未验证 提交 3b7a168a 编写于 作者: H HydrogenSulfate 提交者: GitHub

Merge pull request #2141 from HydrogenSulfate/add_ddp_train

Add 12 fleet train configs
......@@ -108,6 +108,7 @@ bash test_tipc/test_train_inference_python.sh ./test_tipc/configs/MobileNetV3/Mo
- [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_train_ptq_inference_python 使用](docs/test_train_ptq_inference_python.md):测试基于Python的模型KL离线量化等基本功能。
- [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.
......
===========================train_params===========================
model_name:MobileNetV3_large_x1_0
python:python3.7
gpu_list:192.168.0.1,192.168.0.2;0,1
-o Global.device:gpu
-o Global.auto_cast:null
-o Global.epochs:lite_train_lite_infer=2|whole_train_whole_infer=120
-o Global.output_dir:./output/
-o DataLoader.Train.sampler.batch_size:8
-o Global.pretrained_model:null
train_model_name:latest
train_infer_img_dir:./dataset/ILSVRC2012/val
null:null
##
trainer:norm_train
norm_train:tools/train.py -c ppcls/configs/ImageNet/MobileNetV3/MobileNetV3_large_x1_0.yaml -o Global.seed=1234 -o DataLoader.Train.sampler.shuffle=False -o DataLoader.Train.loader.num_workers=0 -o DataLoader.Train.loader.use_shared_memory=False
pact_train: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/MobileNetV3/MobileNetV3_large_x1_0.yaml
null:null
##
===========================infer_params==========================
-o Global.save_inference_dir:./inference
-o Global.pretrained_model:
norm_export:tools/export_model.py -c ppcls/configs/ImageNet/MobileNetV3/MobileNetV3_large_x1_0.yaml
quant_export:null
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/ILSVRC2012_val_00000001.JPEG
-o Global.save_log_path:null
-o Global.benchmark:False
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
===========================train_params===========================
model_name:PPHGNet_tiny
python:python3.7
gpu_list:192.168.0.1,192.168.0.2;0,1
-o Global.device:gpu
-o Global.auto_cast:null
-o Global.epochs:lite_train_lite_infer=2|whole_train_whole_infer=120
-o Global.output_dir:./output/
-o DataLoader.Train.sampler.batch_size:8
-o Global.pretrained_model:null
train_model_name:latest
train_infer_img_dir:./dataset/ILSVRC2012/val
null:null
##
trainer:norm_train
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: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=232
-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/ILSVRC2012_val_00000001.JPEG
-o Global.save_log_path:null
-o Global.benchmark:False
null:null
===========================infer_benchmark_params==========================
random_infer_input:[{float32,[3,224,224]}]
===========================train_params===========================
model_name:PPLCNet_x0_25
python:python3.7
gpu_list:192.168.0.1,192.168.0.2;0,1
-o Global.device:gpu
-o Global.auto_cast:null
-o Global.epochs:lite_train_lite_infer=2|whole_train_whole_infer=120
-o Global.output_dir:./output/
-o DataLoader.Train.sampler.batch_size:8
-o Global.pretrained_model:null
train_model_name:latest
train_infer_img_dir:./dataset/ILSVRC2012/val
null:null
##
trainer:norm_train
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: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/ILSVRC2012_val_00000001.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
===========================train_params===========================
model_name:PPLCNet_x0_35
python:python3.7
gpu_list:192.168.0.1,192.168.0.2;0,1
-o Global.device:gpu
-o Global.auto_cast:null
-o Global.epochs:lite_train_lite_infer=2|whole_train_whole_infer=120
-o Global.output_dir:./output/
-o DataLoader.Train.sampler.batch_size:8
-o Global.pretrained_model:null
train_model_name:latest
train_infer_img_dir:./dataset/ILSVRC2012/val
null:null
##
trainer:norm_train
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: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/ILSVRC2012_val_00000001.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
===========================train_params===========================
model_name:PPLCNet_x0_5
python:python3.7
gpu_list:192.168.0.1,192.168.0.2;0,1
-o Global.device:gpu
-o Global.auto_cast:null
-o Global.epochs:lite_train_lite_infer=2|whole_train_whole_infer=120
