# global configs Global: checkpoints: null pretrained_model: null output_dir: ./output device: gpu save_interval: 15 eval_during_train: True eval_interval: 15 epochs: 150 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 #feature postprocess feature_normalize: False feature_binarize: "sign" # model architecture Arch: name: RecModel infer_output_key: features infer_add_softmax: False Backbone: name: AlexNet pretrained: True class_num: 48 Neck: name: Tanh Head: name: FC class_num: 10 embedding_size: 48 # loss function config for traing/eval process Loss: Train: - DSHSDLoss: weight: 1.0 alpha: 0.05 Eval: - DSHSDLoss: weight: 1.0 alpha: 0.05 Optimizer: name: Adam beta1: 0.9 beta2: 0.999 lr: name: Piecewise learning_rate: 0.00001 decay_epochs: [200] values: [0.00001, 0.000001] # data loader for train and eval DataLoader: Train: dataset: name: CustomizedCifar10 mode: 'train' sampler: batch_size: 128 drop_last: False shuffle: True loader: num_workers: 4 use_shared_memory: True Eval: Query: dataset: name: CustomizedCifar10 mode: 'test' sampler: batch_size: 128 drop_last: False shuffle: False loader: num_workers: 4 use_shared_memory: True Gallery: dataset: name: CustomizedCifar10 mode: 'train' sampler: batch_size: 128 drop_last: False shuffle: False loader: num_workers: 4 use_shared_memory: True Metric: Eval: - mAP: {} - Recallk: topk: [1, 5]