Merge pull request #2106 from HydrogenSulfate/add_pact_chain

Add quant chain

ppcls/arch/slim/quant.py

@@ -48,6 +48,12 @@ def quantize_model(config, model, mode="train"):
         QUANT_CONFIG["activation_preprocess_type"] = "PACT"
         if mode in ["infer", "export"]:
             QUANT_CONFIG['activation_preprocess_type'] = None
+
+        # for rep nets, convert to reparameterized model first
+        for layer in model.sublayers():
+            if hasattr(layer, "rep"):
+                layer.rep()
+
         model.quanter = QAT(config=QUANT_CONFIG)
         model.quanter.quantize(model)
         logger.info("QAT model summary:")

ppcls/engine/engine.py

@@ -466,7 +466,7 @@ class Engine(object):
 
         # for rep nets
         for layer in self.model.sublayers():
-            if hasattr(layer, "rep"):
+            if hasattr(layer, "rep") and not getattr(layer, "is_repped"):
                 layer.rep()
 
         save_path = os.path.join(self.config["Global"]["save_inference_dir"],

test_tipc/README.md

@@ -107,6 +107,7 @@ bash test_tipc/test_train_inference_python.sh ./test_tipc/configs/MobileNetV3/Mo
 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)：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_pact_inference_python 使用](docs/test_train_pact_inference_python.md)：测试基于Python的模型PACT在线量化等基本功能。
 - [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](docs/test_lite_arm_cpu_cpp.md): 测试基于Paddle-Lite的ARM CPU端c++预测部署功能.

test_tipc/config/GeneralRecognition/GeneralRecognition_PPLCNet_x2_5_train_pact_infer_python.txt

+===========================train_params===========================
+model_name:GeneralRecognition_PPLCNet_x2_5
+python:python3.7
+gpu_list:0
+-o Global.device:gpu
+-o Global.auto_cast:null
+-o Global.epochs:lite_train_lite_infer=2|whole_train_whole_infer=100
+-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:pact_train
+norm_train:null
+pact_train:tools/train.py -c ppcls/configs/GeneralRecognition/GeneralRecognition_PPLCNet_x2_5.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 -o Slim.quant.name=pact -o Optimizer.lr.learning_rate=0.004 -o Global.pretrained_model="pretrained_model/general_PPLCNet_x2_5_pretrained_v1.0"
+fpgm_train:null
+distill_train:null
+null:null
+null:null
+##
+===========================eval_params===========================
+eval:tools/eval.py -c ppcls/configs/GeneralRecognition/GeneralRecognition_PPLCNet_x2_5.yaml -o Slim.quant.name=pact
+null:null
+##
+===========================infer_params==========================
+-o Global.save_inference_dir:./inference
+-o Global.pretrained_model:
+norm_export:null
+quant_export:tools/export_model.py -c ppcls/configs/GeneralRecognition/GeneralRecognition_PPLCNet_x2_5.yaml -o Slim.quant.name=pact
+fpgm_export:null
+distill_export:null
+kl_quant:null
+export2:null
+pretrained_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/rec/models/pretrain/general_PPLCNet_x2_5_pretrained_v1.0.pdparams
+infer_model:../inference/
+infer_export:True
+infer_quant:Fasle
+inference:python/predict_rec.py -c configs/inference_rec.yaml
+-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
+null:null
+null:null
+===========================infer_benchmark_params==========================
+random_infer_input:[{float32,[3,224,224]}]
\ No newline at end of file

test_tipc/config/MobileNetV3/MobileNetV3_large_x1_0_PACT_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt

+===========================cpp_infer_params===========================
+model_name:MobileNetV3_large_x1_0_PACT
+cpp_infer_type:cls
+cls_inference_model_dir:./MobileNetV3_large_x1_0_pact_infer/
+det_inference_model_dir:
+cls_inference_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/slim_model/MobileNetV3_large_x1_0_pact_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

test_tipc/config/MobileNetV3/MobileNetV3_large_x1_0_PACT_linux_gpu_normal_normal_serving_cpp_linux_gpu_cpu.txt

+===========================serving_params===========================
+model_name:MobileNetV3_large_x1_0_PACT
+python:python3.7
+inference_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/slim_model/MobileNetV3_large_x1_0_pact_infer.tar
+trans_model:-m paddle_serving_client.convert
+--dirname:./deploy/paddleserving/MobileNetV3_large_x1_0_pact_infer/
+--model_filename:inference.pdmodel
+--params_filename:inference.pdiparams
+--serving_server:./deploy/paddleserving/MobileNetV3_large_x1_0_pact_serving/
+--serving_client:./deploy/paddleserving/MobileNetV3_large_x1_0_pact_client/
+serving_dir:./deploy/paddleserving
+web_service:null
+--use_gpu:0|null
+pipline:test_cpp_serving_client.py

test_tipc/config/MobileNetV3/MobileNetV3_large_x1_0_PACT_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt

+===========================serving_params===========================
+model_name:MobileNetV3_large_x1_0_PACT
+python:python3.7
+inference_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/slim_model/MobileNetV3_large_x1_0_pact_infer.tar
+trans_model:-m paddle_serving_client.convert
+--dirname:./deploy/paddleserving/MobileNetV3_large_x1_0_pact_infer/
+--model_filename:inference.pdmodel
+--params_filename:inference.pdiparams
+--serving_server:./deploy/paddleserving/MobileNetV3_large_x1_0_pact_serving/
+--serving_client:./deploy/paddleserving/MobileNetV3_large_x1_0_pact_client/
+serving_dir:./deploy/paddleserving
+web_service:classification_web_service.py
+--use_gpu:0|null
+pipline:pipeline_http_client.py

test_tipc/config/MobileNetV3/MobileNetV3_large_x1_0_train_pact_infer_python.txt

+===========================train_params===========================
+model_name:MobileNetV3_large_x1_0
+python:python3.7
+gpu_list:0
+-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:pact_train
+norm_train:null
+pact_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 -o Slim.quant.name=pact -o Optimizer.lr.learning_rate=0.01 -o Global.pretrained_model="pretrained_model/MobileNetV3_large_x1_0_pretrained"
+fpgm_train:null
+distill_train:null
+to_static_train:-o Global.to_static=True
+null:null
+##
+===========================eval_params=========================== 
+eval:tools/eval.py -c ppcls/configs/ImageNet/MobileNetV3/MobileNetV3_large_x1_0.yaml -o Slim.quant.name=pact
+null:null
+##
+===========================infer_params==========================
+-o Global.save_inference_dir:./inference
+-o Global.pretrained_model:
+norm_export:null
+quant_export:tools/export_model.py -c ppcls/configs/slim/MobileNetV3_large_x1_0_quantization.yaml -o Slim.quant.name=pact
+fpgm_export:null
+distill_export:null
+kl_quant:null
+export2:null
+pretrained_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/MobileNetV3_large_x1_0_pretrained.pdparams
+infer_model:../inference/
+infer_export:True
+infer_quant:Fasle
+inference:python/predict_cls.py -c configs/inference_cls.yaml
+-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.save_log_path:null
+-o Global.benchmark:True
+null:null
+null:null
+===========================train_benchmark_params==========================
+batch_size:256|640
+fp_items:fp32
+epoch:1
+--profiler_options:batch_range=[10,20];state=GPU;tracer_option=Default;profile_path=model.profile
+flags:FLAGS_eager_delete_tensor_gb=0.0;FLAGS_fraction_of_gpu_memory_to_use=0.98;FLAGS_conv_workspace_size_limit=4096
+===========================infer_benchmark_params==========================
+random_infer_input:[{float32,[3,224,224]}]
\ No newline at end of file

test_tipc/config/PP-ShiTu/PPShiTu_general_rec_PACT_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt

+===========================cpp_infer_params===========================
+model_name:GeneralRecognition_PPLCNet_x2_5_PACT
+cpp_infer_type:cls
+cls_inference_model_dir:./general_PPLCNet_x2_5_lite_v1.0_pact_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_pact_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

test_tipc/config/PP-ShiTu/PPShiTu_general_rec_PACT_linux_gpu_normal_normal_serving_cpp_linux_gpu_cpu.txt

+===========================serving_params===========================
+model_name:GeneralRecognition_PPLCNet_x2_5_PACT
+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_pact_infer.tar
+trans_model:-m paddle_serving_client.convert
+--dirname:./deploy/paddleserving/general_PPLCNet_x2_5_lite_v1.0_pact_infer/
+--model_filename:inference.pdmodel
+--params_filename:inference.pdiparams
+--serving_server:./deploy/paddleserving/GeneralRecognition_PPLCNet_x2_5_pact_serving/
+--serving_client:./deploy/paddleserving/GeneralRecognition_PPLCNet_x2_5_pact_client/
+serving_dir:./deploy/paddleserving
+web_service:null
+--use_gpu:0|null
+pipline:test_cpp_serving_client.py

test_tipc/config/PP-ShiTu/PPShiTu_general_rec_PACT_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt

+===========================serving_params===========================
+model_name:GeneralRecognition_PPLCNet_x2_5_PACT
+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_pact_infer.tar
+trans_model:-m paddle_serving_client.convert
+--dirname:./deploy/paddleserving/general_PPLCNet_x2_5_lite_v1.0_pact_infer/
+--model_filename:inference.pdmodel
+--params_filename:inference.pdiparams
+--serving_server:./deploy/paddleserving/GeneralRecognition_PPLCNet_x2_5_pact_serving/
+--serving_client:./deploy/paddleserving/GeneralRecognition_PPLCNet_x2_5_pact_client/
+serving_dir:./deploy/paddleserving
+web_service:classification_web_service.py
+--use_gpu:0|null
+pipline:pipeline_http_client.py

test_tipc/config/PPHGNet/PPHGNet_small_PACT_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt

+===========================cpp_infer_params===========================
+model_name:PPHGNet_small_PACT
+cpp_infer_type:cls
+cls_inference_model_dir:./PPHGNet_small_pact_infer/
+det_inference_model_dir:
+cls_inference_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/slim_model/PPHGNet_small_pact_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

test_tipc/config/PPHGNet/PPHGNet_small_PACT_linux_gpu_normal_normal_serving_cpp_linux_gpu_cpu.txt