-o Global.output_dir:./output/
-o DataLoader.Train.sampler.batch_size:8
-o Global.pretrained_model:null
train_model_name:latest
train_infer_img_dir:./dataset/ILSVRC2012/val
null:null
##
trainer:norm_train
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: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/ILSVRC2012_val_00000001.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
===========================train_params===========================
model_name:PPLCNet_x0_75
python:python3.7
gpu_list:192.168.0.1,192.168.0.2;0,1
-o Global.device:gpu
-o Global.auto_cast:null
-o Global.epochs:lite_train_lite_infer=2|whole_train_whole_infer=120
-o Global.output_dir:./output/
-o DataLoader.Train.sampler.batch_size:8
-o Global.pretrained_model:null
train_model_name:latest
train_infer_img_dir:./dataset/ILSVRC2012/val
null:null
##
trainer:norm_train
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: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/ILSVRC2012_val_00000001.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
===========================train_params===========================
model_name:PPLCNet_x1_5
python:python3.7
gpu_list:192.168.0.1,192.168.0.2;0,1
-o Global.device:gpu
-o Global.auto_cast:null
-o Global.epochs:lite_train_lite_infer=2|whole_train_whole_infer=120
-o Global.output_dir:./output/
-o DataLoader.Train.sampler.batch_size:8
-o Global.pretrained_model:null
train_model_name:latest
train_infer_img_dir:./dataset/ILSVRC2012/val
null:null
##
trainer:norm_train
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: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/ILSVRC2012_val_00000001.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
===========================train_params===========================
model_name:PPLCNet_x2_0
python:python3.7
gpu_list:192.168.0.1,192.168.0.2;0,1
-o Global.device:gpu
-o Global.auto_cast:null
-o Global.epochs:lite_train_lite_infer=2|whole_train_whole_infer=120
-o Global.output_dir:./output/
-o DataLoader.Train.sampler.batch_size:8
-o Global.pretrained_model:null
train_model_name:latest
train_infer_img_dir:./dataset/ILSVRC2012/val
null:null
##
trainer:norm_train
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: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/ILSVRC2012_val_00000001.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
===========================train_params===========================
model_name:PPLCNet_x2_5
python:python3.7
gpu_list:192.168.0.1,192.168.0.2;0,1
-o Global.device:gpu
-o Global.auto_cast:null
-o Global.epochs:lite_train_lite_infer=2|whole_train_whole_infer=120
-o Global.output_dir:./output/
-o DataLoader.Train.sampler.batch_size:8
-o Global.pretrained_model:null
train_model_name:latest
train_infer_img_dir:./dataset/ILSVRC2012/val
null:null
##
trainer:norm_train
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: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/ILSVRC2012_val_00000001.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
===========================train_params===========================
model_name:ResNet50
python:python3.7
gpu_list:192.168.0.1,192.168.0.2;0,1
-o Global.device:gpu
-o Global.auto_cast:null
-o Global.epochs:lite_train_lite_infer=2|whole_train_whole_infer=120
-o Global.output_dir:./output/
-o DataLoader.Train.sampler.batch_size:8
-o Global.pretrained_model:null
train_model_name:latest
train_infer_img_dir:./dataset/ILSVRC2012/val
null:null
##
trainer:norm_train
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: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/ILSVRC2012_val_00000001.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
===========================train_params===========================
model_name:ResNet50_vd
python:python3.7
gpu_list:192.168.0.1,192.168.0.2;0,1
-o Global.device:gpu
-o Global.auto_cast:null
-o Global.epochs:lite_train_lite_infer=2|whole_train_whole_infer=120
-o Global.output_dir:./output/
-o DataLoader.Train.sampler.batch_size:8
-o Global.pretrained_model:null
train_model_name:latest
train_infer_img_dir:./dataset/ILSVRC2012/val
null:null
##
trainer:norm_train
