diff --git a/docs/zh_CN/extension/train_with_DALI.md b/docs/zh_CN/extension/train_with_DALI.md index b31b5cfdac7ae8d942546ca52252462fd1272019..880a0558bdbbb8930f082655a89c53d4a8072bd3 100644 --- a/docs/zh_CN/extension/train_with_DALI.md +++ b/docs/zh_CN/extension/train_with_DALI.md @@ -28,7 +28,7 @@ export CUDA_VISIBLE_DEVICES="0" # 设置用于神经网络训练的显存大小，可根据具体情况设置，一般可设置为0.8或0.7，剩余显存则预留DALI使用 export FLAGS_fraction_of_gpu_memory_to_use=0.80 -python tools/static/train.py -c configs/ResNet/ResNet50.yaml -o use_dali=True +python ppcls/static/train.py -c ./ppcls/configs/ImageNet/ResNet/ResNet50.yaml -o use_dali=True ``` 也可以使用多卡训练： @@ -42,8 +42,8 @@ export FLAGS_fraction_of_gpu_memory_to_use=0.80 python -m paddle.distributed.launch \ --gpus="0,1,2,3,4,5,6,7" \ - tools/static/train.py \ - -c ./configs/ResNet/ResNet50.yaml \ + ppcls/static/train.py \ + -c ./ppcls/configs/ImageNet/ResNet/ResNet50.yaml \ -o use_dali=True ``` @@ -56,6 +56,6 @@ export FLAGS_fraction_of_gpu_memory_to_use=0.8 python -m paddle.distributed.launch \ --gpus="0,1,2,3,4,5,6,7" \ - tools/static/train.py \ - -c configs/ResNet/ResNet50_fp16.yaml + ppcls/static/train.py \ + -c ./ppcls/configs/ImageNet/ResNet/ResNet50_fp16.yaml ``` diff --git a/ppcls/configs/ImageNet/DeiT/DeiT_base_distilled_patch16_224.yaml b/ppcls/configs/ImageNet/DeiT/DeiT_base_distilled_patch16_224.yaml index fb3b9cca490a1f06a680423cfbde644aca41ccc9..02a2f42d7fa57e0f8ed9d6d43a93f28225c3df7c 100644 --- a/ppcls/configs/ImageNet/DeiT/DeiT_base_distilled_patch16_224.yaml +++ b/ppcls/configs/ImageNet/DeiT/DeiT_base_distilled_patch16_224.yaml @@ -17,6 +17,8 @@ Global: # model architecture Arch: name: DeiT_base_distilled_patch16_224 + drop_path_rate : 0.1 + drop_rate : 0.0 class_num: 1000 # loss function config for traing/eval process diff --git a/ppcls/configs/ImageNet/DeiT/DeiT_base_distilled_patch16_384.yaml b/ppcls/configs/ImageNet/DeiT/DeiT_base_distilled_patch16_384.yaml index d30b5f7dfb30a3e35472b422cb5dc0ca50501929..3565c11242e5cdf86c7973c4cbdf75317e60e606 100644 --- a/ppcls/configs/ImageNet/DeiT/DeiT_base_distilled_patch16_384.yaml +++ b/ppcls/configs/ImageNet/DeiT/DeiT_base_distilled_patch16_384.yaml @@ -17,6 +17,8 @@ Global: # model architecture Arch: name: DeiT_base_distilled_patch16_384 + drop_path_rate : 0.1 + drop_rate : 0.0 class_num: 1000 # loss function config for traing/eval process diff --git a/ppcls/configs/ImageNet/DeiT/DeiT_base_patch16_224.yaml b/ppcls/configs/ImageNet/DeiT/DeiT_base_patch16_224.yaml index 8f4207e4849177cedfec3718854dbbf62b70589b..d8bbf338ea83fa39e10aebcfbbe77d61169c322a 100644 --- a/ppcls/configs/ImageNet/DeiT/DeiT_base_patch16_224.yaml +++ b/ppcls/configs/ImageNet/DeiT/DeiT_base_patch16_224.yaml @@ -17,6 +17,8 @@ Global: # model architecture Arch: name: DeiT_base_patch16_224 + drop_path_rate : 0.1 + drop_rate : 0.0 class_num: 1000 # loss function config for traing/eval process diff --git a/ppcls/configs/ImageNet/DeiT/DeiT_base_patch16_384.yaml b/ppcls/configs/ImageNet/DeiT/DeiT_base_patch16_384.yaml index 00afe54b4c12418896ea1b614f210055dbe434c9..b8f3ced45a3d18653b71758fdd653b9bbabd86a4 