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未验证 提交 8b8d3e2c 编写于 作者: H HydrogenSulfate 提交者： GitHub
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Merge pull request #2129 from HydrogenSulfate/fix_2022_7_4 

Fix TIPC bugs
上级 5b1c5eee 4f79d00c
隐藏空白更改
内联 并排
Showing with 88 addition and 65 deletion
test_tipc/config/GeneralRecognition/GeneralRecognition_PPLCNet_x2_5_train_linux_gpu_fleet_normal_infer_python_linux_gpu_cpu.txt → test_tipc/configs/GeneralRecognition/GeneralRecognition_PPLCNet_x2_5_train_linux_gpu_fleet_normal_infer_python_linux_gpu_cpu.txt
浏览文件 @ 8b8d3e2c
......@@ -38,16 +38,16 @@ infer_model:../inference/
infer_export:True
infer_quant:Fasle
inference:python/predict_rec.py -c configs/inference_rec.yaml
-o Global.use_gpu: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.use_gpu:True|False
-o Global.enable_mkldnn:False
-o Global.cpu_num_threads:1
-o Global.batch_size:1
-o Global.use_tensorrt:False
-o Global.use_fp16:False
-o Global.rec_inference_model_dir:../inference
-o Global.infer_imgs:../dataset/Aliproduct/demo_test/
-o Global.save_log_path:null
-o Global.benchmark:True
-o Global.benchmark:False
null:null
null:null
===========================infer_benchmark_params==========================
......
test_tipc/config/PP-ShiTu/PPShiTu_general_rec_linux_gpu_normal_normal_paddle2onnx_python_linux_cpu.txt → test_tipc/configs/PP-ShiTu/PPShiTu_general_rec_linux_gpu_normal_normal_paddle2onnx_python_linux_cpu.txt
浏览文件 @ 8b8d3e2c
===========================paddle2onnx_params===========================
model_name:PP-ShiTu_general_rec
model_name:GeneralRecognition_PPLCNet_x2_5
python:python3.7
2onnx: paddle2onnx
--model_dir:./deploy/models/general_PPLCNet_x2_5_lite_v1.0_infer/
......@@ -9,8 +9,8 @@ python:python3.7
--opset_version:10
--enable_onnx_checker:True
inference_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/rec/models/inference/general_PPLCNet_x2_5_lite_v1.0_infer.tar
inference:./python/predict_cls.py
inference:./python/predict_rec.py
Global.use_onnx:True
Global.inference_model_dir:./models/general_PPLCNet_x2_5_lite_v1.0_infer
Global.rec_inference_model_dir:./models/general_PPLCNet_x2_5_lite_v1.0_infer
Global.use_gpu:False
-c:configs/inference_cls.yaml
\ No newline at end of file
-c:configs/inference_rec.yaml
\ No newline at end of file
test_tipc/config/PPHGNet/PPHGNet_small_train_linux_gpu_fleet_normal_infer_python_linux_gpu_cpu.txt → test_tipc/configs/PPHGNet/PPHGNet_small_train_linux_gpu_fleet_normal_infer_python_linux_gpu_cpu.txt
浏览文件 @ 8b8d3e2c
......@@ -38,16 +38,16 @@ infer_model:../inference/
infer_export:True
infer_quant:Fasle
inference:python/predict_cls.py -c configs/inference_cls.yaml -o PreProcess.transform_ops.0.ResizeImage.resize_short=236
-o Global.use_gpu: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.use_gpu:True|False
-o Global.enable_mkldnn:False
-o Global.cpu_num_threads:1
-o Global.batch_size:1
-o Global.use_tensorrt:False
-o Global.use_fp16:False
-o Global.inference_model_dir:../inference
-o Global.infer_imgs:../dataset/ILSVRC2012/val
-o Global.infer_imgs:../dataset/ILSVRC2012/val/ILSVRC2012_val_00000001.JPEG
-o Global.save_log_path:null
-o Global.benchmark:True
-o Global.benchmark:False
null:null
===========================infer_benchmark_params==========================
random_infer_input:[{float32,[3,224,224]}]
test_tipc/config/PPLCNet/PPLCNet_x1_0_train_linux_gpu_fleet_normal_infer_python_linux_gpu_cpu.txt → test_tipc/configs/PPLCNet/PPLCNet_x1_0_train_linux_gpu_fleet_normal_infer_python_linux_gpu_cpu.txt
浏览文件 @ 8b8d3e2c
......@@ -38,16 +38,16 @@ infer_model:../inference/
infer_export:True
infer_quant:Fasle
inference:python/predict_cls.py -c configs/inference_cls.yaml