+===========================serving_params===========================
+model_name:PPHGNet_small_PACT
+python:python3.7
+inference_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/slim_model/PPHGNet_small_pact_infer.tar
+trans_model:-m paddle_serving_client.convert
+--dirname:./deploy/paddleserving/PPHGNet_small_pact_infer/
+--model_filename:inference.pdmodel
+--params_filename:inference.pdiparams
+--serving_server:./deploy/paddleserving/PPHGNet_small_pact_serving/
+--serving_client:./deploy/paddleserving/PPHGNet_small_pact_client/
+serving_dir:./deploy/paddleserving
+web_service:null
+--use_gpu:0|null
+pipline:test_cpp_serving_client.py

test_tipc/config/PPHGNet/PPHGNet_small_PACT_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt

+===========================serving_params===========================
+model_name:PPHGNet_small_PACT
+python:python3.7
+inference_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/slim_model/PPHGNet_small_pact_infer.tar
+trans_model:-m paddle_serving_client.convert
+--dirname:./deploy/paddleserving/PPHGNet_small_pact_infer/
+--model_filename:inference.pdmodel
+--params_filename:inference.pdiparams
+--serving_server:./deploy/paddleserving/PPHGNet_small_pact_serving/
+--serving_client:./deploy/paddleserving/PPHGNet_small_pact_client/
+serving_dir:./deploy/paddleserving
+web_service:classification_web_service.py
+--use_gpu:0|null
+pipline:pipeline_http_client.py

test_tipc/config/PPHGNet/PPHGNet_small_train_pact_infer_python.txt

+===========================train_params===========================
+model_name:PPHGNet_small
+python:python3.7
+gpu_list:0
+-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:pact_train
+norm_train:null
+pact_train:tools/train.py -c ppcls/configs/ImageNet/PPHGNet/PPHGNet_small.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 -o Slim.quant.name=pact -o Optimizer.lr.learning_rate=0.01 -o Global.pretrained_model="pretrained_model/PPHGNet_small_pretrained" -o AMP=None
+fpgm_train:null
+distill_train:null
+null:null
+null:null
+##
+===========================eval_params=========================== 
+eval:tools/eval.py -c ppcls/configs/ImageNet/PPHGNet/PPHGNet_small.yaml -o Slim.quant.name=pact
+null:null
+##
+===========================infer_params==========================
+-o Global.save_inference_dir:./inference
+-o Global.pretrained_model:
+norm_export:null
+quant_export:tools/export_model.py -c ppcls/configs/ImageNet/PPHGNet/PPHGNet_small.yaml -o Slim.quant.name=pact
+fpgm_export:null
+distill_export:null
+kl_quant:null
+export2:null
+pretrained_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/PPHGNet_small_pretrained.pdparams
+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: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.save_log_path:null
+-o Global.benchmark:True
+null:null
+===========================infer_benchmark_params==========================
+random_infer_input:[{float32,[3,224,224]}]

test_tipc/config/PPHGNet/PPHGNet_tiny_train_pact_infer_python.txt

+===========================train_params===========================
+model_name:PPHGNet_tiny
+python:python3.7
+gpu_list:0
+-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:pact_train
+norm_train:null
+pact_train:tools/train.py -c ppcls/configs/ImageNet/PPHGNet/PPHGNet_tiny.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 -o Slim.quant.name=pact -o Optimizer.lr.learning_rate=0.01 -o Global.pretrained_model="pretrained_model/PPHGNet_tiny_pretrained" -o AMP=None
+fpgm_train:null
+distill_train:null
+null:null
+null:null
+##
+===========================eval_params===========================
+eval:tools/eval.py -c ppcls/configs/ImageNet/PPHGNet/PPHGNet_tiny.yaml -o Slim.quant.name=pact
+null:null
+##
+===========================infer_params==========================
+-o Global.save_inference_dir:./inference
+-o Global.pretrained_model:
+norm_export:null
+quant_export:tools/export_model.py -c ppcls/configs/ImageNet/PPHGNet/PPHGNet_tiny.yaml -o Slim.quant.name=pact
+fpgm_export:null
+distill_export:null
+kl_quant:null
+export2:null
+pretrained_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/PPHGNet_tiny_pretrained.pdparams
+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: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.save_log_path:null
+-o Global.benchmark:True
+null:null
+===========================infer_benchmark_params==========================
+random_infer_input:[{float32,[3,224,224]}]

test_tipc/config/PPHGNet/PPHGNet_tiny_train_ptq_infer_python.txt

+===========================train_params===========================
+model_name:PPHGNet_tiny
+python:python3.7
+gpu_list:0
+-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
+norm_train:tools/train.py -c ppcls/configs/ImageNet/PPHGNet/PPHGNet_tiny.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:null
+fpgm_train:null
+distill_train:null
+null:null
+null:null
+##
+===========================eval_params=========================== 
+eval:tools/eval.py -c ppcls/configs/ImageNet/PPHGNet/PPHGNet_tiny.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/PPHGNet/PPHGNet_tiny.yaml
+quant_export:null
+fpgm_export:null
+distill_export:null
+kl_quant:deploy/slim/quant_post_static.py -c ppcls/configs/ImageNet/PPHGNet/PPHGNet_tiny.yaml -o Global.save_inference_dir=./PPHGNet_tiny_infer
+export2:null
+pretrained_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/PPHGNet_tiny_infer.tar
+infer_model:./PPHGNet_tiny_infer/
+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: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:../deploy/images/ImageNet/ILSVRC2012_val_00000010.jpeg
+-o Global.save_log_path:null
+-o Global.benchmark:False
+null:null
+===========================infer_benchmark_params==========================
+random_infer_input:[{float32,[3,224,224]}]

test_tipc/config/PPLCNet/PPLCNet_x0_25_train_pact_infer_python.txt

+===========================train_params===========================
+model_name:PPLCNet_x0_25
+python:python3.7
+gpu_list:0
+-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:pact_train
+norm_train:null
+pact_train:tools/train.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x0_25.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 -o Slim.quant.name=pact -o Optimizer.lr.learning_rate=0.08 -o Global.pretrained_model="pretrained_model/PPLCNet_x0_25_pretrained"
+fpgm_train:null
+distill_train:null
+null:null
+null:null
+##
+===========================eval_params=========================== 
+eval:tools/eval.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x0_25.yaml -o Slim.quant.name=pact
+null:null
+##
+===========================infer_params==========================
+-o Global.save_inference_dir:./inference
+-o Global.pretrained_model:
+norm_export:null
+quant_export:tools/export_model.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x0_25.yaml -o Slim.quant.name=pact
+fpgm_export:null
+distill_export:null
+kl_quant:null
+export2:null
+pretrained_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/PPLCNet_x0_25_pretrained.pdparams
+infer_model:../inference/
+infer_export:True
+infer_quant:Fasle
+inference:python/predict_cls.py -c configs/inference_cls.yaml
+-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.save_log_path:null
+-o Global.benchmark:True
+null:null
+===========================infer_benchmark_params==========================
+random_infer_input:[{float32,[3,224,224]}]
\ No newline at end of file

test_tipc/config/PPLCNet/PPLCNet_x0_25_train_ptq_infer_python.txt

+===========================train_params===========================
+model_name:PPLCNet_x0_25
+python:python3.7
+gpu_list:0
+-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
+norm_train:tools/train.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x0_25.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:null
+fpgm_train:null
+distill_train:null
+null:null
+null:null
+##
+===========================eval_params=========================== 
+eval:tools/eval.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x0_25.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/PPLCNet/PPLCNet_x0_25.yaml
+quant_export:null
+fpgm_export:null
+distill_export:null
+kl_quant:deploy/slim/quant_post_static.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x0_25.yaml -o Global.save_inference_dir=./PPLCNet_x0_25_infer
+export2:null
+pretrained_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/PPLCNet_x0_25_infer.tar
+infer_model:./PPLCNet_x0_25_infer/
+infer_export:True
+infer_quant:Fasle
+inference:python/predict_cls.py -c configs/inference_cls.yaml
+-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:../deploy/images/ImageNet/ILSVRC2012_val_00000010.jpeg
+-o Global.save_log_path:null
+-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/PPLCNet/PPLCNet_x0_35_train_pact_infer_python.txt

+===========================train_params===========================
+model_name:PPLCNet_x0_35
+python:python3.7
+gpu_list:0
+-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:pact_train
+norm_train:null
+pact_train:tools/train.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x0_35.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 -o Slim.quant.name=pact -o Optimizer.lr.learning_rate=0.08 -o Global.pretrained_model="pretrained_model/PPLCNet_x0_35_pretrained"
+fpgm_train:null
+distill_train:null
+null:null
+null:null
+##
+===========================eval_params=========================== 
+eval:tools/eval.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x0_35.yaml -o Slim.quant.name=pact
+null:null
+##
+===========================infer_params==========================
+-o Global.save_inference_dir:./inference
+-o Global.pretrained_model:
+norm_export:null
+quant_export:tools/export_model.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x0_35.yaml -o Slim.quant.name=pact
+fpgm_export:null
+distill_export:null
+kl_quant:null
+export2:null
+pretrained_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/PPLCNet_x0_35_pretrained.pdparams
+infer_model:../inference/
+infer_export:True
+infer_quant:Fasle
+inference:python/predict_cls.py -c configs/inference_cls.yaml
+-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.save_log_path:null
+-o Global.benchmark:True
+null:null
+===========================infer_benchmark_params==========================
+random_infer_input:[{float32,[3,224,224]}]
\ No newline at end of file

test_tipc/config/PPLCNet/PPLCNet_x0_35_train_ptq_infer_python.txt

+===========================train_params===========================
+model_name:PPLCNet_x0_35
+python:python3.7
+gpu_list:0
+-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
+norm_train:tools/train.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x0_35.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:null
+fpgm_train:null
+distill_train:null
+null:null
+null:null
+##
+===========================eval_params=========================== 
+eval:tools/eval.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x0_35.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/PPLCNet/PPLCNet_x0_35.yaml
+quant_export:null
+fpgm_export:null
+distill_export:null
+kl_quant:deploy/slim/quant_post_static.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x0_35.yaml -o Global.save_inference_dir=./PPLCNet_x0_35_infer
+export2:null
+pretrained_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/PPLCNet_x0_35_infer.tar
+infer_model:./PPLCNet_x0_35_infer/
+infer_export:True
+infer_quant:Fasle
+inference:python/predict_cls.py -c configs/inference_cls.yaml
+-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:../deploy/images/ImageNet/ILSVRC2012_val_00000010.jpeg
+-o Global.save_log_path:null
+-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/PPLCNet/PPLCNet_x0_5_train_pact_infer_python.txt

