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fix GPUID setting and LOG_PATH

pull/2093/head
HydrogenSulfate 2022-06-22 18:21:30 +08:00
parent 9f1ec3a537
commit e77ba41e99
29 changed files with 318 additions and 72 deletions
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2
deploy/slim/quant_post_static.py
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@ -41,6 +41,8 @@ def main():
'inference.pdmodel')) and os.path.exists(
os.path.join(config["Global"]["save_inference_dir"],
'inference.pdiparams'))
if "Query" in config["DataLoader"]["Eval"]:
config["DataLoader"]["Eval"] = config["DataLoader"]["Eval"]["Query"]
config["DataLoader"]["Eval"]["sampler"]["batch_size"] = 1
config["DataLoader"]["Eval"]["loader"]["num_workers"] = 0

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test_tipc/config/MobileNetV3/MobileNetV3_large_x1_0-KL_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt → test_tipc/config/MobileNetV3/MobileNetV3_large_x1_0_KL_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt
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0
test_tipc/config/MobileNetV3/MobileNetV3_large_x1_0-KL_linux_gpu_normal_normal_serving_cpp_linux_gpu_cpu.txt → test_tipc/config/MobileNetV3/MobileNetV3_large_x1_0_KL_linux_gpu_normal_normal_serving_cpp_linux_gpu_cpu.txt
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0
test_tipc/config/MobileNetV3/MobileNetV3_large_x1_0-KL_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt → test_tipc/config/MobileNetV3/MobileNetV3_large_x1_0_KL_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt
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18
test_tipc/config/PP-ShiTu/PPShiTu_general_rec_KL_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt 100644
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@ -0,0 +1,18 @@
===========================cpp_infer_params===========================
model_name:GeneralRecognition_PPLCNet_x2_5_KL
cpp_infer_type:cls
cls_inference_model_dir:./general_PPLCNet_x2_5_lite_v1.0_kl_quant_infer/
det_inference_model_dir:
cls_inference_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/slim_model/general_PPLCNet_x2_5_lite_v1.0_kl_quant_infer.tar
det_inference_url:
infer_quant:False
inference_cmd:./deploy/cpp/build/clas_system -c inference_cls.yaml
use_gpu:True|False
enable_mkldnn:False
cpu_threads:1
batch_size:1
use_tensorrt:False
precision:fp32
image_dir:./dataset/ILSVRC2012/val/ILSVRC2012_val_00000001.JPEG
benchmark:False
generate_yaml_cmd:python3.7 test_tipc/generate_cpp_yaml.py

14
test_tipc/config/PP-ShiTu/PPShiTu_general_rec_KL_linux_gpu_normal_normal_serving_cpp_linux_gpu_cpu.txt 100644
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@ -0,0 +1,14 @@
===========================serving_params===========================
model_name:GeneralRecognition_PPLCNet_x2_5_KL
python:python3.7
inference_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/slim_model/general_PPLCNet_x2_5_lite_v1.0_kl_quant_infer.tar
trans_model:-m paddle_serving_client.convert
--dirname:./deploy/paddleserving/general_PPLCNet_x2_5_lite_v1.0_kl_quant_infer/
--model_filename:inference.pdmodel
--params_filename:inference.pdiparams
--serving_server:./deploy/paddleserving/GeneralRecognition_PPLCNet_x2_5_kl_quant_serving/
--serving_client:./deploy/paddleserving/GeneralRecognition_PPLCNet_x2_5_kl_quant_client/
serving_dir:./deploy/paddleserving
web_service:null
--use_gpu:0|null
pipline:test_cpp_serving_client.py

