"
+                    done
+                done
+            done
+        elif [ ${device} = "gpu" ]; then
+            for run_mode in ${run_mode_list[*]}; do
+                if [[ ${run_mode} = "paddle" ]] || [[ ${run_mode} = "trt_int8" ]]; then
+                    for batch_size in ${batch_size_list[*]}; do
+                        _save_log_path="${_log_path}/python_infer_gpu_mode_${run_mode}_batchsize_${batch_size}.log"
+                        set_batchsize=$(func_set_params "${batch_size_key}" "${batch_size}")
+                        set_run_mode=$(func_set_params "${run_mode_key}" "${run_mode}")
+                        command="${_python} ${_script} ${set_device} ${set_run_mode} ${_set_model_dir} ${set_batchsize} ${set_image_dir} ${set_run_benchmark} ${set_infer_param1} > ${_save_log_path} 2>&1 "
+                        eval $command
+                        last_status=${PIPESTATUS[0]}
+                        eval "cat ${_save_log_path}"
+                        status_check $last_status "${command}" "${status_log}" "${model_name}"
+                    done
+                fi
+            done
+        else
+            echo "Does not support hardware other than CPU and GPU Currently!"
+        fi
+    done
+}
+
+IFS="|"
+# run ptq
+set_export_weight=$(func_set_params "${export_weight_key}" "${export_weight_value}")
+set_save_export_dir=$(func_set_params "${save_export_key}" "${save_export_value}")
+set_filename=$(func_set_params "${filename_key}" "${model_name}")
+export_log_path="${LOG_PATH}/export.log"
+ptq_cmd="${python} ${kl_quant_export} ${set_export_weight} ${set_filename} ${set_save_export_dir}"
+echo  $ptq_cmd
+eval "${ptq_cmd} > ${export_log_path} 2>&1"
+status_export=$?
+status_check $status_export "${ptq_cmd}" "${status_log}" "${model_name}"
+
+#run inference
+set_export_model_dir=$(func_set_params "${model_dir_key}" "${save_export_value}/${model_name}")
+func_ptq_inference "${python}" "${LOG_PATH}" "${inference_py}" "${set_export_model_dir}"

test_tipc/test_serving_infer_cpp.sh

@@ -2,13 +2,14 @@
 source test_tipc/utils_func.sh
 
 FILENAME=$1
+MODE="serving_infer"
 
 # parser model_name
 dataline=$(cat ${FILENAME})
 IFS=$'\n'
 lines=(${dataline})
 model_name=$(func_parser_value "${lines[1]}")
-echo "ppdet serving_infer: ${model_name}"
+echo "ppdet serving_cpp_infer: ${model_name}"
 python=$(func_parser_value "${lines[2]}")
 filename_key=$(func_parser_key "${lines[3]}")
 filename_value=$(func_parser_value "${lines[3]}")
@@ -48,7 +49,7 @@ infer_image_value=$(func_parser_value "${lines[24]}")
 http_client_key1=$(func_parser_key "${lines[25]}")
 http_client_value1=$(func_parser_value "${lines[25]}")
 
-LOG_PATH="./test_tipc/output"
+LOG_PATH="./test_tipc/output/${model_name}/${MODE}"
 mkdir -p ${LOG_PATH}
 status_log="${LOG_PATH}/results_serving_cpp.log"
 
@@ -67,23 +68,25 @@ function func_serving_inference(){
     # inference
     for gpu_ids in ${gpu_ids_value[*]}; do
         if [ ${gpu_ids} = "null" ];then
-            _save_log_path="${_log_path}/serving_infer_cpp_cpu_batchsize_1.log"
+            server_log_path="${_log_path}/cpp_server_cpu.log"
+            client_log_path="${_log_path}/cpp_client_cpu.log"
         else
-            _save_log_path="${_log_path}/serving_infer_cpp_gpu_batchsize_1.log"
+            server_log_path="${_log_path}/cpp_server_gpu.log"
+            client_log_path="${_log_path}/cpp_client_gpu.log"
         fi
         set_gpu_ids=$(func_set_params "${gpu_ids_key}" "${gpu_ids}")
         # run web service
-        web_service_cmd="${_python} -m paddle_serving_server.serve ${_set_server_model_dir} ${set_op} ${set_port} ${set_gpu_ids} ${set_web_service_params1} &"
+        web_service_cmd="${_python} -m paddle_serving_server.serve ${_set_server_model_dir} ${set_op} ${set_port} ${set_gpu_ids} ${set_web_service_params1} > ${server_log_path} 2>&1 &"
         eval $web_service_cmd
         last_status=${PIPESTATUS[0]}
         status_check $last_status "${web_service_cmd}" "${status_log}" "${model_name}"
         sleep 5s
         # run http client
-        http_client_cmd="${_python} ${http_client_py} ${_set_client_model_dir} ${_set_image_file} ${set_http_client_params1} > ${_save_log_path} 2>&1 "
+        http_client_cmd="${_python} ${http_client_py} ${_set_client_model_dir} ${_set_image_file} ${set_http_client_params1} > ${client_log_path} 2>&1"
         eval $http_client_cmd
         last_status=${PIPESTATUS[0]}
         status_check $last_status "${http_client_cmd}" "${status_log}" "${model_name}"
-        eval "cat ${_save_log_path}"
+        eval "cat ${client_log_path}"
         ps ux | grep -i ${port_value} | awk '{print $2}' | xargs kill -s 9
         sleep 2s
     done
@@ -107,9 +110,10 @@ for infer_mode in ${infer_mode_list[*]}; do
         set_export_weight=$(func_set_params "${export_weight_key}" "${export_weight_value}")
         set_save_export_dir=$(func_set_params "${save_export_key}" "${save_export_value}")
         set_filename=$(func_set_params "${filename_key}" "${model_name}")
+        export_log_path="${LOG_PATH}/export.log"
         export_cmd="${python} ${run_export} ${set_export_weight} ${set_filename} ${set_save_export_dir} "
         echo  $export_cmd
-        eval $export_cmd
+        eval "${export_cmd} > ${export_log_path} 2>&1"
         status_export=$?
         status_check $status_export "${export_cmd}" "${status_log}" "${model_name}"
     fi