+===========================train_params===========================
+model_name:PPLCNet_x0_5
+python:python3.7
+gpu_list:0
+-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:pact_train
+norm_train:null
+pact_train:tools/train.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x0_5.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 -o Slim.quant.name=pact -o Optimizer.lr.learning_rate=0.08 -o Global.pretrained_model="pretrained_model/PPLCNet_x0_5_pretrained"
+fpgm_train:null
+distill_train:null
+null:null
+null:null
+##
+===========================eval_params=========================== 
+eval:tools/eval.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x0_5.yaml -o Slim.quant.name=pact
+null:null
+##
+===========================infer_params==========================
+-o Global.save_inference_dir:./inference
+-o Global.pretrained_model:
+norm_export:null
+quant_export:tools/export_model.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x0_5.yaml -o Slim.quant.name=pact
+fpgm_export:null
+distill_export:null
+kl_quant:null
+export2:null
+pretrained_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/PPLCNet_x0_5_pretrained.pdparams
+infer_model:../inference/
+infer_export:True
+infer_quant:Fasle
+inference:python/predict_cls.py -c configs/inference_cls.yaml
+-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.save_log_path:null
+-o Global.benchmark:True
+null:null
+===========================infer_benchmark_params==========================
+random_infer_input:[{float32,[3,224,224]}]
\ No newline at end of file

test_tipc/config/PPLCNet/PPLCNet_x0_5_train_ptq_infer_python.txt

+===========================train_params===========================
+model_name:PPLCNet_x0_5
+python:python3.7
+gpu_list:0
+-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
+norm_train:tools/train.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x0_5.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:null
+fpgm_train:null
+distill_train:null
+null:null
+null:null
+##
+===========================eval_params=========================== 
+eval:tools/eval.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x0_5.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/PPLCNet/PPLCNet_x0_5.yaml
+quant_export:null
+fpgm_export:null
+distill_export:null
+kl_quant:deploy/slim/quant_post_static.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x0_5.yaml -o Global.save_inference_dir=./PPLCNet_x0_5_infer
+export2:null
+pretrained_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/PPLCNet_x0_5_infer.tar
+infer_model:./PPLCNet_x0_5_infer/
+infer_export:True
+infer_quant:Fasle
+inference:python/predict_cls.py -c configs/inference_cls.yaml
+-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:../deploy/images/ImageNet/ILSVRC2012_val_00000010.jpeg
+-o Global.save_log_path:null
+-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/PPLCNet/PPLCNet_x0_75_train_pact_infer_python.txt

+===========================train_params===========================
+model_name:PPLCNet_x0_75
+python:python3.7
+gpu_list:0
+-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:pact_train
+norm_train:null
+pact_train:tools/train.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x0_75.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 -o Slim.quant.name=pact -o Optimizer.lr.learning_rate=0.08 -o Global.pretrained_model="pretrained_model/PPLCNet_x0_75_pretrained"
+fpgm_train:null
+distill_train:null
+null:null
+null:null
+##
+===========================eval_params=========================== 
+eval:tools/eval.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x0_75.yaml -o Slim.quant.name=pact
+null:null
+##
+===========================infer_params==========================
+-o Global.save_inference_dir:./inference
+-o Global.pretrained_model:
+norm_export:null
+quant_export:tools/export_model.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x0_75.yaml -o Slim.quant.name=pact
+fpgm_export:null
+distill_export:null
+kl_quant:null
+export2:null
+pretrained_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/PPLCNet_x0_75_pretrained.pdparams
+infer_model:../inference/
+infer_export:True
+infer_quant:Fasle
+inference:python/predict_cls.py -c configs/inference_cls.yaml
+-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.save_log_path:null
+-o Global.benchmark:True
+null:null
+===========================infer_benchmark_params==========================
+random_infer_input:[{float32,[3,224,224]}]
\ No newline at end of file

test_tipc/config/PPLCNet/PPLCNet_x0_75_train_ptq_infer_python.txt

+===========================train_params===========================
+model_name:PPLCNet_x0_75
+python:python3.7
+gpu_list:0
+-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
+norm_train:tools/train.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x0_75.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:null
+fpgm_train:null
+distill_train:null
+null:null
+null:null
+##
+===========================eval_params=========================== 
+eval:tools/eval.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x0_75.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/PPLCNet/PPLCNet_x0_75.yaml
+quant_export:null
+fpgm_export:null
+distill_export:null
+kl_quant:deploy/slim/quant_post_static.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x0_75.yaml -o Global.save_inference_dir=./PPLCNet_x0_75_infer
+export2:null
+pretrained_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/PPLCNet_x0_75_infer.tar
+infer_model:./PPLCNet_x0_75_infer/
+infer_export:True
+infer_quant:Fasle
+inference:python/predict_cls.py -c configs/inference_cls.yaml
+-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:../deploy/images/ImageNet/ILSVRC2012_val_00000010.jpeg
+-o Global.save_log_path:null
+-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/PPLCNet/PPLCNet_x1_0_PACT_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt

+===========================cpp_infer_params===========================
+model_name:PPLCNet_x1_0_PACT
+cpp_infer_type:cls
+cls_inference_model_dir:./PPLCNet_x1_0_pact_infer/
+det_inference_model_dir:
+cls_inference_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/slim_model/PPLCNet_x1_0_pact_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

test_tipc/config/PPLCNet/PPLCNet_x1_0_PACT_linux_gpu_normal_normal_serving_cpp_linux_gpu_cpu.txt

+===========================serving_params===========================
+model_name:PPLCNet_x1_0_PACT
+python:python3.7
+inference_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/slim_model/PPLCNet_x1_0_pact_infer.tar
+trans_model:-m paddle_serving_client.convert
+--dirname:./deploy/paddleserving/PPLCNet_x1_0_pact_infer/
+--model_filename:inference.pdmodel
+--params_filename:inference.pdiparams
+--serving_server:./deploy/paddleserving/PPLCNet_x1_0_pact_serving/
+--serving_client:./deploy/paddleserving/PPLCNet_x1_0_pact_client/
+serving_dir:./deploy/paddleserving
+web_service:null
+--use_gpu:0|null
+pipline:test_cpp_serving_client.py

test_tipc/config/PPLCNet/PPLCNet_x1_0_PACT_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt

+===========================serving_params===========================
+model_name:PPLCNet_x1_0_PACT
+python:python3.7
+inference_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/slim_model/PPLCNet_x1_0_pact_infer.tar
+trans_model:-m paddle_serving_client.convert
+--dirname:./deploy/paddleserving/PPLCNet_x1_0_pact_infer/
+--model_filename:inference.pdmodel
+--params_filename:inference.pdiparams
+--serving_server:./deploy/paddleserving/PPLCNet_x1_0_pact_serving/
+--serving_client:./deploy/paddleserving/PPLCNet_x1_0_pact_client/
+serving_dir:./deploy/paddleserving
+web_service:classification_web_service.py
+--use_gpu:0|null
+pipline:pipeline_http_client.py

test_tipc/config/PPLCNet/PPLCNet_x1_0_train_pact_infer_python.txt

+===========================train_params===========================
+model_name:PPLCNet_x1_0
+python:python3.7
+gpu_list:0
+-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:pact_train
+norm_train:null
+pact_train:tools/train.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_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 -o Slim.quant.name=pact -o Optimizer.lr.learning_rate=0.08 -o Global.pretrained_model="pretrained_model/PPLCNet_x1_0_pretrained"
+fpgm_train:null
+distill_train:null
+null:null
+null:null
+##
+===========================eval_params=========================== 
+eval:tools/eval.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x1_0.yaml -o Slim.quant.name=pact
+null:null
+##
+===========================infer_params==========================
+-o Global.save_inference_dir:./inference
+-o Global.pretrained_model:
+norm_export:null
+quant_export:tools/export_model.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x1_0.yaml -o Slim.quant.name=pact
+fpgm_export:null
+distill_export:null
+kl_quant:null
+export2:null
+pretrained_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/PPLCNet_x1_0_pretrained.pdparams
+infer_model:../inference/
+infer_export:True
+infer_quant:Fasle
+inference:python/predict_cls.py -c configs/inference_cls.yaml
+-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.save_log_path:null
+-o Global.benchmark:True
+null:null
+===========================infer_benchmark_params==========================
+random_infer_input:[{float32,[3,224,224]}]
\ No newline at end of file

test_tipc/config/PPLCNet/PPLCNet_x1_5_train_pact_infer_python.txt

+===========================train_params===========================
+model_name:PPLCNet_x1_5
+python:python3.7
+gpu_list:0
+-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:pact_train
+norm_train:null
+pact_train:tools/train.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x1_5.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 -o Slim.quant.name=pact -o Optimizer.lr.learning_rate=0.08 -o Global.pretrained_model="pretrained_model/PPLCNet_x1_5_pretrained"
+fpgm_train:null
+distill_train:null
+null:null
+null:null
+##
+===========================eval_params=========================== 
+eval:tools/eval.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x1_5.yaml -o Slim.quant.name=pact
+null:null
+##
+===========================infer_params==========================
+-o Global.save_inference_dir:./inference
+-o Global.pretrained_model:
+norm_export:null
+quant_export:tools/export_model.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x1_5.yaml -o Slim.quant.name=pact
+fpgm_export:null
+distill_export:null
+kl_quant:null
+export2:null
+pretrained_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/PPLCNet_x1_5_pretrained.pdparams
+infer_model:../inference/
+infer_export:True
+infer_quant:Fasle
+inference:python/predict_cls.py -c configs/inference_cls.yaml
+-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.save_log_path:null
+-o Global.benchmark:True
+null:null
+===========================infer_benchmark_params==========================
+random_infer_input:[{float32,[3,224,224]}]
\ No newline at end of file

test_tipc/config/PPLCNet/PPLCNet_x1_5_train_ptq_infer_python.txt

+===========================train_params===========================
+model_name:PPLCNet_x1_5
+python:python3.7
+gpu_list:0
+-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
+norm_train:tools/train.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x1_5.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:null
+fpgm_train:null
+distill_train:null
+null:null
+null:null
+##
+===========================eval_params=========================== 
+eval:tools/eval.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x1_5.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/PPLCNet/PPLCNet_x1_5.yaml
+quant_export:null
+fpgm_export:null
+distill_export:null
+kl_quant:deploy/slim/quant_post_static.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x1_5.yaml -o Global.save_inference_dir=./PPLCNet_x1_5_infer
+export2:null
+pretrained_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/PPLCNet_x1_5_infer.tar
+infer_model:./PPLCNet_x1_5_infer/
+infer_export:True
+infer_quant:Fasle
+inference:python/predict_cls.py -c configs/inference_cls.yaml
+-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:../deploy/images/ImageNet/ILSVRC2012_val_00000010.jpeg
+-o Global.save_log_path:null
+-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/PPLCNet/PPLCNet_x2_0_train_pact_infer_python.txt