14
test_tipc/config/PP-ShiTu/PPShiTu_general_rec_KL_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt 100644
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@ -0,0 +1,14 @@
===========================serving_params===========================
model_name:GeneralRecognition_PPLCNet_x2_5_KL
python:python3.7
inference_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/slim_model/general_PPLCNet_x2_5_lite_v1.0_kl_quant_infer.tar
trans_model:-m paddle_serving_client.convert
--dirname:./deploy/paddleserving/general_PPLCNet_x2_5_lite_v1.0_kl_quant_infer/
--model_filename:inference.pdmodel
--params_filename:inference.pdiparams
--serving_server:./deploy/paddleserving/GeneralRecognition_PPLCNet_x2_5_kl_quant_serving/
--serving_client:./deploy/paddleserving/GeneralRecognition_PPLCNet_x2_5_kl_quant_client/
serving_dir:./deploy/paddleserving
web_service:classification_web_service.py
--use_gpu:0|null
pipline:pipeline_http_client.py

18
test_tipc/config/PPHGNet/PPHGNet_small_KL_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt 100644
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@ -0,0 +1,18 @@
===========================cpp_infer_params===========================
model_name:PPHGNet_small_KL
cpp_infer_type:cls
cls_inference_model_dir:./PPHGNet_small_kl_quant_infer/
det_inference_model_dir:
cls_inference_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/slim_model/PPHGNet_small_kl_quant_infer.tar
det_inference_url:
infer_quant:False
inference_cmd:./deploy/cpp/build/clas_system -c inference_cls.yaml
use_gpu:True|False
enable_mkldnn:False
cpu_threads:1
batch_size:1
use_tensorrt:False
precision:fp32
image_dir:./dataset/ILSVRC2012/val/ILSVRC2012_val_00000001.JPEG
benchmark:False
generate_yaml_cmd:python3.7 test_tipc/generate_cpp_yaml.py

14
test_tipc/config/PPHGNet/PPHGNet_small_KL_linux_gpu_normal_normal_serving_cpp_linux_gpu_cpu.txt 100644
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@ -0,0 +1,14 @@
===========================serving_params===========================
model_name:PPHGNet_small_KL
python:python3.7
inference_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/slim_model/PPHGNet_small_kl_quant_infer.tar
trans_model:-m paddle_serving_client.convert
--dirname:./deploy/paddleserving/PPHGNet_small_kl_quant_infer/
--model_filename:inference.pdmodel
--params_filename:inference.pdiparams
--serving_server:./deploy/paddleserving/PPHGNet_small_kl_quant_serving/
--serving_client:./deploy/paddleserving/PPHGNet_small_kl_quant_client/
serving_dir:./deploy/paddleserving
web_service:null
--use_gpu:0|null
pipline:test_cpp_serving_client.py

14
test_tipc/config/PPHGNet/PPHGNet_small_KL_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt 100644
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@ -0,0 +1,14 @@
===========================serving_params===========================
model_name:PPHGNet_small_KL
python:python3.7
inference_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/slim_model/PPHGNet_small_kl_quant_infer.tar
trans_model:-m paddle_serving_client.convert
--dirname:./deploy/paddleserving/PPHGNet_small_kl_quant_infer/
--model_filename:inference.pdmodel
--params_filename:inference.pdiparams
--serving_server:./deploy/paddleserving/PPHGNet_small_kl_quant_serving/
--serving_client:./deploy/paddleserving/PPHGNet_small_kl_quant_client/
serving_dir:./deploy/paddleserving
web_service:classification_web_service.py
--use_gpu:0|null
pipline:pipeline_http_client.py

18
test_tipc/config/PPLCNet/PPLCNet_x1_0_KL_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt 100644
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@ -0,0 +1,18 @@
===========================cpp_infer_params===========================
model_name:PPLCNet_x1_0_KL
cpp_infer_type:cls
cls_inference_model_dir:./PPLCNet_x1_0_kl_quant_infer/
det_inference_model_dir:
cls_inference_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/slim_model/PPLCNet_x1_0_kl_quant_infer.tar
det_inference_url:
infer_quant:False
inference_cmd:./deploy/cpp/build/clas_system -c inference_cls.yaml
use_gpu:True|False
enable_mkldnn:False
cpu_threads:1
batch_size:1
use_tensorrt:False
precision:fp32
image_dir:./dataset/ILSVRC2012/val/ILSVRC2012_val_00000001.JPEG
benchmark:False
generate_yaml_cmd:python3.7 test_tipc/generate_cpp_yaml.py

