Add legendary_model's congigs and fix some trainer's bug
cuicheng01
parent
aecbf40bed
commit
d13cb22378
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@ -12,9 +12,14 @@
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from ppcls.arch.backbone.model_zoo.resnet import ResNet18, ResNet34, ResNet50, ResNet101, ResNet152
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from ppcls.arch.backbone.legendary_models.mobilenet_v1 import MobileNetV1_x0_25, MobileNetV1_x0_5, MobileNetV1_x0_75, MobileNetV1
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from ppcls.arch.backbone.legendary_models.mobilenet_v3 import MobileNetV3_small_x0_35, MobileNetV3_small_x0_5, MobileNetV3_small_x0_75, MobileNetV3_small_x1_0, MobileNetV3_small_x1_25, MobileNetV3_large_x0_35, MobileNetV3_large_x0_5, MobileNetV3_large_x0_75, MobileNetV3_large_x1_0, MobileNetV3_large_x1_25
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from ppcls.arch.backbone.legendary_models.resnet import ResNet18, ResNet18_vd, ResNet34, ResNet34_vd, ResNet50, ResNet50_vd, ResNet101, ResNet101_vd, ResNet152, ResNet152_vd, ResNet200_vd
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from ppcls.arch.backbone.legendary_models.vgg import VGG11, VGG13, VGG16, VGG19
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from ppcls.arch.backbone.legendary_models.inception_v3 import InceptionV3
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from ppcls.arch.backbone.legendary_models.hrnet import HRNet_W18_C, HRNet_W30_C, HRNet_W32_C, HRNet_W40_C, HRNet_W44_C, HRNet_W48_C, HRNet_W60_C, HRNet_W64_C, SE_HRNet_W64_C
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from ppcls.arch.backbone.model_zoo.resnet_vc import ResNet18_vc, ResNet34_vc, ResNet50_vc, ResNet101_vc, ResNet152_vc
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from ppcls.arch.backbone.model_zoo.resnet_vd import ResNet18_vd, ResNet34_vd, ResNet50_vd, ResNet101_vd, ResNet152_vd, ResNet200_vd
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from ppcls.arch.backbone.model_zoo.resnext import ResNeXt50_32x4d, ResNeXt50_64x4d, ResNeXt101_32x4d, ResNeXt101_64x4d, ResNeXt152_32x4d, ResNeXt152_64x4d
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from ppcls.arch.backbone.model_zoo.res2net import Res2Net50_48w_2s, Res2Net50_26w_4s, Res2Net50_14w_8s, Res2Net50_48w_2s, Res2Net50_26w_6s, Res2Net50_26w_8s, Res2Net101_26w_4s, Res2Net152_26w_4s, Res2Net200_26w_4s
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from ppcls.arch.backbone.model_zoo.res2net_vd import Res2Net50_vd_48w_2s, Res2Net50_vd_26w_4s, Res2Net50_vd_14w_8s, Res2Net50_vd_48w_2s, Res2Net50_vd_26w_6s, Res2Net50_vd_26w_8s, Res2Net101_vd_26w_4s, Res2Net152_vd_26w_4s, Res2Net200_vd_26w_4s
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@ -23,22 +28,17 @@ from ppcls.arch.backbone.model_zoo.se_resnext_vd import SE_ResNeXt50_vd_32x4d, S
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from ppcls.arch.backbone.model_zoo.se_resnext import SE_ResNeXt50_32x4d, SE_ResNeXt101_32x4d, SE_ResNeXt152_64x4d
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from ppcls.arch.backbone.model_zoo.dpn import DPN68, DPN92, DPN98, DPN107, DPN131
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from ppcls.arch.backbone.model_zoo.densenet import DenseNet121, DenseNet161, DenseNet169, DenseNet201, DenseNet264
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from ppcls.arch.backbone.model_zoo.hrnet import HRNet_W18_C, HRNet_W30_C, HRNet_W32_C, HRNet_W40_C, HRNet_W44_C, HRNet_W48_C, HRNet_W60_C, HRNet_W64_C, SE_HRNet_W18_C, SE_HRNet_W30_C, SE_HRNet_W32_C, SE_HRNet_W40_C, SE_HRNet_W44_C, SE_HRNet_W48_C, SE_HRNet_W60_C, SE_HRNet_W64_C
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from ppcls.arch.backbone.model_zoo.efficientnet import EfficientNetB0, EfficientNetB1, EfficientNetB2, EfficientNetB3, EfficientNetB4, EfficientNetB5, EfficientNetB6, EfficientNetB7, EfficientNetB0_small
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from ppcls.arch.backbone.model_zoo.resnest import ResNeSt50_fast_1s1x64d, ResNeSt50, ResNeSt101
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from ppcls.arch.backbone.model_zoo.googlenet import GoogLeNet
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from ppcls.arch.backbone.model_zoo.mobilenet_v1 import MobileNetV1_x0_25, MobileNetV1_x0_5, MobileNetV1_x0_75, MobileNetV1
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from ppcls.arch.backbone.model_zoo.mobilenet_v2 import MobileNetV2_x0_25, MobileNetV2_x0_5, MobileNetV2_x0_75, MobileNetV2, MobileNetV2_x1_5, MobileNetV2_x2_0
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from ppcls.arch.backbone.model_zoo.mobilenet_v3 import MobileNetV3_small_x0_35, MobileNetV3_small_x0_5, MobileNetV3_small_x0_75, MobileNetV3_small_x1_0, MobileNetV3_small_x1_25, MobileNetV3_large_x0_35, MobileNetV3_large_x0_5, MobileNetV3_large_x0_75, MobileNetV3_large_x1_0, MobileNetV3_large_x1_25
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from ppcls.arch.backbone.model_zoo.shufflenet_v2 import ShuffleNetV2_x0_25, ShuffleNetV2_x0_33, ShuffleNetV2_x0_5, ShuffleNetV2_x1_0, ShuffleNetV2_x1_5, ShuffleNetV2_x2_0, ShuffleNetV2_swish
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from ppcls.arch.backbone.model_zoo.alexnet import AlexNet
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from ppcls.arch.backbone.model_zoo.inception_v3 import InceptionV3
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from ppcls.arch.backbone.model_zoo.inception_v4 import InceptionV4
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from ppcls.arch.backbone.model_zoo.xception import Xception41, Xception65, Xception71
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from ppcls.arch.backbone.model_zoo.xception_deeplab import Xception41_deeplab, Xception65_deeplab, Xception71_deeplab
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from ppcls.arch.backbone.model_zoo.resnext101_wsl import ResNeXt101_32x8d_wsl, ResNeXt101_32x16d_wsl, ResNeXt101_32x32d_wsl, ResNeXt101_32x48d_wsl
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from ppcls.arch.backbone.model_zoo.squeezenet import SqueezeNet1_0, SqueezeNet1_1
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from ppcls.arch.backbone.model_zoo.vgg import VGG11, VGG13, VGG16, VGG19
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from ppcls.arch.backbone.model_zoo.darknet import DarkNet53
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from ppcls.arch.backbone.model_zoo.regnet import RegNetX_200MF, RegNetX_4GF, RegNetX_32GF, RegNetY_200MF, RegNetY_4GF, RegNetY_32GF
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from ppcls.arch.backbone.model_zoo.vision_transformer import ViT_small_patch16_224, ViT_base_patch16_224, ViT_base_patch16_384, ViT_base_patch32_384, ViT_large_patch16_224, ViT_large_patch16_384, ViT_large_patch32_384, ViT_huge_patch16_224, ViT_huge_patch32_384
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@ -0,0 +1,124 @@
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# global configs
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Global:
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checkpoints: null
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pretrained_model: null
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output_dir: "./output/"
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device: "gpu"
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class_num: 1000
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save_interval: 1
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eval_during_train: True
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eval_interval: 1
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epochs: 120
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print_batch_step: 10
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use_visualdl: False
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# used for static mode and model export
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image_shape: [3, 224, 224]
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save_inference_dir: "./inference"
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# model architecture
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Arch:
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name: "HRNet_W18_C"
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# loss function config for traing/eval process
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Loss:
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Train:
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- CELoss:
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weight: 1.0
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Eval:
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- CELoss:
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weight: 1.0
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Optimizer:
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name: Momentum
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momentum: 0.9
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lr:
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name: Piecewise
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learning_rate: 0.1
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decay_epochs: [30, 60, 90]
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values: [0.1, 0.01, 0.001, 0.0001]
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regularizer:
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name: 'L2'
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coeff: 0.0001
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# data loader for train and eval
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DataLoader:
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Train:
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dataset:
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name: ImageNetDataset
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image_root: "./dataset/ILSVRC2012/"
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cls_label_path: "./dataset/ILSVRC2012/train_list.txt"
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transform_ops:
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- RandCropImage:
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size: 224
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- RandFlipImage:
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flip_code: 1
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- NormalizeImage:
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scale: 0.00392157
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mean: [0.485, 0.456, 0.406]
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std: [0.229, 0.224, 0.225]
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order: ''
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sampler:
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name: DistributedBatchSampler
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batch_size: 64
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drop_last: False
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shuffle: True
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loader:
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num_workers: 6
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use_shared_memory: False
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Eval:
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# TOTO: modify to the latest trainer
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dataset:
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name: ImageNetDataset
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image_root: "./dataset/ILSVRC2012/"
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cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
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transform_ops:
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- ResizeImage:
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size: 224
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- NormalizeImage:
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scale: 0.00392157
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mean: [0.485, 0.456, 0.406]
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std: [0.229, 0.224, 0.225]
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order: ''
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sampler:
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name: DistributedBatchSampler
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batch_size: 64
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drop_last: False
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shuffle: False
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loader:
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num_workers: 6
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use_shared_memory: False
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Infer:
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infer_imgs: "docs/images/whl/demo.jpg"
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batch_size: 10
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transforms:
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- DecodeImage:
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to_rgb: True
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channel_first: False
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- ResizeImage:
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resize_short: 256
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- CropImage:
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size: 224
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- NormalizeImage:
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scale: 1.0/255.0
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mean: [0.485, 0.456, 0.406]
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std: [0.229, 0.224, 0.225]
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order: ''
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- ToCHWImage:
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PostProcess:
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name: Topk
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topk: 5
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class_id_map_file: "ppcls/utils/imagenet1k_label_list.txt"
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Metric:
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Train:
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- Topk:
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k: [1, 5]
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Eval:
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- Topk:
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k: [1, 5]
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@ -0,0 +1,124 @@
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# global configs
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Global:
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checkpoints: null
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pretrained_model: null
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output_dir: "./output/"
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device: "gpu"
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class_num: 1000
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save_interval: 1
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eval_during_train: True
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eval_interval: 1
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epochs: 120
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print_batch_step: 10
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use_visualdl: False
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# used for static mode and model export
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image_shape: [3, 224, 224]
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save_inference_dir: "./inference"
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# model architecture
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Arch:
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name: "HRNet_W30_C"
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# loss function config for traing/eval process
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Loss:
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Train:
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- CELoss:
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weight: 1.0
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Eval:
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- CELoss:
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weight: 1.0
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Optimizer:
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name: Momentum
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momentum: 0.9
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lr:
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name: Piecewise
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learning_rate: 0.1
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decay_epochs: [30, 60, 90]
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values: [0.1, 0.01, 0.001, 0.0001]
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regularizer:
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name: 'L2'
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coeff: 0.0001
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# data loader for train and eval
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DataLoader:
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Train:
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dataset:
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name: ImageNetDataset
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image_root: "./dataset/ILSVRC2012/"
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cls_label_path: "./dataset/ILSVRC2012/train_list.txt"
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transform_ops:
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- RandCropImage:
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size: 224
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- RandFlipImage:
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flip_code: 1
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- NormalizeImage:
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scale: 0.00392157
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mean: [0.485, 0.456, 0.406]
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std: [0.229, 0.224, 0.225]
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order: ''
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sampler:
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name: DistributedBatchSampler
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batch_size: 64
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drop_last: False
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shuffle: True
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loader:
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num_workers: 6
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use_shared_memory: False
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Eval:
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# TOTO: modify to the latest trainer
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dataset:
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name: ImageNetDataset
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image_root: "./dataset/ILSVRC2012/"
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cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
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transform_ops:
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- ResizeImage:
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size: 224
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- NormalizeImage:
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scale: 0.00392157
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mean: [0.485, 0.456, 0.406]
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std: [0.229, 0.224, 0.225]
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order: ''
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sampler:
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name: DistributedBatchSampler
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batch_size: 64
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drop_last: False
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shuffle: False
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loader:
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num_workers: 6
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use_shared_memory: False
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Infer:
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infer_imgs: "docs/images/whl/demo.jpg"
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batch_size: 10
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transforms:
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- DecodeImage:
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to_rgb: True
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channel_first: False
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- ResizeImage:
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resize_short: 256
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- CropImage:
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size: 224
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- NormalizeImage:
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scale: 1.0/255.0
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mean: [0.485, 0.456, 0.406]
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std: [0.229, 0.224, 0.225]
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order: ''
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- ToCHWImage:
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PostProcess:
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name: Topk
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topk: 5
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class_id_map_file: "ppcls/utils/imagenet1k_label_list.txt"
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Metric:
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Train:
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- Topk:
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k: [1, 5]
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Eval:
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- Topk:
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k: [1, 5]
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@ -0,0 +1,124 @@
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# global configs
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Global:
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checkpoints: null
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pretrained_model: null
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output_dir: "./output/"
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device: "gpu"
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class_num: 1000
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save_interval: 1
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eval_during_train: True
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eval_interval: 1
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epochs: 120
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print_batch_step: 10
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use_visualdl: False
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# used for static mode and model export
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image_shape: [3, 224, 224]
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save_inference_dir: "./inference"
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# model architecture
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Arch:
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name: "HRNet_W32_C"
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# loss function config for traing/eval process
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Loss:
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Train:
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- CELoss:
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weight: 1.0
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Eval:
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- CELoss:
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weight: 1.0
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Optimizer:
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name: Momentum
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momentum: 0.9
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lr:
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name: Piecewise
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learning_rate: 0.1
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decay_epochs: [30, 60, 90]
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values: [0.1, 0.01, 0.001, 0.0001]
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regularizer:
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name: 'L2'
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coeff: 0.0001
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# data loader for train and eval
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DataLoader:
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Train:
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dataset:
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name: ImageNetDataset
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image_root: "./dataset/ILSVRC2012/"
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cls_label_path: "./dataset/ILSVRC2012/train_list.txt"
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transform_ops:
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- RandCropImage:
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size: 224
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- RandFlipImage:
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flip_code: 1
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- NormalizeImage:
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scale: 0.00392157
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mean: [0.485, 0.456, 0.406]
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std: [0.229, 0.224, 0.225]
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order: ''
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sampler:
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name: DistributedBatchSampler
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batch_size: 64
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drop_last: False
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shuffle: True
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loader:
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num_workers: 6
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use_shared_memory: False
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Eval:
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# TOTO: modify to the latest trainer
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dataset:
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name: ImageNetDataset
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image_root: "./dataset/ILSVRC2012/"
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cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
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transform_ops:
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- ResizeImage:
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size: 224
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- NormalizeImage:
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scale: 0.00392157
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mean: [0.485, 0.456, 0.406]
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std: [0.229, 0.224, 0.225]
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order: ''
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sampler:
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name: DistributedBatchSampler
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batch_size: 64
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drop_last: False
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shuffle: False
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loader:
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num_workers: 6
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use_shared_memory: False
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Infer:
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infer_imgs: "docs/images/whl/demo.jpg"
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batch_size: 10
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transforms:
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- DecodeImage:
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to_rgb: True
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channel_first: False
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- ResizeImage:
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resize_short: 256
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- CropImage:
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size: 224
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- NormalizeImage:
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scale: 1.0/255.0
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mean: [0.485, 0.456, 0.406]
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std: [0.229, 0.224, 0.225]
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order: ''
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- ToCHWImage:
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PostProcess:
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name: Topk
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topk: 5
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class_id_map_file: "ppcls/utils/imagenet1k_label_list.txt"
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Metric:
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Train:
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- Topk:
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k: [1, 5]
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Eval:
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- Topk:
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k: [1, 5]
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@ -0,0 +1,124 @@
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# global configs
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Global:
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checkpoints: null
|
||||
pretrained_model: null
|
||||
output_dir: "./output/"
|
||||
device: "gpu"
|
||||
class_num: 1000
|
||||
save_interval: 1
|
||||
eval_during_train: True
|
||||
eval_interval: 1
|
||||
epochs: 120
|
||||
print_batch_step: 10
|
||||
use_visualdl: False
|
||||
# used for static mode and model export
|
||||
image_shape: [3, 224, 224]
|
||||
save_inference_dir: "./inference"
|
||||
|
||||
# model architecture
|
||||
Arch:
|
||||
name: "HRNet_W40_C"
|
||||
|
||||
# loss function config for traing/eval process
|
||||
Loss:
|
||||
Train:
|
||||
- CELoss:
|
||||
weight: 1.0
|
||||
Eval:
|
||||
- CELoss:
|
||||
weight: 1.0
|
||||
|
||||
|
||||
Optimizer:
|
||||
name: Momentum
|
||||
momentum: 0.9
|
||||
lr:
|
||||
name: Piecewise
|
||||
learning_rate: 0.1
|
||||
decay_epochs: [30, 60, 90]
|
||||
values: [0.1, 0.01, 0.001, 0.0001]
|
||||
regularizer:
|
||||
name: 'L2'
|
||||
coeff: 0.0001
|
||||
|
||||
|
||||
# data loader for train and eval
|
||||
DataLoader:
|
||||
Train:
|
||||
dataset:
|
||||
name: ImageNetDataset
|
||||
image_root: "./dataset/ILSVRC2012/"
|
||||
cls_label_path: "./dataset/ILSVRC2012/train_list.txt"
|
||||
transform_ops:
|
||||
- RandCropImage:
|
||||
size: 224
|
||||
- RandFlipImage:
|
||||
flip_code: 1
|
||||
- NormalizeImage:
|
||||
scale: 0.00392157
|
||||
mean: [0.485, 0.456, 0.406]
|
||||
std: [0.229, 0.224, 0.225]
|
||||
order: ''
|
||||
|
||||
sampler:
|
||||
name: DistributedBatchSampler
|
||||
batch_size: 64
|
||||
drop_last: False
|
||||
shuffle: True
|
||||
loader:
|
||||
num_workers: 6
|
||||
use_shared_memory: False
|
||||
|
||||
Eval:
|
||||
# TOTO: modify to the latest trainer
|
||||
dataset:
|
||||
name: ImageNetDataset
|
||||
image_root: "./dataset/ILSVRC2012/"
|
||||
cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
|
||||
transform_ops:
|
||||
- ResizeImage:
|
||||
size: 224
|
||||
- NormalizeImage:
|
||||
scale: 0.00392157
|
||||
mean: [0.485, 0.456, 0.406]
|
||||
std: [0.229, 0.224, 0.225]
|
||||
order: ''
|
||||
sampler:
|
||||
name: DistributedBatchSampler
|
||||
batch_size: 64
|
||||
drop_last: False
|
||||
shuffle: False
|
||||
loader:
|
||||
num_workers: 6
|
||||
use_shared_memory: False
|
||||
|
||||
Infer:
|
||||
infer_imgs: "docs/images/whl/demo.jpg"
|
||||
batch_size: 10
|
||||
transforms:
|
||||
- DecodeImage:
|
||||
to_rgb: True
|
||||
channel_first: False
|
||||
- ResizeImage:
|
||||
resize_short: 256
|
||||
- CropImage:
|
||||
size: 224
|
||||
- NormalizeImage:
|
||||
scale: 1.0/255.0
|
||||
mean: [0.485, 0.456, 0.406]
|
||||
std: [0.229, 0.224, 0.225]
|
||||
order: ''
|
||||
- ToCHWImage:
|
||||
PostProcess:
|
||||
name: Topk
|
||||
topk: 5
|
||||
class_id_map_file: "ppcls/utils/imagenet1k_label_list.txt"
|
||||
|
||||
Metric:
|
||||
Train:
|
||||
- Topk:
|
||||
k: [1, 5]
|
||||
Eval:
|
||||
- Topk:
|
||||
k: [1, 5]
|
||||
|
||||
|
|
@ -0,0 +1,124 @@
|
|||
# global configs
|
||||
Global:
|
||||
checkpoints: null
|
||||
pretrained_model: null
|
||||
output_dir: "./output/"
|
||||
device: "gpu"
|
||||
class_num: 1000
|
||||
save_interval: 1
|
||||
eval_during_train: True
|
||||
eval_interval: 1
|
||||
epochs: 120
|
||||
print_batch_step: 10
|
||||
use_visualdl: False
|
||||
# used for static mode and model export
|
||||
image_shape: [3, 224, 224]
|
||||
save_inference_dir: "./inference"
|
||||
|
||||
# model architecture
|
||||
Arch:
|
||||
name: "HRNet_W44_C"
|
||||
|
||||
# loss function config for traing/eval process
|
||||
Loss:
|
||||
Train:
|
||||
- CELoss:
|
||||
weight: 1.0
|
||||
Eval:
|
||||
- CELoss:
|
||||
weight: 1.0
|
||||
|
||||
|
||||
Optimizer:
|
||||
name: Momentum
|
||||
momentum: 0.9
|
||||
lr:
|
||||
name: Piecewise
|
||||
learning_rate: 0.1
|
||||
decay_epochs: [30, 60, 90]
|
||||
values: [0.1, 0.01, 0.001, 0.0001]
|
||||
regularizer:
|
||||
name: 'L2'
|
||||
coeff: 0.0001
|
||||
|
||||
|
||||
# data loader for train and eval
|
||||
DataLoader:
|
||||
Train:
|
||||
dataset:
|
||||
name: ImageNetDataset
|
||||
image_root: "./dataset/ILSVRC2012/"
|
||||
cls_label_path: "./dataset/ILSVRC2012/train_list.txt"
|
||||
transform_ops:
|
||||
- RandCropImage:
|
||||
size: 224
|
||||
- RandFlipImage:
|
||||
flip_code: 1
|
||||
- NormalizeImage:
|
||||
scale: 0.00392157
|
||||
mean: [0.485, 0.456, 0.406]
|
||||
std: [0.229, 0.224, 0.225]
|
||||
order: ''
|
||||
|
||||
sampler:
|
||||
name: DistributedBatchSampler
|
||||
batch_size: 64
|
||||
drop_last: False
|
||||
shuffle: True
|
||||
loader:
|
||||
num_workers: 6
|
||||
use_shared_memory: False
|
||||
|
||||
Eval:
|
||||
# TOTO: modify to the latest trainer
|
||||
dataset:
|
||||
name: ImageNetDataset
|
||||
image_root: "./dataset/ILSVRC2012/"
|
||||
cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
|
||||
transform_ops:
|
||||
- ResizeImage:
|
||||
size: 224
|
||||
- NormalizeImage:
|
||||
scale: 0.00392157
|
||||
mean: [0.485, 0.456, 0.406]
|
||||
std: [0.229, 0.224, 0.225]
|
||||
order: ''
|
||||
sampler:
|
||||
name: DistributedBatchSampler
|
||||
batch_size: 64
|
||||
drop_last: False
|
||||
shuffle: False
|
||||
loader:
|
||||
num_workers: 6
|
||||
use_shared_memory: False
|
||||
|
||||
Infer:
|
||||
infer_imgs: "docs/images/whl/demo.jpg"
|
||||
batch_size: 10
|
||||
transforms:
|
||||
- DecodeImage:
|
||||
to_rgb: True
|
||||
channel_first: False
|
||||
- ResizeImage:
|
||||
resize_short: 256
|
||||
- CropImage:
|
||||
size: 224
|
||||
- NormalizeImage:
|
||||
scale: 1.0/255.0
|
||||
mean: [0.485, 0.456, 0.406]
|
||||
std: [0.229, 0.224, 0.225]
|
||||
order: ''
|
||||
- ToCHWImage:
|
||||
PostProcess:
|
||||
name: Topk
|
||||
topk: 5
|
||||
class_id_map_file: "ppcls/utils/imagenet1k_label_list.txt"
|
||||
|
||||
Metric:
|
||||
Train:
|
||||
- Topk:
|
||||
k: [1, 5]
|
||||
Eval:
|
||||
- Topk:
|
||||
k: [1, 5]
|
||||
|
||||
|
|
@ -0,0 +1,124 @@
|
|||
# global configs
|
||||
Global:
|
||||
checkpoints: null
|
||||
pretrained_model: null
|
||||
output_dir: "./output/"
|
||||
device: "gpu"
|
||||
class_num: 1000
|
||||
save_interval: 1
|
||||
eval_during_train: True
|
||||
eval_interval: 1
|
||||
epochs: 120
|
||||
print_batch_step: 10
|
||||
use_visualdl: False
|
||||
# used for static mode and model export
|
||||
image_shape: [3, 224, 224]
|
||||
save_inference_dir: "./inference"
|
||||
|
||||
# model architecture
|
||||
Arch:
|
||||
name: "HRNet_W48_C"
|
||||
|
||||
# loss function config for traing/eval process
|
||||
Loss:
|
||||
Train:
|
||||
- CELoss:
|
||||
weight: 1.0
|
||||
Eval:
|
||||
- CELoss:
|
||||
weight: 1.0
|
||||
|
||||
|
||||
Optimizer:
|
||||
name: Momentum
|
||||
momentum: 0.9
|
||||
lr:
|
||||
name: Piecewise
|
||||
learning_rate: 0.1
|
||||
decay_epochs: [30, 60, 90]
|
||||
values: [0.1, 0.01, 0.001, 0.0001]
|
||||
regularizer:
|
||||
name: 'L2'
|
||||
coeff: 0.0001
|
||||
|
||||
|
||||
# data loader for train and eval
|
||||
DataLoader:
|
||||
Train:
|
||||
dataset:
|
||||
name: ImageNetDataset
|
||||
image_root: "./dataset/ILSVRC2012/"
|
||||
cls_label_path: "./dataset/ILSVRC2012/train_list.txt"
|
||||
transform_ops:
|
||||
- RandCropImage:
|
||||
size: 224
|
||||
- RandFlipImage:
|
||||
flip_code: 1
|
||||
- NormalizeImage:
|
||||
scale: 0.00392157
|
||||
mean: [0.485, 0.456, 0.406]
|
||||
std: [0.229, 0.224, 0.225]
|
||||
order: ''
|
||||
|
||||
sampler:
|
||||
name: DistributedBatchSampler
|
||||
batch_size: 64
|
||||
drop_last: False
|
||||
shuffle: True
|
||||
loader:
|
||||
num_workers: 6
|
||||
use_shared_memory: False
|
||||
|
||||
Eval:
|
||||
# TOTO: modify to the latest trainer
|
||||
dataset:
|
||||
name: ImageNetDataset
|
||||
image_root: "./dataset/ILSVRC2012/"
|
||||
cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
|
||||
transform_ops:
|
||||
- ResizeImage:
|
||||
size: 224
|
||||
- NormalizeImage:
|
||||
scale: 0.00392157
|
||||
mean: [0.485, 0.456, 0.406]
|
||||
std: [0.229, 0.224, 0.225]
|
||||
order: ''
|
||||
sampler:
|
||||
name: DistributedBatchSampler
|
||||
batch_size: 64
|
||||
drop_last: False
|
||||
shuffle: False
|
||||
loader:
|
||||
num_workers: 6
|
||||
use_shared_memory: False
|
||||
|
||||
Infer:
|
||||
infer_imgs: "docs/images/whl/demo.jpg"
|
||||
batch_size: 10
|
||||
transforms:
|
||||
- DecodeImage:
|
||||
to_rgb: True
|
||||
channel_first: False
|
||||
- ResizeImage:
|
||||
resize_short: 256
|
||||
- CropImage:
|
||||
size: 224
|
||||
- NormalizeImage:
|
||||
scale: 1.0/255.0
|
||||
mean: [0.485, 0.456, 0.406]
|
||||
std: [0.229, 0.224, 0.225]
|
||||
order: ''
|
||||
- ToCHWImage:
|
||||
PostProcess:
|
||||
name: Topk
|
||||
topk: 5
|
||||
class_id_map_file: "ppcls/utils/imagenet1k_label_list.txt"
|
||||
|
||||
Metric:
|
||||
Train:
|
||||
- Topk:
|
||||
k: [1, 5]
|
||||
Eval:
|
||||
- Topk:
|
||||
k: [1, 5]
|
||||
|
||||
|
|
@ -0,0 +1,124 @@
|
|||
# global configs
|
||||
Global:
|
||||
checkpoints: null
|
||||
pretrained_model: null
|
||||
output_dir: "./output/"
|
||||
device: "gpu"
|
||||
class_num: 1000
|
||||
save_interval: 1
|
||||
eval_during_train: True
|
||||
eval_interval: 1
|
||||
epochs: 120
|
||||
print_batch_step: 10
|
||||
use_visualdl: False
|
||||
# used for static mode and model export
|
||||
image_shape: [3, 224, 224]
|
||||
save_inference_dir: "./inference"
|
||||
|
||||
# model architecture
|
||||
Arch:
|
||||
name: "HRNet_W64_C"
|
||||
|
||||
# loss function config for traing/eval process
|
||||
Loss:
|
||||
Train:
|
||||
- CELoss:
|
||||
weight: 1.0
|
||||
Eval:
|
||||
- CELoss:
|
||||
weight: 1.0
|
||||
|
||||
|
||||
Optimizer:
|
||||
name: Momentum
|
||||
momentum: 0.9
|
||||
lr:
|
||||
name: Piecewise
|
||||
learning_rate: 0.1
|
||||
decay_epochs: [30, 60, 90]
|
||||
values: [0.1, 0.01, 0.001, 0.0001]
|
||||
regularizer:
|
||||
name: 'L2'
|
||||
coeff: 0.0001
|
||||
|
||||
|
||||
# data loader for train and eval
|
||||
DataLoader:
|
||||
Train:
|
||||
dataset:
|
||||
name: ImageNetDataset
|
||||
image_root: "./dataset/ILSVRC2012/"
|
||||
cls_label_path: "./dataset/ILSVRC2012/train_list.txt"
|
||||
transform_ops:
|
||||
- RandCropImage:
|
||||
size: 224
|
||||
- RandFlipImage:
|
||||
flip_code: 1
|
||||
- NormalizeImage:
|
||||
scale: 0.00392157
|
||||
mean: [0.485, 0.456, 0.406]
|
||||
std: [0.229, 0.224, 0.225]
|
||||
order: ''
|
||||
|
||||
sampler:
|
||||
name: DistributedBatchSampler
|
||||
batch_size: 64
|
||||
drop_last: False
|
||||
shuffle: True
|
||||
loader:
|
||||
num_workers: 6
|
||||
use_shared_memory: False
|
||||
|
||||
Eval:
|
||||
# TOTO: modify to the latest trainer
|
||||
dataset:
|
||||
name: ImageNetDataset
|
||||
image_root: "./dataset/ILSVRC2012/"
|
||||
cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
|
||||
transform_ops:
|
||||
- ResizeImage:
|
||||
size: 224
|
||||
- NormalizeImage:
|
||||
scale: 0.00392157
|
||||
mean: [0.485, 0.456, 0.406]
|
||||
std: [0.229, 0.224, 0.225]
|
||||
order: ''
|
||||
sampler:
|
||||
name: DistributedBatchSampler
|
||||
batch_size: 64
|
||||
drop_last: False
|
||||
shuffle: False
|
||||
loader:
|
||||
num_workers: 6
|
||||
use_shared_memory: False
|
||||
|
||||
Infer:
|
||||
infer_imgs: "docs/images/whl/demo.jpg"
|
||||
batch_size: 10
|
||||
transforms:
|
||||
- DecodeImage:
|
||||
to_rgb: True
|
||||
channel_first: False
|
||||
- ResizeImage:
|
||||
resize_short: 256
|
||||
- CropImage:
|
||||
size: 224
|
||||
- NormalizeImage:
|
||||
scale: 1.0/255.0
|
||||
mean: [0.485, 0.456, 0.406]
|
||||
std: [0.229, 0.224, 0.225]
|
||||
order: ''
|
||||
- ToCHWImage:
|
||||
PostProcess:
|
||||
name: Topk
|
||||
topk: 5
|
||||
class_id_map_file: "ppcls/utils/imagenet1k_label_list.txt"
|
||||
|
||||
Metric:
|
||||
Train:
|
||||
- Topk:
|
||||
k: [1, 5]
|
||||
Eval:
|
||||
- Topk:
|
||||
k: [1, 5]
|
||||
|
||||
|
|
@ -0,0 +1,124 @@
|
|||
# global configs
|
||||
Global:
|
||||
checkpoints: null
|
||||
pretrained_model: null
|
||||
output_dir: "./output/"
|
||||
device: "gpu"
|
||||
class_num: 1000
|
||||
save_interval: 1
|
||||
eval_during_train: True
|
||||
eval_interval: 1
|
||||
epochs: 200
|
||||
print_batch_step: 10
|
||||
use_visualdl: False
|
||||
# used for static mode and model export
|
||||
image_shape: [3, 224, 224]
|
||||
save_inference_dir: "./inference"
|
||||
|
||||
# model architecture
|
||||
Arch:
|
||||
name: "InceptionV3"
|
||||
|
||||
# loss function config for traing/eval process
|
||||
Loss:
|
||||
Train:
|
||||
- CELoss:
|
||||
weight: 1.0
|
||||
Eval:
|
||||
- CELoss:
|
||||
weight: 1.0
|
||||
|
||||
|
||||
Optimizer:
|
||||
name: Momentum
|
||||
momentum: 0.9
|
||||
lr:
|
||||
name: Cosine
|
||||
learning_rate: 0.045
|
||||
decay_epochs: [30, 60, 90]
|
||||
values: [0.1, 0.01, 0.001, 0.0001]
|
||||
regularizer:
|
||||
name: 'L2'
|
||||
coeff: 0.0001
|
||||
|
||||
|
||||
# data loader for train and eval
|
||||
DataLoader:
|
||||
Train:
|
||||
dataset:
|
||||
name: ImageNetDataset
|
||||
image_root: "./dataset/ILSVRC2012/"
|
||||
cls_label_path: "./dataset/ILSVRC2012/train_list.txt"
|
||||
transform_ops:
|
||||
- RandCropImage:
|
||||
size: 299
|
||||
- RandFlipImage:
|
||||
flip_code: 1
|
||||
- NormalizeImage:
|
||||
scale: 0.00392157
|
||||
mean: [0.485, 0.456, 0.406]
|
||||
std: [0.229, 0.224, 0.225]
|
||||
order: ''
|
||||
|
||||
sampler:
|
||||
name: DistributedBatchSampler
|
||||
batch_size: 64
|
||||
drop_last: False
|
||||
shuffle: True
|
||||
loader:
|
||||
num_workers: 6
|
||||
use_shared_memory: False
|
||||
|
||||
Eval:
|
||||
# TOTO: modify to the latest trainer
|
||||
dataset:
|
||||
name: ImageNetDataset
|
||||
image_root: "./dataset/ILSVRC2012/"
|
||||
cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
|
||||
transform_ops:
|
||||
- ResizeImage:
|
||||
size: 224
|
||||
- NormalizeImage:
|
||||
scale: 0.00392157
|
||||
mean: [0.485, 0.456, 0.406]
|
||||
std: [0.229, 0.224, 0.225]
|
||||
order: ''
|
||||
sampler:
|
||||
name: DistributedBatchSampler
|
||||
batch_size: 64
|
||||
drop_last: False
|
||||
shuffle: False
|
||||
loader:
|
||||
num_workers: 6
|
||||
use_shared_memory: False
|
||||
|
||||
Infer:
|
||||
infer_imgs: "docs/images/whl/demo.jpg"
|
||||
batch_size: 10
|
||||
transforms:
|
||||
- DecodeImage:
|
||||
to_rgb: True
|
||||
channel_first: False
|
||||
- ResizeImage:
|
||||
resize_short: 320
|
||||
- CropImage:
|
||||
size: 299
|
||||
- NormalizeImage:
|
||||
scale: 1.0/255.0
|
||||
mean: [0.485, 0.456, 0.406]
|
||||
std: [0.229, 0.224, 0.225]
|
||||
order: ''
|
||||
- ToCHWImage:
|
||||
PostProcess:
|
||||
name: Topk
|
||||
topk: 5
|
||||
class_id_map_file: "ppcls/utils/imagenet1k_label_list.txt"
|
||||
|
||||
Metric:
|
||||
Train:
|
||||
- Topk:
|
||||
k: [1, 5]
|
||||
Eval:
|
||||
- Topk:
|
||||
k: [1, 5]
|
||||
|
||||
|
|
@ -0,0 +1,124 @@
|
|||
# global configs
|
||||
Global:
|
||||
checkpoints: null
|
||||
pretrained_model: null
|
||||
output_dir: "./output/"
|
||||
device: "gpu"
|
||||
class_num: 1000
|
||||
save_interval: 1
|
||||
eval_during_train: True
|
||||
eval_interval: 1
|
||||
epochs: 120
|
||||
print_batch_step: 10
|
||||
use_visualdl: False
|
||||
# used for static mode and model export
|
||||
image_shape: [3, 224, 224]
|
||||
save_inference_dir: "./inference"
|
||||
|
||||
# model architecture
|
||||
Arch:
|
||||
name: "MobileNetV1"
|
||||
|
||||
# loss function config for traing/eval process
|
||||
Loss:
|
||||
Train:
|
||||
- CELoss:
|
||||
weight: 1.0
|
||||
Eval:
|
||||
- CELoss:
|
||||
weight: 1.0
|
||||
|
||||
|
||||
Optimizer:
|
||||
name: Momentum
|
||||
momentum: 0.9
|
||||
lr:
|
||||
name: Piecewise
|
||||
learning_rate: 0.1
|
||||
decay_epochs: [30, 60, 90]
|
||||
values: [0.1, 0.01, 0.001, 0.0001]
|
||||
regularizer:
|
||||
name: 'L2'
|
||||
coeff: 0.00003
|
||||
|
||||
|
||||
# data loader for train and eval
|
||||
DataLoader:
|
||||
Train:
|
||||
dataset:
|
||||
name: ImageNetDataset
|
||||
image_root: "./dataset/ILSVRC2012/"
|
||||
cls_label_path: "./dataset/ILSVRC2012/train_list.txt"
|
||||
transform_ops:
|
||||
- RandCropImage:
|
||||
size: 224
|
||||
- RandFlipImage:
|
||||
flip_code: 1
|
||||
- NormalizeImage:
|
||||
scale: 0.00392157
|
||||
mean: [0.485, 0.456, 0.406]
|
||||
std: [0.229, 0.224, 0.225]
|
||||
order: ''
|
||||
|
||||
sampler:
|
||||
name: DistributedBatchSampler
|
||||
batch_size: 64
|
||||
drop_last: False
|
||||
shuffle: True
|
||||
loader:
|
||||
num_workers: 6
|
||||
use_shared_memory: False
|
||||
|
||||
Eval:
|
||||
# TOTO: modify to the latest trainer
|
||||
dataset:
|
||||
name: ImageNetDataset
|
||||
image_root: "./dataset/ILSVRC2012/"
|
||||
cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
|
||||
transform_ops:
|
||||
- ResizeImage:
|
||||
size: 224
|
||||
- NormalizeImage:
|
||||
scale: 0.00392157
|
||||
mean: [0.485, 0.456, 0.406]
|
||||
std: [0.229, 0.224, 0.225]
|
||||
order: ''
|
||||
sampler:
|
||||
name: DistributedBatchSampler
|
||||
batch_size: 64
|
||||
drop_last: False
|
||||
shuffle: False
|
||||
loader:
|
||||
num_workers: 6
|
||||
use_shared_memory: False
|
||||
|
||||
Infer:
|
||||
infer_imgs: "docs/images/whl/demo.jpg"
|
||||
batch_size: 10
|
||||
transforms:
|
||||
- DecodeImage:
|
||||
to_rgb: True
|
||||
channel_first: False
|
||||
- ResizeImage:
|
||||
resize_short: 256
|
||||
- CropImage:
|
||||
size: 224
|
||||
- NormalizeImage:
|
||||
scale: 1.0/255.0
|
||||
mean: [0.485, 0.456, 0.406]
|
||||
std: [0.229, 0.224, 0.225]
|
||||
order: ''
|
||||
- ToCHWImage:
|
||||
PostProcess:
|
||||
name: Topk
|
||||
topk: 5
|
||||
class_id_map_file: "ppcls/utils/imagenet1k_label_list.txt"
|
||||
|
||||
Metric:
|
||||
Train:
|
||||
- Topk:
|
||||
k: [1, 5]
|
||||
Eval:
|
||||
- Topk:
|
||||
k: [1, 5]
|
||||
|
||||
|
|
@ -0,0 +1,124 @@
|
|||
# global configs
|
||||
Global:
|
||||
checkpoints: null
|
||||
pretrained_model: null
|
||||
output_dir: "./output/"
|
||||
device: "gpu"
|
||||
class_num: 1000
|
||||
save_interval: 1
|
||||
eval_during_train: True
|
||||
eval_interval: 1
|
||||
epochs: 120
|
||||
print_batch_step: 10
|
||||
use_visualdl: False
|
||||
# used for static mode and model export
|
||||
image_shape: [3, 224, 224]
|
||||
save_inference_dir: "./inference"
|
||||
|
||||
# model architecture
|
||||
Arch:
|
||||
name: "MobileNetV1_x0_25"
|
||||
|
||||
# loss function config for traing/eval process
|
||||
Loss:
|
||||
Train:
|
||||
- CELoss:
|
||||
weight: 1.0
|
||||
Eval:
|
||||
- CELoss:
|
||||
weight: 1.0
|
||||
|
||||
|
||||
Optimizer:
|
||||
name: Momentum
|
||||
momentum: 0.9
|
||||
lr:
|
||||
name: Piecewise
|
||||
learning_rate: 0.1
|
||||
decay_epochs: [30, 60, 90]
|
||||