test_tipc/test_serving_infer_python.sh

@@ -2,13 +2,14 @@
 source test_tipc/utils_func.sh
 
 FILENAME=$1
+MODE="serving_infer"
 
 # parser model_name
 dataline=$(cat ${FILENAME})
 IFS=$'\n'
 lines=(${dataline})
 model_name=$(func_parser_value "${lines[1]}")
-echo "ppdet serving_infer: ${model_name}"
+echo "ppdet serving_python_infer: ${model_name}"
 python=$(func_parser_value "${lines[2]}")
 filename_key=$(func_parser_key "${lines[3]}")
 filename_value=$(func_parser_value "${lines[3]}")
@@ -44,7 +45,7 @@ infer_image_value=$(func_parser_value "${lines[22]}")
 http_client_key1=$(func_parser_key "${lines[23]}")
 http_client_value1=$(func_parser_value "${lines[23]}")
 
-LOG_PATH="./test_tipc/output"
+LOG_PATH="./test_tipc/output/${model_name}/${MODE}"
 mkdir -p ${LOG_PATH}
 status_log="${LOG_PATH}/results_serving_python.log"
 
@@ -61,21 +62,22 @@ function func_serving_inference(){
     # inference
     for opt in ${opt_use_gpu_list[*]}; do
         device_type=$(func_parser_key "${opt}")
-        _save_log_path="${_log_path}/serving_infer_python_${device_type}_batchsize_1.log"
+        server_log_path="${_log_path}/python_server_${device_type}.log"
+        client_log_path="${_log_path}/python_client_${device_type}.log"
         opt_value=$(func_parser_value "${opt}")
         _set_opt=$(func_set_params "${opt_key}" "${opt_value}")
         # run web service
-        web_service_cmd="${_python} ${_service_script} ${_set_model_dir} ${_set_opt} ${set_web_service_params1} &"
+        web_service_cmd="${_python} ${_service_script} ${_set_model_dir} ${_set_opt} ${set_web_service_params1} > ${server_log_path} 2>&1 &"
         eval $web_service_cmd
         last_status=${PIPESTATUS[0]}
         status_check $last_status "${web_service_cmd}" "${status_log}" "${model_name}"
         sleep 5s
         # run http client
-        http_client_cmd="${_python} ${_client_script} ${_set_image_file} ${set_http_client_params1} > ${_save_log_path} 2>&1 "
+        http_client_cmd="${_python} ${_client_script} ${_set_image_file} ${set_http_client_params1} > ${client_log_path} 2>&1"
         eval $http_client_cmd
         last_status=${PIPESTATUS[0]}
         status_check $last_status "${http_client_cmd}" "${status_log}" "${model_name}"
-        eval "cat ${_save_log_path}"
+        eval "cat ${client_log_path}"
         ps ux | grep -E 'web_service' | awk '{print $2}' | xargs kill -s 9
         sleep 2s
     done
@@ -108,9 +110,10 @@ for infer_mode in ${infer_mode_list[*]}; do
         set_export_weight=$(func_set_params "${export_weight_key}" "${export_weight_value}")
         set_save_export_dir=$(func_set_params "${save_export_key}" "${save_export_value}")
         set_filename=$(func_set_params "${filename_key}" "${model_name}")
+        export_log_path="${LOG_PATH}/export.log"
         export_cmd="${python} ${run_export} ${set_export_weight} ${set_filename} ${set_save_export_dir} "
         echo  $export_cmd
-        eval $export_cmd
+        eval "${export_cmd} > ${export_log_path} 2>&1"
         status_export=$?
         status_check $status_export "${export_cmd}" "${status_log}" "${model_name}"
     fi

test_tipc/test_train_inference_python.sh

@@ -92,7 +92,7 @@ benchmark_value=$(func_parser_value "${lines[49]}")
 infer_key1=$(func_parser_key "${lines[50]}")
 infer_value1=$(func_parser_value "${lines[50]}")
 