+===========================train_params===========================
+model_name:PPLCNet_x2_0
+python:python3.7
+gpu_list:0
+-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:pact_train
+norm_train:null
+pact_train:tools/train.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x2_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 -o Slim.quant.name=pact -o Optimizer.lr.learning_rate=0.08 -o Global.pretrained_model="pretrained_model/PPLCNet_x2_0_pretrained"
+fpgm_train:null
+distill_train:null
+null:null
+null:null
+##
+===========================eval_params=========================== 
+eval:tools/eval.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x2_0.yaml -o Slim.quant.name=pact
+null:null
+##
+===========================infer_params==========================
+-o Global.save_inference_dir:./inference
+-o Global.pretrained_model:
+norm_export:null
+quant_export:tools/export_model.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x2_0.yaml -o Slim.quant.name=pact
+fpgm_export:null
+distill_export:null
+kl_quant:null
+export2:null
+pretrained_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/PPLCNet_x2_0_pretrained.pdparams
+infer_model:../inference/
+infer_export:True
+infer_quant:Fasle
+inference:python/predict_cls.py -c configs/inference_cls.yaml
+-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.save_log_path:null
+-o Global.benchmark:True
+null:null
+===========================infer_benchmark_params==========================
+random_infer_input:[{float32,[3,224,224]}]
\ No newline at end of file

test_tipc/config/PPLCNet/PPLCNet_x2_0_train_ptq_infer_python.txt

+===========================train_params===========================
+model_name:PPLCNet_x2_0
+python:python3.7
+gpu_list:0
+-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
+norm_train:tools/train.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x2_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:null
+fpgm_train:null
+distill_train:null
+null:null
+null:null
+##
+===========================eval_params=========================== 
+eval:tools/eval.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x2_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/PPLCNet/PPLCNet_x2_0.yaml
+quant_export:null
+fpgm_export:null
+distill_export:null
+kl_quant:deploy/slim/quant_post_static.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x2_0.yaml -o Global.save_inference_dir=./PPLCNet_x2_0_infer
+export2:null
+pretrained_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/PPLCNet_x2_0_infer.tar
+infer_model:./PPLCNet_x2_0_infer/
+infer_export:True
+infer_quant:Fasle
+inference:python/predict_cls.py -c configs/inference_cls.yaml
+-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:../deploy/images/ImageNet/ILSVRC2012_val_00000010.jpeg
+-o Global.save_log_path:null
+-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/PPLCNet/PPLCNet_x2_5_train_pact_infer_python.txt

+===========================train_params===========================
+model_name:PPLCNet_x2_5
+python:python3.7
+gpu_list:0
+-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:pact_train
+norm_train:null
+pact_train:tools/train.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x2_5.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 -o Slim.quant.name=pact -o Optimizer.lr.learning_rate=0.08 -o Global.pretrained_model="pretrained_model/PPLCNet_x2_5_pretrained"
+fpgm_train:null
+distill_train:null
+null:null
+null:null
+##
+===========================eval_params=========================== 
+eval:tools/eval.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x2_5.yaml -o Slim.quant.name=pact
+null:null
+##
+===========================infer_params==========================
+-o Global.save_inference_dir:./inference
+-o Global.pretrained_model:
+norm_export:null
+quant_export:tools/export_model.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x2_5.yaml -o Slim.quant.name=pact
+fpgm_export:null
+distill_export:null
+kl_quant:null
+export2:null
+pretrained_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/PPLCNet_x2_5_pretrained.pdparams
+infer_model:../inference/
+infer_export:True
+infer_quant:Fasle
+inference:python/predict_cls.py -c configs/inference_cls.yaml
+-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.save_log_path:null
+-o Global.benchmark:True
+null:null
+===========================infer_benchmark_params==========================
+random_infer_input:[{float32,[3,224,224]}]
\ No newline at end of file

test_tipc/config/PPLCNet/PPLCNet_x2_5_train_ptq_infer_python.txt

+===========================train_params===========================
+model_name:PPLCNet_x2_5
+python:python3.7
+gpu_list:0
+-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
+norm_train:tools/train.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x2_5.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:null
+fpgm_train:null
+distill_train:null
+null:null
+null:null
+##
+===========================eval_params=========================== 
+eval:tools/eval.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x2_5.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/PPLCNet/PPLCNet_x2_5.yaml
+quant_export:null
+fpgm_export:null
+distill_export:null
+kl_quant:deploy/slim/quant_post_static.py -c ppcls/configs/ImageNet/PPLCNet/PPLCNet_x2_5.yaml -o Global.save_inference_dir=./PPLCNet_x2_5_infer
+export2:null
+pretrained_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/PPLCNet_x2_5_infer.tar
+infer_model:./PPLCNet_x2_5_infer/
+infer_export:True
+infer_quant:Fasle
+inference:python/predict_cls.py -c configs/inference_cls.yaml
+-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:../deploy/images/ImageNet/ILSVRC2012_val_00000010.jpeg
+-o Global.save_log_path:null
+-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_PACT_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt

+===========================cpp_infer_params===========================
+model_name:PPLCNetV2_base_PACT
+cpp_infer_type:cls
+cls_inference_model_dir:./PPLCNetV2_base_pact_infer/
+det_inference_model_dir:
+cls_inference_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/slim_model/PPLCNetV2_base_pact_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

test_tipc/config/PPLCNetV2/PPLCNetV2_base_PACT_linux_gpu_normal_normal_serving_cpp_linux_gpu_cpu.txt

+===========================serving_params===========================
+model_name:PPLCNetV2_base_PACT
+python:python3.7
+inference_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/slim_model/PPLCNetV2_base_pact_infer.tar
+trans_model:-m paddle_serving_client.convert
+--dirname:./deploy/paddleserving/PPLCNetV2_base_pact_infer/
+--model_filename:inference.pdmodel
+--params_filename:inference.pdiparams
+--serving_server:./deploy/paddleserving/PPLCNetV2_base_pact_serving/
+--serving_client:./deploy/paddleserving/PPLCNetV2_base_pact_client/
+serving_dir:./deploy/paddleserving
+web_service:null
+--use_gpu:0|null
+pipline:test_cpp_serving_client.py

test_tipc/config/PPLCNetV2/PPLCNetV2_base_PACT_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt

+===========================serving_params===========================
+model_name:PPLCNetV2_base_PACT
+python:python3.7
+inference_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/slim_model/PPLCNetV2_base_pact_infer.tar
+trans_model:-m paddle_serving_client.convert
+--dirname:./deploy/paddleserving/PPLCNetV2_base_pact_infer/
+--model_filename:inference.pdmodel
+--params_filename:inference.pdiparams
+--serving_server:./deploy/paddleserving/PPLCNetV2_base_pact_serving/
+--serving_client:./deploy/paddleserving/PPLCNetV2_base_pact_client/
+serving_dir:./deploy/paddleserving
+web_service:classification_web_service.py
+--use_gpu:0|null
+pipline:pipeline_http_client.py

test_tipc/config/PPLCNetV2/PPLCNetV2_base_train_pact_infer_python.txt

+===========================train_params===========================
+model_name:PPLCNetV2_base
+python:python3.7
+gpu_list:0
+-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.first_bs:8
+-o Global.pretrained_model:null
+train_model_name:latest
+train_infer_img_dir:./dataset/ILSVRC2012/val
+null:null
+##
+trainer:pact_train
+norm_train:null
+pact_train:tools/train.py -c ppcls/configs/ImageNet/PPLCNetV2/PPLCNetV2_base.yaml -o Global.seed=1234 -o DataLoader.Train.loader.num_workers=0 -o DataLoader.Train.loader.use_shared_memory=False -o Slim.quant.name=pact -o Optimizer.lr.learning_rate=0.08 -o Global.pretrained_model="pretrained_model/PPLCNetV2_base_pretrained"
+fpgm_train:null
+distill_train:null
+null:null
+null:null
+##
+===========================eval_params===========================
+eval:tools/eval.py -c ppcls/configs/ImageNet/PPLCNetV2/PPLCNetV2_base.yaml -o Slim.quant.name=pact
+null:null
+##
+===========================infer_params==========================
+-o Global.save_inference_dir:./inference
+-o Global.pretrained_model:
+norm_export:null
+quant_export:tools/export_model.py -c ppcls/configs/ImageNet/PPLCNetV2/PPLCNetV2_base.yaml -o Slim.quant.name=pact
+fpgm_export:null
+distill_export:null
+kl_quant:null
+export2:null
+pretrained_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/PPLCNetV2_base_pretrained.pdparams
+infer_model:../inference/
+infer_export:True
+infer_quant:Fasle
+inference:python/predict_cls.py -c configs/inference_cls.yaml
+-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.save_log_path:null
+-o Global.benchmark:True
+null:null
+===========================infer_benchmark_params==========================
+random_infer_input:[{float32,[3,224,224]}]

test_tipc/config/ResNet/ResNet50_train_pact_infer_python.txt

+===========================train_params===========================
+model_name:ResNet50
+python:python3.7
+gpu_list:0
+-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:pact_train
+norm_train:null
+pact_train:tools/train.py -c ppcls/configs/ImageNet/ResNet/ResNet50.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 -o Slim.quant.name=pact -o Optimizer.lr.learning_rate=0.01 -o Global.pretrained_model="pretrained_model/ResNet50_pretrained"
+fpgm_train:null
+distill_train:null
+to_static_train:-o Global.to_static=True
+null:null
+##
+===========================eval_params===========================
+eval:tools/eval.py -c ppcls/configs/ImageNet/ResNet/ResNet50.yaml -o Slim.quant.name=pact
+null:null
+##
+===========================infer_params==========================
+-o Global.save_inference_dir:./inference
+-o Global.pretrained_model:
+norm_export:null
+quant_export:tools/export_model.py -c ppcls/configs/ImageNet/ResNet/ResNet50.yaml -o Slim.quant.name=pact
+fpgm_export:null
+distill_export:null
+kl_quant:null
+export2:null
+pretrained_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/ResNet50_pretrained.pdparams
+infer_model:../inference/
+infer_export:True
+infer_quant:Fasle
+inference:python/predict_cls.py -c configs/inference_cls.yaml
+-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.save_log_path:null
+-o Global.benchmark:True
+null:null
+null:null
+===========================train_benchmark_params==========================
+batch_size:128
+fp_items:fp32
+epoch:1
+--profiler_options:batch_range=[10,20];state=GPU;tracer_option=Default;profile_path=model.profile
+flags:FLAGS_eager_delete_tensor_gb=0.0;FLAGS_fraction_of_gpu_memory_to_use=0.98;FLAGS_conv_workspace_size_limit=4096
+===========================infer_benchmark_params==========================
+random_infer_input:[{float32,[3,224,224]}]
\ No newline at end of file