-o Global.use_gpu: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.use_gpu:True|False
-o Global.enable_mkldnn:False
-o Global.cpu_num_threads:1
-o Global.batch_size:1
-o Global.use_tensorrt:False
-o Global.use_fp16:False
-o Global.inference_model_dir:../inference
-o Global.infer_imgs:../dataset/ILSVRC2012/val
-o Global.infer_imgs:../dataset/ILSVRC2012/val/ILSVRC2012_val_00000001.JPEG
-o Global.save_log_path:null
-o Global.benchmark:True
-o Global.benchmark:False
null:null
===========================infer_benchmark_params==========================
random_infer_input:[{float32,[3,224,224]}]
\ No newline at end of file
test_tipc/config/PPLCNetV2/PPLCNetV2_base_train_linux_gpu_fleet_normal_infer_python_linux_gpu_cpu.txt → test_tipc/configs/PPLCNetV2/PPLCNetV2_base_train_linux_gpu_fleet_normal_infer_python_linux_gpu_cpu.txt
浏览文件 @ 8b8d3e2c
......@@ -38,16 +38,16 @@ infer_model:../inference/
infer_export:True
infer_quant:Fasle
inference:python/predict_cls.py -c configs/inference_cls.yaml
-o Global.use_gpu: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.use_gpu:True|False
-o Global.enable_mkldnn:False
-o Global.cpu_num_threads:1
-o Global.batch_size:1
-o Global.use_tensorrt:False
-o Global.use_fp16:False
-o Global.inference_model_dir:../inference
-o Global.infer_imgs:../dataset/ILSVRC2012/val
-o Global.infer_imgs:../dataset/ILSVRC2012/val/ILSVRC2012_val_00000001.JPEG
-o Global.save_log_path:null
-o Global.benchmark:True
-o Global.benchmark:False
null:null
===========================infer_benchmark_params==========================
random_infer_input:[{float32,[3,224,224]}]
test_tipc/docs/benchmark_train.md
浏览文件 @ 8b8d3e2c
......@@ -9,7 +9,7 @@
```shell
# 运行格式：bash test_tipc/prepare.sh train_benchmark.txt mode
bash test_tipc/prepare.sh test_tipc/config/MobileNetV2/MobileNetV2_train_infer_python.txt benchmark_train
bash test_tipc/prepare.sh test_tipc/configs/MobileNetV2/MobileNetV2_train_infer_python.txt benchmark_train
```
## 1.2 功能测试
......@@ -17,14 +17,14 @@ bash test_tipc/prepare.sh test_tipc/config/MobileNetV2/MobileNetV2_train_infer_p
```shell
# 运行格式：bash test_tipc/benchmark_train.sh train_benchmark.txt mode
bash test_tipc/benchmark_train.sh test_tipc/config/MobileNetV2/MobileNetV2_train_infer_python.txt benchmark_train
bash test_tipc/benchmark_train.sh test_tipc/configs/MobileNetV2/MobileNetV2_train_infer_python.txt benchmark_train
```
`test_tipc/benchmark_train.sh`支持根据传入的第三个参数实现只运行某一个训练配置，如下：
```shell
# 运行格式：bash test_tipc/benchmark_train.sh train_benchmark.txt mode params
bash test_tipc/benchmark_train.sh test_tipc/config/MobileNetV2/MobileNetV2_train_infer_python.txt benchmark_train dynamic_bs8_fp32_DP_N1C1
bash test_tipc/benchmark_train.sh test_tipc/configs/MobileNetV2/MobileNetV2_train_infer_python.txt benchmark_train dynamic_bs8_fp32_DP_N1C1
```
dynamic_bs8_fp32_DP_N1C1为test_tipc/benchmark_train.sh传入的参数，格式如下：
`${modeltype}_${batch_size}_${fp_item}_${run_mode}_${device_num}`
......@@ -33,7 +33,7 @@ dynamic_bs8_fp32_DP_N1C1为test_tipc/benchmark_train.sh传入的参数，格式
## 2. 日志输出
运行后将保存模型的训练日志和解析日志，使用 `test_tipc/config/MobileNetV2/MobileNetV2_train_infer_python.txt` 参数文件的训练日志解析结果是：
运行后将保存模型的训练日志和解析日志，使用 `test_tipc/configs/MobileNetV2/MobileNetV2_train_infer_python.txt` 参数文件的训练日志解析结果是：
```
{"model_branch": "dygaph", "model_commit": "7c39a1996b19087737c05d883fd346d2f39dbcc0", "model_name": "cls_MobileNetV2_bs8_fp32_SingleP_DP", "batch_size": 8, "fp_item": "fp32", "run_process_type": "SingleP", "run_mode": "DP", "convergence_value": "5.413110", "convergence_key": "loss:", "ips": 19.333, "speed_unit": "samples/s", "device_num": "N1C1", "model_run_time": "0", "frame_commit": "8cc09552473b842c651ead3b9848d41827a3dbab", "frame_version": "0.0.0"}
......
