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modified batch_size and update_freq & add more tipc_test configs
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61 changes: 61 additions & 0 deletions
61
test_tipc/configs/MobileViTv3/MobileViTv3_S_L2_train_infer_python.txt
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,61 @@ | ||
| ===========================train_params=========================== | ||
| model_name:MobileViTv3_S_L2 | ||
| python:python3.7 | ||
| gpu_list:0|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.first_bs: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/MobileViTv3/MobileViTv3_S_L2.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 Global.print_batch_step=1 -o Global.eval_during_train=False -o Global.save_interval=2 | ||
| pact_train:null | ||
| fpgm_train:null | ||
| distill_train:null | ||
| null:null | ||
| null:null | ||
| ## | ||
| ===========================eval_params=========================== | ||
| eval:tools/eval.py -c ppcls/configs/ImageNet/MobileViTv3/MobileViTv3_S_L2.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/MobileViTv3/MobileViTv3_S_L2.yaml | ||
| quant_export:null | ||
| fpgm_export:null | ||
| distill_export:null | ||
| kl_quant:null | ||
| export2:null | ||
| inference_dir:null | ||
| 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=288 -o PreProcess.transform_ops.1.CropImage.size=256 -o PreProcess.transform_ops.2.NormalizeImage.mean=[0.,0.,0.] -o PreProcess.transform_ops.2.NormalizeImage.std=[1.,1.,1.] | ||
| -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 | ||
| model_type:norm_train | ||
| --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,[3,256,256]}] |
61 changes: 61 additions & 0 deletions
61
test_tipc/configs/MobileViTv3/MobileViTv3_XS_L2_train_infer_python.txt
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,61 @@ | ||
| ===========================train_params=========================== | ||
| model_name:MobileViTv3_XS_L2 | ||
| python:python3.7 | ||
| gpu_list:0|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.first_bs: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/MobileViTv3/MobileViTv3_XS_L2.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 Global.print_batch_step=1 -o Global.eval_during_train=False -o Global.save_interval=2 | ||
| pact_train:null | ||
| fpgm_train:null | ||
| distill_train:null | ||
| null:null | ||
| null:null | ||
| ## | ||
| ===========================eval_params=========================== | ||
| eval:tools/eval.py -c ppcls/configs/ImageNet/MobileViTv3/MobileViTv3_XS_L2.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/MobileViTv3/MobileViTv3_XS_L2.yaml | ||
| quant_export:null | ||
| fpgm_export:null | ||
| distill_export:null | ||
| kl_quant:null | ||
| export2:null | ||
| inference_dir:null | ||
| 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=288 -o PreProcess.transform_ops.1.CropImage.size=256 -o PreProcess.transform_ops.2.NormalizeImage.mean=[0.,0.,0.] -o PreProcess.transform_ops.2.NormalizeImage.std=[1.,1.,1.] | ||
| -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 | ||
| model_type:norm_train | ||
| --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,[3,256,256]}] |
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