values: [0.1, 0.01, 0.001, 0.0001]
|
||||
regularizer:
|
||||
name: 'L2'
|
||||
coeff: 0.00003
|
||||
|
||||
|
||||
# data loader for train and eval
|
||||
DataLoader:
|
||||
Train:
|
||||
dataset:
|
||||
name: ImageNetDataset
|
||||
image_root: "./dataset/ILSVRC2012/"
|
||||
cls_label_path: "./dataset/ILSVRC2012/train_list.txt"
|
||||
transform_ops:
|
||||
- RandCropImage:
|
||||
size: 224
|
||||
- RandFlipImage:
|
||||
flip_code: 1
|
||||
- NormalizeImage:
|
||||
scale: 0.00392157
|
||||
mean: [0.485, 0.456, 0.406]
|
||||
std: [0.229, 0.224, 0.225]
|
||||
order: ''
|
||||
|
||||
sampler:
|
||||
name: DistributedBatchSampler
|
||||
batch_size: 64
|
||||
drop_last: False
|
||||
shuffle: True
|
||||
loader:
|
||||
num_workers: 6
|
||||
use_shared_memory: False
|
||||
|
||||
Eval:
|
||||
# TOTO: modify to the latest trainer
|
||||
dataset:
|
||||
name: ImageNetDataset
|
||||
image_root: "./dataset/ILSVRC2012/"
|
||||
cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
|
||||
transform_ops:
|
||||
- ResizeImage:
|
||||
size: 224
|
||||
- NormalizeImage:
|
||||
scale: 0.00392157
|
||||
mean: [0.485, 0.456, 0.406]
|
||||
std: [0.229, 0.224, 0.225]
|
||||
order: ''
|
||||
sampler:
|
||||
name: DistributedBatchSampler
|
||||
batch_size: 64
|
||||
drop_last: False
|
||||
shuffle: False
|
||||
loader:
|
||||
num_workers: 6
|
||||
use_shared_memory: False
|
||||
|
||||
Infer:
|
||||
infer_imgs: "docs/images/whl/demo.jpg"
|
||||
batch_size: 10
|
||||
transforms:
|
||||
- DecodeImage:
|
||||
to_rgb: True
|
||||
channel_first: False
|
||||
- ResizeImage:
|
||||
resize_short: 256
|
||||
- CropImage:
|
||||
size: 224
|
||||
- NormalizeImage:
|
||||
scale: 1.0/255.0
|
||||
mean: [0.485, 0.456, 0.406]
|
||||
std: [0.229, 0.224, 0.225]
|
||||
order: ''
|
||||
- ToCHWImage:
|
||||
PostProcess:
|
||||
name: Topk
|
||||
topk: 5
|
||||
class_id_map_file: "ppcls/utils/imagenet1k_label_list.txt"
|
||||
|
||||
Metric:
|
||||
Train:
|
||||
- Topk:
|
||||
k: [1, 5]
|
||||
Eval:
|
||||
- Topk:
|
||||
k: [1, 5]
|
||||
|
||||
|
|
@ -0,0 +1,124 @@
|
|||
# global configs
|
||||
Global:
|
||||
checkpoints: null
|
||||
pretrained_model: null
|
||||
output_dir: "./output/"
|
||||
device: "gpu"
|
||||
class_num: 1000
|
||||
save_interval: 1
|
||||
eval_during_train: True
|
||||
eval_interval: 1
|
||||
epochs: 120
|
||||
print_batch_step: 10
|
||||
use_visualdl: False
|
||||
# used for static mode and model export
|
||||
image_shape: [3, 224, 224]
|
||||
save_inference_dir: "./inference"
|
||||
|
||||
# model architecture
|
||||
Arch:
|
||||
name: "MobileNetV1_x0_5"
|
||||
|
||||
# loss function config for traing/eval process
|
||||
Loss:
|
||||
Train:
|
||||
- CELoss:
|
||||
weight: 1.0
|
||||
Eval:
|
||||
- CELoss:
|
||||
weight: 1.0
|
||||
|
||||
|
||||
Optimizer:
|
||||
name: Momentum
|
||||
momentum: 0.9
|
||||
lr:
|
||||
name: Piecewise
|
||||
learning_rate: 0.1
|
||||
decay_epochs: [30, 60, 90]
|
||||
values: [0.1, 0.01, 0.001, 0.0001]
|
||||
regularizer:
|
||||
name: 'L2'
|
||||
coeff: 0.00003
|
||||
|
||||
|
||||
# data loader for train and eval
|
||||
DataLoader:
|
||||
Train:
|
||||
dataset:
|
||||
name: ImageNetDataset
|
||||
image_root: "./dataset/ILSVRC2012/"
|
||||
cls_label_path: "./dataset/ILSVRC2012/train_list.txt"
|
||||
transform_ops:
|
||||
- RandCropImage:
|
||||
size: 224
|
||||
- RandFlipImage:
|
||||
flip_code: 1
|
||||
- NormalizeImage:
|
||||
scale: 0.00392157
|
||||
mean: [0.485, 0.456, 0.406]
|
||||
std: [0.229, 0.224, 0.225]
|
||||
order: ''
|
||||
|
||||
sampler:
|
||||
name: DistributedBatchSampler
|
||||
batch_size: 64
|
||||
drop_last: False
|
||||
shuffle: True
|
||||
loader:
|
||||
num_workers: 6
|
||||
use_shared_memory: False
|
||||
|
||||
Eval:
|
||||
# TOTO: modify to the latest trainer
|
||||
dataset:
|
||||
name: ImageNetDataset
|
||||
image_root: "./dataset/ILSVRC2012/"
|
||||
cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
|
||||
transform_ops:
|
||||
- ResizeImage:
|
||||
size: 224
|
||||
- NormalizeImage:
|
||||
scale: 0.00392157
|
||||
mean: [0.485, 0.456, 0.406]
|
||||
std: [0.229, 0.224, 0.225]
|
||||
order: ''
|
||||
sampler:
|
||||
name: DistributedBatchSampler
|
||||
batch_size: 64
|
||||
drop_last: False
|
||||
shuffle: False
|
||||
loader:
|
||||
num_workers: 6
|
||||
use_shared_memory: False
|
||||
|
||||
Infer:
|
||||
infer_imgs: "docs/images/whl/demo.jpg"
|
||||
batch_size: 10
|
||||
transforms:
|
||||
- DecodeImage:
|
||||
to_rgb: True
|
||||
channel_first: False
|
||||
- ResizeImage:
|
||||
resize_short: 256
|
||||
- CropImage:
|
||||
size: 224
|
||||
- NormalizeImage:
|
||||
scale: 1.0/255.0
|
||||
mean: [0.485, 0.456, 0.406]
|
||||
std: [0.229, 0.224, 0.225]
|
||||
order: ''
|
||||
- ToCHWImage:
|
||||
PostProcess:
|
||||
name: Topk
|
||||
topk: 5
|
||||
class_id_map_file: "ppcls/utils/imagenet1k_label_list.txt"
|
||||
|
||||
Metric:
|
||||
Train:
|
||||
- Topk:
|
||||
k: [1, 5]
|
||||
Eval:
|
||||
- Topk:
|
||||
k: [1, 5]
|
||||
|
||||
|
|
@ -0,0 +1,124 @@
|
|||
# global configs
|
||||
Global:
|
||||
checkpoints: null
|
||||
pretrained_model: null
|
||||
output_dir: "./output/"
|
||||
device: "gpu"
|
||||
class_num: 1000
|
||||
save_interval: 1
|
||||
eval_during_train: True
|
||||
eval_interval: 1
|
||||
epochs: 120
|
||||
print_batch_step: 10
|
||||
use_visualdl: False
|
||||
# used for static mode and model export
|
||||
image_shape: [3, 224, 224]
|
||||
save_inference_dir: "./inference"
|
||||
|
||||
# model architecture
|
||||
Arch:
|
||||
name: "MobileNetV1_x0_75"
|
||||
|
||||
# loss function config for traing/eval process
|
||||
Loss:
|
||||
Train:
|
||||
- CELoss:
|
||||
weight: 1.0
|
||||
Eval:
|
||||
- CELoss:
|
||||
weight: 1.0
|
||||
|
||||
|
||||
Optimizer:
|
||||
name: Momentum
|
||||
momentum: 0.9
|
||||
lr:
|
||||
name: Piecewise
|
||||
learning_rate: 0.1
|
||||
decay_epochs: [30, 60, 90]
|
||||
values: [0.1, 0.01, 0.001, 0.0001]
|
||||
regularizer:
|
||||
name: 'L2'
|
||||
coeff: 0.00003
|
||||
|
||||
|
||||
# data loader for train and eval
|
||||
DataLoader:
|
||||
Train:
|
||||
dataset:
|
||||
name: ImageNetDataset
|
||||
image_root: "./dataset/ILSVRC2012/"
|
||||
cls_label_path: "./dataset/ILSVRC2012/train_list.txt"
|
||||
transform_ops:
|
||||
- RandCropImage:
|
||||
size: 224
|
||||
- RandFlipImage:
|
||||
flip_code: 1
|
||||
- NormalizeImage:
|
||||
scale: 0.00392157
|
||||
mean: [0.485, 0.456, 0.406]
|
||||
std: [0.229, 0.224, 0.225]
|
||||
order: ''
|
||||
|
||||
sampler:
|
||||
name: DistributedBatchSampler
|
||||
batch_size: 64
|
||||
drop_last: False
|
||||
shuffle: True
|
||||
loader:
|
||||
num_workers: 6
|
||||
use_shared_memory: False
|
||||
|
||||
Eval:
|
||||
# TOTO: modify to the latest trainer
|
||||
dataset:
|
||||
name: ImageNetDataset
|
||||
image_root: "./dataset/ILSVRC2012/"
|
||||
cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
|
||||
transform_ops:
|
||||
- ResizeImage:
|
||||
size: 224
|
||||
- NormalizeImage:
|
||||
scale: 0.00392157
|
||||
mean: [0.485, 0.456, 0.406]
|
||||
std: [0.229, 0.224, 0.225]
|
||||
order: ''
|
||||
sampler:
|
||||
name: DistributedBatchSampler
|
||||
batch_size: 64
|
||||
drop_last: False
|
||||
shuffle: False
|
||||
loader:
|
||||
num_workers: 6
|
||||
use_shared_memory: False
|
||||
|
||||
Infer:
|
||||
infer_imgs: "docs/images/whl/demo.jpg"
|
||||
batch_size: 10
|
||||
transforms:
|
||||
- DecodeImage:
|
||||
to_rgb: True
|
||||
channel_first: False
|
||||
- ResizeImage:
|
||||
resize_short: 256
|
||||
- CropImage:
|
||||
size: 224
|
||||
- NormalizeImage:
|
||||
scale: 1.0/255.0
|
||||
mean: [0.485, 0.456, 0.406]
|
||||
std: [0.229, 0.224, 0.225]
|
||||
order: ''
|
||||
- ToCHWImage:
|
||||
PostProcess:
|
||||
name: Topk
|
||||
topk: 5
|
||||
class_id_map_file: "ppcls/utils/imagenet1k_label_list.txt"
|
||||
|
||||
Metric:
|
||||
Train:
|
||||
- Topk:
|
||||
k: [1, 5]
|
||||
Eval:
|
||||
- Topk:
|
||||
k: [1, 5]
|
||||
|
||||
|
|
@ -0,0 +1,122 @@
|
|||
# global configs
|
||||
Global:
|
||||
checkpoints: null
|
||||
pretrained_model: null
|
||||
output_dir: "./output/"
|
||||
device: "gpu"
|
||||
class_num: 1000
|
||||
save_interval: 1
|
||||
eval_during_train: True
|
||||
eval_interval: 1
|
||||
epochs: 360
|
||||
print_batch_step: 10
|
||||
use_visualdl: False
|
||||
# used for static mode and model export
|
||||
image_shape: [3, 224, 224]
|
||||
save_inference_dir: "./inference"
|
||||
|
||||
# model architecture
|
||||
Arch:
|
||||
name: "MobileNetV3_large_x0_35"
|
||||
|
||||
# loss function config for traing/eval process
|
||||
Loss:
|
||||
Train:
|
||||
- CELoss:
|
||||
weight: 1.0
|
||||
Eval:
|
||||
- CELoss:
|
||||
weight: 1.0
|
||||
|
||||
|
||||
Optimizer:
|
||||
name: Momentum
|
||||
momentum: 0.9
|
||||
lr:
|
||||
name: Cosine
|
||||
learning_rate: 1.3
|
||||
regularizer:
|
||||
name: 'L2'
|
||||
coeff: 0.00002
|
||||
|
||||
|
||||
# data loader for train and eval
|
||||
DataLoader:
|
||||
Train:
|
||||
dataset:
|
||||
name: ImageNetDataset
|
||||
image_root: "./dataset/ILSVRC2012/"
|
||||
cls_label_path: "./dataset/ILSVRC2012/train_list.txt"
|
||||
transform_ops:
|
||||
- RandCropImage:
|
||||
size: 224
|
||||
- RandFlipImage:
|
||||
flip_code: 1
|
||||
- NormalizeImage:
|
||||
scale: 0.00392157
|
||||
mean: [0.485, 0.456, 0.406]
|
||||
std: [0.229, 0.224, 0.225]
|
||||
order: ''
|
||||
|
||||
sampler:
|
||||
name: DistributedBatchSampler
|
||||
batch_size: 512
|
||||
drop_last: False
|
||||
shuffle: True
|
||||
loader:
|
||||
num_workers: 6
|
||||
use_shared_memory: False
|
||||
|
||||
Eval:
|
||||
# TOTO: modify to the latest trainer
|
||||
dataset:
|
||||
name: ImageNetDataset
|
||||
image_root: "./dataset/ILSVRC2012/"
|
||||
cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
|
||||
transform_ops:
|
||||
- ResizeImage:
|
||||
size: 224
|
||||
- NormalizeImage:
|
||||
scale: 0.00392157
|
||||
mean: [0.485, 0.456, 0.406]
|
||||
std: [0.229, 0.224, 0.225]
|
||||
order: ''
|
||||
sampler:
|
||||
name: DistributedBatchSampler
|
||||
batch_size: 64
|
||||
drop_last: False
|
||||
shuffle: False
|
||||
loader:
|
||||
num_workers: 6
|
||||
use_shared_memory: False
|
||||
|
||||
Infer:
|
||||
infer_imgs: "docs/images/whl/demo.jpg"
|
||||
batch_size: 10
|
||||
transforms:
|
||||
- DecodeImage:
|
||||
to_rgb: True
|
||||
channel_first: False
|
||||
- ResizeImage:
|
||||
resize_short: 256
|
||||
- CropImage:
|
||||
size: 224
|
||||
- NormalizeImage:
|
||||
scale: 1.0/255.0
|
||||
mean: [0.485, 0.456, 0.406]
|
||||
std: [0.229, 0.224, 0.225]
|
||||
order: ''
|
||||
- ToCHWImage:
|
||||
PostProcess:
|
||||
name: Topk
|
||||
topk: 5
|
||||
class_id_map_file: "ppcls/utils/imagenet1k_label_list.txt"
|
||||
|
||||
Metric:
|
||||
Train:
|
||||
- Topk:
|
||||
k: [1, 5]
|
||||
Eval:
|
||||
- Topk:
|
||||
k: [1, 5]
|
||||
|
||||
|
|
@ -0,0 +1,122 @@
|
|||
# global configs
|
||||
Global:
|
||||
checkpoints: null
|
||||
pretrained_model: null
|
||||
output_dir: "./output/"
|
||||
device: "gpu"
|
||||
class_num: 1000
|
||||
save_interval: 1
|
||||
eval_during_train: True
|
||||
eval_interval: 1
|
||||
epochs: 360
|
||||
print_batch_step: 10
|
||||
use_visualdl: False
|
||||
# used for static mode and model export
|
||||
image_shape: [3, 224, 224]
|
||||
save_inference_dir: "./inference"
|
||||
|
||||
# model architecture
|
||||
Arch:
|
||||
name: "MobileNetV3_large_x0_5"
|
||||
|
||||
# loss function config for traing/eval process
|
||||
Loss:
|
||||
Train:
|
||||
- CELoss:
|
||||
weight: 1.0
|
||||
Eval:
|
||||
- CELoss:
|
||||
weight: 1.0
|
||||
|
||||
|
||||
Optimizer:
|
||||
name: Momentum
|
||||
momentum: 0.9
|
||||
lr:
|
||||
name: Cosine
|
||||
learning_rate: 1.3
|
||||
regularizer:
|
||||
name: 'L2'
|
||||
coeff: 0.00002
|
||||
|
||||
|
||||
# data loader for train and eval
|
||||
DataLoader:
|
||||
Train:
|
||||
dataset:
|
||||
name: ImageNetDataset
|
||||
image_root: "./dataset/ILSVRC2012/"
|
||||
cls_label_path: "./dataset/ILSVRC2012/train_list.txt"
|
||||
transform_ops:
|
||||
- RandCropImage:
|
||||
size: 224
|
||||
- RandFlipImage:
|
||||
flip_code: 1
|
||||
- NormalizeImage:
|
||||
scale: 0.00392157
|
||||
mean: [0.485, 0.456, 0.406]
|
||||
std: [0.229, 0.224, 0.225]
|
||||
order: ''
|
||||
|
||||
sampler:
|
||||
name: DistributedBatchSampler
|
||||
batch_size: 512
|
||||
drop_last: False
|
||||
shuffle: True
|
||||
loader:
|
||||
num_workers: 6
|
||||
use_shared_memory: False
|
||||
|
||||
Eval:
|
||||
# TOTO: modify to the latest trainer
|
||||
dataset:
|
||||
name: ImageNetDataset
|
||||
image_root: "./dataset/ILSVRC2012/"
|
||||
cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
|
||||
transform_ops:
|
||||
- ResizeImage:
|
||||
size: 224
|
||||
- NormalizeImage:
|
||||
scale: 0.00392157
|
||||
mean: [0.485, 0.456, 0.406]
|
||||
std: [0.229, 0.224, 0.225]
|
||||
order: ''
|
||||
sampler:
|
||||
name: DistributedBatchSampler
|
||||
batch_size: 64
|
||||
drop_last: False
|
||||
shuffle: False
|
||||
loader:
|
||||
num_workers: 6
|
||||
use_shared_memory: False
|
||||
|
||||
Infer:
|
||||
infer_imgs: "docs/images/whl/demo.jpg"
|
||||
batch_size: 10
|
||||
transforms:
|
||||
- DecodeImage:
|
||||
to_rgb: True
|
||||
channel_first: False
|
||||
- ResizeImage:
|
||||
resize_short: 256
|
||||
- CropImage:
|
||||
size: 224
|
||||
- NormalizeImage:
|
||||
scale: 1.0/255.0
|
||||
mean: [0.485, 0.456, 0.406]
|
||||
std: [0.229, 0.224, 0.225]
|
||||
order: ''
|
||||
- ToCHWImage:
|
||||
PostProcess:
|
||||
name: Topk
|
||||
topk: 5
|
||||
class_id_map_file: "ppcls/utils/imagenet1k_label_list.txt"
|
||||
|
||||
Metric:
|
||||
Train:
|
||||
- Topk:
|
||||
k: [1, 5]
|
||||
Eval:
|
||||
- Topk:
|
||||
k: [1, 5]
|
||||
|
||||
|
|
@ -0,0 +1,122 @@
|
|||
# global configs
|
||||
Global:
|
||||
checkpoints: null
|
||||
pretrained_model: null
|
||||
output_dir: "./output/"
|
||||
device: "gpu"
|
||||
class_num: 1000
|
||||
save_interval: 1
|
||||
eval_during_train: True
|
||||
eval_interval: 1
|
||||
epochs: 360
|
||||
print_batch_step: 10
|
||||
use_visualdl: False
|
||||
# used for static mode and model export
|
||||
image_shape: [3, 224, 224]
|
||||
save_inference_dir: "./inference"
|
||||
|
||||
# model architecture
|
||||
Arch:
|
||||
name: "MobileNetV3_large_x0_75"
|
||||
|
||||
# loss function config for traing/eval process
|
||||
Loss:
|
||||
Train:
|
||||
- CELoss:
|
||||
weight: 1.0
|
||||
Eval:
|
||||
- CELoss:
|
||||
weight: 1.0
|
||||
|
||||
|
||||
Optimizer:
|
||||
name: Momentum
|
||||
momentum: 0.9
|
||||
lr:
|
||||
name: Cosine
|
||||
learning_rate: 1.3
|
||||
regularizer:
|
||||
name: 'L2'
|
||||
coeff: 0.00002
|
||||
|
||||
|
||||
# data loader for train and eval
|
||||
DataLoader:
|
||||
Train:
|
||||
dataset:
|
||||
name: ImageNetDataset
|
||||
image_root: "./dataset/ILSVRC2012/"
|
||||
cls_label_path: "./dataset/ILSVRC2012/train_list.txt"
|
||||
transform_ops:
|
||||
- RandCropImage:
|
||||
size: 224
|
||||
- RandFlipImage:
|
||||
flip_code: 1
|
||||
- NormalizeImage:
|
||||
scale: 0.00392157
|
||||
mean: [0.485, 0.456, 0.406]
|
||||
std: [0.229, 0.224, 0.225]
|
||||
order: ''
|
||||
|
||||
sampler:
|
||||
name: DistributedBatchSampler
|
||||
batch_size: 512
|
||||
drop_last: False
|
||||
shuffle: True
|
||||
loader:
|
||||
num_workers: 6
|
||||
use_shared_memory: False
|
||||
|
||||
Eval:
|
||||
# TOTO: modify to the latest trainer
|
||||
dataset:
|
||||
name: ImageNetDataset
|
||||
image_root: "./dataset/ILSVRC2012/"
|
||||
cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
|
||||
transform_ops:
|
||||
- ResizeImage:
|
||||
size: 224
|
||||
- NormalizeImage:
|
||||
scale: 0.00392157
|
||||
mean: [0.485, 0.456, 0.406]
|
||||
std: [0.229, 0.224, 0.225]
|
||||
order: ''
|
||||
sampler:
|
||||
name: DistributedBatchSampler
|
||||
batch_size: 64
|
||||
drop_last: False
|
||||
shuffle: False
|
||||
loader:
|
||||
num_workers: 6
|
||||
use_shared_memory: False
|
||||
|
||||
Infer:
|
||||
infer_imgs: "docs/images/whl/demo.jpg"
|
||||
batch_size: 10
|
||||
transforms:
|
||||
- DecodeImage:
|
||||
to_rgb: True
|
||||
channel_first: False
|
||||
- ResizeImage:
|
||||
resize_short: 256
|
||||
- CropImage:
|
||||
size: 224
|
||||
- NormalizeImage:
|
||||
scale: 1.0/255.0
|
||||
mean: [0.485, 0.456, 0.406]
|
||||
std: [0.229, 0.224, 0.225]
|
||||
order: ''
|
||||
- ToCHWImage:
|
||||
PostProcess:
|
||||
name: Topk
|
||||
topk: 5
|
||||
class_id_map_file: "ppcls/utils/imagenet1k_label_list.txt"
|
||||
|
||||
Metric:
|
||||
Train:
|
||||
- Topk:
|
||||
k: [1, 5]
|
||||
Eval:
|
||||
- Topk:
|
||||
k: [1, 5]
|
||||
|
||||
|
|
@ -0,0 +1,122 @@
|
|||
# global configs
|
||||
Global:
|
||||
checkpoints: null
|
||||
pretrained_model: null
|
||||
output_dir: "./output/"
|
||||