test_tipc/config/ResNet/ResNet50_train_ptq_infer_python.txt

+===========================train_params===========================
+model_name:ResNet50
+python:python3.7
+gpu_list:0
+-o Global.device:gpu
+-o Global.auto_cast:null
+-o Global.epochs:lite_train_lite_infer=2|whole_train_whole_infer=200
+-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
+norm_train:tools/train.py -c ppcls/configs/ImageNet/ResNet/ResNet50.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:null
+fpgm_train:null
+distill_train:null
+to_static_train:-o Global.to_static=True
+null:null
+##
+===========================eval_params=========================== 
+eval:tools/eval.py -c ppcls/configs/ImageNet/ResNet/ResNet50.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.yaml
+quant_export:null
+fpgm_export:null
+distill_export:null
+kl_quant:deploy/slim/quant_post_static.py -c ppcls/configs/ImageNet/ResNet/ResNet50.yaml -o Global.save_inference_dir=./ResNet50_infer
+export2:null
+pretrained_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/ResNet50_infer.tar
+infer_model:./ResNet50_infer/
+infer_export:True
+infer_quant:Fasle
+inference:python/predict_cls.py -c configs/inference_cls.yaml
+-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:../deploy/images/ImageNet/ILSVRC2012_val_00000010.jpeg
+-o Global.save_log_path:null
+-o Global.benchmark:False
+null:null
+null:null
+===========================train_benchmark_params==========================
+batch_size:128
+fp_items:fp32
+epoch:1
+--profiler_options:batch_range=[10,20];state=GPU;tracer_option=Default;profile_path=model.profile
+flags:FLAGS_eager_delete_tensor_gb=0.0;FLAGS_fraction_of_gpu_memory_to_use=0.98;FLAGS_conv_workspace_size_limit=4096
+===========================infer_benchmark_params==========================
+random_infer_input:[{float32,[3,224,224]}]
\ No newline at end of file

test_tipc/config/ResNet/ResNet50_vd_PACT_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt

+===========================cpp_infer_params===========================
+model_name:ResNet50_vd_PACT
+cpp_infer_type:cls
+cls_inference_model_dir:./ResNet50_vd_pact_infer/
+det_inference_model_dir:
+cls_inference_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/slim_model/ResNet50_vd_pact_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

test_tipc/config/ResNet/ResNet50_vd_PACT_linux_gpu_normal_normal_serving_cpp_linux_gpu_cpu.txt

+===========================serving_params===========================
+model_name:ResNet50_vd_PACT
+python:python3.7
+inference_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/slim_model/ResNet50_vd_pact_infer.tar
+trans_model:-m paddle_serving_client.convert
+--dirname:./deploy/paddleserving/ResNet50_vd_pact_infer/
+--model_filename:inference.pdmodel
+--params_filename:inference.pdiparams
+--serving_server:./deploy/paddleserving/ResNet50_vd_pact_serving/
+--serving_client:./deploy/paddleserving/ResNet50_vd_pact_client/
+serving_dir:./deploy/paddleserving
+web_service:null
+--use_gpu:0|null
+pipline:test_cpp_serving_client.py

test_tipc/config/ResNet/ResNet50_vd_PACT_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt

+===========================serving_params===========================
+model_name:ResNet50_vd_PACT
+python:python3.7
+inference_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/slim_model/ResNet50_vd_pact_infer.tar
+trans_model:-m paddle_serving_client.convert
+--dirname:./deploy/paddleserving/ResNet50_vd_pact_infer/
+--model_filename:inference.pdmodel
+--params_filename:inference.pdiparams
+--serving_server:./deploy/paddleserving/ResNet50_vd_pact_serving/
+--serving_client:./deploy/paddleserving/ResNet50_vd_pact_client/
+serving_dir:./deploy/paddleserving
+web_service:classification_web_service.py
+--use_gpu:0|null
+pipline:pipeline_http_client.py

test_tipc/config/ResNet/ResNet50_vd_train_pact_infer_python.txt

+===========================train_params===========================
+model_name:ResNet50_vd
+python:python3.7
+gpu_list:0
+-o Global.device:gpu
+-o Global.auto_cast:null
+-o Global.epochs:lite_train_lite_infer=2|whole_train_whole_infer=200
+-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:pact_train
+norm_train:null
+pact_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 -o Slim.quant.name=pact -o Optimizer.lr.learning_rate=0.01 -o Global.pretrained_model="pretrained_model/ResNet50_vd_pretrained"
+fpgm_train:null
+distill_train:null
+to_static_train:-o Global.to_static=True
+null:null
+##
+===========================eval_params===========================
+eval:tools/eval.py -c ppcls/configs/ImageNet/ResNet/ResNet50_vd.yaml -o Slim.quant.name=pact
+null:null
+##
+===========================infer_params==========================
+-o Global.save_inference_dir:./inference
+-o Global.pretrained_model:
+norm_export:null
+quant_export:tools/export_model.py -c ppcls/configs/ImageNet/ResNet/ResNet50_vd.yaml -o Slim.quant.name=pact
+fpgm_export:null
+distill_export:null
+kl_quant:null
+export2:null
+pretrained_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/ResNet50_vd_pretrained.pdparams
+infer_model:../inference/
+infer_export:True
+infer_quant:Fasle
+inference:python/predict_cls.py -c configs/inference_cls.yaml
+-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.save_log_path:null
+-o Global.benchmark:True
+null:null
+null:null
+===========================train_benchmark_params==========================
+batch_size:128
+fp_items:fp32
+epoch:1
+--profiler_options:batch_range=[10,20];state=GPU;tracer_option=Default;profile_path=model.profile
+flags:FLAGS_eager_delete_tensor_gb=0.0;FLAGS_fraction_of_gpu_memory_to_use=0.98;FLAGS_conv_workspace_size_limit=4096
+===========================infer_benchmark_params==========================
+random_infer_input:[{float32,[3,224,224]}]
\ No newline at end of file

test_tipc/config/SwinTransformer/SwinTransformer_tiny_patch4_window7_224_PACT_linux_gpu_normal_normal_infer_cpp_linux_gpu_cpu.txt

+===========================cpp_infer_params===========================
+model_name:SwinTransformer_tiny_patch4_window7_224_PACT
+cpp_infer_type:cls
+cls_inference_model_dir:./SwinTransformer_tiny_patch4_window7_224_pact_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_pact_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

test_tipc/config/SwinTransformer/SwinTransformer_tiny_patch4_window7_224_PACT_linux_gpu_normal_normal_serving_cpp_linux_gpu_cpu.txt

+===========================serving_params===========================
+model_name:SwinTransformer_tiny_patch4_window7_224_PACT
+python:python3.7
+inference_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/slim_model/SwinTransformer_tiny_patch4_window7_224_pact_infer.tar
+trans_model:-m paddle_serving_client.convert
+--dirname:./deploy/paddleserving/SwinTransformer_tiny_patch4_window7_224_pact_infer/
+--model_filename:inference.pdmodel
+--params_filename:inference.pdiparams
+--serving_server:./deploy/paddleserving/SwinTransformer_tiny_patch4_window7_224_pact_serving/
+--serving_client:./deploy/paddleserving/SwinTransformer_tiny_patch4_window7_224_pact_client/
+serving_dir:./deploy/paddleserving
+web_service:null
+--use_gpu:0|null
+pipline:test_cpp_serving_client.py

test_tipc/config/SwinTransformer/SwinTransformer_tiny_patch4_window7_224_PACT_linux_gpu_normal_normal_serving_python_linux_gpu_cpu.txt

+===========================serving_params===========================
+model_name:SwinTransformer_tiny_patch4_window7_224_PACT
+python:python3.7
+inference_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/slim_model/SwinTransformer_tiny_patch4_window7_224_pact_infer.tar
+trans_model:-m paddle_serving_client.convert
+--dirname:./deploy/paddleserving/SwinTransformer_tiny_patch4_window7_224_pact_infer/
+--model_filename:inference.pdmodel
+--params_filename:inference.pdiparams
+--serving_server:./deploy/paddleserving/SwinTransformer_tiny_patch4_window7_224_pact_serving/
+--serving_client:./deploy/paddleserving/SwinTransformer_tiny_patch4_window7_224_pact_client/
+serving_dir:./deploy/paddleserving
+web_service:classification_web_service.py
+--use_gpu:0|null
+pipline:pipeline_http_client.py

test_tipc/config/SwinTransformer/SwinTransformer_tiny_patch4_window7_224_train_pact_infer_python.txt

+===========================train_params===========================
+model_name:SwinTransformer_tiny_patch4_window7_224
+python:python3.7
+gpu_list:0
+-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:pact_train
+norm_train:null
+pact_train:tools/train.py -c ppcls/configs/ImageNet/SwinTransformer/SwinTransformer_tiny_patch4_window7_224.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 -o Slim.quant.name=pact -o Optimizer.lr.learning_rate=0.01 -o Global.pretrained_model="pretrained_model/SwinTransformer_tiny_patch4_window7_224_pretrained"
+fpgm_train:null
+distill_train:null
+null:null
+null:null
+##
+===========================eval_params=========================== 
+eval:tools/eval.py -c ppcls/configs/ImageNet/SwinTransformer/SwinTransformer_tiny_patch4_window7_224.yaml -o Slim.quant.name=pact
+null:null
+##
+===========================infer_params==========================
+-o Global.save_inference_dir:./inference
+-o Global.pretrained_model:
+norm_export:null
+quant_export:tools/export_model.py -c ppcls/configs/ImageNet/SwinTransformer/SwinTransformer_tiny_patch4_window7_224.yaml -o Slim.quant.name=pact
+fpgm_export:null
+distill_export:null
+kl_quant:null
+export2:null
+pretrained_model_url:https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/SwinTransformer_tiny_patch4_window7_224_pretrained.pdparams
+infer_model:../inference/
+infer_export:True
+infer_quant:Fasle
+inference:python/predict_cls.py -c configs/inference_cls.yaml
+-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.save_log_path:null
+-o Global.benchmark:True
+null:null
+null:null
+===========================train_benchmark_params==========================
+batch_size:64|104
+fp_items:fp32
+epoch:1
+--profiler_options:batch_range=[10,20];state=GPU;tracer_option=Default;profile_path=model.profile
+flags:FLAGS_eager_delete_tensor_gb=0.0;FLAGS_fraction_of_gpu_memory_to_use=0.98;FLAGS_conv_workspace_size_limit=4096
+===========================infer_benchmark_params==========================
+random_infer_input:[{float32,[3,224,224]}]
\ No newline at end of file

test_tipc/docs/test_inference_cpp.md

@@ -6,31 +6,37 @@ 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     |     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    |
+|    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    |
+|   MobileNetV3   |         MobileNetV3_large_x1_0_PACT          |    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    |
+|    PP-ShiTu     |     GeneralRecognition_PPLCNet_x2_5_PACT     |    支持    |    支持    |
+|     PPHGNet     |                PPHGNet_small                 |    支持    |    支持    |
+|     PPHGNet     |               PPHGNet_small_KL               |    支持    |    支持    |
+|     PPHGNet     |              PPHGNet_small_PACT              |    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_0_PACT               |    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    |
+|     ResNet      |               ResNet50_vd_PACT               |    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    |
+| SwinTransformer | SwinTransformer_tiny_patch4_window7_224_PACT |    支持    |    支持    |
 
