DocumentAIKit/configs/slim/quant/ppyolov2_r50vd_dcn_qat.yml

pretrain_weights: https://paddledet.bj.bcebos.com/models/ppyolov2_r50vd_dcn_365e_coco.pdparams
slim: QAT

QAT:
  quant_config: {
    'activation_preprocess_type': 'PACT',
    'weight_quantize_type': 'channel_wise_abs_max', 'activation_quantize_type': 'moving_average_abs_max',
    'weight_bits': 8, 'activation_bits': 8, 'dtype': 'int8', 'window_size': 10000, 'moving_rate': 0.9,
    'quantizable_layer_type': ['Conv2D', 'Linear']}
  print_model: True

epoch: 50
snapshot_epoch: 8
LearningRate:
  base_lr: 0.0005
  schedulers:
  - !PiecewiseDecay
    gamma: 0.1
    milestones:
    - 30
    - 45
  - !LinearWarmup
    start_factor: 0.
    steps: 2000

TrainReader:
   batch_size: 8

PPYOLOPAN:
  drop_block: false
  block_size: 3
  keep_prob: 0.9
  spp: true