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132 lines
2.8 KiB
YAML
132 lines
2.8 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/ResNet50_face
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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: 25
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print_batch_step: 20
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use_visualdl: False
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eval_mode: face_recognition
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retrieval_feature_from: backbone
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flip_test: True
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feature_normalize: False
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re_ranking: False
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use_dali: 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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AMP:
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scale_loss: 27648.0
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use_dynamic_loss_scaling: True
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# O1: mixed fp16
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level: O1
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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: ResNet50
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max_pool: False
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stride_list: [1, 2, 2, 2, 2]
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class_num: 512
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Head:
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name: ArcMargin
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embedding_size: 512
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class_num: 93431
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margin: 0.5
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scale: 64
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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: AdamW
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beta1: 0.9
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beta2: 0.999
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epsilon: 1e-8
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weight_decay: 0.05
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one_dim_param_no_weight_decay: True
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lr:
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# for 8 cards
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name: Cosine
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learning_rate: 4e-3 # lr 4e-3 for total_batch_size 1024
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eta_min: 1e-6
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warmup_epoch: 1
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warmup_start_lr: 0
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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/MS1M_v3/
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cls_label_path: dataset/MS1M_v3/label.txt
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delimiter: "\t"
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transform_ops:
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- DecodeImage:
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to_rgb: True
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channel_first: False
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backend: cv2
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- RandFlipImage:
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flip_code: 1
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- ResizeImage:
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size: [112, 112]
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return_numpy: False
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interpolation: bilinear
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backend: cv2
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- NormalizeImage:
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scale: 1.0/255.0
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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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order: hwc
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sampler:
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name: DistributedBatchSampler
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batch_size: 128
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drop_last: False
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shuffle: True
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loader:
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num_workers: 8
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use_shared_memory: True
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Eval:
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dataset:
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name: FiveFaceEvalDataset
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val_data_path: dataset/MS1M_v3/
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transform_ops:
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- DecodeImage:
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to_rgb: True
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channel_first: False
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backend: cv2
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- ResizeImage:
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size: [112, 112]
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return_numpy: False
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interpolation: bilinear
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backend: cv2
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- NormalizeImage:
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scale: 1.0/255.0
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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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order: hwc
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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: 4
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use_shared_memory: True
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Metric:
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Eval:
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- FaceAccOnFiveDatasets: {}
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