 ## 2. 测试流程(以**ResNet50**为例)
 

test_tipc/docs/test_serving_infer_cpp.md

@@ -7,31 +7,37 @@ 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    |
+|    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    |
+|   MobileNetV3   |         MobileNetV3_large_x1_0_PACT          |    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    |
+|    PP-ShiTu     |     GeneralRecognition_PPLCNet_x2_5_PACT     |    支持    |    支持    |
+|     PPHGNet     |                PPHGNet_small                 |    支持    |    支持    |
+|     PPHGNet     |               PPHGNet_small_KL               |    支持    |    支持    |
+|     PPHGNet     |              PPHGNet_small_PACT              |    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_0_PACT               |    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    |
+|     ResNet      |               ResNet50_vd_PACT               |    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    |
+| SwinTransformer | SwinTransformer_tiny_patch4_window7_224_PACT |    支持    |    支持    |
 
 
 ## 2. 测试流程

test_tipc/docs/test_serving_infer_python.md

@@ -7,31 +7,37 @@ 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    |
+|    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    |
+|   MobileNetV3   |         MobileNetV3_large_x1_0_PACT          |    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    |
+|    PP-ShiTu     |     GeneralRecognition_PPLCNet_x2_5_PACT     |    支持    |    支持    |
+|     PPHGNet     |                PPHGNet_small                 |    支持    |    支持    |
+|     PPHGNet     |               PPHGNet_small_KL               |    支持    |    支持    |
+|     PPHGNet     |              PPHGNet_small_PACT              |    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_0_PACT               |    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    |
+|     ResNet      |               ResNet50_vd_PACT               |    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    |
+| SwinTransformer | SwinTransformer_tiny_patch4_window7_224_PACT |    支持    |    支持    |
 
 
 ## 2. 测试流程

test_tipc/docs/test_train_pact_inference_python.md

+# Linux GPU/CPU PACT量化训练推理测试
+
+Linux GPU/CPU PACT量化训练推理测试的主程序为`test_train_inference_python.sh`，可以测试基于Python的模型PACT在线量化等基本功能。
+
+## 1. 测试结论汇总
+
+- 训练相关：
+
+|    算法名称     |                模型名称                 |   单机单卡   |
+| :-------------: | :-------------------------------------: | :----------: |
+|   MobileNetV3   |         MobileNetV3_large_x1_0          | PACT量化训练 |
+|    PP-ShiTu     |     GeneralRecognition_PPLCNet_x2_5     | PACT量化训练 |
+|     PPHGNet     |              PPHGNet_small              | PACT量化训练 |
+|     PPHGNet     |              PPHGNet_tiny               | PACT量化训练 |
+|     PPLCNet     |              PPLCNet_x0_25              | PACT量化训练 |
+|     PPLCNet     |              PPLCNet_x0_35              | PACT量化训练 |
+|     PPLCNet     |              PPLCNet_x0_5               | PACT量化训练 |
+|     PPLCNet     |              PPLCNet_x0_75              | PACT量化训练 |
+|     PPLCNet     |              PPLCNet_x1_0               | PACT量化训练 |
+|     PPLCNet     |              PPLCNet_x1_5               | PACT量化训练 |
+|     PPLCNet     |              PPLCNet_x2_0               | PACT量化训练 |
+|     PPLCNet     |              PPLCNet_x2_5               | PACT量化训练 |
+|    PPLCNetV2    |             PPLCNetV2_base              | PACT量化训练 |
+|     ResNet      |                ResNet50                 | PACT量化训练 |
+|     ResNet      |               ResNet50_vd               | PACT量化训练 |
+| SwinTransformer | SwinTransformer_tiny_patch4_window7_224 | PACT量化训练 |
+
+- 推理相关：
+
+|    算法名称     |                模型名称                 | device_CPU | device_GPU | batchsize |
+| :-------------: | :-------------------------------------: | :--------: | :--------: | :-------: |
+|   MobileNetV3   |         MobileNetV3_large_x1_0          |    支持    |    支持    |     1     |
+|    PP-ShiTu     |     GeneralRecognition_PPLCNet_x2_5     |    支持    |    支持    |     1     |
+|     PPHGNet     |              PPHGNet_small              |    支持    |    支持    |     1     |
+|     PPHGNet     |              PPHGNet_tiny               |    支持    |    支持    |     1     |
+|     PPLCNet     |              PPLCNet_x0_25              |    支持    |    支持    |     1     |
+|     PPLCNet     |              PPLCNet_x0_35              |    支持    |    支持    |     1     |
+|     PPLCNet     |              PPLCNet_x0_5               |    支持    |    支持    |     1     |
+|     PPLCNet     |              PPLCNet_x0_75              |    支持    |    支持    |     1     |
+|     PPLCNet     |              PPLCNet_x1_0               |    支持    |    支持    |     1     |
+|     PPLCNet     |              PPLCNet_x1_5               |    支持    |    支持    |     1     |
+|     PPLCNet     |              PPLCNet_x2_0               |    支持    |    支持    |     1     |
+|     PPLCNet     |              PPLCNet_x2_5               |    支持    |    支持    |     1     |
+|    PPLCNetV2    |             PPLCNetV2_base              |    支持    |    支持    |     1     |
+|     ResNet      |                ResNet50                 |    支持    |    支持    |     1     |
+|     ResNet      |               ResNet50_vd               |    支持    |    支持    |     1     |
+| SwinTransformer | SwinTransformer_tiny_patch4_window7_224 |    支持    |    支持    |     1     |
+
+## 2. 测试流程
+
+一下测试流程以 MobileNetV3_large_x1_0 模型为例。
+
+### 2.1 准备环境
+
+- 安装PaddlePaddle：如果您已经安装了2.2或者以上版本的paddlepaddle，那么无需运行下面的命令安装paddlepaddle。
+  ```bash
+  # 需要安装2.2及以上版本的Paddle
+  # 安装GPU版本的Paddle
+  python3.7 -m pip install paddlepaddle-gpu==2.2.0
+  # 安装CPU版本的Paddle
+  python3.7 -m pip install paddlepaddle==2.2.0
+  ```
+
+- 安装PaddleSlim
+  ```bash
+  python3.7 -m pip install paddleslim==2.2.0
+  ```
+
+- 安装依赖
+  ```bash
+  python3.7 -m pip install -r requirements.txt -i https://pypi.tuna.tsinghua.edu.cn/simple
+  ```
+
+- 安装AutoLog（规范化日志输出工具）
+  ```bash
+  python3.7 -m pip install https://paddleocr.bj.bcebos.com/libs/auto_log-1.2.0-py3-none-any.whl
+  ```
+
+### 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
+```
+
+在线量化的操作流程，可参考[文档](../../deploy/slim/README.md)。
+
+### 2.3 功能测试
+
+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
+```
+
+输出结果如下，表示命令运行成功。
+
+```log
+Run successfully with command - MobileNetV3_large_x1_0 - python3.7 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 -o Slim.quant.name=pact -o Optimizer.lr.learning_rate=0.01 -o Global.device=gpu  -o Global.output_dir=./test_tipc/output/MobileNetV3_large_x1_0/lite_train_lite_infer/pact_train_gpus_0_autocast_null -o Global.epochs=2     -o DataLoader.Train.sampler.batch_size=8   !
+Run successfully with command - MobileNetV3_large_x1_0 - python3.7 tools/eval.py -c ppcls/configs/ImageNet/MobileNetV3/MobileNetV3_large_x1_0.yaml -o Slim.quant.name=pact -o Global.pretrained_model=./test_tipc/output/MobileNetV3_large_x1_0/lite_train_lite_infer/pact_train_gpus_0_autocast_null/MobileNetV3_large_x1_0/latest -o Global.device=gpu  !
+Run successfully with command - MobileNetV3_large_x1_0 - python3.7 tools/export_model.py -c ppcls/configs/slim/MobileNetV3_large_x1_0_quantization.yaml -o Slim.quant.name=pact -o Global.pretrained_model=./test_tipc/output/MobileNetV3_large_x1_0/lite_train_lite_infer/pact_train_gpus_0_autocast_null/MobileNetV3_large_x1_0/latest -o Global.save_inference_dir=./test_tipc/output/MobileNetV3_large_x1_0/lite_train_lite_infer/pact_train_gpus_0_autocast_null!
+Run successfully with command - MobileNetV3_large_x1_0 - python3.7 python/predict_cls.py -c configs/inference_cls.yaml -o Global.use_gpu=True -o Global.use_tensorrt=False -o Global.use_fp16=False -o Global.inference_model_dir=.././test_tipc/output/MobileNetV3_large_x1_0/lite_train_lite_infer/pact_train_gpus_0_autocast_null -o Global.batch_size=1 -o Global.infer_imgs=../dataset/ILSVRC2012/val -o Global.benchmark=True > .././test_tipc/output/MobileNetV3_large_x1_0/lite_train_lite_infer/infer_gpu_usetrt_False_precision_False_batchsize_1.log 2>&1 !
+Run successfully with command - MobileNetV3_large_x1_0 - python3.7 python/predict_cls.py -c configs/inference_cls.yaml -o Global.use_gpu=False -o Global.enable_mkldnn=False -o Global.cpu_num_threads=1 -o Global.inference_model_dir=.././test_tipc/output/MobileNetV3_large_x1_0/lite_train_lite_infer/pact_train_gpus_0_autocast_null -o Global.batch_size=1 -o Global.infer_imgs=../dataset/ILSVRC2012/val -o Global.benchmark=True   > .././test_tipc/output/MobileNetV3_large_x1_0/lite_train_lite_infer/infer_cpu_usemkldnn_False_threads_1_batchsize_1.log 2>&1 !
+```
+同时，测试过程中的日志保存在`PaddleClas/test_tipc/output/MobileNetV3_large_x1_0/lite_train_lite_infer`下。
+
+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。