14
test_tipc/config/PPLCNet/PPLCNet_x1_0_KL_linux_gpu_normal_normal_serving_cpp_linux_gpu_cpu.txt 100644
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@ -0,0 +1,14 @@
===========================serving_params===========================
model_name:PPLCNet_x1_0_KL
python:python3.7
inference_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/slim_model/PPLCNet_x1_0_kl_quant_infer.tar
trans_model:-m paddle_serving_client.convert
--dirname:./deploy/paddleserving/PPLCNet_x1_0_kl_quant_infer/
--model_filename:inference.pdmodel
--params_filename:inference.pdiparams
--serving_server:./deploy/paddleserving/PPLCNet_x1_0_kl_quant_serving/
--serving_client:./deploy/paddleserving/PPLCNet_x1_0_kl_quant_client/
serving_dir:./deploy/paddleserving
web_service:null
--use_gpu:0|null
pipline:test_cpp_serving_client.py

14
test_tipc/config/PPLCNet/PPLCNet_x1_0_KL_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt 100644
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@ -0,0 +1,14 @@
===========================serving_params===========================
model_name:PPLCNet_x1_0_KL
python:python3.7
inference_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/slim_model/PPLCNet_x1_0_kl_quant_infer.tar
trans_model:-m paddle_serving_client.convert
--dirname:./deploy/paddleserving/PPLCNet_x1_0_kl_quant_infer/
--model_filename:inference.pdmodel
--params_filename:inference.pdiparams
--serving_server:./deploy/paddleserving/PPLCNet_x1_0_kl_quant_serving/
--serving_client:./deploy/paddleserving/PPLCNet_x1_0_kl_quant_client/
serving_dir:./deploy/paddleserving
web_service:classification_web_service.py
--use_gpu:0|null
pipline:pipeline_http_client.py

18
test_tipc/config/PPLCNetV2/PPLCNetV2_base_KL_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt 100644
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@ -0,0 +1,18 @@
===========================cpp_infer_params===========================
model_name:PPLCNetV2_base_KL
cpp_infer_type:cls
cls_inference_model_dir:./PPLCNetV2_base_kl_quant_infer/
det_inference_model_dir:
cls_inference_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/slim_model/PPLCNetV2_base_kl_quant_infer.tar
det_inference_url:
infer_quant:False
inference_cmd:./deploy/cpp/build/clas_system -c inference_cls.yaml
use_gpu:True|False
enable_mkldnn:False
cpu_threads:1
batch_size:1
use_tensorrt:False
precision:fp32
image_dir:./dataset/ILSVRC2012/val/ILSVRC2012_val_00000001.JPEG
benchmark:False
generate_yaml_cmd:python3.7 test_tipc/generate_cpp_yaml.py

14
test_tipc/config/PPLCNetV2/PPLCNetV2_base_KL_linux_gpu_normal_normal_serving_cpp_linux_gpu_cpu.txt 100644
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@ -0,0 +1,14 @@
===========================serving_params===========================
model_name:PPLCNetV2_base_KL
python:python3.7
inference_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/slim_model/PPLCNetV2_base_kl_quant_infer.tar
trans_model:-m paddle_serving_client.convert
--dirname:./deploy/paddleserving/PPLCNetV2_base_kl_quant_infer/
--model_filename:inference.pdmodel
--params_filename:inference.pdiparams
--serving_server:./deploy/paddleserving/PPLCNetV2_base_kl_quant_serving/
--serving_client:./deploy/paddleserving/PPLCNetV2_base_kl_quant_client/
serving_dir:./deploy/paddleserving
web_service:null
--use_gpu:0|null
pipline:test_cpp_serving_client.py

