125 lines
2.6 KiB
YAML
125 lines
2.6 KiB
YAML
# 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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