test_tipc/docs/test_inference_cpp.md
浏览文件 @ 8b8d3e2c
......@@ -246,7 +246,7 @@ make -j
* 可执行以下命令，自动完成上述准备环境中的所需内容
```shell
bash test_tipc/prepare.sh test_tipc/config/ResNet/ResNet50_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt cpp_infer
bash test_tipc/prepare.sh test_tipc/configs/ResNet/ResNet50_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt cpp_infer
```
### 2.3 功能测试
......@@ -260,7 +260,7 @@ 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 cpp_infer
bash test_tipc/test_inference_cpp.sh test_tipc/configs/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。
......
test_tipc/docs/test_lite_arm_cpu_cpp.md
浏览文件 @ 8b8d3e2c
......@@ -15,7 +15,7 @@ Lite_arm_cpp_cpu 预测功能测试的主程序为`test_lite_arm_cpu_cpp.sh`，
先运行 `prepare_lite_arm_cpu_cpp.sh` 准备数据和模型，然后运行 `test_lite_arm_cpu_cpp.sh` 进行测试，最终在 `./output` 目录下生成 `lite_*.log` 后缀的日志文件。
```shell
bash test_tipc/prepare_lite_arm_cpu_cpp.sh test_tipc/config/MobileNetV3/MobileNetV3_large_x1_0_lite_arm_cpu_cpp.txt
bash test_tipc/prepare_lite_arm_cpu_cpp.sh test_tipc/configs/MobileNetV3/MobileNetV3_large_x1_0_lite_arm_cpu_cpp.txt
```
运行预测指令后，在`./output`文件夹下自动会保存运行日志，包括以下文件：
......
test_tipc/docs/test_paddle2onnx.md
浏览文件 @ 8b8d3e2c
......@@ -21,10 +21,10 @@ PaddleServing预测功能测试的主程序为`test_paddle2onnx.sh`，可以测
下方展示以PPHGNet_small为例的测试命令与结果。
```shell
bash test_tipc/prepare.sh ./test_tipc/config/ResNet/ResNet50_linux_gpu_normal_normal_paddle2onnx_python_linux_cpu.txt paddle2onnx_infer
bash test_tipc/prepare.sh ./test_tipc/configs/ResNet/ResNet50_linux_gpu_normal_normal_paddle2onnx_python_linux_cpu.txt paddle2onnx_infer
# 用法:
bash test_tipc/test_paddle2onnx.sh ./test_tipc/config/ResNet/ResNet50_linux_gpu_normal_normal_paddle2onnx_python_linux_cpu.txt
bash test_tipc/test_paddle2onnx.sh ./test_tipc/configs/ResNet/ResNet50_linux_gpu_normal_normal_paddle2onnx_python_linux_cpu.txt
```
#### 运行结果
......