14
test_tipc/config/PPLCNetV2/PPLCNetV2_base_KL_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt 100644
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@ -0,0 +1,14 @@
===========================serving_params===========================
model_name:PPLCNetV2_base_KL
python:python3.7
inference_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/slim_model/PPLCNetV2_base_kl_quant_infer.tar
trans_model:-m paddle_serving_client.convert
--dirname:./deploy/paddleserving/PPLCNetV2_base_kl_quant_infer/
--model_filename:inference.pdmodel
--params_filename:inference.pdiparams
--serving_server:./deploy/paddleserving/PPLCNetV2_base_kl_quant_serving/
--serving_client:./deploy/paddleserving/PPLCNetV2_base_kl_quant_client/
serving_dir:./deploy/paddleserving
web_service:classification_web_service.py
--use_gpu:0|null
pipline:pipeline_http_client.py

0
test_tipc/config/ResNet/ResNet50_vd-KL_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt → test_tipc/config/ResNet/ResNet50_vd_KL_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt
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0
test_tipc/config/ResNet/ResNet50_vd-KL_linux_gpu_normal_normal_serving_cpp_linux_gpu_cpu.txt → test_tipc/config/ResNet/ResNet50_vd_KL_linux_gpu_normal_normal_serving_cpp_linux_gpu_cpu.txt
View File

0
test_tipc/config/ResNet/ResNet50_vd-KL_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt → test_tipc/config/ResNet/ResNet50_vd_KL_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt
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18
test_tipc/config/SwinTransformer/SwinTransformer_tiny_patch4_window7_224_KL_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt 100644
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@ -0,0 +1,18 @@
===========================cpp_infer_params===========================
model_name:SwinTransformer_tiny_patch4_window7_224_KL
cpp_infer_type:cls
cls_inference_model_dir:./SwinTransformer_tiny_patch4_window7_224_kl_quant_infer/
det_inference_model_dir:
cls_inference_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/slim_model/SwinTransformer_tiny_patch4_window7_224_kl_quant_infer.tar
det_inference_url:
infer_quant:False
inference_cmd:./deploy/cpp/build/clas_system -c inference_cls.yaml
use_gpu:True|False
enable_mkldnn:False
cpu_threads:1
batch_size:1
use_tensorrt:False
precision:fp32
image_dir:./dataset/ILSVRC2012/val/ILSVRC2012_val_00000001.JPEG
benchmark:False
generate_yaml_cmd:python3.7 test_tipc/generate_cpp_yaml.py

14
test_tipc/config/SwinTransformer/SwinTransformer_tiny_patch4_window7_224_KL_linux_gpu_normal_normal_serving_cpp_linux_gpu_cpu.txt 100644
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@ -0,0 +1,14 @@
===========================serving_params===========================
model_name:SwinTransformer_tiny_patch4_window7_224_KL
python:python3.7
inference_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/slim_model/SwinTransformer_tiny_patch4_window7_224_kl_quant_infer.tar
trans_model:-m paddle_serving_client.convert
--dirname:./deploy/paddleserving/SwinTransformer_tiny_patch4_window7_224_kl_quant_infer/
--model_filename:inference.pdmodel
--params_filename:inference.pdiparams
--serving_server:./deploy/paddleserving/SwinTransformer_tiny_patch4_window7_224_kl_quant_serving/
--serving_client:./deploy/paddleserving/SwinTransformer_tiny_patch4_window7_224_kl_quant_client/
serving_dir:./deploy/paddleserving
web_service:null
--use_gpu:0|null
pipline:test_cpp_serving_client.py

