DSHSD.yaml

# 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]