test_tipc/docs/test_train_fleet_inference_python.md
浏览文件 @ 8b8d3e2c
......@@ -34,7 +34,7 @@ Linux GPU/CPU 多机多卡训练推理测试的主程序为`test_train_inference
#### 2.1.1 修改配置文件
首先，修改配置文件`test_tipc/config/PPLCNet/PPLCNet_x1_0_train_linux_gpu_fleet_normal_infer_python_linux_gpu_cpu.txt`中的`gpu_list`设置：假设两台机器的`ip`地址分别为`192.168.0.1`和`192.168.0.2`，则对应的配置文件`gpu_list`字段需要修改为`gpu_list:192.168.0.1,192.168.0.2;0,1`。
首先，修改配置文件`test_tipc/configs/PPLCNet/PPLCNet_x1_0_train_linux_gpu_fleet_normal_infer_python_linux_gpu_cpu.txt`中的`gpu_list`设置：假设两台机器的`ip`地址分别为`192.168.0.1`和`192.168.0.2`，则对应的配置文件`gpu_list`字段需要修改为`gpu_list:192.168.0.1,192.168.0.2;0,1`。
**`ip`地址查看命令为`ifconfig`，在`inet addr:`字段后的即为ip地址**。
......@@ -44,7 +44,7 @@ Linux GPU/CPU 多机多卡训练推理测试的主程序为`test_train_inference
运行`prepare.sh`准备数据和模型，数据准备命令如下所示。
```shell
bash test_tipc/prepare.sh test_tipc/config/PPLCNet/PPLCNet_x1_0_train_linux_gpu_fleet_normal_infer_python_linux_gpu_cpu.txt lite_train_lite_infer
bash test_tipc/prepare.sh test_tipc/configs/PPLCNet/PPLCNet_x1_0_train_linux_gpu_fleet_normal_infer_python_linux_gpu_cpu.txt lite_train_lite_infer
```
**注意：** 由于是多机训练，这里需要在所有节点上都运行一次启动上述命令来准备数据。
......@@ -60,7 +60,7 @@ export FLAGS_START_PORT=17000
接下来就可以开始执行测试，命令如下所示。
```shell
bash test_tipc/test_train_inference_python.sh test_tipc/config/PPLCNet/PPLCNet_x1_0_train_linux_gpu_fleet_normal_infer_python_linux_gpu_cpu.txt
bash test_tipc/test_train_inference_python.sh test_tipc/configs/PPLCNet/PPLCNet_x1_0_train_linux_gpu_fleet_normal_infer_python_linux_gpu_cpu.txt
```
**注意：** 由于是多机训练，这里需要在所有的节点上均运行启动上述命令进行测试。
......
test_tipc/docs/test_train_inference_python.md
浏览文件 @ 8b8d3e2c
......@@ -58,36 +58,36 @@ Linux端基础训练预测功能测试的主程序为`test_train_inference_pytho
- 模式1：lite_train_lite_infer，使用少量数据训练，用于快速验证训练到预测的走通流程，不验证精度和速度；
```shell
bash test_tipc/prepare.sh ./test_tipc/config/ResNet/ResNet50_vd_train_infer_python.txt 'lite_train_lite_infer'
bash test_tipc/test_train_inference_python.sh ./test_tipc/config/ResNet/ResNet50_vd_train_infer_python.txt 'lite_train_lite_infer'
bash test_tipc/prepare.sh ./test_tipc/configs/ResNet/ResNet50_vd_train_infer_python.txt 'lite_train_lite_infer'
bash test_tipc/test_train_inference_python.sh ./test_tipc/configs/ResNet/ResNet50_vd_train_infer_python.txt 'lite_train_lite_infer'
```
- 模式2：lite_train_whole_infer，使用少量数据训练，一定量数据预测，用于验证训练后的模型执行预测，预测速度是否合理；
```shell
bash test_tipc/prepare.sh ./test_tipc/config/ResNet/ResNet50_vd_train_infer_python.txt 'lite_train_whole_infer'
bash test_tipc/test_train_inference_python.sh ./test_tipc/config/ResNet/ResNet50_vd_train_infer_python.txt 'lite_train_whole_infer'
bash test_tipc/prepare.sh ./test_tipc/configs/ResNet/ResNet50_vd_train_infer_python.txt 'lite_train_whole_infer'
bash test_tipc/test_train_inference_python.sh ./test_tipc/configs/ResNet/ResNet50_vd_train_infer_python.txt 'lite_train_whole_infer'
```