test_tipc/docs/test_train_ptq_inference_python.md

+# Linux GPU/CPU KL离线量化推理测试
+
+Linux GPU/CPU KL离线量化推理测试的主程序为`test_ptq_inference_python.sh`，可以测试基于Python的模型KL离线量化推理等基本功能。
+
+## 1. 测试结论汇总
+
+- KL离线量化：
+
+|    算法名称     |                模型名称                 |   CPU   |
+| :-------------: | :-------------------------------------: | :----------: |
+|   MobileNetV3   |         MobileNetV3_large_x1_0          | KL离线量化 |
+|    PP-ShiTu     |     GeneralRecognition_PPLCNet_x2_5     | KL离线量化 |
+|     PPHGNet     |              PPHGNet_small              | KL离线量化 |
+|     PPHGNet     |              PPHGNet_tiny               | KL离线量化 |
+|     PPLCNet     |              PPLCNet_x0_25              | KL离线量化 |
+|     PPLCNet     |              PPLCNet_x0_35              | KL离线量化 |
+|     PPLCNet     |              PPLCNet_x0_5               | KL离线量化 |
+|     PPLCNet     |              PPLCNet_x0_75              | KL离线量化 |
+|     PPLCNet     |              PPLCNet_x1_0               | KL离线量化 |
+|     PPLCNet     |              PPLCNet_x1_5               | KL离线量化 |
+|     PPLCNet     |              PPLCNet_x2_0               | KL离线量化 |
+|     PPLCNet     |              PPLCNet_x2_5               | KL离线量化 |
+|    PPLCNetV2    |             PPLCNetV2_base              | KL离线量化 |
+|     ResNet      |                ResNet50                 | KL离线量化 |
+|     ResNet      |               ResNet50_vd               | KL离线量化 |
+| SwinTransformer | SwinTransformer_tiny_patch4_window7_224 | KL离线量化 |
+
+- 推理相关：
+
+|    算法名称     |                模型名称                 |   CPU   |
+| :-------------: | :-------------------------------------: | :----------: |
+|   MobileNetV3   |         MobileNetV3_large_x1_0          | KL离线量化 |
+|    PP-ShiTu     |     GeneralRecognition_PPLCNet_x2_5     | KL离线量化 |
+|     PPHGNet     |              PPHGNet_small              | KL离线量化 |
+|     PPHGNet     |              PPHGNet_tiny               | KL离线量化 |
+|     PPLCNet     |              PPLCNet_x0_25              | KL离线量化 |
+|     PPLCNet     |              PPLCNet_x0_35              | KL离线量化 |
+|     PPLCNet     |              PPLCNet_x0_5               | KL离线量化 |
+|     PPLCNet     |              PPLCNet_x0_75              | KL离线量化 |
+|     PPLCNet     |              PPLCNet_x1_0               | KL离线量化 |
+|     PPLCNet     |              PPLCNet_x1_5               | KL离线量化 |
+|     PPLCNet     |              PPLCNet_x2_0               | KL离线量化 |
+|     PPLCNet     |              PPLCNet_x2_5               | KL离线量化 |
+|    PPLCNetV2    |             PPLCNetV2_base              | KL离线量化 |
+|     ResNet      |                ResNet50                 | KL离线量化 |
+|     ResNet      |               ResNet50_vd               | KL离线量化 |
+| SwinTransformer | SwinTransformer_tiny_patch4_window7_224 | KL离线量化 |
+
+
+## 2. 测试流程
+
+一下测试流程以 MobileNetV3_large_x1_0 模型为例。
+
+### 2.1 准备环境
+
+- 安装PaddlePaddle：如果您已经安装了2.2或者以上版本的paddlepaddle，那么无需运行下面的命令安装paddlepaddle。
+  ```bash
+  # 需要安装2.2及以上版本的Paddle
+  # 安装GPU版本的Paddle
+  python3.7 -m pip install paddlepaddle-gpu==2.2.0
+  # 安装CPU版本的Paddle
+  python3.7 -m pip install paddlepaddle==2.2.0
+  ```
+
+- 安装PaddleSlim
+  ```bash
+  python3.7 -m pip install paddleslim==2.2.0
+  ```
+
+- 安装依赖
+  ```bash
+  python3.7 -m pip install -r requirements.txt -i https://pypi.tuna.tsinghua.edu.cn/simple
+  ```
+
+- 安装AutoLog（规范化日志输出工具）
+  ```bash
+  python3.7 -m pip install https://paddleocr.bj.bcebos.com/libs/auto_log-1.2.0-py3-none-any.whl
+  ```
+
+### 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
+```
+
+离线量化的操作流程，可参考[文档](../../deploy/slim/README.md)。
+
+### 2.3 功能测试
+
+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
+```
+
+输出结果如下，表示命令运行成功。
+
+```log
+Run successfully with command - MobileNetV3_large_x1_0 - python3.7 deploy/slim/quant_post_static.py -c ppcls/configs/ImageNet/MobileNetV3/MobileNetV3_large_x1_0.yaml -o Global.save_inference_dir=./MobileNetV3_large_x1_0_infer!
+Run successfully with command - MobileNetV3_large_x1_0 - python3.7 python/predict_cls.py -c configs/inference_cls.yaml -o Global.use_gpu=True -o Global.use_tensorrt=False -o Global.use_fp16=False -o Global.inference_model_dir=.././MobileNetV3_large_x1_0_infer//quant_post_static_model -o Global.batch_size=1 -o Global.infer_imgs=../deploy/images/ImageNet/ILSVRC2012_val_00000010.jpeg -o Global.benchmark=False > .././test_tipc/output/MobileNetV3_large_x1_0/whole_infer/infer_gpu_usetrt_False_precision_False_batchsize_1.log 2>&1 !
+Run successfully with command - MobileNetV3_large_x1_0 - python3.7 python/predict_cls.py -c configs/inference_cls.yaml -o Global.use_gpu=False -o Global.enable_mkldnn=False -o Global.cpu_num_threads=1 -o Global.inference_model_dir=.././MobileNetV3_large_x1_0_infer//quant_post_static_model -o Global.batch_size=1 -o Global.infer_imgs=../deploy/images/ImageNet/ILSVRC2012_val_00000010.jpeg -o Global.benchmark=False   > .././test_tipc/output/MobileNetV3_large_x1_0/whole_infer/infer_cpu_usemkldnn_False_threads_1_batchsize_1.log 2>&1 !
+```
+同时，测试过程中的日志保存在`PaddleClas/test_tipc/output/MobileNetV3_large_x1_0/whole_infer`下。
+
+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。

test_tipc/prepare.sh

@@ -2,8 +2,7 @@
 FILENAME=$1
 
 # MODE be one of ['lite_train_lite_infer' 'lite_train_whole_infer' 'whole_train_whole_infer',
-#                 'whole_infer', 'klquant_whole_infer',
-#                 'cpp_infer', 'serving_infer',  'lite_infer']
+#                 'whole_infer', 'cpp_infer', 'serving_infer',  'lite_infer']
 
 MODE=$2
 
@@ -107,6 +106,14 @@ if [[ ${MODE} = "cpp_infer" ]]; then
             model_dir=${tar_name%.*}
             eval "tar xf ${tar_name}"
 
+            # move '_int8' suffix in pact models
+            if [[ ${tar_name} =~ "pact_infer" ]]; then
+                cd ${cls_inference_model_dir}
+                mv inference_int8.pdiparams inference.pdiparams
+                mv inference_int8.pdmodel inference.pdmodel
+                cd ..
+            fi
+
             cd dataset
             rm -rf ILSVRC2012
             wget -nc https://paddle-imagenet-models-name.bj.bcebos.com/data/whole_chain/whole_chain_infer.tar
@@ -176,6 +183,14 @@ if [[ ${MODE} = "lite_train_lite_infer" ]] || [[ ${MODE} = "lite_train_whole_inf
     mv val.txt val_list.txt
     cp -r train/* val/
     cd ../../
+    if [[ ${FILENAME} =~ "pact_infer" ]]; then
+        # download pretrained model for PACT training
+        pretrpretrained_model_url=$(func_parser_value "${lines[35]}")
+        mkdir pretrained_model
+        cd pretrained_model
+        wget -nc ${pretrpretrained_model_url} --no-check-certificate
+        cd ..
+    fi
 elif [[ ${MODE} = "whole_infer" ]]; then
     # download data
     if [[ ${model_name} =~ "GeneralRecognition" ]]; then
@@ -225,6 +240,14 @@ elif [[ ${MODE} = "whole_train_whole_infer" ]]; then
     mv train.txt train_list.txt
     mv test.txt val_list.txt
     cd ../../
+    if [[ ${FILENAME} =~ "pact_infer" ]]; then
+        # download pretrained model for PACT training
+        pretrpretrained_model_url=$(func_parser_value "${lines[35]}")
+        mkdir pretrained_model
+        cd pretrained_model
+        wget -nc ${pretrpretrained_model_url} --no-check-certificate
+        cd ..
+    fi
 fi
 
 if [[ ${MODE} = "serving_infer" ]]; then
@@ -247,7 +270,18 @@ if [[ ${MODE} = "serving_infer" ]]; then
         cls_inference_model_url=$(func_parser_value "${lines[3]}")
         cls_tar_name=$(func_get_url_file_name "${cls_inference_model_url}")
         cd ./deploy/paddleserving
-        wget -nc ${cls_inference_model_url} && tar xf ${cls_tar_name}
+        wget -nc ${cls_inference_model_url}
+        tar xf ${cls_tar_name}
+
+        # move '_int8' suffix in pact models
+        if [[ ${cls_tar_name} =~ "pact_infer" ]]; then
+            cls_inference_model_dir=${cls_tar_name%%.tar}
+            cd ${cls_inference_model_dir}
+            mv inference_int8.pdiparams inference.pdiparams
+            mv inference_int8.pdmodel inference.pdmodel
+            cd ..
+        fi
+
         cd ../../
     fi
     unset http_proxy

