# global configs Global: checkpoints: null pretrained_model: null output_dir: ./output/ device: gpu save_interval: 1 eval_during_train: True eval_interval: 1 epochs: 100 print_batch_step: 10 use_visualdl: False # used for static mode and model export image_shape: [3, 224, 224] save_inference_dir: ./inference eval_mode: retrieval use_dali: False to_static: False # model architecture Arch: name: RecModel infer_output_key: features infer_add_softmax: False Backbone: name: PPLCNet_x2_5 pretrained: True use_ssld: True BackboneStopLayer: name: "flatten" Neck: name: FC embedding_size: 1280 class_num: 512 Head: name: ArcMargin embedding_size: 512 class_num: 185341 margin: 0.2 scale: 30 # 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: 0.04 warmup_epoch: 5 regularizer: name: "L2" coeff: 0.00001 # data loader for train and eval DataLoader: Train: dataset: name: ImageNetDataset image_root: ./dataset/ cls_label_path: ./dataset/train_reg_all_data.txt transform_ops: - DecodeImage: to_rgb: True channel_first: False - RandCropImage: size: 224 - RandFlipImage: flip_code: 1 - NormalizeImage: scale: 1.0/255.0 mean: [0.485, 0.456, 0.406] std: [0.229, 0.224, 0.225] order: "" sampler: name: DistributedBatchSampler batch_size: 256 drop_last: False shuffle: True loader: num_workers: 4 use_shared_memory: True Eval: Query: dataset: name: VeriWild image_root: ./dataset/Aliproduct/ cls_label_path: ./dataset/Aliproduct/val_list.txt transform_ops: - DecodeImage: to_rgb: True channel_first: False - 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: 4 use_shared_memory: True Gallery: dataset: name: VeriWild image_root: ./dataset/Aliproduct/ cls_label_path: ./dataset/Aliproduct/val_list.txt transform_ops: - DecodeImage: to_rgb: True channel_first: False - 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: 4 use_shared_memory: True Metric: Eval: - Recallk: topk: [1, 5] - mAP: {}