105 lines
2.3 KiB
YAML
105 lines
2.3 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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save_interval: 1
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eval_during_train: True
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eval_interval: 1
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epochs: 26
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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, 112, 112]
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save_inference_dir: "./inference"
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eval_mode: "adaface"
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# model architecture
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Arch:
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name: "RecModel"
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infer_output_key: "features"
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infer_add_softmax: False
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Backbone:
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name: "AdaFace_IR_18"
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input_size: [112, 112]
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Head:
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name: "AdaMargin"
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embedding_size: 512
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class_num: 70722
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m: 0.4
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s: 64
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h: 0.333
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t_alpha: 0.01
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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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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: [12, 20, 24]
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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: 0.0005
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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: "AdaFaceDataset"
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root_dir: "dataset/face/"
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label_path: "dataset/face/train_filter_label.txt"
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transform:
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- CropWithPadding:
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prob: 0.2
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padding_num: 0
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size: [112, 112]
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scale: [0.2, 1.0]
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ratio: [0.75, 1.3333333333333333]
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- RandomInterpolationAugment:
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prob: 0.2
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- ColorJitter:
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prob: 0.2
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brightness: 0.5
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contrast: 0.5
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saturation: 0.5
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hue: 0
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- RandomHorizontalFlip:
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- ToTensor:
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- Normalize:
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mean: [0.5, 0.5, 0.5]
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std: [0.5, 0.5, 0.5]
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sampler:
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name: DistributedBatchSampler
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batch_size: 256
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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: True
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Eval:
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dataset:
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name: FiveValidationDataset
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val_data_path: dataset/face/faces_emore
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concat_mem_file_name: dataset/face/faces_emore/concat_validation_memfile
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sampler:
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name: BatchSampler
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batch_size: 256
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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: True
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Metric:
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Train:
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- TopkAcc:
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topk: [1, 5] |