14
test_tipc/config/SwinTransformer/SwinTransformer_tiny_patch4_window7_224_KL_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt 100644
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@ -0,0 +1,14 @@
===========================serving_params===========================
model_name:SwinTransformer_tiny_patch4_window7_224_KL
python:python3.7
inference_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/slim_model/SwinTransformer_tiny_patch4_window7_224_kl_quant_infer.tar
trans_model:-m paddle_serving_client.convert
--dirname:./deploy/paddleserving/SwinTransformer_tiny_patch4_window7_224_kl_quant_infer/
--model_filename:inference.pdmodel
--params_filename:inference.pdiparams
--serving_server:./deploy/paddleserving/SwinTransformer_tiny_patch4_window7_224_kl_quant_serving/
--serving_client:./deploy/paddleserving/SwinTransformer_tiny_patch4_window7_224_kl_quant_client/
serving_dir:./deploy/paddleserving
web_service:classification_web_service.py
--use_gpu:0|null
pipline:pipeline_http_client.py

18
test_tipc/docs/test_inference_cpp.md
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@ -7,26 +7,30 @@ Linux GPU/CPU C++ 推理功能测试的主程序为`test_inference_cpp.sh`，可
- 推理相关：
| 算法名称 | 模型名称 | device_CPU | device_GPU |
| :-------------: | :---------------------------------------: | :--------: | :--------: |
| :-------------: | :----------------------------------------: | :--------: | :--------: |
| MobileNetV3 | MobileNetV3_large_x1_0 | 支持 | 支持 |
| MobileNetV3 | MobileNetV3_large_x1_0_KL | 支持 | 支持 |
| PP-ShiTu | PPShiTu_general_rec、PPShiTu_mainbody_det | 支持 | 支持 |
| PP-ShiTu | PPShiTu_mainbody_det | 支持 | 支持 |
| PP-ShiTu | GeneralRecognition_PPLCNet_x2_5_KL | 支持 | 支持 |
| PPHGNet | PPHGNet_small | 支持 | 支持 |
| PPHGNet | PPHGNet_small_KL | 支持 | 支持 |
| PPHGNet | PPHGNet_tiny | 支持 | 支持 |
| PPLCNet | PPLCNet_x0_25 | 支持 | 支持 |
| PPLCNet | PPLCNet_x0_35 | 支持 | 支持 |
| PPLCNet | PPLCNet_x0_5 | 支持 | 支持 |
| PPLCNet | PPLCNet_x0_75 | 支持 | 支持 |
| PPLCNet | PPLCNet_x1_0 | 支持 | 支持 |
| PPLCNet | PPLCNet_x1_0_KL | 支持 | 支持 |
| PPLCNet | PPLCNet_x1_5 | 支持 | 支持 |
| PPLCNet | PPLCNet_x2_0 | 支持 | 支持 |
| PPLCNet | PPLCNet_x2_5 | 支持 | 支持 |
| PPLCNetV2 | PPLCNetV2_base | 支持 | 支持 |
| PPLCNetV2 | PPLCNetV2_base_KL | 支持 | 支持 |
| ResNet | ResNet50 | 支持 | 支持 |
| ResNet | ResNet50_vd | 支持 | 支持 |
| ResNet | ResNet50_vd_KL | 支持 | 支持 |
| SwinTransformer | SwinTransformer_tiny_patch4_window7_224 | 支持 | 支持 |
| SwinTransformer | SwinTransformer_tiny_patch4_window7_224_KL | 支持 | 支持 |
## 2. 测试流程(以**ResNet50**为例)
@ -244,20 +248,20 @@ bash test_tipc/prepare.sh test_tipc/config/ResNet/ResNet50_linux_gpu_normal_norm
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。
```shell
bash test_tipc/test_inference_cpp.sh ${your_params_file}