-LOG_PATH="./test_tipc/output/${model_name}"
+LOG_PATH="./test_tipc/output/${model_name}/${MODE}"
 mkdir -p ${LOG_PATH}
 status_log="${LOG_PATH}/results_python.log"
 
@@ -114,7 +114,7 @@ function func_inference(){
                 fi
                 for threads in ${cpu_threads_list[*]}; do
                     for batch_size in ${batch_size_list[*]}; do
-                        _save_log_path="${_log_path}/python_infer_cpu_usemkldnn_${use_mkldnn}_threads_${threads}_precision_fluid_batchsize_${batch_size}.log"
+                        _save_log_path="${_log_path}/python_infer_cpu_usemkldnn_${use_mkldnn}_threads_${threads}_mode_paddle_batchsize_${batch_size}.log"
                         set_infer_data=$(func_set_params "${image_dir_key}" "${_img_dir}")
                         set_benchmark=$(func_set_params "${benchmark_key}" "${benchmark_value}")
                         set_batchsize=$(func_set_params "${batch_size_key}" "${batch_size}")
@@ -131,7 +131,7 @@ function func_inference(){
             done
         elif [ ${use_gpu} = "True" ] || [ ${use_gpu} = "gpu" ]; then
             for precision in ${precision_list[*]}; do
-                if [[ ${precision} != "fluid" ]]; then
+                if [[ ${precision} != "paddle" ]]; then
                     if [[ ${_flag_quant} = "False" ]] && [[ ${precision} = "trt_int8" ]]; then
                         continue
                     fi
@@ -140,7 +140,7 @@ function func_inference(){
                     fi
                 fi
                 for batch_size in ${batch_size_list[*]}; do
-                    _save_log_path="${_log_path}/python_infer_gpu_precision_${precision}_batchsize_${batch_size}.log"
+                    _save_log_path="${_log_path}/python_infer_gpu_mode_${precision}_batchsize_${batch_size}.log"
                     set_infer_data=$(func_set_params "${image_dir_key}" "${_img_dir}")
                     set_benchmark=$(func_set_params "${benchmark_key}" "${benchmark_value}")
                     set_batchsize=$(func_set_params "${batch_size_key}" "${batch_size}")
@@ -276,6 +276,7 @@ else
                 save_log="${LOG_PATH}/${trainer}_gpus_${gpu}_autocast_${autocast}"
 
                 set_save_model=$(func_set_params "${save_model_key}" "${save_log}")
+                nodes="1"
                 if [ ${#gpu} -le 2 ];then  # train with cpu or single gpu
                     cmd="${python} ${run_train} LearningRate.base_lr=0.0001 log_iter=1 ${set_use_gpu} ${set_save_model} ${set_epoch} ${set_pretrain} ${set_batchsize} ${set_filename} ${set_train_params1} ${set_autocast}"
                 elif [ ${#ips} -le 15 ];then  # train with multi-gpu
@@ -290,15 +291,17 @@ else
                     cmd="${python} -m paddle.distributed.launch --ips=${ips} --gpus=${gpu} ${run_train} log_iter=1 ${set_use_gpu} ${set_save_model} ${set_epoch} ${set_pretrain} ${set_batchsize} ${set_filename} ${set_train_params1} ${set_autocast}"
                 fi
                 # run train
-                eval $cmd
+                train_log_path="${LOG_PATH}/${trainer}_gpus_${gpu}_autocast_${autocast}_nodes_${nodes}.log"
+                eval "${cmd} > ${train_log_path} 2>&1"
                 status_check $? "${cmd}" "${status_log}" "${model_name}"
 
                 set_eval_trained_weight=$(func_set_params "${export_weight_key}" "${save_log}/${model_name}/${train_model_name}")
                 # run eval
                 if [ ${eval_py} != "null" ]; then
                     set_eval_params1=$(func_set_params "${eval_key1}" "${eval_value1}")
+                    eval_log_path="${LOG_PATH}/${trainer}_gpus_${gpu}_autocast_${autocast}_nodes_${nodes}_eval.log"
                     eval_cmd="${python} ${eval_py} ${set_eval_trained_weight} ${set_use_gpu} ${set_eval_params1}"
-                    eval $eval_cmd
+                    eval "${eval_cmd} > ${eval_log_path} 2>&1"
                     status_check $? "${eval_cmd}" "${status_log}" "${model_name}"
                 fi
                 # run export model
@@ -315,8 +318,9 @@ else
                         eval "cp ${save_export_model_dir}/* ${save_log}/"
                     fi
                     # run export model
+                    export_log_path="${LOG_PATH}/${trainer}_gpus_${gpu}_autocast_${autocast}_nodes_${nodes}_export.log"
                     export_cmd="${python} ${run_export} ${set_export_weight} ${set_filename} ${set_save_export_dir} "
-                    eval $export_cmd
+                    eval "${export_cmd} > ${export_log_path} 2>&1"
                     status_check $? "${export_cmd}" "${status_log}" "${model_name}"
 
                     #run inference