device: "gpu"
|
||||
class_num: 1000
|
||||
save_interval: 1
|
||||
eval_during_train: True
|
||||
eval_interval: 1
|
||||
epochs: 360
|
||||
print_batch_step: 10
|
||||
use_visualdl: False
|
||||
# used for static mode and model export
|
||||
image_shape: [3, 224, 224]
|
||||
save_inference_dir: "./inference"
|
||||
|
||||
# model architecture
|
||||
Arch:
|
||||
name: "MobileNetV3_large_x1_0"
|
||||
|
||||
# loss function config for traing/eval process
|
||||
Loss:
|
||||
Train:
|
||||
- CELoss:
|
||||
weight: 1.0
|
||||
Eval:
|
||||
- CELoss:
|
||||
weight: 1.0
|
||||
|
||||
|
||||
Optimizer:
|
||||
name: Momentum
|
||||
momentum: 0.9
|
||||
lr:
|
||||
name: Cosine
|
||||
learning_rate: 1.3
|
||||
regularizer:
|
||||
name: 'L2'
|
||||
coeff: 0.00002
|
||||
|
||||
|
||||
# data loader for train and eval
|
||||
DataLoader:
|
||||
Train:
|
||||
dataset:
|
||||
name: ImageNetDataset
|
||||
image_root: "./dataset/ILSVRC2012/"
|
||||
cls_label_path: "./dataset/ILSVRC2012/train_list.txt"
|
||||
transform_ops:
|
||||
- RandCropImage:
|
||||
size: 224
|
||||
- RandFlipImage:
|
||||
flip_code: 1
|
||||
- NormalizeImage:
|
||||
scale: 0.00392157
|
||||
mean: [0.485, 0.456, 0.406]
|
||||
std: [0.229, 0.224, 0.225]
|
||||
order: ''
|
||||
|
||||
sampler:
|
||||
name: DistributedBatchSampler
|
||||
batch_size: 512
|
||||
drop_last: False
|
||||
shuffle: True
|
||||
loader:
|
||||
num_workers: 6
|
||||
use_shared_memory: False
|
||||
|
||||
Eval:
|
||||
# TOTO: modify to the latest trainer
|
||||
dataset:
|
||||
name: ImageNetDataset
|
||||
image_root: "./dataset/ILSVRC2012/"
|
||||
cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
|
||||
transform_ops:
|
||||
- ResizeImage:
|
||||
size: 224
|
||||
- NormalizeImage:
|
||||
scale: 0.00392157
|
||||
mean: [0.485, 0.456, 0.406]
|
||||
std: [0.229, 0.224, 0.225]
|
||||
order: ''
|
||||
sampler:
|
||||
name: DistributedBatchSampler
|
||||
batch_size: 64
|
||||
drop_last: False
|
||||
shuffle: False
|
||||
loader:
|
||||
num_workers: 6
|
||||
use_shared_memory: False
|
||||
|
||||
Infer:
|
||||
infer_imgs: "docs/images/whl/demo.jpg"
|
||||
batch_size: 10
|
||||
transforms:
|
||||
- DecodeImage:
|
||||
to_rgb: True
|
||||
channel_first: False
|
||||
- ResizeImage:
|
||||
resize_short: 256
|
||||
- CropImage:
|
||||
size: 224
|
||||
- NormalizeImage:
|
||||
scale: 1.0/255.0
|
||||
mean: [0.485, 0.456, 0.406]
|
||||
std: [0.229, 0.224, 0.225]
|
||||
order: ''
|
||||
- ToCHWImage:
|
||||
PostProcess:
|
||||
name: Topk
|
||||
topk: 5
|
||||
class_id_map_file: "ppcls/utils/imagenet1k_label_list.txt"
|
||||
|
||||
Metric:
|
||||
Train:
|
||||
- Topk:
|
||||
k: [1, 5]
|
||||
Eval:
|
||||
- Topk:
|
||||
k: [1, 5]
|
||||
|
||||
|
|
@ -0,0 +1,122 @@
|
|||
# global configs
|
||||
Global:
|
||||
checkpoints: null
|
||||
pretrained_model: null
|
||||
output_dir: "./output/"
|
||||
device: "gpu"
|
||||
class_num: 1000
|
||||
save_interval: 1
|
||||
eval_during_train: True
|
||||
eval_interval: 1
|
||||
epochs: 360
|
||||
print_batch_step: 10
|
||||
use_visualdl: False
|
||||
# used for static mode and model export
|
||||
image_shape: [3, 224, 224]
|
||||
save_inference_dir: "./inference"
|
||||
|
||||
# model architecture
|
||||
Arch:
|
||||
name: "MobileNetV3_large_x1_25"
|
||||
|
||||
# loss function config for traing/eval process
|
||||
Loss:
|
||||
Train:
|
||||
- CELoss:
|
||||
weight: 1.0
|
||||
Eval:
|
||||
- CELoss:
|
||||
weight: 1.0
|
||||
|
||||
|
||||
Optimizer:
|
||||
name: Momentum
|
||||
momentum: 0.9
|
||||
lr:
|
||||
name: Cosine
|
||||
learning_rate: 1.3
|
||||
regularizer:
|
||||
name: 'L2'
|
||||
coeff: 0.00002
|
||||
|
||||
|
||||
# data loader for train and eval
|
||||
DataLoader:
|
||||
Train:
|
||||
dataset:
|
||||
name: ImageNetDataset
|
||||
image_root: "./dataset/ILSVRC2012/"
|
||||
cls_label_path: "./dataset/ILSVRC2012/train_list.txt"
|
||||
transform_ops:
|
||||
- RandCropImage:
|
||||
size: 224
|
||||
- RandFlipImage:
|
||||
flip_code: 1
|
||||
- NormalizeImage:
|
||||
scale: 0.00392157
|
||||
mean: [0.485, 0.456, 0.406]
|
||||
std: [0.229, 0.224, 0.225]
|
||||
order: ''
|
||||
|
||||
sampler:
|
||||
name: DistributedBatchSampler
|
||||
batch_size: 512
|
||||
drop_last: False
|
||||
shuffle: True
|
||||
loader:
|
||||
num_workers: 6
|
||||
use_shared_memory: False
|
||||
|
||||
Eval:
|
||||
# TOTO: modify to the latest trainer
|
||||
dataset:
|
||||
name: ImageNetDataset
|
||||
image_root: "./dataset/ILSVRC2012/"
|
||||
cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
|
||||
transform_ops:
|
||||
- ResizeImage:
|
||||
size: 224
|
||||
- NormalizeImage:
|
||||
scale: 0.00392157
|
||||
mean: [0.485, 0.456, 0.406]
|
||||
std: [0.229, 0.224, 0.225]
|
||||
order: ''
|
||||
sampler:
|
||||
name: DistributedBatchSampler
|
||||
batch_size: 64
|
||||
drop_last: False
|
||||
shuffle: False
|
||||
loader:
|
||||
num_workers: 6
|
||||
use_shared_memory: False
|
||||
|
||||
Infer:
|
||||
infer_imgs: "docs/images/whl/demo.jpg"
|
||||
batch_size: 10
|
||||
transforms:
|
||||
- DecodeImage:
|
||||
to_rgb: True
|
||||
channel_first: False
|
||||
- ResizeImage:
|
||||
resize_short: 256
|
||||
- CropImage:
|
||||
size: 224
|
||||
- NormalizeImage:
|
||||
scale: 1.0/255.0
|
||||
mean: [0.485, 0.456, 0.406]
|
||||
std: [0.229, 0.224, 0.225]
|
||||
order: ''
|
||||
- ToCHWImage:
|
||||
PostProcess:
|
||||
name: Topk
|
||||
topk: 5
|
||||
class_id_map_file: "ppcls/utils/imagenet1k_label_list.txt"
|
||||
|
||||
Metric:
|
||||
Train:
|
||||
- Topk:
|
||||
k: [1, 5]
|
||||
Eval:
|
||||
- Topk:
|
||||
k: [1, 5]
|
||||
|
||||
|
|
@ -0,0 +1,122 @@
|
|||
# global configs
|
||||
Global:
|
||||
checkpoints: null
|
||||
pretrained_model: null
|
||||
output_dir: "./output/"
|
||||
device: "gpu"
|
||||
class_num: 1000
|
||||
save_interval: 1
|
||||
eval_during_train: True
|
||||
eval_interval: 1
|
||||
epochs: 360
|
||||
print_batch_step: 10
|
||||
use_visualdl: False
|
||||
# used for static mode and model export
|
||||
image_shape: [3, 224, 224]
|
||||
save_inference_dir: "./inference"
|
||||
|
||||
# model architecture
|
||||
Arch:
|
||||
name: "MobileNetV3_small_x0_35"
|
||||
|
||||
# loss function config for traing/eval process
|
||||
Loss:
|
||||
Train:
|
||||
- CELoss:
|
||||
weight: 1.0
|
||||
Eval:
|
||||
- CELoss:
|
||||
weight: 1.0
|
||||
|
||||
|
||||
Optimizer:
|
||||
name: Momentum
|
||||
momentum: 0.9
|
||||
lr:
|
||||
name: Cosine
|
||||
learning_rate: 1.3
|
||||
regularizer:
|
||||
name: 'L2'
|
||||
coeff: 0.00002
|
||||
|
||||
|
||||
# data loader for train and eval
|
||||
DataLoader:
|
||||
Train:
|
||||
dataset:
|
||||
name: ImageNetDataset
|
||||
image_root: "./dataset/ILSVRC2012/"
|
||||
cls_label_path: "./dataset/ILSVRC2012/train_list.txt"
|
||||
transform_ops:
|
||||
- RandCropImage:
|
||||
size: 224
|
||||
- RandFlipImage:
|
||||
flip_code: 1
|
||||
- NormalizeImage:
|
||||
scale: 0.00392157
|
||||
mean: [0.485, 0.456, 0.406]
|
||||
std: [0.229, 0.224, 0.225]
|
||||
order: ''
|
||||
|
||||
sampler:
|
||||
name: DistributedBatchSampler
|
||||
batch_size: 512
|
||||
drop_last: False
|
||||
shuffle: True
|
||||
loader:
|
||||
num_workers: 6
|
||||
use_shared_memory: False
|
||||
|
||||
Eval:
|
||||
# TOTO: modify to the latest trainer
|
||||
dataset:
|
||||
name: ImageNetDataset
|
||||
image_root: "./dataset/ILSVRC2012/"
|
||||
cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
|
||||
transform_ops:
|
||||
- ResizeImage:
|
||||
size: 224
|
||||
- NormalizeImage:
|
||||
scale: 0.00392157
|
||||
mean: [0.485, 0.456, 0.406]
|
||||
std: [0.229, 0.224, 0.225]
|
||||
order: ''
|
||||
sampler:
|
||||
name: DistributedBatchSampler
|
||||
batch_size: 64
|
||||
drop_last: False
|
||||
shuffle: False
|
||||
loader:
|
||||
num_workers: 6
|
||||
use_shared_memory: False
|
||||
|
||||
Infer:
|
||||
infer_imgs: "docs/images/whl/demo.jpg"
|
||||
batch_size: 10
|
||||
transforms:
|
||||
- DecodeImage:
|
||||
to_rgb: True
|
||||
channel_first: False
|
||||
- ResizeImage:
|
||||
resize_short: 256
|
||||
- CropImage:
|
||||
size: 224
|
||||
- NormalizeImage:
|
||||
scale: 1.0/255.0
|
||||
mean: [0.485, 0.456, 0.406]
|
||||
std: [0.229, 0.224, 0.225]
|
||||
order: ''
|
||||
- ToCHWImage:
|
||||
PostProcess:
|
||||
name: Topk
|
||||
topk: 5
|
||||
class_id_map_file: "ppcls/utils/imagenet1k_label_list.txt"
|
||||
|
||||
Metric:
|
||||
Train:
|
||||
- Topk:
|
||||
k: [1, 5]
|
||||
Eval:
|
||||
- Topk:
|
||||
k: [1, 5]
|
||||
|
||||
|
|
@ -0,0 +1,122 @@
|
|||
# global configs
|
||||
Global:
|
||||
checkpoints: null
|
||||
pretrained_model: null
|
||||
output_dir: "./output/"
|
||||
device: "gpu"
|
||||
class_num: 1000
|
||||
save_interval: 1
|
||||
eval_during_train: True
|
||||
eval_interval: 1
|
||||
epochs: 360
|
||||
print_batch_step: 10
|
||||
use_visualdl: False
|
||||
# used for static mode and model export
|
||||
image_shape: [3, 224, 224]
|
||||
save_inference_dir: "./inference"
|
||||
|
||||
# model architecture
|
||||
Arch:
|
||||
name: "MobileNetV3_small_x0_5"
|
||||
|
||||
# loss function config for traing/eval process
|
||||
Loss:
|
||||
Train:
|
||||
- CELoss:
|
||||
weight: 1.0
|
||||
Eval:
|
||||
- CELoss:
|
||||
weight: 1.0
|
||||
|
||||
|
||||
Optimizer:
|
||||
name: Momentum
|
||||
momentum: 0.9
|
||||
lr:
|
||||
name: Cosine
|
||||
learning_rate: 1.3
|
||||
regularizer:
|
||||
name: 'L2'
|
||||
coeff: 0.00002
|
||||
|
||||
|
||||
# data loader for train and eval
|
||||
DataLoader:
|
||||
Train:
|
||||
dataset:
|
||||
name: ImageNetDataset
|
||||
image_root: "./dataset/ILSVRC2012/"
|
||||
cls_label_path: "./dataset/ILSVRC2012/train_list.txt"
|
||||
transform_ops:
|
||||
- RandCropImage:
|
||||
size: 224
|
||||
- RandFlipImage:
|
||||
flip_code: 1
|
||||
- NormalizeImage:
|
||||
scale: 0.00392157
|
||||
mean: [0.485, 0.456, 0.406]
|
||||
std: [0.229, 0.224, 0.225]
|
||||
order: ''
|
||||
|
||||
sampler:
|
||||
name: DistributedBatchSampler
|
||||
batch_size: 512
|
||||
drop_last: False
|
||||
shuffle: True
|
||||
loader:
|
||||
num_workers: 6
|
||||
use_shared_memory: False
|
||||
|
||||
Eval:
|
||||
# TOTO: modify to the latest trainer
|
||||
dataset:
|
||||
name: ImageNetDataset
|
||||
image_root: "./dataset/ILSVRC2012/"
|
||||
cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
|
||||
transform_ops:
|
||||
- ResizeImage:
|
||||
size: 224
|
||||
- NormalizeImage:
|
||||
scale: 0.00392157
|
||||
mean: [0.485, 0.456, 0.406]
|
||||
std: [0.229, 0.224, 0.225]
|
||||
order: ''
|
||||
sampler:
|
||||
name: DistributedBatchSampler
|
||||
batch_size: 64
|
||||
drop_last: False
|
||||
shuffle: False
|
||||
loader:
|
||||
num_workers: 6
|
||||
use_shared_memory: False
|
||||
|
||||
Infer:
|
||||
infer_imgs: "docs/images/whl/demo.jpg"
|
||||
batch_size: 10
|
||||
transforms:
|
||||
- DecodeImage:
|
||||
to_rgb: True
|
||||
channel_first: False
|
||||
- ResizeImage:
|
||||
resize_short: 256
|
||||
- CropImage:
|
||||
size: 224
|
||||
- NormalizeImage:
|
||||
scale: 1.0/255.0
|
||||
mean: [0.485, 0.456, 0.406]
|
||||
std: [0.229, 0.224, 0.225]
|
||||
order: ''
|
||||
- ToCHWImage:
|
||||
PostProcess:
|
||||
name: Topk
|
||||
topk: 5
|
||||
class_id_map_file: "ppcls/utils/imagenet1k_label_list.txt"
|
||||
|
||||
Metric:
|
||||
Train:
|
||||
- Topk:
|
||||
k: [1, 5]
|
||||
Eval:
|
||||
- Topk:
|
||||
k: [1, 5]
|
||||
|
||||
|
|
@ -0,0 +1,122 @@
|
|||
# global configs
|
||||
Global:
|
||||
checkpoints: null
|
||||
pretrained_model: null
|
||||
output_dir: "./output/"
|
||||
device: "gpu"
|
||||
class_num: 1000
|
||||
save_interval: 1
|
||||
eval_during_train: True
|
||||
eval_interval: 1
|
||||
epochs: 360
|
||||
print_batch_step: 10
|
||||
use_visualdl: False
|
||||
# used for static mode and model export
|
||||
image_shape: [3, 224, 224]
|
||||
save_inference_dir: "./inference"
|
||||
|
||||
# model architecture
|
||||
Arch:
|
||||
name: "MobileNetV3_small_x0_75"
|
||||
|
||||
# loss function config for traing/eval process
|
||||
Loss:
|
||||
Train:
|
||||
- CELoss:
|
||||
weight: 1.0
|
||||
Eval:
|
||||
- CELoss:
|
||||
weight: 1.0
|
||||
|
||||
|
||||
Optimizer:
|
||||
name: Momentum
|
||||
momentum: 0.9
|
||||
lr:
|
||||
name: Cosine
|
||||
learning_rate: 1.3
|
||||
regularizer:
|
||||
name: 'L2'
|
||||
coeff: 0.00002
|
||||
|
||||
|
||||
# data loader for train and eval
|
||||
DataLoader:
|
||||
Train:
|
||||
dataset:
|
||||
name: ImageNetDataset
|
||||
image_root: "./dataset/ILSVRC2012/"
|
||||
cls_label_path: "./dataset/ILSVRC2012/train_list.txt"
|
||||
transform_ops:
|
||||
- RandCropImage:
|
||||
size: 224
|
||||
- RandFlipImage:
|
||||
flip_code: 1
|
||||
- NormalizeImage:
|
||||
scale: 0.00392157
|
||||
mean: [0.485, 0.456, 0.406]
|
||||
std: [0.229, 0.224, 0.225]
|
||||
order: ''
|
||||
|
||||
sampler:
|
||||
name: DistributedBatchSampler
|
||||
batch_size: 512
|
||||
drop_last: False
|
||||
shuffle: True
|
||||
loader:
|
||||
num_workers: 6
|
||||
use_shared_memory: False
|
||||
|
||||
Eval:
|
||||
# TOTO: modify to the latest trainer
|
||||
dataset:
|
||||
name: ImageNetDataset
|
||||
image_root: "./dataset/ILSVRC2012/"
|
||||
cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
|
||||
transform_ops:
|
||||
- ResizeImage:
|
||||
size: 224
|
||||
- NormalizeImage:
|
||||
scale: 0.00392157
|
||||
mean: [0.485, 0.456, 0.406]
|
||||
std: [0.229, 0.224, 0.225]
|
||||
order: ''
|
||||
sampler:
|
||||
name: DistributedBatchSampler
|
||||
batch_size: 64
|
||||
drop_last: False
|
||||
shuffle: False
|
||||
loader:
|
||||
num_workers: 6
|
||||
use_shared_memory: False
|
||||
|
||||
Infer:
|
||||
infer_imgs: "docs/images/whl/demo.jpg"
|
||||
batch_size: 10
|
||||
transforms:
|
||||
- DecodeImage:
|
||||
to_rgb: True
|
||||
channel_first: False
|
||||
- ResizeImage:
|
||||
resize_short: 256
|
||||
- CropImage:
|
||||
size: 224
|
||||
- NormalizeImage:
|
||||
scale: 1.0/255.0
|
||||
mean: [0.485, 0.456, 0.406]
|
||||
std: [0.229, 0.224, 0.225]
|
||||
order: ''
|
||||
- ToCHWImage:
|
||||
PostProcess:
|
||||
name: Topk
|
||||
topk: 5
|
||||
class_id_map_file: "ppcls/utils/imagenet1k_label_list.txt"
|
||||
|
||||
Metric:
|
||||
Train:
|
||||
- Topk:
|
||||
k: [1, 5]
|
||||
Eval:
|
||||
- Topk:
|
||||
k: [1, 5]
|
||||
|
||||
|
|
@ -0,0 +1,122 @@
|
|||
# global configs
|
||||
Global:
|
||||
checkpoints: null
|
||||
pretrained_model: null
|
||||
output_dir: "./output/"
|
||||
device: "gpu"
|
||||
class_num: 1000
|
||||
save_interval: 1
|
||||
eval_during_train: True
|
||||
eval_interval: 1
|
||||
epochs: 360
|
||||
print_batch_step: 10
|
||||
use_visualdl: False
|
||||
# used for static mode and model export
|
||||
image_shape: [3, 224, 224]
|
||||
save_inference_dir: "./inference"
|
||||
|
||||
# model architecture
|
||||
Arch:
|
||||
name: "MobileNetV3_small_x1_0"
|
||||
|
||||
# loss function config for traing/eval process
|
||||
Loss:
|
||||
Train:
|
||||
- CELoss:
|
||||
weight: 1.0
|
||||
Eval:
|
||||
- CELoss:
|
||||
weight: 1.0
|
||||
|
||||
|
||||
Optimizer:
|
||||
name: Momentum
|
||||
momentum: 0.9
|
||||
lr:
|
||||
name: Cosine
|
||||
learning_rate: 1.3
|
||||
regularizer:
|
||||
name: 'L2'
|
||||
coeff: 0.00002
|
||||
|
||||
|
||||
# data loader for train and eval
|
||||
DataLoader:
|
||||
Train:
|
||||
dataset:
|
||||
name: ImageNetDataset
|
||||
image_root: "./dataset/ILSVRC2012/"
|
||||
cls_label_path: "./dataset/ILSVRC2012/train_list.txt"
|
||||
transform_ops:
|
||||
- RandCropImage:
|
||||
size: 224
|
||||
- RandFlipImage:
|
||||
flip_code: 1
|
||||
- NormalizeImage:
|
||||
scale: 0.00392157
|
||||
mean: [0.485, 0.456, 0.406]
|
||||
std: [0.229, 0.224, 0.225]
|
||||
order: ''
|
||||
|
||||
sampler:
|
||||
name: DistributedBatchSampler
|
||||
batch_size: 512
|
||||
drop_last: False
|
||||
shuffle: True
|
||||
loader:
|
||||
num_workers: 6
|
||||
use_shared_memory: False
|
||||
|
||||
Eval:
|
||||
# TOTO: modify to the latest trainer
|
||||
dataset:
|
||||
name: ImageNetDataset
|
||||
image_root: "./dataset/ILSVRC2012/"
|
||||
cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
|
||||
transform_ops:
|
||||
- ResizeImage:
|
||||
size: 224
|
||||
- NormalizeImage:
|
||||
scale: 0.00392157
|
||||
mean: [0.485, 0.456, 0.406]
|
||||
std: [0.229, 0.224, 0.225]
|
||||
order: ''
|
||||
sampler:
|
||||
name: DistributedBatchSampler
|
||||
batch_size: 64
|
||||
drop_last: False
|
||||
shuffle: False
|
||||
loader:
|
||||
num_workers: 6
|
||||
use_shared_memory: False
|
||||
|
||||
Infer:
|
||||
infer_imgs: "docs/images/whl/demo.jpg"
|
||||
batch_size: 10
|
||||
transforms:
|
||||
- DecodeImage:
|
||||
to_rgb: True
|
||||
channel_first: False
|
||||
- ResizeImage:
|
||||
resize_short: 256
|
||||
- CropImage:
|
||||
size: 224
|
||||
- NormalizeImage:
|
||||
scale: 1.0/255.0
|
||||
mean: [0.485, 0.456, 0.406]
|
||||
std: [0.229, 0.224, 0.225]
|
||||
order: ''
|
||||
- ToCHWImage:
|
||||
PostProcess:
|
||||
name: Topk
|
||||
topk: 5
|
||||
class_id_map_file: "ppcls/utils/imagenet1k_label_list.txt"
|
||||
|
||||
Metric:
|
||||
Train:
|
||||
- Topk:
|
||||
k: [1, 5]
|
||||
Eval:
|
||||
- Topk:
|
||||
k: [1, 5]
|
||||
|
||||
|
|
@ -0,0 +1,122 @@
|
|||
# global configs
|
||||
Global:
|
||||
checkpoints: null
|
||||
pretrained_model: null
|
||||
output_dir: "./output/"
|
||||
device: "gpu"
|
||||
class_num: 1000
|
||||
save_interval: 1
|
||||
eval_during_train: True
|
||||
eval_interval: 1
|
||||
epochs: 360
|
||||
print_batch_step: 10
|
||||
use_visualdl: False
|
||||
# used for static mode and model export
|
||||
image_shape: [3, 224, 224]
|
||||
save_inference_dir: "./inference"
|
||||
|
||||
# model architecture
|
||||
Arch:
|
||||
name: "MobileNetV3_small_x1_25"
|
||||
|
||||
# loss function config for traing/eval process
|
||||
Loss:
|
||||
Train:
|
||||
- CELoss:
|
||||
weight: 1.0
|
||||
Eval:
|
||||
- CELoss:
|
||||
weight: 1.0
|
||||
|
||||
|
||||
Optimizer:
|
||||
name: Momentum
|
||||
momentum: 0.9
|
||||
lr:
|
||||
name: Cosine
|
||||
learning_rate: 1.3
|
||||
regularizer:
|
||||
name: 'L2'
|
||||
coeff: 0.00002
|
||||
|
||||
|
||||
# data loader for train and eval
|
||||
DataLoader:
|
||||
Train:
|
||||
dataset:
|
||||
name: ImageNetDataset
|
||||
image_root: "./dataset/ILSVRC2012/"
|
||||
cls_label_path: "./dataset/ILSVRC2012/train_list.txt"
|
||||
transform_ops:
|
||||
- RandCropImage:
|
||||
size: 224
|
||||
- RandFlipImage:
|
||||
flip_code: 1
|
||||
- NormalizeImage:
|
||||
scale: 0.00392157
|
||||
mean: [0.485, 0.456, 0.406]
|
||||
std: [0.229, 0.224, 0.225]
|
||||
order: ''
|
||||
|
||||
sampler:
|
||||
name: DistributedBatchSampler
|
||||
batch_size: 512
|
||||
drop_last: False
|
||||
shuffle: True
|
||||
loader:
|
||||
num_workers: 6
|
||||
use_shared_memory: False
|
||||
|
||||
Eval:
|
||||
# TOTO: modify to the latest trainer
|
||||
dataset:
|
||||
name: ImageNetDataset
|
||||
image_root: "./dataset/ILSVRC2012/"
|
||||
cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
|
||||
transform_ops:
|
||||
- ResizeImage:
|
||||
size: 224
|
||||
- NormalizeImage:
|
||||
scale: 0.00392157
|
||||
mean: [0.485, 0.456, 0.406]
|
||||
std: [0.229, 0.224, 0.225]
|
||||
order: ''
|
||||
sampler:
|
||||
name: DistributedBatchSampler
|
||||
batch_size: 64
|
||||
drop_last: False
|
||||
shuffle: False
|
||||
loader:
|
||||
num_workers: 6
|
||||
use_shared_memory: False
|
||||
|
||||
Infer:
|
||||
infer_imgs: "docs/images/whl/demo.jpg"
|
||||
batch_size: 10
|
||||
transforms:
|
||||
- DecodeImage:
|
||||
to_rgb: True
|
||||
channel_first: False
|
||||
- ResizeImage:
|
||||
resize_short: 256
|
||||
- CropImage:
|
||||
size: 224
|
||||
- NormalizeImage:
|
||||
scale: 1.0/255.0
|
||||
mean: [0.485, 0.456, 0.406]
|
||||
std: [0.229, 0.224, 0.225]
|
||||
order: ''
|
||||
- ToCHWImage:
|
||||
PostProcess:
|
||||
name: Topk
|
||||
topk: 5
|
||||
class_id_map_file: "ppcls/utils/imagenet1k_label_list.txt"
|
||||
|
||||
Metric:
|
||||
Train:
|
||||
- Topk:
|
||||
k: [1, 5]
|
||||
Eval:
|
||||
- Topk:
|
||||
k: [1, 5]
|
||||
|
||||
|
|
@ -0,0 +1,124 @@
|
|||
# global configs
|
||||
Global:
|
||||
checkpoints: null
|
||||
pretrained_model: null
|
||||
output_dir: "./output/"
|
||||
device: "gpu"
|
||||
class_num: 1000
|
||||
save_interval: 1
|
||||
eval_during_train: True
|
||||
eval_interval: 1
|
||||
epochs: 120
|
||||
print_batch_step: 10
|
||||
use_visualdl: False
|
||||
# used for static mode and model export
|
||||
image_shape: [3, 224, 224]
|
||||
save_inference_dir: "./inference"
|
||||
|
||||
# model architecture
|
||||
Arch:
|
||||
name: "ResNet101"
|
||||
|
||||
# loss function config for traing/eval process
|
||||
Loss:
|
||||
Train:
|
||||
- CELoss:
|
||||
weight: 1.0
|
||||
Eval:
|
||||
- CELoss:
|
||||
weight: 1.0
|
||||
|
||||
|
||||
Optimizer:
|
||||
name: Momentum
|
||||
momentum: 0.9
|
||||
lr:
|
||||
name: Piecewise
|
||||
learning_rate: 0.1
|
||||
decay_epochs: [30, 60, 90]
|
||||
values: [0.1, 0.01, 0.001, 0.0001]
|
||||
regularizer:
|
||||
name: 'L2'
|
||||
coeff: 0.0001
|
||||
|
||||
|
||||
# data loader for train and eval
|
||||
DataLoader:
|
||||
Train:
|
||||
dataset:
|
||||
name: ImageNetDataset
|
||||
image_root: "./dataset/ILSVRC2012/"
|
||||
cls_label_path: "./dataset/ILSVRC2012/train_list.txt"
|
||||
transform_ops:
|
||||
- RandCropImage:
|
||||
size: 224
|
||||
- RandFlipImage:
|
||||
flip_code: 1
|
||||
- NormalizeImage:
|
||||
scale: 0.00392157
|
||||
mean: [0.485, 0.456, 0.406]
|
||||
std: [0.229, 0.224, 0.225]
|
||||
order: ''
|
||||
|
||||
sampler:
|
||||
name: DistributedBatchSampler
|
||||
batch_size: 64
|
||||
drop_last: False
|
||||
shuffle: True
|
||||
loader:
|
||||
num_workers: 6
|
||||
use_shared_memory: False
|
||||
|
||||
Eval:
|
||||
# TOTO: modify to the latest trainer
|
||||
dataset:
|
||||
name: ImageNetDataset
|
||||
image_root: "./dataset/ILSVRC2012/"
|
||||
cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
|
||||
transform_ops:
|
||||
- ResizeImage:
|
||||
size: 224
|
||||
- NormalizeImage:
|
||||
scale: 0.00392157
|
||||
mean: [0.485, 0.456, 0.406]
|
||||
std: [0.229, 0.224, 0.225]
|
||||
order: ''
|
||||
sampler:
|
||||
name: DistributedBatchSampler
|
||||
batch_size: 64
|
||||
drop_last: False
|
||||
shuffle: False
|
||||
loader:
|
||||
num_workers: 6
|
||||
use_shared_memory: False
|
||||
|
||||
Infer:
|
||||
infer_imgs: "docs/images/whl/demo.jpg"
|
||||
batch_size: 10
|
||||
transforms:
|
||||
- DecodeImage:
|
||||
to_rgb: True
|
||||
channel_first: False
|
||||
- ResizeImage:
|
||||
resize_short: 256
|
||||
- CropImage:
|
||||
size: 224
|
||||
- NormalizeImage:
|
||||
scale: 1.0/255.0
|
||||
mean: [0.485, 0.456, 0.406]
|
||||
std: [0.229, 0.224, 0.225]
|
||||
order: ''
|
||||
- ToCHWImage:
|
||||
PostProcess:
|
||||
name: Topk
|
||||
topk: 5
|
||||
class_id_map_file: "ppcls/utils/imagenet1k_label_list.txt"
|
||||
|
||||
Metric:
|
||||
Train:
|
||||
- Topk:
|
||||
k: [1, 5]
|
||||
Eval:
|
||||
- Topk:
|
||||
k: [1, 5]
|
||||
|
||||
|
|
@ -0,0 +1,122 @@
|
|||
# global configs
|
||||
Global:
|
||||
checkpoints: null
|
||||
pretrained_model: null
|
||||
output_dir: "./output/"
|
||||
device: "gpu"
|
||||
class_num: 1000
|
||||
save_interval: 1
|
||||
eval_during_train: True
|
||||
eval_interval: 1
|
||||
epochs: 200
|
||||
print_batch_step: 10
|
||||
use_visualdl: False
|
||||
# used for static mode and model export
|
||||
image_shape: [3, 224, 224]
|
||||
save_inference_dir: "./inference"
|
||||
|
||||
# model architecture
|
||||
Arch:
|
||||
name: "ResNet101_vd"
|
||||
|
||||
# loss function config for traing/eval process
|
||||
Loss:
|
||||
Train:
|
||||
- CELoss:
|
||||
weight: 1.0
|
||||
Eval:
|
||||
- CELoss:
|
||||
weight: 1.0
|
||||
|
||||
|
||||
Optimizer:
|
||||
name: Momentum
|
||||
momentum: 0.9
|
||||
lr:
|
||||
name: Cosine
|
||||
learning_rate: 0.1
|
||||
regularizer:
|
||||
name: 'L2'
|
||||
coeff: 0.0001
|
||||
|
||||
|
||||
# data loader for train and eval
|
||||
DataLoader:
|
||||
Train:
|
||||
dataset:
|
||||
name: ImageNetDataset
|
||||
image_root: "./dataset/ILSVRC2012/"
|
||||
cls_label_path: "./dataset/ILSVRC2012/train_list.txt"
|
||||
transform_ops:
|
||||
- RandCropImage:
|
||||
size: 224
|
||||
- RandFlipImage:
|
||||
flip_code: 1
|
||||
- NormalizeImage:
|
||||
scale: 0.00392157
|
||||
mean: [0.485, 0.456, 0.406]
|
||||
std: [0.229, 0.224, 0.225]
|
||||
order: ''
|
||||
|
||||
sampler:
|
||||
name: DistributedBatchSampler
|
||||
batch_size: 64
|
||||
drop_last: False
|
||||
shuffle: True
|
||||
loader:
|
||||
num_workers: 6
|
||||
use_shared_memory: False
|
||||
|
||||
Eval:
|
||||
# TOTO: modify to the latest trainer
|
||||
dataset:
|
||||
name: ImageNetDataset
|
||||
image_root: "./dataset/ILSVRC2012/"
|
||||
cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
|
||||
transform_ops:
|
||||
- ResizeImage:
|
||||
size: 224
|
||||
- NormalizeImage:
|
||||
scale: 0.00392157
|
||||
mean: [0.485, 0.456, 0.406]
|
||||
std: [0.229, 0.224, 0.225]
|
||||
order: ''
|
||||
sampler:
|
||||
name: DistributedBatchSampler
|
||||
batch_size: 64
|
||||
drop_last: False
|
||||
shuffle: False
|
||||
loader:
|
||||
num_workers: 6
|
||||
use_shared_memory: False
|
||||
|
||||
Infer:
|
||||
infer_imgs: "docs/images/whl/demo.jpg"
|
||||
batch_size: 10
|
||||
transforms:
|
||||
- DecodeImage:
|
||||
to_rgb: True
|
||||
channel_first: False
|
||||
- ResizeImage:
|
||||
resize_short: 256
|
||||
- CropImage:
|
||||
size: 224
|
||||
- NormalizeImage:
|
||||
scale: 1.0/255.0
|
||||
mean: [0.485, 0.456, 0.406]
|
||||
std: [0.229, 0.224, 0.225]
|
||||
order: ''
|
||||
- ToCHWImage:
|
||||
PostProcess:
|
||||
name: Topk
|
||||
topk: 5
|
||||
class_id_map_file: "ppcls/utils/imagenet1k_label_list.txt"
|
||||
|
||||
Metric:
|
||||
Train:
|
||||
- Topk:
|
||||
k: [1, 5]
|
||||
Eval:
|
||||
- Topk:
|
||||
k: [1, 5]
|
||||
|
||||
|
|
@ -0,0 +1,124 @@
|
|||
# global configs
|
||||
Global:
|
||||
checkpoints: null
|
||||
pretrained_model: null
|
||||
output_dir: "./output/"
|
||||
device: "gpu"
|
||||
class_num: 1000
|
||||
save_interval: 1
|
||||
eval_during_train: True
|
||||
eval_interval: 1
|
||||
epochs: 120
|
||||
print_batch_step: 10
|
||||
use_visualdl: False
|
||||
# used for static mode and model export
|
||||
image_shape: [3, 224, 224]
|
||||
save_inference_dir: "./inference"
|
||||
|
||||
# model architecture
|
||||
Arch:
|
||||
name: "ResNet152"
|
||||
|
||||
# loss function config for traing/eval process
|
||||
Loss:
|
||||
Train:
|
||||
- CELoss:
|
||||
weight: 1.0
|
||||
Eval:
|
||||
- CELoss:
|
||||
weight: 1.0
|
||||
|
||||
|
||||
Optimizer:
|
||||
name: Momentum
|
||||
momentum: 0.9
|
||||
lr:
|
||||
name: Piecewise
|
||||
learning_rate: 0.1
|
||||
decay_epochs: [30, 60, 90]
|
||||
values: [0.1, 0.01, 0.001, 0.0001]
|
||||
regularizer:
|
||||
name: 'L2'
|
||||
coeff: 0.0001
|
||||
|
||||
|
||||
# data loader for train and eval
|
||||
DataLoader:
|
||||
Train:
|
||||
dataset:
|
||||
name: ImageNetDataset
|
||||
image_root: "./dataset/ILSVRC2012/"
|
||||
cls_label_path: "./dataset/ILSVRC2012/train_list.txt"
|
||||
transform_ops:
|
||||
- RandCropImage:
|
||||
size: 224
|
||||
- RandFlipImage:
|
||||
flip_code: 1
|
||||
- NormalizeImage:
|
||||
scale: 0.00392157
|
||||
mean: [0.485, 0.456, 0.406]
|
||||
std: [0.229, 0.224, 0.225]
|
||||
order: ''
|
||||
|
||||
sampler:
|
||||
name: DistributedBatchSampler
|
||||
batch_size: 64
|
||||
drop_last: False
|
||||
shuffle: True
|
||||
loader:
|
||||
num_workers: 6
|
||||
use_shared_memory: False
|
||||
|
||||
Eval:
|
||||
# TOTO: modify to the latest trainer
|
||||
dataset:
|
||||
name: ImageNetDataset
|
||||
image_root: "./dataset/ILSVRC2012/"
|
||||
cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
|
||||
transform_ops:
|
||||
- ResizeImage:
|
||||
size: 224
|
||||
- NormalizeImage:
|
||||
scale: 0.00392157
|
||||
mean: [0.485, 0.456, 0.406]
|
||||
std: [0.229, 0.224, 0.225]
|
||||
order: ''
|
||||
sampler:
|
||||
name: DistributedBatchSampler
|
||||
batch_size: 64
|
||||
drop_last: False
|
||||
shuffle: False
|
||||
loader:
|
||||
num_workers: 6
|
||||
use_shared_memory: False
|
||||
|
||||
Infer:
|
||||
infer_imgs: "docs/images/whl/demo.jpg"
|
||||
batch_size: 10
|
||||
transforms:
|
||||
- DecodeImage:
|
||||
to_rgb: True
|
||||
channel_first: False
|
||||
- ResizeImage:
|
||||
resize_short: 256
|
||||
- CropImage:
|
||||
size: 224
|
||||
- NormalizeImage:
|
||||
scale: 1.0/255.0
|
||||
mean: [0.485, 0.456, 0.406]
|
||||
std: [0.229, 0.224, 0.225]
|
||||
order: ''
|
||||
- ToCHWImage:
|
||||
PostProcess:
|
||||
name: Topk
|
||||
topk: 5
|
||||
class_id_map_file: "ppcls/utils/imagenet1k_label_list.txt"
|
||||
|
||||
Metric:
|
||||
Train:
|
||||
- Topk:
|
||||
k: [1, 5]
|
||||
Eval:
|
||||
- Topk:
|
||||
k: [1, 5]
|
||||
|
||||
|
|
@ -0,0 +1,122 @@
|
|||
# global configs
|
||||
Global:
|
||||
checkpoints: null
|
||||
pretrained_model: null
|
||||
output_dir: "./output/"
|
||||
device: "gpu"
|
||||
class_num: 1000
|
||||
save_interval: 1
|
||||
eval_during_train: True
|
||||
eval_interval: 1
|
||||
epochs: 200
|
||||
print_batch_step: 10
|
||||
use_visualdl: False
|
||||
# used for static mode and model export
|
||||
image_shape: [3, 224, 224]
|
||||
save_inference_dir: "./inference"
|
||||
|
||||
# model architecture
|
||||
Arch:
|
||||
name: "ResNet152_vd"
|
||||
|
||||
# loss function config for traing/eval process
|
||||
Loss:
|
||||
Train:
|
||||
- CELoss:
|
||||
weight: 1.0
|
||||
Eval:
|
||||
- CELoss:
|
||||
weight: 1.0
|
||||
|
||||
|
||||
Optimizer:
|
||||
name: Momentum
|
||||
momentum: 0.9
|
||||
lr:
|
||||
name: Cosine
|
||||
learning_rate: 0.1
|
||||
regularizer:
|
||||
name: 'L2'
|
||||
coeff: 0.0001
|
||||
|
||||
|
||||
# data loader for train and eval
|
||||
DataLoader:
|
||||
Train:
|
||||
dataset:
|
||||
name: ImageNetDataset
|
||||
image_root: "./dataset/ILSVRC2012/"
|
||||
cls_label_path: "./dataset/ILSVRC2012/train_list.txt"
|
||||
transform_ops:
|
||||
- RandCropImage:
|
||||
size: 224
|
||||
- RandFlipImage:
|
||||
flip_code: 1
|
||||
- NormalizeImage:
|
||||
scale: 0.00392157
|
||||
mean: [0.485, 0.456, 0.406]
|
||||
std: [0.229, 0.224, 0.225]
|
||||
order: ''
|
||||
|
||||
sampler:
|
||||
name: DistributedBatchSampler
|
||||
batch_size: 64
|
||||
drop_last: False
|
||||
shuffle: True
|
||||
loader:
|
||||
num_workers: 6
|
||||
use_shared_memory: False
|
||||
|
||||
Eval:
|
||||
# TOTO: modify to the latest trainer
|
||||
dataset:
|
||||
name: ImageNetDataset
|
||||
image_root: "./dataset/ILSVRC2012/"
|
||||
cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
|
||||
transform_ops:
|
||||
- ResizeImage:
|
||||
size: 224
|
||||
- NormalizeImage:
|
||||
scale: 0.00392157
|
||||
mean: [0.485, 0.456, 0.406]
|
||||
std: [0.229, 0.224, 0.225]
|
||||
order: ''
|
||||
sampler:
|
||||
name: DistributedBatchSampler
|
||||
batch_size: 64
|
||||
drop_last: False
|
||||
shuffle: False
|
||||
loader:
|
||||
num_workers: 6
|
||||
use_shared_memory: False
|
||||
|
||||
Infer:
|
||||
infer_imgs: "docs/images/whl/demo.jpg"
|
||||
batch_size: 10
|
||||
transforms:
|
||||
- DecodeImage:
|
||||
to_rgb: True
|
||||
channel_first: False
|
||||
- ResizeImage:
|
||||
resize_short: 256
|
||||
- CropImage:
|
||||
size: 224
|
||||
- NormalizeImage:
|
||||
scale: 1.0/255.0
|
||||
mean: [0.485, 0.456, 0.406]
|
||||
std: [0.229, 0.224, 0.225]
|
||||
order: ''
|
||||
- ToCHWImage:
|
||||
PostProcess:
|
||||
name: Topk
|
||||
topk: 5
|
||||
class_id_map_file: "ppcls/utils/imagenet1k_label_list.txt"
|
||||
|
||||
Metric:
|
||||
Train:
|
||||
- Topk:
|
||||
k: [1, 5]
|
||||
Eval:
|
||||
- Topk:
|
||||
k: [1, 5]
|
||||
|
||||
|
|
@ -0,0 +1,124 @@
|
|||
# global configs
|
||||
Global:
|
||||
checkpoints: null
|
||||
pretrained_model: null
|
||||
output_dir: "./output/"
|
||||
device: "gpu"
|
||||
class_num: 1000
|
||||
save_interval: 1
|
||||
eval_during_train: True
|
||||
eval_interval: 1
|
||||
epochs: 120
|
||||
print_batch_step: 10
|
||||
use_visualdl: False
|
||||
# used for static mode and model export
|
||||
image_shape: [3, 224, 224]
|
||||
save_inference_dir: "./inference"
|
||||
|
||||
# model architecture
|
||||
Arch:
|
||||
name: "ResNet18"
|
||||
|
||||
# loss function config for traing/eval process
|
||||
Loss:
|
||||
Train:
|
||||
- CELoss:
|
||||
weight: 1.0
|
||||
Eval:
|
||||
- CELoss:
|
||||
weight: 1.0
|
||||
|
||||
|
||||
Optimizer:
|
||||
name: Momentum
|
||||
momentum: 0.9
|
||||
lr:
|
||||
name: Piecewise
|
||||
learning_rate: 0.1
|
||||
decay_epochs: [30, 60, 90]
|
||||
values: [0.1, 0.01, 0.001, 0.0001]
|
||||
regularizer:
|
||||
name: 'L2'
|
||||
coeff: 0.0001
|
||||
|
||||
|
||||
# data loader for train and eval
|
||||
DataLoader:
|
||||
Train:
|
||||
dataset:
|
||||
name: ImageNetDataset
|
||||
image_root: "./dataset/ILSVRC2012/"
|
||||
cls_label_path: "./dataset/ILSVRC2012/train_list.txt"
|
||||
transform_ops:
|
||||
- RandCropImage:
|
||||
size: 224
|
||||
- RandFlipImage:
|
||||
flip_code: 1
|
||||
- NormalizeImage:
|
||||
scale: 0.00392157
|
||||
mean: [0.485, 0.456, 0.406]
|
||||
std: [0.229, 0.224, 0.225]
|
||||
order: ''
|
||||
|
||||
sampler:
|
||||
name: DistributedBatchSampler
|
||||
batch_size: 64
|
||||
drop_last: False
|
||||
shuffle: True
|
||||
loader:
|
||||
num_workers: 6
|
||||
use_shared_memory: False
|
||||
|
||||
Eval:
|
||||
# TOTO: modify to the latest trainer
|
||||
dataset:
|
||||
name: ImageNetDataset
|
||||
image_root: "./dataset/ILSVRC2012/"
|
||||
cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
|
||||
transform_ops:
|
||||
- ResizeImage:
|
||||
size: 224
|
||||
- NormalizeImage:
|
||||
scale: 0.00392157
|
||||
mean: [0.485, 0.456, 0.406]
|
||||
std: [0.229, 0.224, 0.225]
|
||||
order: ''
|
||||
sampler:
|
||||
name: DistributedBatchSampler
|
||||
batch_size: 64
|
||||
drop_last: False
|
||||
shuffle: False
|
||||
loader:
|
||||
num_workers: 6
|
||||
use_shared_memory: False
|
||||
|
||||
Infer:
|
||||
infer_imgs: "docs/images/whl/demo.jpg"
|
||||
batch_size: 10
|
||||
transforms:
|
||||
- DecodeImage:
|
||||
to_rgb: True
|
||||
channel_first: False
|
||||
- ResizeImage:
|
||||
resize_short: 256
|
||||
- CropImage:
|
||||
size: 224
|
||||
- NormalizeImage:
|
||||
scale: 1.0/255.0
|
||||
mean: [0.485, 0.456, 0.406]
|
||||
std: [0.229, 0.224, 0.225]
|
||||
order: ''
|
||||
- ToCHWImage:
|
||||
PostProcess:
|
||||
name: Topk
|
||||
topk: 5
|
||||
class_id_map_file: "ppcls/utils/imagenet1k_label_list.txt"
|
||||
|
||||
Metric:
|
||||
Train:
|
||||
- Topk:
|
||||
k: [1, 5]
|
||||
Eval:
|
||||
- Topk:
|
||||
k: [1, 5]
|
||||
|
||||
|
|
@ -0,0 +1,122 @@
|
|||
# global configs
|
||||
Global:
|
||||
checkpoints: null
|
||||
pretrained_model: null
|
||||
output_dir: "./output/"
|
||||
device: "gpu"
|
||||
class_num: 1000
|
||||
save_interval: 1
|
||||
eval_during_train: True
|
||||
eval_interval: 1
|
||||
epochs: 200
|
||||
print_batch_step: 10
|
||||
use_visualdl: False
|
||||
# used for static mode and model export
|
||||
image_shape: [3, 224, 224]
|
||||
save_inference_dir: "./inference"
|
||||
|
||||
# model architecture
|
||||
Arch:
|
||||
name: "ResNet18_vd"
|
||||
|
||||
# loss function config for traing/eval process
|
||||
Loss:
|
||||
Train:
|
||||
- CELoss:
|
||||
weight: 1.0
|
||||
Eval:
|
||||
- CELoss:
|
||||
weight: 1.0
|
||||
|
||||
|
||||
Optimizer:
|
||||
name: Momentum
|
||||
momentum: 0.9
|
||||
lr:
|
||||
name: Cosine
|
||||
learning_rate: 0.1
|
||||
regularizer:
|
||||
name: 'L2'
|
||||
coeff: 0.00007
|
||||
|
||||
|
||||
# data loader for train and eval
|
||||
DataLoader:
|
||||
Train:
|
||||
dataset:
|
||||
name: ImageNetDataset
|
||||
image_root: "./dataset/ILSVRC2012/"
|
||||
cls_label_path: "./dataset/ILSVRC2012/train_list.txt"
|
||||
transform_ops:
|
||||
- RandCropImage:
|
||||
size: 224
|
||||
- RandFlipImage:
|
||||
flip_code: 1
|
||||
- NormalizeImage:
|
||||
scale: 0.00392157
|
||||
mean: [0.485, 0.456, 0.406]
|
||||
std: [0.229, 0.224, 0.225]
|
||||
order: ''
|
||||
|
||||
sampler:
|
||||
name: DistributedBatchSampler
|
||||
batch_size: 64
|
||||
drop_last: False
|
||||
shuffle: True
|
||||
loader:
|
||||
num_workers: 6
|
||||
use_shared_memory: False
|
||||
|
||||
Eval:
|
||||
# TOTO: modify to the latest trainer
|
||||
dataset:
|
||||
name: ImageNetDataset
|
||||
image_root: "./dataset/ILSVRC2012/"
|
||||
cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
|
||||
transform_ops:
|
||||
- ResizeImage:
|
||||
size: 224
|
||||
- NormalizeImage:
|
||||
scale: 0.00392157
|
||||
mean: [0.485, 0.456, 0.406]
|
||||
std: [0.229, 0.224, 0.225]
|
||||
order: ''
|
||||
sampler:
|
||||
name: DistributedBatchSampler
|
||||
batch_size: 64
|
||||
drop_last: False
|
||||
shuffle: False
|
||||
loader:
|
||||
num_workers: 6
|
||||
use_shared_memory: False
|
||||
|
||||
Infer:
|
||||
infer_imgs: "docs/images/whl/demo.jpg"
|
||||
batch_size: 10
|
||||
transforms:
|
||||
- DecodeImage:
|
||||
to_rgb: True
|
||||
channel_first: False
|
||||
- ResizeImage:
|
||||
resize_short: 256
|
||||
- CropImage:
|
||||
size: 224
|
||||
- NormalizeImage:
|
||||
scale: 1.0/255.0
|
||||
mean: [0.485, 0.456, 0.406]
|
||||
std: [0.229, 0.224, 0.225]
|
||||
order: ''
|
||||
- ToCHWImage:
|
||||
PostProcess:
|
||||
name: Topk
|
||||
topk: 5
|
||||
class_id_map_file: "ppcls/utils/imagenet1k_label_list.txt"
|
||||
|
||||
Metric:
|
||||
Train:
|
||||
- Topk:
|
||||
k: [1, 5]
|
||||
Eval:
|
||||
- Topk:
|
||||
k: [1, 5]
|
||||
|
||||
|
|
@ -0,0 +1,122 @@
|
|||
# global configs
|
||||
Global:
|
||||
checkpoints: null
|
||||
pretrained_model: null
|
||||
output_dir: "./output/"
|
||||
device: "gpu"
|
||||
class_num: 1000
|
||||
save_interval: 1
|
||||
eval_during_train: True
|
||||
eval_interval: 1
|
||||
epochs: 200
|
||||
print_batch_step: 10
|
||||
use_visualdl: False
|
||||
# used for static mode and model export
|
||||
image_shape: [3, 224, 224]
|
||||
save_inference_dir: "./inference"
|
||||
|
||||
# model architecture
|
||||
Arch:
|
||||
name: "ResNet200_vd"
|
||||
|
||||
# loss function config for traing/eval process
|
||||
Loss:
|
||||
Train:
|
||||
- CELoss:
|
||||
weight: 1.0
|
||||
Eval:
|
||||
- CELoss:
|
||||
weight: 1.0
|
||||
|
||||
|
||||
Optimizer:
|
||||
name: Momentum
|
||||
momentum: 0.9
|
||||
lr:
|
||||
name: Cosine
|
||||
learning_rate: 0.1
|
||||
regularizer:
|
||||
name: 'L2'
|
||||
coeff: 0.0001
|
||||
|
||||
|
||||
# data loader for train and eval
|
||||
DataLoader:
|
||||
Train:
|
||||
dataset:
|
||||
name: ImageNetDataset
|
||||
image_root: "./dataset/ILSVRC2012/"
|
||||
cls_label_path: "./dataset/ILSVRC2012/train_list.txt"
|
||||
transform_ops:
|
||||
- RandCropImage:
|
||||
size: 224
|
||||
- RandFlipImage:
|
||||
flip_code: 1
|
||||
- NormalizeImage:
|
||||
scale: 0.00392157
|
||||
mean: [0.485, 0.456, 0.406]
|
||||
std: [0.229, 0.224, 0.225]
|
||||
order: ''
|
||||
|
||||
sampler:
|
||||
name: DistributedBatchSampler
|
||||
batch_size: 64
|
||||
drop_last: False
|
||||
shuffle: True
|
||||
loader:
|
||||
num_workers: 6
|
||||
use_shared_memory: False
|
||||
|
||||
Eval:
|
||||
# TOTO: modify to the latest trainer
|
||||
dataset:
|
||||
name: ImageNetDataset
|
||||
image_root: "./dataset/ILSVRC2012/"
|
||||
cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
|
||||
transform_ops:
|
||||
- ResizeImage:
|
||||
size: 224
|
||||
- NormalizeImage:
|
||||
scale: 0.00392157
|
||||
mean: [0.485, 0.456, 0.406]
|
||||
std: [0.229, 0.224, 0.225]
|
||||
order: ''
|
||||
sampler:
|
||||
name: DistributedBatchSampler
|
||||
batch_size: 64
|
||||
drop_last: False
|
||||
shuffle: False
|
||||
loader:
|
||||
num_workers: 6
|
||||
use_shared_memory: False
|
||||
|
||||
Infer:
|
||||
infer_imgs: "docs/images/whl/demo.jpg"
|
||||
batch_size: 10
|
||||
transforms:
|
||||
- DecodeImage:
|
||||
to_rgb: True
|
||||
channel_first: False
|
||||
- ResizeImage:
|
||||
resize_short: 256
|
||||
- CropImage:
|
||||
size: 224
|
||||
- NormalizeImage:
|
||||
scale: 1.0/255.0
|
||||
mean: [0.485, 0.456, 0.406]
|
||||
std: [0.229, 0.224, 0.225]
|
||||
order: ''
|
||||
- ToCHWImage:
|
||||
PostProcess:
|
||||
name: Topk
|
||||
topk: 5
|
||||
class_id_map_file: "ppcls/utils/imagenet1k_label_list.txt"
|
||||
|
||||
Metric:
|
||||
Train:
|
||||
- Topk:
|
||||
k: [1, 5]
|
||||
Eval:
|
||||
- Topk:
|
||||
k: [1, 5]
|
||||
|
||||
|
|
@ -0,0 +1,124 @@
|
|||
# global configs
|
||||
Global:
|
||||
checkpoints: null
|
||||
pretrained_model: null
|
||||
output_dir: "./output/"
|
||||
device: "gpu"
|
||||
class_num: 1000
|
||||
save_interval: 1
|
||||
eval_during_train: True
|
||||
eval_interval: 1
|
||||
epochs: 120
|
||||
print_batch_step: 10
|
||||
use_visualdl: False
|
||||
# used for static mode and model export
|
||||
image_shape: [3, 224, 224]
|
||||
save_inference_dir: "./inference"
|
||||
|
||||
# model architecture
|
||||
Arch:
|
||||
name: "ResNet34"
|
||||
|
||||
# loss function config for traing/eval process
|
||||
Loss:
|
||||
Train:
|
||||
- CELoss:
|
||||
weight: 1.0
|
||||
Eval:
|
||||
- CELoss:
|
||||
weight: 1.0
|
||||
|
||||
|
||||
Optimizer:
|
||||
name: Momentum
|
||||
momentum: 0.9
|
||||
lr:
|
||||
name: Piecewise
|
||||
learning_rate: 0.1
|
||||
decay_epochs: [30, 60, 90]
|
||||
values: [0.1, 0.01, 0.001, 0.0001]
|
||||
regularizer:
|
||||
name: 'L2'
|
||||
coeff: 0.0001
|
||||
|
||||
|
||||
# data loader for train and eval
|
||||
DataLoader:
|
||||
Train:
|
||||
dataset:
|
||||
name: ImageNetDataset
|
||||
image_root: "./dataset/ILSVRC2012/"
|
||||
cls_label_path: "./dataset/ILSVRC2012/train_list.txt"
|
||||
transform_ops:
|
||||
- RandCropImage:
|
||||
size: 224
|
||||
- RandFlipImage:
|
||||
flip_code: 1
|
||||
- NormalizeImage:
|
||||
scale: 0.00392157
|
||||
mean: [0.485, 0.456, 0.406]
|
||||
std: [0.229, 0.224, 0.225]
|
||||
order: ''
|
||||
|
||||
sampler:
|
||||
name: DistributedBatchSampler
|
||||
batch_size: 64
|
||||
drop_last: False
|
||||
shuffle: True
|
||||
loader:
|
||||
num_workers: 6
|
||||
use_shared_memory: False
|
||||
|
||||
Eval:
|
||||
# TOTO: modify to the latest trainer
|
||||
dataset:
|
||||
name: ImageNetDataset
|
||||
image_root: "./dataset/ILSVRC2012/"
|
||||
cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
|
||||
transform_ops:
|
||||
- ResizeImage:
|
||||
size: 224
|
||||
- NormalizeImage:
|
||||
scale: 0.00392157
|
||||
mean: [0.485, 0.456, 0.406]
|
||||
std: [0.229, 0.224, 0.225]
|
||||
order: ''
|
||||
sampler:
|
||||
name: DistributedBatchSampler
|
||||
batch_size: 64
|
||||
drop_last: False
|
||||
shuffle: False
|
||||
loader:
|
||||
num_workers: 6
|
||||
use_shared_memory: False
|
||||
|
||||
Infer:
|
||||
infer_imgs: "docs/images/whl/demo.jpg"
|
||||
batch_size: 10
|
||||
transforms:
|
||||
- DecodeImage:
|
||||
to_rgb: True
|
||||
channel_first: False
|
||||
- ResizeImage:
|
||||
resize_short: 256
|
||||
- CropImage:
|
||||
size: 224
|
||||
- NormalizeImage:
|
||||
scale: 1.0/255.0
|
||||
mean: [0.485, 0.456, 0.406]
|
||||
std: [0.229, 0.224, 0.225]
|
||||
order: ''
|
||||
- ToCHWImage:
|
||||
PostProcess:
|
||||
name: Topk
|
||||
topk: 5
|
||||
class_id_map_file: "ppcls/utils/imagenet1k_label_list.txt"
|
||||
|
||||
Metric:
|
||||
Train:
|
||||
- Topk:
|
||||
k: [1, 5]
|
||||
Eval:
|
||||
- Topk:
|
||||
k: [1, 5]
|
||||
|
||||
|
|
@ -0,0 +1,122 @@
|
|||
# global configs
|
||||
Global:
|
||||
checkpoints: null
|
||||
pretrained_model: null
|
||||
output_dir: "./output/"
|
||||
device: "gpu"
|
||||
class_num: 1000
|
||||
save_interval: 1
|
||||
eval_during_train: True
|
||||
eval_interval: 1
|
||||
epochs: 200
|
||||
print_batch_step: 10
|
||||
use_visualdl: False
|
||||
# used for static mode and model export
|
||||
image_shape: [3, 224, 224]
|
||||
save_inference_dir: "./inference"
|
||||
|
||||
# model architecture
|
||||
Arch:
|
||||
name: "ResNet101_vd"
|
||||
|
||||
# loss function config for traing/eval process
|
||||
Loss:
|
||||
Train:
|
||||
- CELoss:
|
||||
weight: 1.0
|
||||
Eval:
|
||||
- CELoss:
|
||||
weight: 1.0
|
||||
|
||||
|
||||
Optimizer:
|
||||
name: Momentum
|
||||
momentum: 0.9
|
||||
lr:
|
||||
name: Cosine
|
||||
learning_rate: 0.1
|
||||
regularizer:
|
||||
name: 'L2'
|
||||
coeff: 0.00007
|
||||
|
||||
|
||||
# data loader for train and eval
|
||||
DataLoader:
|
||||
Train:
|
||||
dataset:
|
||||
name: ImageNetDataset
|
||||
image_root: "./dataset/ILSVRC2012/"
|
||||
cls_label_path: "./dataset/ILSVRC2012/train_list.txt"
|
||||
transform_ops:
|
||||
- RandCropImage:
|
||||
size: 224
|
||||
- RandFlipImage:
|
||||
flip_code: 1
|
||||
- NormalizeImage:
|
||||
scale: 0.00392157
|
||||
mean: [0.485, 0.456, 0.406]
|
||||
std: [0.229, 0.224, 0.225]
|
||||
order: ''
|
||||
|
||||
sampler:
|
||||
name: DistributedBatchSampler
|
||||
batch_size: 64
|
||||
drop_last: False
|
||||
shuffle: True
|
||||
loader:
|
||||
num_workers: 6
|
||||
use_shared_memory: False
|
||||
|
||||
Eval:
|
||||
# TOTO: modify to the latest trainer
|
||||
dataset:
|
||||
name: ImageNetDataset
|
||||
image_root: "./dataset/ILSVRC2012/"
|
||||
cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
|
||||
transform_ops:
|
||||
- ResizeImage:
|
||||
size: 224
|
||||
- NormalizeImage:
|
||||
scale: 0.00392157
|
||||
mean: [0.485, 0.456, 0.406]
|
||||
std: [0.229, 0.224, 0.225]
|
||||
order: ''
|
||||
sampler:
|
||||
name: DistributedBatchSampler
|
||||
batch_size: 64
|
||||
drop_last: False
|
||||
shuffle: False
|
||||
loader:
|
||||
num_workers: 6
|
||||
use_shared_memory: False
|
||||
|
||||
Infer:
|
||||
infer_imgs: "docs/images/whl/demo.jpg"
|
||||
batch_size: 10
|
||||
transforms:
|
||||
- DecodeImage:
|
||||
to_rgb: True
|
||||
channel_first: False
|
||||
- ResizeImage:
|
||||
resize_short: 256
|
||||
- CropImage:
|
||||
size: 224
|
||||
- NormalizeImage:
|
||||
scale: 1.0/255.0
|
||||
mean: [0.485, 0.456, 0.406]
|
||||
std: [0.229, 0.224, 0.225]
|
||||
order: ''
|
||||
- ToCHWImage:
|
||||
PostProcess:
|
||||
name: Topk
|
||||
topk: 5
|
||||
class_id_map_file: "ppcls/utils/imagenet1k_label_list.txt"
|
||||
|
||||
Metric:
|
||||
Train:
|
||||
- Topk:
|
||||
k: [1, 5]
|
||||
Eval:
|
||||
- Topk:
|
||||
k: [1, 5]
|
||||
|
||||
|
|
@ -45,52 +45,52 @@ Optimizer:
|
|||
# data loader for train and eval
|
||||
DataLoader:
|
||||
Train:
|
||||
# Dataset:
|
||||
# Sampler:
|
||||
# Loader:
|
||||
batch_size: 256
|
||||
num_workers: 4
|
||||
file_list: "./dataset/ILSVRC2012/train_list.txt"
|
||||
data_dir: "./dataset/ILSVRC2012/"
|
||||
shuffle_seed: 0
|
||||
transforms:
|
||||
- DecodeImage:
|
||||
to_rgb: True
|
||||
channel_first: False
|
||||
- RandCropImage:
|
||||
size: 224
|
||||
- RandFlipImage:
|
||||
flip_code: 1
|
||||
- NormalizeImage:
|
||||
scale: 1./255.
|
||||
mean: [0.485, 0.456, 0.406]
|
||||
std: [0.229, 0.224, 0.225]
|
||||
order: ''
|
||||
- ToCHWImage:
|
||||
dataset:
|
||||
name: ImageNetDataset
|
||||
image_root: "./dataset/ILSVRC2012/"
|
||||
cls_label_path: "./dataset/ILSVRC2012/train_list.txt"
|
||||
transform_ops:
|
||||
- RandCropImage:
|
||||
size: 224
|
||||
- RandFlipImage:
|
||||
flip_code: 1
|
||||
- NormalizeImage:
|
||||
scale: 0.00392157
|
||||
mean: [0.485, 0.456, 0.406]
|
||||
std: [0.229, 0.224, 0.225]
|
||||
order: ''
|
||||
|
||||
sampler:
|
||||
name: DistributedBatchSampler
|
||||
batch_size: 64
|
||||
drop_last: False
|
||||
shuffle: True
|
||||
loader:
|
||||
num_workers: 6
|
||||
use_shared_memory: False
|
||||
|
||||
Eval:
|
||||
# TOTO: modify to the latest trainer
|
||||
# Dataset:
|
||||
# Sampler:
|
||||
# Loader:
|
||||
batch_size: 128
|
||||
num_workers: 4
|
||||
file_list: "./dataset/ILSVRC2012/val_list.txt"
|
||||
data_dir: "./dataset/ILSVRC2012/"
|
||||
shuffle_seed: 0
|
||||
transforms:
|
||||
- DecodeImage:
|
||||
to_rgb: True
|
||||
channel_first: False
|
||||
- ResizeImage:
|
||||
resize_short: 256
|
||||
- CropImage:
|
||||
size: 224
|
||||
- NormalizeImage:
|
||||
scale: 1.0/255.0
|
||||
mean: [0.485, 0.456, 0.406]
|
||||
std: [0.229, 0.224, 0.225]
|
||||
order: ''
|
||||
- ToCHWImage:
|
||||
dataset:
|
||||
name: ImageNetDataset
|
||||
image_root: "./dataset/ILSVRC2012/"
|
||||
cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
|
||||
transform_ops:
|
||||
- ResizeImage:
|
||||
size: 224
|
||||
- NormalizeImage:
|
||||
scale: 0.00392157
|
||||
mean: [0.485, 0.456, 0.406]
|
||||
std: [0.229, 0.224, 0.225]
|
||||
order: ''
|
||||
sampler:
|
||||
name: DistributedBatchSampler
|
||||
batch_size: 64
|
||||
drop_last: False
|
||||
shuffle: False
|
||||
loader:
|
||||
num_workers: 6
|
||||
use_shared_memory: False
|
||||
|
||||
Infer:
|
||||
infer_imgs: "docs/images/whl/demo.jpg"
|
||||
|
|
|
|||
|
|
@ -0,0 +1,122 @@
|
|||
# global configs
|
||||
Global:
|
||||
checkpoints: null
|
||||
pretrained_model: null
|
||||
output_dir: "./output/"
|
||||
device: "gpu"
|
||||
class_num: 1000
|
||||
save_interval: 1
|
||||
eval_during_train: True
|
||||
eval_interval: 1
|
||||
epochs: 200
|
||||
print_batch_step: 10
|
||||
use_visualdl: False
|
||||
# used for static mode and model export
|
||||
image_shape: [3, 224, 224]
|
||||
save_inference_dir: "./inference"
|
||||
|
||||
# model architecture
|
||||
Arch:
|
||||
name: "ResNet50_vd"
|
||||
|
||||
# loss function config for traing/eval process
|
||||
Loss:
|
||||
Train:
|
||||
- CELoss:
|
||||
weight: 1.0
|
||||
Eval:
|
||||
- CELoss:
|
||||
weight: 1.0
|
||||
|
||||
|
||||
Optimizer:
|
||||
name: Momentum
|
||||
momentum: 0.9
|
||||
lr:
|
||||
name: Cosine
|
||||
learning_rate: 0.1
|
||||
regularizer:
|
||||
name: 'L2'
|
||||
coeff: 0.00007
|
||||
|
||||
|
||||
# data loader for train and eval
|
||||
DataLoader:
|
||||
Train:
|
||||
dataset:
|
||||
name: ImageNetDataset
|
||||
image_root: "./dataset/ILSVRC2012/"
|
||||
cls_label_path: "./dataset/ILSVRC2012/train_list.txt"
|
||||
transform_ops:
|
||||
- RandCropImage:
|
||||
size: 224
|
||||
- RandFlipImage:
|
||||
flip_code: 1
|
||||
- NormalizeImage:
|
||||
scale: 0.00392157
|
||||
mean: [0.485, 0.456, 0.406]
|
||||
std: [0.229, 0.224, 0.225]
|
||||
order: ''
|
||||
|
||||
sampler:
|
||||
name: DistributedBatchSampler
|
||||
batch_size: 64
|
||||
drop_last: False
|
||||
shuffle: True
|
||||
loader:
|
||||
num_workers: 6
|
||||
use_shared_memory: False
|
||||
|
||||
Eval:
|
||||
# TOTO: modify to the latest trainer
|
||||
dataset:
|
||||
name: ImageNetDataset
|
||||
image_root: "./dataset/ILSVRC2012/"
|
||||
cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
|
||||
transform_ops:
|
||||
- ResizeImage:
|
||||
size: 224
|
||||
- NormalizeImage:
|
||||
scale: 0.00392157
|
||||
mean: [0.485, 0.456, 0.406]
|
||||
std: [0.229, 0.224, 0.225]
|
||||
order: ''
|
||||
sampler:
|
||||
name: DistributedBatchSampler
|
||||
batch_size: 64
|
||||
drop_last: False
|
||||
shuffle: False
|
||||
loader:
|
||||
num_workers: 6
|
||||
use_shared_memory: False
|
||||
|
||||
Infer:
|
||||
infer_imgs: "docs/images/whl/demo.jpg"
|
||||
batch_size: 10
|
||||
transforms:
|
||||
- DecodeImage:
|
||||
to_rgb: True
|
||||
channel_first: False
|
||||
- ResizeImage:
|
||||
resize_short: 256
|
||||
- CropImage:
|
||||
size: 224
|
||||
- NormalizeImage:
|
||||
scale: 1.0/255.0
|
||||
mean: [0.485, 0.456, 0.406]
|
||||
std: [0.229, 0.224, 0.225]
|
||||
order: ''
|
||||
- ToCHWImage:
|
||||
PostProcess:
|
||||
name: Topk
|
||||
topk: 5
|
||||
class_id_map_file: "ppcls/utils/imagenet1k_label_list.txt"
|
||||
|
||||
Metric:
|
||||
Train:
|
||||
- Topk:
|
||||
k: [1, 5]
|
||||
Eval:
|
||||
- Topk:
|
||||
k: [1, 5]
|
||||
|
||||
|
|
@ -0,0 +1,122 @@
|
|||
# global configs
|
||||
Global:
|
||||
checkpoints: null
|
||||
pretrained_model: null
|
||||
output_dir: "./output/"
|
||||
device: "gpu"
|
||||
class_num: 1000
|
||||
save_interval: 1
|
||||
eval_during_train: True
|
||||
eval_interval: 1
|
||||
epochs: 90
|
||||
print_batch_step: 10
|
||||
use_visualdl: False
|
||||
# used for static mode and model export
|
||||
image_shape: [3, 224, 224]
|
||||
save_inference_dir: "./inference"
|
||||
|
||||
# model architecture
|
||||
Arch:
|
||||
name: "VGG11"
|
||||
|
||||
# loss function config for traing/eval process
|
||||
Loss:
|
||||
Train:
|
||||
- CELoss:
|
||||
weight: 1.0
|
||||
Eval:
|
||||
- CELoss:
|
||||
weight: 1.0
|
||||
|
||||
|
||||
Optimizer:
|
||||
name: Momentum
|
||||
momentum: 0.9
|
||||
lr:
|
||||
name: Cosine
|
||||
learning_rate: 0.1
|
||||
regularizer:
|
||||
name: 'L2'
|
||||
coeff: 0.0002
|
||||
|
||||
|
||||
# data loader for train and eval
|
||||
DataLoader:
|
||||
Train:
|
||||
dataset:
|
||||
name: ImageNetDataset
|
||||
image_root: "./dataset/ILSVRC2012/"
|
||||
cls_label_path: "./dataset/ILSVRC2012/train_list.txt"
|
||||
transform_ops:
|
||||
- RandCropImage:
|
||||
size: 224
|
||||
- RandFlipImage:
|
||||
flip_code: 1
|
||||
- NormalizeImage:
|
||||
scale: 0.00392157
|
||||
mean: [0.485, 0.456, 0.406]
|
||||
std: [0.229, 0.224, 0.225]
|
||||
order: ''
|
||||
|
||||
sampler:
|
||||
name: DistributedBatchSampler
|
||||
batch_size: 64
|
||||
drop_last: False
|
||||
shuffle: True
|
||||
loader:
|
||||
num_workers: 6
|
||||
use_shared_memory: False
|
||||
|
||||
Eval:
|
||||
# TOTO: modify to the latest trainer
|
||||
dataset:
|
||||
name: ImageNetDataset
|
||||
image_root: "./dataset/ILSVRC2012/"
|
||||
cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
|
||||
transform_ops:
|
||||
- ResizeImage:
|
||||
size: 224
|
||||
- NormalizeImage:
|
||||
scale: 0.00392157
|
||||
mean: [0.485, 0.456, 0.406]
|
||||
std: [0.229, 0.224, 0.225]
|
||||
order: ''
|
||||
sampler:
|
||||
name: DistributedBatchSampler
|
||||
batch_size: 64
|
||||
drop_last: False
|
||||
shuffle: False
|
||||
loader:
|
||||
num_workers: 6
|
||||
use_shared_memory: False
|
||||
|
||||
Infer:
|
||||
infer_imgs: "docs/images/whl/demo.jpg"
|
||||
batch_size: 10
|
||||
transforms:
|
||||
- DecodeImage:
|
||||
to_rgb: True
|
||||
channel_first: False
|
||||
- ResizeImage:
|
||||
resize_short: 256
|
||||
- CropImage:
|
||||
size: 224
|
||||
- NormalizeImage:
|
||||
scale: 1.0/255.0
|
||||
mean: [0.485, 0.456, 0.406]
|
||||
std: [0.229, 0.224, 0.225]
|
||||
order: ''
|
||||
- ToCHWImage:
|
||||
PostProcess:
|
||||
name: Topk
|
||||
topk: 5
|
||||
class_id_map_file: "ppcls/utils/imagenet1k_label_list.txt"
|
||||
|
||||
Metric:
|
||||
Train:
|
||||
- Topk:
|
||||
k: [1, 5]
|
||||
Eval:
|
||||
- Topk:
|
||||
k: [1, 5]
|
||||
|
||||
|
|
@ -0,0 +1,122 @@
|
|||
# global configs
|
||||
Global:
|
||||
checkpoints: null
|
||||
pretrained_model: null
|
||||
output_dir: "./output/"
|
||||
device: "gpu"
|
||||
class_num: 1000
|
||||
save_interval: 1
|
||||
eval_during_train: True
|
||||
eval_interval: 1
|
||||
epochs: 90
|
||||
print_batch_step: 10
|
||||
use_visualdl: False
|
||||
# used for static mode and model export
|
||||
image_shape: [3, 224, 224]
|
||||
save_inference_dir: "./inference"
|
||||
|
||||
# model architecture
|
||||
Arch:
|
||||
name: "VGG13"
|
||||
|
||||
# loss function config for traing/eval process
|
||||
Loss:
|
||||
Train:
|
||||
- CELoss:
|
||||
weight: 1.0
|
||||
Eval:
|
||||
- CELoss:
|
||||
weight: 1.0
|
||||
|
||||
|
||||
Optimizer:
|
||||
name: Momentum
|
||||
momentum: 0.9
|
||||
lr:
|
||||
name: Cosine
|
||||
learning_rate: 0.01
|
||||
regularizer:
|
||||
name: 'L2'
|
||||
coeff: 0.0003
|
||||
|
||||
|
||||
# data loader for train and eval
|
||||
DataLoader:
|
||||
Train:
|
||||
dataset:
|
||||
name: ImageNetDataset
|
||||
image_root: "./dataset/ILSVRC2012/"
|
||||
cls_label_path: "./dataset/ILSVRC2012/train_list.txt"
|
||||
transform_ops:
|
||||
- RandCropImage:
|
||||
size: 224
|
||||
- RandFlipImage:
|
||||
flip_code: 1
|
||||
- NormalizeImage:
|
||||
scale: 0.00392157
|
||||
mean: [0.485, 0.456, 0.406]
|
||||
std: [0.229, 0.224, 0.225]
|
||||
order: ''
|
||||
|
||||
sampler:
|
||||
name: DistributedBatchSampler
|
||||
batch_size: 64
|
||||
drop_last: False
|
||||
shuffle: True
|
||||
loader:
|
||||
num_workers: 6
|
||||
use_shared_memory: False
|
||||
|
||||
Eval:
|
||||
# TOTO: modify to the latest trainer
|
||||
dataset:
|
||||
name: ImageNetDataset
|
||||
image_root: "./dataset/ILSVRC2012/"
|
||||
cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
|
||||
transform_ops:
|
||||
- ResizeImage:
|
||||
size: 224
|
||||
- NormalizeImage:
|
||||
scale: 0.00392157
|
||||
mean: [0.485, 0.456, 0.406]
|
||||
std: [0.229, 0.224, 0.225]
|
||||
order: ''
|
||||
sampler:
|
||||
name: DistributedBatchSampler
|
||||
batch_size: 64
|
||||
drop_last: False
|
||||
shuffle: False
|
||||
loader:
|
||||
num_workers: 6
|
||||
use_shared_memory: False
|
||||
|
||||
Infer:
|
||||
infer_imgs: "docs/images/whl/demo.jpg"
|
||||
batch_size: 10
|
||||
transforms:
|
||||
- DecodeImage:
|
||||
to_rgb: True
|
||||
channel_first: False
|
||||
- ResizeImage:
|
||||
resize_short: 256
|
||||
- CropImage:
|
||||
size: 224
|
||||
- NormalizeImage:
|
||||
scale: 1.0/255.0
|
||||
mean: [0.485, 0.456, 0.406]
|
||||
std: [0.229, 0.224, 0.225]
|
||||
order: ''
|
||||
- ToCHWImage:
|
||||
PostProcess:
|
||||
name: Topk
|
||||
topk: 5
|
||||
class_id_map_file: "ppcls/utils/imagenet1k_label_list.txt"
|
||||
|
||||
Metric:
|
||||
Train:
|
||||
- Topk:
|
||||
k: [1, 5]
|
||||
Eval:
|
||||
- Topk:
|
||||
k: [1, 5]
|
||||
|
||||
|
|
@ -0,0 +1,122 @@
|
|||
# global configs
|
||||
Global:
|
||||
checkpoints: null
|
||||
pretrained_model: null
|
||||
output_dir: "./output/"
|
||||
device: "gpu"
|
||||
class_num: 1000
|
||||
save_interval: 1
|
||||
eval_during_train: True
|
||||
eval_interval: 1
|
||||
epochs: 90
|
||||
print_batch_step: 10
|
||||
use_visualdl: False
|
||||
# used for static mode and model export
|
||||
image_shape: [3, 224, 224]
|
||||
save_inference_dir: "./inference"
|
||||
|
||||
# model architecture
|
||||
Arch:
|
||||
name: "VGG16"
|
||||
|
||||
# loss function config for traing/eval process
|
||||
Loss:
|
||||
Train:
|
||||
- CELoss:
|
||||
weight: 1.0
|
||||
Eval:
|
||||
- CELoss:
|
||||
weight: 1.0
|
||||
|
||||
|
||||
Optimizer:
|
||||
name: Momentum
|
||||
momentum: 0.9
|
||||
lr:
|
||||
name: Cosine
|
||||
learning_rate: 0.01
|
||||
regularizer:
|
||||
name: 'L2'
|
||||
coeff: 0.0004
|
||||
|
||||
|
||||
# data loader for train and eval
|
||||
DataLoader:
|
||||
Train:
|
||||
dataset:
|
||||
name: ImageNetDataset
|
||||
image_root: "./dataset/ILSVRC2012/"
|
||||
cls_label_path: "./dataset/ILSVRC2012/train_list.txt"
|
||||
transform_ops:
|
||||
- RandCropImage:
|
||||
size: 224
|
||||
- RandFlipImage:
|
||||
flip_code: 1
|
||||
- NormalizeImage:
|
||||
scale: 0.00392157
|
||||
mean: [0.485, 0.456, 0.406]
|
||||
std: [0.229, 0.224, 0.225]
|
||||
order: ''
|
||||
|
||||
sampler:
|
||||
name: DistributedBatchSampler
|
||||
batch_size: 64
|
||||
drop_last: False
|
||||
shuffle: True
|
||||
loader:
|
||||
num_workers: 6
|
||||
use_shared_memory: False
|
||||
|
||||
Eval:
|
||||
# TOTO: modify to the latest trainer
|
||||
dataset:
|
||||
name: ImageNetDataset
|
||||
image_root: "./dataset/ILSVRC2012/"
|
||||
cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
|
||||
transform_ops:
|
||||
- ResizeImage:
|
||||
size: 224
|
||||
- NormalizeImage:
|
||||
scale: 0.00392157
|
||||
mean: [0.485, 0.456, 0.406]
|
||||
std: [0.229, 0.224, 0.225]
|
||||
order: ''
|
||||
sampler:
|
||||
name: DistributedBatchSampler
|
||||
batch_size: 64
|
||||
drop_last: False
|
||||
shuffle: False
|
||||
loader:
|
||||
num_workers: 6
|
||||
use_shared_memory: False
|
||||
|
||||
Infer:
|
||||
infer_imgs: "docs/images/whl/demo.jpg"
|
||||
batch_size: 10
|
||||
transforms:
|
||||
- DecodeImage:
|
||||
to_rgb: True
|
||||
channel_first: False
|
||||
- ResizeImage:
|
||||
resize_short: 256
|
||||
- CropImage:
|
||||
size: 224
|
||||
- NormalizeImage:
|
||||
scale: 1.0/255.0
|
||||
mean: [0.485, 0.456, 0.406]
|
||||
std: [0.229, 0.224, 0.225]
|
||||
order: ''
|
||||
- ToCHWImage:
|
||||
PostProcess:
|
||||
name: Topk
|
||||
topk: 5
|
||||
class_id_map_file: "ppcls/utils/imagenet1k_label_list.txt"
|
||||
|
||||
Metric:
|
||||
Train:
|
||||
- Topk:
|
||||
k: [1, 5]
|
||||
Eval:
|
||||
- Topk:
|
||||
k: [1, 5]
|
||||
|
||||
|
|
@ -0,0 +1,122 @@
|
|||
# global configs
|
||||
Global:
|
||||
checkpoints: null
|
||||
pretrained_model: null
|
||||
output_dir: "./output/"
|
||||
device: "gpu"
|
||||
class_num: 1000
|
||||
save_interval: 1
|
||||
eval_during_train: True
|
||||
eval_interval: 1
|
||||
epochs: 150
|
||||
print_batch_step: 10
|
||||
use_visualdl: False
|
||||
# used for static mode and model export
|
||||
image_shape: [3, 224, 224]
|
||||
save_inference_dir: "./inference"
|
||||
|
||||
# model architecture
|
||||
Arch:
|
||||
name: "VGG19"
|
||||
|
||||
# loss function config for traing/eval process
|
||||
Loss:
|
||||
Train:
|
||||
- CELoss:
|
||||
weight: 1.0
|
||||
Eval:
|
||||
- CELoss:
|
||||
weight: 1.0
|
||||
|
||||
|
||||
Optimizer:
|
||||
name: Momentum
|
||||
momentum: 0.9
|
||||
lr:
|
||||
name: Cosine
|
||||
learning_rate: 0.01
|
||||
regularizer:
|
||||
name: 'L2'
|
||||
coeff: 0.0004
|
||||
|
||||
|
||||
# data loader for train and eval
|
||||
DataLoader:
|
||||
Train:
|
||||
dataset:
|
||||
name: ImageNetDataset
|
||||
image_root: "./dataset/ILSVRC2012/"
|
||||
cls_label_path: "./dataset/ILSVRC2012/train_list.txt"
|
||||
transform_ops:
|
||||
- RandCropImage:
|
||||
size: 224
|
||||
- RandFlipImage:
|
||||
flip_code: 1
|
||||
- NormalizeImage:
|
||||
scale: 0.00392157
|
||||
mean: [0.485, 0.456, 0.406]
|
||||
std: [0.229, 0.224, 0.225]
|
||||
order: ''
|
||||
|
||||
sampler:
|
||||
name: DistributedBatchSampler
|
||||
batch_size: 64
|
||||
drop_last: False
|
||||
shuffle: True
|
||||
loader:
|
||||
num_workers: 6
|
||||
use_shared_memory: False
|
||||
|
||||
Eval:
|
||||
# TOTO: modify to the latest trainer
|
||||
dataset:
|
||||
name: ImageNetDataset
|
||||
image_root: "./dataset/ILSVRC2012/"
|
||||
cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
|
||||
transform_ops:
|
||||
- ResizeImage:
|
||||
size: 224
|
||||
- NormalizeImage:
|
||||
scale: 0.00392157
|
||||
mean: [0.485, 0.456, 0.406]
|
||||
std: [0.229, 0.224, 0.225]
|
||||
order: ''
|
||||
sampler:
|
||||
name: DistributedBatchSampler
|
||||
batch_size: 64
|
||||
drop_last: False
|
||||
shuffle: False
|
||||
loader:
|
||||
num_workers: 6
|
||||
use_shared_memory: False
|
||||
|
||||
Infer:
|
||||
infer_imgs: "docs/images/whl/demo.jpg"
|
||||
batch_size: 10
|
||||
transforms:
|
||||
- DecodeImage:
|
||||
to_rgb: True
|
||||
channel_first: False
|
||||
- ResizeImage:
|
||||
resize_short: 256
|
||||
- CropImage:
|
||||
size: 224
|
||||
- NormalizeImage:
|
||||
scale: 1.0/255.0
|
||||
mean: [0.485, 0.456, 0.406]
|
||||
std: [0.229, 0.224, 0.225]
|
||||
order: ''
|
||||
- ToCHWImage:
|
||||
PostProcess:
|
||||
name: Topk
|
||||
topk: 5
|
||||
class_id_map_file: "ppcls/utils/imagenet1k_label_list.txt"
|
||||
|
||||
Metric:
|
||||
Train:
|
||||
- Topk:
|
||||
k: [1, 5]
|
||||
Eval:
|
||||
- Topk:
|
||||
k: [1, 5]
|
||||
|
||||
|
|
@ -18,13 +18,13 @@ from paddle.io import DistributedBatchSampler, BatchSampler, DataLoader
|
|||
|
||||
from ppcls.utils import logger
|
||||
|
||||
from . import datasets
|
||||
from . import dataset
|
||||
from . import imaug
|
||||
from . import samplers
|
||||
# dataset
|
||||
from .datasets.imagenet_dataset import ImageNetDataset
|
||||
from .dataset.imagenet_dataset import ImageNetDataset
|
||||
from .dataset.multilabel_dataset import MultiLabelDataset
|
||||
from .datasets.common_dataset import create_operators
|
||||
from .dataset.common_dataset import create_operators
|
||||
|
||||
# sampler
|
||||
from .samplers import DistributedRandomIdentitySampler
|
||||
|
|
@ -35,6 +35,7 @@ def build_dataloader(config, mode, device, seed=None):
|
|||
assert mode in ['Train', 'Eval', 'Test'], "Mode should be Train, Eval or Test."
|
||||
# build dataset
|
||||
config_dataset = config[mode]['dataset']
|
||||
config_dataset = copy.deepcopy(config_dataset)
|
||||
dataset_name = config_dataset.pop('name')
|
||||
if 'batch_transform_ops' in config_dataset:
|
||||
batch_transform = config_dataset.pop('batch_transform_ops')
|
||||
|
|
@ -105,7 +106,7 @@ def build_dataloader(config, mode, device, seed=None):
|
|||
|
||||
logger.info("build data_loader({}) success...".format(data_loader))
|
||||
|
||||
return dataloader
|
||||
return data_loader
|
||||
|
||||
'''
|
||||
# TODO: fix the format
|
||||
|
|
|
|||
|
|
@ -40,7 +40,6 @@ def create_operators(params):
|
|||
assert isinstance(params, list), ('operator config should be a list')
|
||||
ops = []
|
||||
for operator in params:
|
||||
print(operator)
|
||||
assert isinstance(operator,
|
||||
dict) and len(operator) == 1, "yaml format error"
|
||||
op_name = list(operator)[0]
|
||||
|
|
|
|||
|
|
@ -14,9 +14,9 @@
|
|||
import copy
|
||||
import importlib
|
||||
|
||||
from . import topk_process
|
||||
from . import topk
|
||||
|
||||
from .topk_process import Topk
|
||||
from .topk import Topk
|
||||
|
||||
|
||||
def build_postprocess(config):
|
||||
|
|
|
|||
|
|
@ -40,7 +40,6 @@ def transform(data, ops=[]):
|
|||
""" transform """
|
||||
for op in ops:
|
||||
data = op(data)
|
||||
#print(data.shape, op)
|
||||
return data
|
||||
|
||||
|
||||
|
|
|
|||
|
|
@ -104,7 +104,7 @@ class Trainer(object):
|
|||
|
||||
metric_func = self._build_metric_info(self.config["Metric"])
|
||||
|
||||
train_dataloader = build_dataloader(self.config["DataLoader"], "train",
|
||||
train_dataloader = build_dataloader(self.config["DataLoader"], "Train",
|
||||
self.device)
|
||||
|
||||
step_each_epoch = len(train_dataloader)
|
||||
|
|
@ -217,7 +217,7 @@ class Trainer(object):
|
|||
def eval(self, epoch_id=0):
|
||||
output_info = dict()
|
||||
|
||||
eval_dataloader = build_dataloader(self.config["DataLoader"], "eval",
|
||||
eval_dataloader = build_dataloader(self.config["DataLoader"], "Eval",
|
||||
self.device)
|
||||
|
||||
self.model.eval()
|
||||
|
|
|
|||
|
|
@ -48,7 +48,6 @@ class TripletLossV2(nn.Layer):
|
|||
|
||||
# `dist_ap` means distance(anchor, positive)
|
||||
## both `dist_ap` and `relative_p_inds` with shape [N, 1]
|
||||
#print(is_pos.shape, dist.shape, type(is_pos), type(dist), paddle.reshape(paddle.masked_select(dist, is_pos),(bs, -1)))
|
||||
'''
|
||||
dist_ap, relative_p_inds = paddle.max(
|
||||
paddle.reshape(dist[is_pos], (bs, -1)), axis=1, keepdim=True)
|
||||
|
|
@ -98,7 +97,6 @@ class TripletLoss(nn.Layer):
|
|||
"""
|
||||
inputs = input["features"]
|
||||
|
||||
#print(inputs.shape, targets.shape)
|
||||
bs = inputs.shape[0]
|
||||
# Compute pairwise distance, replace by the official when merged
|
||||
dist = paddle.pow(inputs, 2).sum(axis=1, keepdim=True).expand([bs, bs])
|
||||
|
|
|
|||
|
|
@ -3,5 +3,5 @@
|
|||
python3.7 -m paddle.distributed.launch \
|
||||
--gpus="0,1,2,3" \
|
||||
tools/train.py \
|
||||
-c ./configs/ResNet/ResNet50.yaml \
|
||||
-c ./ppcls/configs/ImageNet/ResNet/ResNet50.yaml \
|
||||
-o print_interval=10
|
||||
|
|
|
|||
Loading…
Reference in New Issue