bash test_tipc/test_inference_cpp.sh ${your_params_file} cpp_infer
```
以`ResNet50`的`Linux GPU/CPU C++推理测试`为例，命令如下所示。
```shell
bash test_tipc/test_inference_cpp.sh test_tipc/config/ResNet/ResNet50_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt
bash test_tipc/test_inference_cpp.sh test_tipc/config/ResNet/ResNet50_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt cpp_infer
```
输出结果如下，表示命令运行成功。
```shell
Run successfully with command - ./deploy/cpp/build/clas_system -c inference_cls.yaml > ./test_tipc/output/ResNet50/cls_cpp_infer_gpu_usetrt_False_precision_fp32_batchsize_1.log 2>&1!
Run successfully with command - ./deploy/cpp/build/clas_system -c inference_cls.yaml > ./test_tipc/output/ResNet50/cls_cpp_infer_cpu_usemkldnn_False_threads_1_precision_fp32_batchsize_1.log 2>&1!
Run successfully with command - ResNet50 - ./deploy/cpp/build/clas_system -c inference_cls.yaml > ./test_tipc/output/ResNet50/cpp_infer/cpp_infer_gpu_usetrt_False_precision_fp32_batchsize_1.log 2>&1!
Run successfully with command - ResNet50 - ./deploy/cpp/build/clas_system -c inference_cls.yaml > ./test_tipc/output/ResNet50/cpp_infer/cpp_infer_cpu_usemkldnn_False_threads_1_precision_fp32_batchsize_1.log 2>&1!
```
最终log中会打印出结果，如下所示
@ -308,6 +312,6 @@ Current total inferen time cost: 5449.39 ms.
Top5: class_id: 265, score: 0.0420, label: toy poodle
```
详细log位于`./test_tipc/output/ResNet50/cls_cpp_infer_gpu_usetrt_False_precision_fp32_batchsize_1.log`和`./test_tipc/output/ResNet50/cls_cpp_infer_cpu_usemkldnn_False_threads_1_precision_fp32_batchsize_1.log`中。
详细log位于`./test_tipc/output/ResNet50/cpp_infer/cpp_infer_gpu_usetrt_False_precision_fp32_batchsize_1.log`和`./test_tipc/output/ResNet50/cpp_infer_cpu_usemkldnn_False_threads_1_precision_fp32_batchsize_1.log`中。
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。

7
test_tipc/docs/test_serving_infer_cpp.md
View File

@ -8,25 +8,30 @@ Linux GPU/CPU C++ 服务化部署测试的主程序为`test_serving_infer_cpp.sh
- 推理相关：
| 算法名称 | 模型名称 | device_CPU | device_GPU |
| :-------------: | :---------------------------------------: | :--------: | :--------: |
| :-------------: | :----------------------------------------: | :--------: | :--------: |
| MobileNetV3 | MobileNetV3_large_x1_0 | 支持 | 支持 |
| MobileNetV3 | MobileNetV3_large_x1_0_KL | 支持 | 支持 |
| PP-ShiTu | PPShiTu_general_rec、PPShiTu_mainbody_det | 支持 | 支持 |
| PP-ShiTu | GeneralRecognition_PPLCNet_x2_5_KL | 支持 | 支持 |
| PPHGNet | PPHGNet_small | 支持 | 支持 |
| PPHGNet | PPHGNet_small_KL | 支持 | 支持 |
| PPHGNet | PPHGNet_tiny | 支持 | 支持 |
| PPLCNet | PPLCNet_x0_25 | 支持 | 支持 |
| PPLCNet | PPLCNet_x0_35 | 支持 | 支持 |
| PPLCNet | PPLCNet_x0_5 | 支持 | 支持 |
| PPLCNet | PPLCNet_x0_75 | 支持 | 支持 |
| PPLCNet | PPLCNet_x1_0 | 支持 | 支持 |
| PPLCNet | PPLCNet_x1_0_KL | 支持 | 支持 |
