retrain:
    iter_max_epoch: 10
    tolerance: 0.001
    retrain_mode: vairables
    run_status: normal
    parameters:
        target: ['conv0/weights/DynamicNetworkSurgeryPruner.alpha']
        associated: ['conv0/weights:0']
        update_overrider: True
        range: {from: 0, to: 2, scale: 0.5, min_scale: 0.2, scale_update_factor: 0.5}
        # range: {from: 16, to: 1, scale: -2, min_scale: -1, scale_update_factor: 0.5}

# retrain:
#     iter_max_epoch: 10
#     tolerance: 0.001
#     retrain_mode: custom
#     run_status: normal
#     _width: &width
#           from: 16
#           to: 1
#           init_scale: -2
#           min_scale: -1
#           scale_update_factor: 0.5
#     parameters:
#           conv0/weights/DGQuantizer.width:
#               <<: *width
#               associate: conv1/weights