100644 --- a/ppcls/configs/ImageNet/DeiT/DeiT_base_patch16_384.yaml +++ b/ppcls/configs/ImageNet/DeiT/DeiT_base_patch16_384.yaml @@ -17,6 +17,8 @@ Global: # model architecture Arch: name: DeiT_base_patch16_384 + drop_path_rate : 0.1 + drop_rate : 0.0 class_num: 1000 # loss function config for traing/eval process diff --git a/ppcls/configs/ImageNet/DeiT/DeiT_small_distilled_patch16_224.yaml b/ppcls/configs/ImageNet/DeiT/DeiT_small_distilled_patch16_224.yaml index c27bed40695022f1127f888fb1fb7d85193ab2cb..7a68e292b0bba89985c19f6107eeffc6c9e70035 100644 --- a/ppcls/configs/ImageNet/DeiT/DeiT_small_distilled_patch16_224.yaml +++ b/ppcls/configs/ImageNet/DeiT/DeiT_small_distilled_patch16_224.yaml @@ -17,6 +17,8 @@ Global: # model architecture Arch: name: DeiT_small_distilled_patch16_224 + drop_path_rate : 0.1 + drop_rate : 0.0 class_num: 1000 # loss function config for traing/eval process diff --git a/ppcls/configs/ImageNet/DeiT/DeiT_small_patch16_224.yaml b/ppcls/configs/ImageNet/DeiT/DeiT_small_patch16_224.yaml index f53b8ec1f582d5c5782f5d7f65e92dec2aa5a955..0ef9344e07a02fa8796c34a4392b3b209cdda297 100644 --- a/ppcls/configs/ImageNet/DeiT/DeiT_small_patch16_224.yaml +++ b/ppcls/configs/ImageNet/DeiT/DeiT_small_patch16_224.yaml @@ -17,6 +17,8 @@ Global: # model architecture Arch: name: DeiT_small_patch16_224 + drop_path_rate : 0.1 + drop_rate : 0.0 class_num: 1000 # loss function config for traing/eval process diff --git a/ppcls/configs/ImageNet/DeiT/DeiT_tiny_distilled_patch16_224.yaml b/ppcls/configs/ImageNet/DeiT/DeiT_tiny_distilled_patch16_224.yaml index 8b9e00fd6cffcd50e0e186466ec5adb9e4b6d320..8ee54657f65a0460845b2a022e67a43fd3aa18ff 100644 --- a/ppcls/configs/ImageNet/DeiT/DeiT_tiny_distilled_patch16_224.yaml +++ b/ppcls/configs/ImageNet/DeiT/DeiT_tiny_distilled_patch16_224.yaml @@ -17,6 +17,8 @@ Global: # model architecture Arch: name: DeiT_tiny_distilled_patch16_224 + drop_path_rate : 0.1 + drop_rate : 0.0 class_num: 1000 # loss function config for traing/eval process diff --git a/ppcls/configs/ImageNet/DeiT/DeiT_tiny_patch16_224.yaml b/ppcls/configs/ImageNet/DeiT/DeiT_tiny_patch16_224.yaml index 242093db4910071e70a8062b7901b1b2bd3c6fc2..3d2ab38b77481bb96f47215c181c21dcec3c070b 100644 --- a/ppcls/configs/ImageNet/DeiT/DeiT_tiny_patch16_224.yaml +++ b/ppcls/configs/ImageNet/DeiT/DeiT_tiny_patch16_224.yaml @@ -17,6 +17,8 @@ Global: # model architecture Arch: name: DeiT_tiny_patch16_224 + drop_path_rate : 0.1 + drop_rate : 0.0 class_num: 1000 # loss function config for traing/eval process diff --git a/ppcls/static/run_dali.sh b/ppcls/static/run_dali.sh index 8b33b28d28d0b83a163244495a6076fb63fd4a02..748ac84c732ddfe2382747118f2abaf3e005a484 100644 --- a/ppcls/static/run_dali.sh +++ b/ppcls/static/run_dali.sh @@ -5,7 +5,7 @@ export FLAGS_fraction_of_gpu_memory_to_use=0.80 python3.7 -m paddle.distributed.launch \ --gpus="0,1,2,3,4,5,6,7" \ - ppcls/static//train.py \ + ppcls/static/train.py \ -c ./ppcls/configs/ImageNet/ResNet/ResNet50_fp16.yaml \ -o Global.use_dali=True