| PPLCNet | PPLCNet_x1_5 | 支持 | 支持 |
| PPLCNet | PPLCNet_x2_0 | 支持 | 支持 |
| PPLCNet | PPLCNet_x2_5 | 支持 | 支持 |
| PPLCNetV2 | PPLCNetV2_base | 支持 | 支持 |
| PPLCNetV2 | PPLCNetV2_base_KL | 支持 | 支持 |
| ResNet | ResNet50 | 支持 | 支持 |
| ResNet | ResNet50_vd | 支持 | 支持 |
| ResNet | ResNet50_vd_KL | 支持 | 支持 |
| SwinTransformer | SwinTransformer_tiny_patch4_window7_224 | 支持 | 支持 |
| SwinTransformer | SwinTransformer_tiny_patch4_window7_224_KL | 支持 | 支持 |
## 2. 测试流程

7
test_tipc/docs/test_serving_infer_python.md
View File

@ -8,25 +8,30 @@ Linux GPU/CPU PYTHON 服务化部署测试的主程序为`test_serving_infer_pyt
- 推理相关：
| 算法名称 | 模型名称 | device_CPU | device_GPU |
| :-------------: | :---------------------------------------: | :--------: | :--------: |
| :-------------: | :----------------------------------------: | :--------: | :--------: |
| MobileNetV3 | MobileNetV3_large_x1_0 | 支持 | 支持 |
| MobileNetV3 | MobileNetV3_large_x1_0_KL | 支持 | 支持 |
| PP-ShiTu | PPShiTu_general_rec、PPShiTu_mainbody_det | 支持 | 支持 |
| PP-ShiTu | GeneralRecognition_PPLCNet_x2_5_KL | 支持 | 支持 |
| PPHGNet | PPHGNet_small | 支持 | 支持 |
| PPHGNet | PPHGNet_small_KL | 支持 | 支持 |
| PPHGNet | PPHGNet_tiny | 支持 | 支持 |
| PPLCNet | PPLCNet_x0_25 | 支持 | 支持 |
| PPLCNet | PPLCNet_x0_35 | 支持 | 支持 |
| PPLCNet | PPLCNet_x0_5 | 支持 | 支持 |
| PPLCNet | PPLCNet_x0_75 | 支持 | 支持 |
| PPLCNet | PPLCNet_x1_0 | 支持 | 支持 |
| PPLCNet | PPLCNet_x1_0_KL | 支持 | 支持 |
| PPLCNet | PPLCNet_x1_5 | 支持 | 支持 |
| PPLCNet | PPLCNet_x2_0 | 支持 | 支持 |
| PPLCNet | PPLCNet_x2_5 | 支持 | 支持 |
| PPLCNetV2 | PPLCNetV2_base | 支持 | 支持 |
| PPLCNetV2 | PPLCNetV2_base_KL | 支持 | 支持 |
| ResNet | ResNet50 | 支持 | 支持 |
| ResNet | ResNet50_vd | 支持 | 支持 |
| ResNet | ResNet50_vd_KL | 支持 | 支持 |
| SwinTransformer | SwinTransformer_tiny_patch4_window7_224 | 支持 | 支持 |
| SwinTransformer | SwinTransformer_tiny_patch4_window7_224_KL | 支持 | 支持 |
## 2. 测试流程

2
test_tipc/prepare.sh
View File

@ -208,7 +208,7 @@ fi
if [[ ${MODE} = "serving_infer" ]]; then
# prepare serving env
python_name=$(func_parser_value "${lines[2]}")
if [[ ${model_name} =~ "ShiTu" ]]; then
if [[ ${model_name} = "PPShiTu" ]]; then
cls_inference_model_url=$(func_parser_value "${lines[3]}")
cls_tar_name=$(func_get_url_file_name "${cls_inference_model_url}")
det_inference_model_url=$(func_parser_value "${lines[4]}")

8
test_tipc/test_inference_cpp.sh
View File

@ -63,7 +63,7 @@ function func_shitu_cpp_inference(){
if [ ${use_mkldnn} = "False" ] && [ ${_flag_quant} = "True" ]; then
precison="int8"
fi
_save_log_path="${_log_path}/shitu_cpp_infer_cpu_usemkldnn_${use_mkldnn}_threads_${threads}_precision_${precision}_batchsize_${batch_size}.log"
_save_log_path="${_log_path}/cpp_infer_cpu_usemkldnn_${use_mkldnn}_threads_${threads}_precision_${precision}_batchsize_${batch_size}.log"