test_tipc/test_ptq_inference_python.sh

+#!/bin/bash
+FILENAME=$1
+source test_tipc/common_func.sh
+
+# MODE be one of ['whole_infer']
+MODE=$2
+
+dataline=$(cat ${FILENAME})
+
+# parser params
+IFS=$'\n'
+lines=(${dataline})
+
+# The training params
+model_name=$(func_parser_value "${lines[1]}")
+python=$(func_parser_value "${lines[2]}")
+gpu_list=$(func_parser_value "${lines[3]}")
+train_use_gpu_key=$(func_parser_key "${lines[4]}")
+train_use_gpu_value=$(func_parser_value "${lines[4]}")
+autocast_list=$(func_parser_value "${lines[5]}")
+autocast_key=$(func_parser_key "${lines[5]}")
+epoch_key=$(func_parser_key "${lines[6]}")
+epoch_num=$(func_parser_params "${lines[6]}")
+save_model_key=$(func_parser_key "${lines[7]}")
+train_batch_key=$(func_parser_key "${lines[8]}")
+train_batch_value=$(func_parser_value "${lines[8]}")
+pretrain_model_key=$(func_parser_key "${lines[9]}")
+pretrain_model_value=$(func_parser_value "${lines[9]}")
+train_model_name=$(func_parser_value "${lines[10]}")
+train_infer_img_dir=$(func_parser_value "${lines[11]}")
+train_param_key1=$(func_parser_key "${lines[12]}")
+train_param_value1=$(func_parser_value "${lines[12]}")
+
+trainer_list=$(func_parser_value "${lines[14]}")
+trainer_norm=$(func_parser_key "${lines[15]}")
+norm_trainer=$(func_parser_value "${lines[15]}")
+pact_key=$(func_parser_key "${lines[16]}")
+pact_trainer=$(func_parser_value "${lines[16]}")
+fpgm_key=$(func_parser_key "${lines[17]}")
+fpgm_trainer=$(func_parser_value "${lines[17]}")
+distill_key=$(func_parser_key "${lines[18]}")
+distill_trainer=$(func_parser_value "${lines[18]}")
+to_static_key=$(func_parser_key "${lines[19]}")
+to_static_trainer=$(func_parser_value "${lines[19]}")
+trainer_key2=$(func_parser_key "${lines[20]}")
+trainer_value2=$(func_parser_value "${lines[20]}")
+
+eval_py=$(func_parser_value "${lines[23]}")
+eval_key1=$(func_parser_key "${lines[24]}")
+eval_value1=$(func_parser_value "${lines[24]}")
+
+save_infer_key=$(func_parser_key "${lines[27]}")
+export_weight=$(func_parser_key "${lines[28]}")
+norm_export=$(func_parser_value "${lines[29]}")
+pact_export=$(func_parser_value "${lines[30]}")
+fpgm_export=$(func_parser_value "${lines[31]}")
+distill_export=$(func_parser_value "${lines[32]}")
+kl_quant_cmd_key=$(func_parser_key "${lines[33]}")
+kl_quant_cmd_value=$(func_parser_value "${lines[33]}")
+export_key2=$(func_parser_key "${lines[34]}")
+export_value2=$(func_parser_value "${lines[34]}")
+
+# parser inference model
+infer_model_dir_list=$(func_parser_value "${lines[36]}")
+infer_export_flag=$(func_parser_value "${lines[37]}")
+infer_is_quant=$(func_parser_value "${lines[38]}")
+
+# parser inference
+inference_py=$(func_parser_value "${lines[39]}")
+use_gpu_key=$(func_parser_key "${lines[40]}")
+use_gpu_list=$(func_parser_value "${lines[40]}")
+use_mkldnn_key=$(func_parser_key "${lines[41]}")
+use_mkldnn_list=$(func_parser_value "${lines[41]}")
+cpu_threads_key=$(func_parser_key "${lines[42]}")
+cpu_threads_list=$(func_parser_value "${lines[42]}")
+batch_size_key=$(func_parser_key "${lines[43]}")
+batch_size_list=$(func_parser_value "${lines[43]}")
+use_trt_key=$(func_parser_key "${lines[44]}")
+use_trt_list=$(func_parser_value "${lines[44]}")
+precision_key=$(func_parser_key "${lines[45]}")
+precision_list=$(func_parser_value "${lines[45]}")
+infer_model_key=$(func_parser_key "${lines[46]}")
+image_dir_key=$(func_parser_key "${lines[47]}")
+infer_img_dir=$(func_parser_value "${lines[47]}")
+save_log_key=$(func_parser_key "${lines[48]}")
+benchmark_key=$(func_parser_key "${lines[49]}")
+benchmark_value=$(func_parser_value "${lines[49]}")
+infer_key1=$(func_parser_key "${lines[50]}")
+infer_value1=$(func_parser_value "${lines[50]}")
+if [ ! $epoch_num ]; then
+    epoch_num=2
+fi
+if [[ $MODE = 'benchmark_train' ]]; then
+    epoch_num=1
+fi
+
+LOG_PATH="./test_tipc/output/${model_name}/${MODE}"
+mkdir -p ${LOG_PATH}
+status_log="${LOG_PATH}/results_python.log"
+
+function func_inference() {
+    IFS='|'
+    _python=$1
+    _script=$2
+    _model_dir=$3
+    _log_path=$4
+    _img_dir=$5
+    _flag_quant=$6
+    # inference
+    for use_gpu in ${use_gpu_list[*]}; do
+        if [ ${use_gpu} = "False" ] || [ ${use_gpu} = "cpu" ]; then
+            for use_mkldnn in ${use_mkldnn_list[*]}; do
+                for threads in ${cpu_threads_list[*]}; do
+                    for batch_size in ${batch_size_list[*]}; do
+                        _save_log_path="${_log_path}/infer_cpu_usemkldnn_${use_mkldnn}_threads_${threads}_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}")
+                        set_cpu_threads=$(func_set_params "${cpu_threads_key}" "${threads}")
+                        set_model_dir=$(func_set_params "${infer_model_key}" "${_model_dir}")
+                        set_infer_params1=$(func_set_params "${infer_key1}" "${infer_value1}")
+                        command="${_python} ${_script} ${use_gpu_key}=${use_gpu} ${use_mkldnn_key}=${use_mkldnn} ${set_cpu_threads} ${set_model_dir} ${set_batchsize} ${set_infer_data} ${set_benchmark} ${set_infer_params1} > ${_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 [ ${use_gpu} = "True" ] || [ ${use_gpu} = "gpu" ]; then
+            for use_trt in ${use_trt_list[*]}; do
+                for precision in ${precision_list[*]}; do
+                    if [ ${precision} = "True" ] && [ ${use_trt} = "False" ]; then
+                        continue
+                    fi
+                    for batch_size in ${batch_size_list[*]}; do
+                        _save_log_path="${_log_path}/infer_gpu_usetrt_${use_trt}_precision_${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}")
+                        set_tensorrt=$(func_set_params "${use_trt_key}" "${use_trt}")
+                        set_precision=$(func_set_params "${precision_key}" "${precision}")
+                        set_model_dir=$(func_set_params "${infer_model_key}" "${_model_dir}")
+                        command="${_python} ${_script} ${use_gpu_key}=${use_gpu} ${set_tensorrt} ${set_precision} ${set_model_dir} ${set_batchsize} ${set_infer_data} ${set_benchmark} > ${_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
+        else
+            echo "Does not support hardware other than CPU and GPU Currently!"
+        fi
+    done
+}
+
+# for kl_quant
+if [ ${kl_quant_cmd_value} != "null" ] && [ ${kl_quant_cmd_value} != "False" ]; then
+    echo "kl_quant"
+    command="${python} ${kl_quant_cmd_value}"
+    echo ${command}
+    eval $command
+    last_status=${PIPESTATUS[0]}
+    status_check $last_status "${command}" "${status_log}" "${model_name}"
+    cd ${infer_model_dir_list}/quant_post_static_model
+    ln -s __model__ inference.pdmodel
+    ln -s __params__ inference.pdiparams
+    cd ../../deploy
+    is_quant=True
+    func_inference "${python}" "${inference_py}" "../${infer_model_dir_list}/quant_post_static_model" "../${LOG_PATH}" "${infer_img_dir}" ${is_quant}
+    cd ..
+fi

test_tipc/test_serving_infer_python.sh

@@ -2,6 +2,7 @@
 source test_tipc/common_func.sh
 
 FILENAME=$1
+MODE=$2
 dataline=$(awk 'NR==1, NR==19{print}'  $FILENAME)
 
 # parser params
@@ -38,7 +39,7 @@ pipeline_py=$(func_parser_value "${lines[13]}")
 
 
 function func_serving_cls(){
-    LOG_PATH="test_tipc/output/${model_name}"
+    LOG_PATH="test_tipc/output/${model_name}/${MODE}"
     mkdir -p ${LOG_PATH}
     LOG_PATH="../../${LOG_PATH}"
     status_log="${LOG_PATH}/results_serving.log"
@@ -153,7 +154,7 @@ function func_serving_cls(){
 
 
 function func_serving_rec(){
-    LOG_PATH="test_tipc/output/${model_name}"
+    LOG_PATH="test_tipc/output/${model_name}/${MODE}"
     mkdir -p ${LOG_PATH}
     LOG_PATH="../../../${LOG_PATH}"
     status_log="${LOG_PATH}/results_serving.log"

test_tipc/test_train_inference_python.sh

@@ -32,6 +32,7 @@ train_param_key1=$(func_parser_key "${lines[12]}")
 train_param_value1=$(func_parser_value "${lines[12]}")
 
 trainer_list=$(func_parser_value "${lines[14]}")
+
 trainer_norm=$(func_parser_key "${lines[15]}")
 norm_trainer=$(func_parser_value "${lines[15]}")
 pact_key=$(func_parser_key "${lines[16]}")
@@ -276,7 +277,7 @@ else
                     set_eval_pretrain=$(func_set_params "${pretrain_model_key}" "${save_log}/${model_name}/${train_model_name}")
                 fi
                 # save norm trained models to set pretrain for pact training and fpgm training
-                if [ ${trainer} = ${trainer_norm} ]; then
+                if [[ ${trainer} = ${trainer_norm}  ||  ${trainer} = ${pact_key} ]]; then
                     load_norm_train_model=${set_eval_pretrain}
                 fi
                 # run eval