- 模式3：whole_infer，不训练，全量数据预测，走通开源模型评估、动转静，检查inference model预测时间和精度;
```shell
bash test_tipc/prepare.sh ./test_tipc/config/ResNet/ResNet50_vd_train_infer_python.txt 'whole_infer'
bash test_tipc/prepare.sh ./test_tipc/configs/ResNet/ResNet50_vd_train_infer_python.txt 'whole_infer'
# 用法1:
bash test_tipc/test_train_inference_python.sh ./test_tipc/config/ResNet/ResNet50_vd_train_infer_python.txt 'whole_infer'
bash test_tipc/test_train_inference_python.sh ./test_tipc/configs/ResNet/ResNet50_vd_train_infer_python.txt 'whole_infer'
# 用法2: 指定GPU卡预测，第三个传入参数为GPU卡号
bash test_tipc/test_train_inference_python.sh ./test_tipc/config/ResNet/ResNet50_vd_train_infer_python.txt 'whole_infer' '1'
bash test_tipc/test_train_inference_python.sh ./test_tipc/configs/ResNet/ResNet50_vd_train_infer_python.txt 'whole_infer' '1'
```
- 模式4：whole_train_whole_infer，CE： 全量数据训练，全量数据预测，验证模型训练精度，预测精度，预测速度；
```shell
bash test_tipc/prepare.sh ./test_tipc/config/ResNet/ResNet50_vd_train_infer_python.txt 'whole_train_whole_infer'
bash test_tipc/test_train_inference_python.sh ./test_tipc/config/ResNet/ResNet50_vd_train_infer_python.txt 'whole_train_whole_infer'
bash test_tipc/prepare.sh ./test_tipc/configs/ResNet/ResNet50_vd_train_infer_python.txt 'whole_train_whole_infer'
bash test_tipc/test_train_inference_python.sh ./test_tipc/configs/ResNet/ResNet50_vd_train_infer_python.txt 'whole_train_whole_infer'
```
- 模式5: klquant_whole_infer，测试离线量化；
```shell
bash test_tipc/prepare.sh ./test_tipc/config/ResNet/ResNet50_vd_train_infer_python.txt 'klquant_whole_infer'
bash test_tipc/test_train_inference_python.sh ./test_tipc/config/ResNet/ResNet50_vd_train_infer_python.txt 'klquant_whole_infer'
bash test_tipc/prepare.sh ./test_tipc/configs/ResNet/ResNet50_vd_train_infer_python.txt 'klquant_whole_infer'
bash test_tipc/test_train_inference_python.sh ./test_tipc/configs/ResNet/ResNet50_vd_train_infer_python.txt 'klquant_whole_infer'
```
......
test_tipc/docs/test_train_pact_inference_python.md
浏览文件 @ 8b8d3e2c
......@@ -79,7 +79,7 @@ Linux GPU/CPU PACT量化训练推理测试的主程序为`test_train_inference_p
### 2.2 准备数据和模型
```bash
bash test_tipc/prepare.sh test_tipc/config/PPLCNetV2/PPLCNetV2_base_train_pact_infer_python.txt lite_train_lite_infer
bash test_tipc/prepare.sh test_tipc/configs/PPLCNetV2/PPLCNetV2_base_train_pact_infer_python.txt lite_train_lite_infer
```
在线量化的操作流程，可参考[文档](../../deploy/slim/README.md)。
......@@ -89,7 +89,7 @@ bash test_tipc/prepare.sh test_tipc/config/PPLCNetV2/PPLCNetV2_base_train_pact_i
以`MobileNetV3_large_x1_0`的`Linux GPU/CPU PACT在线量化训练推理测试`为例，命令如下所示。
```bash
bash test_tipc/test_train_inference_python.sh test_tipc/config/PPLCNetV2/PPLCNetV2_base_train_pact_infer_python.txt lite_train_lite_infer
bash test_tipc/test_train_inference_python.sh test_tipc/configs/PPLCNetV2/PPLCNetV2_base_train_pact_infer_python.txt lite_train_lite_infer
```
输出结果如下，表示命令运行成功。
......