norm_train:tools/train.py -c ppcls/configs/ImageNet/ResNet/ResNet50_vd.yaml -o Global.seed=1234 -o DataLoader.Train.sampler.shuffle=False -o DataLoader.Train.loader.num_workers=0 -o DataLoader.Train.loader.use_shared_memory=False
pact_train:null
fpgm_train:null
distill_train:null
null:null
null:null
##
===========================eval_params===========================
eval:tools/eval.py -c ppcls/configs/ImageNet/ResNet/ResNet50_vd.yaml
null:null
##
===========================infer_params==========================
-o Global.save_inference_dir:./inference
-o Global.pretrained_model:
norm_export:tools/export_model.py -c ppcls/configs/ImageNet/ResNet/ResNet50_vd.yaml
quant_export:null
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/ILSVRC2012_val_00000001.JPEG
-o Global.save_log_path:null
-o Global.benchmark:False
null:null
null:null
===========================infer_benchmark_params==========================
random_infer_input:[{float32,[3,224,224]}]
\ No newline at end of file
===========================train_params===========================
model_name:SwinTransformer_tiny_patch4_window7_224
python:python3.7
gpu_list:192.168.0.1,192.168.0.2;0,1
-o Global.device:gpu
-o Global.auto_cast:null
-o Global.epochs:lite_train_lite_infer=2|whole_train_whole_infer=120
-o Global.output_dir:./output/
-o DataLoader.Train.sampler.batch_size:8
-o Global.pretrained_model:null
train_model_name:latest
train_infer_img_dir:./dataset/ILSVRC2012/val
null:null
##
trainer:norm_train
norm_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
pact_train:null
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
null:null
##
===========================infer_params==========================
-o Global.save_inference_dir:./inference
-o Global.pretrained_model:
norm_export:tools/export_model.py -c ppcls/configs/ImageNet/SwinTransformer/SwinTransformer_tiny_patch4_window7_224.yaml
quant_export:null
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/ILSVRC2012_val_00000001.JPEG
-o Global.save_log_path:null
-o Global.benchmark:False
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
......@@ -6,22 +6,45 @@ Linux GPU/CPU 多机多卡训练推理测试的主程序为`test_train_inference
- 训练相关:
| 算法名称 | 模型名称 | 多机多卡 |
| :-------: | :-----------------: | :--------: |
| PPLCNet | PPLCNet_x1_0 | 分布式训练 |
| PPLCNetV2 | PPLCNetV2_base | 分布式训练 |
| PPHGNet | PPHGNet_small | 分布式训练 |
| PP-ShiTu | PPShiTu_general_rec | 分布式训练 |
| 算法名称 | 模型名称 | 多机多卡 |
| :-------------: | :-------------------------------------: | :------: |
| MobileNetV3 | MobileNetV3_large_x1_0 | 支持 |
| PP-ShiTu | GeneralRecognition_PPLCNet_x2_5 | 支持 |
| PPHGNet | PPHGNet_small | 支持 |
| PPHGNet | PPHGNet_tiny | 支持 |
| PPLCNet | PPLCNet_x0_25 | 支持 |
| PPLCNet | PPLCNet_x0_35 | 支持 |
| PPLCNet | PPLCNet_x0_5 | 支持 |
| PPLCNet | PPLCNet_x0_75 | 支持 |
| PPLCNet | PPLCNet_x1_0 | 支持 |
| PPLCNet | PPLCNet_x1_5 | 支持 |
| PPLCNet | PPLCNet_x2_0 | 支持 |
| PPLCNet | PPLCNet_x2_5 | 支持 |
| PPLCNetV2 | PPLCNetV2_base | 支持 |
| ResNet | ResNet50 | 支持 |
| ResNet | ResNet50_vd | 支持 |
| SwinTransformer | SwinTransformer_tiny_patch4_window7_224 | 支持 |
- 推理相关:
| 算法名称 | 模型名称 | device_CPU | device_GPU | batchsize |
| :-------: | :-----------------: | :--------: | :--------: | :-------: |
| PPLCNet | PPLCNet_x1_0 | 支持 | 支持 | 1 |
| PPLCNetV2 | PPLCNetV2_base | 支持 | 支持 | 1 |
| PPHGNet | PPHGNet_small | 支持 | 支持 | 1 |
| PP-ShiTu | PPShiTu_general_rec | 支持 | 支持 | 1 |
| 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
......@@ -81,7 +104,7 @@ est_tipc/output/PPLCNet_x1_0/norm_train_gpus_0,1_autocast_null_nodes_2 -o Global
emkldnn_True_threads_1_batchsize_16.log 2>&1 !
```
在配置文件中默认设置`-o Global.benchmark:True`表示开启benchmark选项,此时可以得到测试的详细数据,包含运行环境信息(系统版本、CUDA版本、CUDNN版本、驱动版本),Paddle版本信息,参数设置信息(运行设备、线程数、是否开启内存优化等),模型信息(模型名称、精度),数据信息(batchsize、是否为动态shape等),性能信息(CPU,GPU的占用、运行耗时、预处理耗时、推理耗时、后处理耗时),内容如下所示:
可以在配置文件中设置`-o Global.benchmark:True`,表示开启benchmark选项,此时就能得到测试的详细数据,包含运行环境信息(系统版本、CUDA版本、CUDNN版本、驱动版本),Paddle版本信息,参数设置信息(运行设备、线程数、是否开启内存优化等),模型信息(模型名称、精度),数据信息(batchsize、是否为动态shape等),性能信息(CPU,GPU的占用、运行耗时、预处理耗时、推理耗时、后处理耗时),内容如下所示:
```log
[2022/06/07 17:01:41] root INFO: ---------------------- Env info ----------------------
......
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