eval $transform_index_cmd
command="${generate_yaml_cmd} --type shitu --batch_size ${batch_size} --mkldnn ${use_mkldnn} --gpu ${use_gpu} --cpu_thread ${threads} --tensorrt False --precision ${precision} --data_dir ${_img_dir} --benchmark True --cls_model_dir ${cpp_infer_model_dir} --det_model_dir ${cpp_det_infer_model_dir} --gpu_id ${GPUID}"
eval $command
@ -87,7 +87,7 @@ function func_shitu_cpp_inference(){
continue
fi
for batch_size in ${cpp_batch_size_list[*]}; do
_save_log_path="${_log_path}/shitu_cpp_infer_gpu_usetrt_${use_trt}_precision_${precision}_batchsize_${batch_size}.log"
_save_log_path="${_log_path}/cpp_infer_gpu_usetrt_${use_trt}_precision_${precision}_batchsize_${batch_size}.log"
eval $transform_index_cmd
command="${generate_yaml_cmd} --type shitu --batch_size ${batch_size} --mkldnn False --gpu ${use_gpu} --cpu_thread 1 --tensorrt ${use_trt} --precision ${precision} --data_dir ${_img_dir} --benchmark True --cls_model_dir ${cpp_infer_model_dir} --det_model_dir ${cpp_det_infer_model_dir} --gpu_id ${GPUID}"
eval $command
@ -125,7 +125,7 @@ function func_cls_cpp_inference(){
if [ ${use_mkldnn} = "False" ] && [ ${_flag_quant} = "True" ]; then
precison="int8"
fi
_save_log_path="${_log_path}/cls_cpp_infer_cpu_usemkldnn_${use_mkldnn}_threads_${threads}_precision_${precision}_batchsize_${batch_size}.log"
_save_log_path="${_log_path}/cpp_infer_cpu_usemkldnn_${use_mkldnn}_threads_${threads}_precision_${precision}_batchsize_${batch_size}.log"
command="${generate_yaml_cmd} --type cls --batch_size ${batch_size} --mkldnn ${use_mkldnn} --gpu ${use_gpu} --cpu_thread ${threads} --tensorrt False --precision ${precision} --data_dir ${_img_dir} --benchmark True --cls_model_dir ${cpp_infer_model_dir} --gpu_id ${GPUID}"
eval $command
@ -149,7 +149,7 @@ function func_cls_cpp_inference(){
continue
fi
for batch_size in ${cpp_batch_size_list[*]}; do
_save_log_path="${_log_path}/cls_cpp_infer_gpu_usetrt_${use_trt}_precision_${precision}_batchsize_${batch_size}.log"
_save_log_path="${_log_path}/cpp_infer_gpu_usetrt_${use_trt}_precision_${precision}_batchsize_${batch_size}.log"
command="${generate_yaml_cmd} --type cls --batch_size ${batch_size} --mkldnn False --gpu ${use_gpu} --cpu_thread 1 --tensorrt ${use_trt} --precision ${precision} --data_dir ${_img_dir} --benchmark True --cls_model_dir ${cpp_infer_model_dir} --gpu_id ${GPUID}"
eval $command
command="${_script} > ${_save_log_path} 2>&1"

2
test_tipc/test_serving_infer_python.sh
View File

@ -310,7 +310,7 @@ echo "################### run test ###################"
export Count=0
IFS="|"
if [[ ${model_name} =~ "ShiTu" ]]; then
if [[ ${model_name} = "PPShiTu" ]]; then
func_serving_rec
else
func_serving_cls