135 lines
2.9 KiB
YAML
135 lines
2.9 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: 160
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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: "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_last_stage_stride1"
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pretrained: True
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BackboneStopLayer:
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name: "adaptive_avg_pool2d_0"
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Neck:
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name: "VehicleNeck"
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in_channels: 2048
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out_channels: 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: 431
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margin: 0.15
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scale: 32
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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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- SupConLoss:
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weight: 1.0
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views: 2
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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: MultiStepDecay
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learning_rate: 0.01
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milestones: [30, 60, 70, 80, 90, 100, 120, 140]
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gamma: 0.5
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verbose: False
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last_epoch: -1
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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: "CompCars"
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image_root: "./dataset/CompCars/image/"
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label_root: "./dataset/CompCars/label/"
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bbox_crop: True
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cls_label_path: "./dataset/CompCars/train_test_split/classification/train_label.txt"
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transform_ops:
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- ResizeImage:
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size: 224
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- RandFlipImage:
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flip_code: 1
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- AugMix:
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prob: 0.5
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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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- RandomErasing:
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EPSILON: 0.5
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sl: 0.02
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sh: 0.4
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r1: 0.3
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mean: [0., 0., 0.]
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sampler:
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name: DistributedRandomIdentitySampler
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batch_size: 128
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num_instances: 2
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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: "CompCars"
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image_root: "./dataset/CompCars/image/"
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label_root: "./dataset/CompCars/label/"
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cls_label_path: "./dataset/CompCars/train_test_split/classification/test_label.txt"
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bbox_crop: True
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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: 128
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drop_last: False
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shuffle: False
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loader:
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num_workers: 8
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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]
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Eval:
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- TopkAcc:
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topk: [1, 5]
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