test_tipc/docs/test_train_ptq_inference_python.md
浏览文件 @ 8b8d3e2c
......@@ -80,7 +80,7 @@ Linux GPU/CPU KL离线量化推理测试的主程序为`test_ptq_inference_pytho
### 2.2 准备数据和模型
```bash
bash test_tipc/prepare.sh test_tipc/config/MobileNetV3/MobileNetV3_large_x1_0_train_ptq_infer_python.txt whole_infer
bash test_tipc/prepare.sh test_tipc/configs/MobileNetV3/MobileNetV3_large_x1_0_train_ptq_infer_python.txt whole_infer
```
离线量化的操作流程，可参考[文档](../../deploy/slim/README.md)。
......@@ -90,7 +90,7 @@ bash test_tipc/prepare.sh test_tipc/config/MobileNetV3/MobileNetV3_large_x1_0_tr
以`MobileNetV3_large_x1_0`的`Linux GPU/CPU KL离线量化训练推理测试`为例，命令如下所示。
```bash
bash test_tipc/test_ptq_inference_python.sh test_tipc/config/MobileNetV3/MobileNetV3_large_x1_0_train_ptq_infer_python.txt whole_infer
bash test_tipc/test_ptq_inference_python.sh test_tipc/configs/MobileNetV3/MobileNetV3_large_x1_0_train_ptq_infer_python.txt whole_infer
```
输出结果如下，表示命令运行成功。
......
test_tipc/prepare.sh
浏览文件 @ 8b8d3e2c
......@@ -85,12 +85,18 @@ if [[ ${MODE} = "cpp_infer" ]]; then
if [[ ! -d "./deploy/cpp/paddle_inference/" ]]; then
pushd ./deploy/cpp/
PADDLEInfer=$3
if [ "" = "$PADDLEInfer" ];then
if [ "" = "$PADDLEInfer" ]; then
wget -nc https://paddle-inference-lib.bj.bcebos.com/2.2.2/cxx_c/Linux/GPU/x86-64_gcc8.2_avx_mkl_cuda10.1_cudnn7.6.5_trt6.0.1.5/paddle_inference.tgz --no-check-certificate
tar xf paddle_inference.tgz
else
wget -nc ${PADDLEInfer} --no-check-certificate
tar_name=$(func_get_url_file_name "$PADDLEInfer")
tar xf ${tar_name}
paddle_inference_install_dir=${tar_name%.*}
if [ ! -d "paddle_inference" ]; then
ln -s ${paddle_inference_install_dir} paddle_inference
fi
fi
tar xf paddle_inference.tgz
popd
fi
if [[ $FILENAME == *infer_cpp_linux_gpu_cpu.txt ]]; then
......@@ -311,6 +317,22 @@ if [[ ${MODE} = "paddle2onnx_infer" ]]; then
${python_name} -m pip install paddle2onnx
${python_name} -m pip install onnxruntime
if [[ ${model_name} =~ "GeneralRecognition" ]]; then
cd dataset
rm -rf Aliproduct
rm -rf train_reg_all_data.txt
rm -rf demo_train
wget -nc https://paddle-imagenet-models-name.bj.bcebos.com/data/whole_chain/tipc_shitu_demo_data.tar --no-check-certificate
tar -xf tipc_shitu_demo_data.tar
ln -s tipc_shitu_demo_data Aliproduct
ln -s tipc_shitu_demo_data/demo_train.txt train_reg_all_data.txt
ln -s tipc_shitu_demo_data/demo_train demo_train
cd tipc_shitu_demo_data
ln -s demo_test.txt val_list.txt
cd ../../
eval "wget -nc $model_url_value --no-check-certificate"
mv general_PPLCNet_x2_5_pretrained_v1.0.pdparams GeneralRecognition_PPLCNet_x2_5_pretrained.pdparams
fi
cd deploy
mkdir models
cd models
......
test_tipc/test_paddle2onnx.sh
浏览文件 @ 8b8d3e2c
......@@ -2,6 +2,7 @@
source test_tipc/common_func.sh
FILENAME=$1
MODE=$2
# parser params
dataline=$(awk 'NR==1, NR==16{print}' $FILENAME)
......@@ -35,7 +36,7 @@ inference_hardware_value=$(func_parser_value "${lines[14]}")
inference_config_key=$(func_parser_key "${lines[15]}")
inference_config_value=$(func_parser_value "${lines[15]}")
LOG_PATH="./test_tipc/output/${model_name}"
LOG_PATH="./test_tipc/output/${model_name}/${MODE}"
mkdir -p ${LOG_PATH}
status_log="${LOG_PATH}/results_paddle2onnx.log"
......
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