#start_epoch:         The 'on_epoch_begin' function will be called in start_epoch. default: 0.
#end_epoch:           The 'on_epoch_end' function will be called in end_epoch. default: 10.
#delta_rate:          The delta used to generate ratios when calculating sensitivities.
#target_ratio:        The flops ratio to be pruned from current model.
#metric_name:         The metric used to evaluate the model.
#pruned_params:       The pattern str to match the parameter names to be pruned.
#sensitivities_file:  The sensitivities file.
#num_steps:           The number of pruning steps.
#eval_rate:           The rate of sampled data used to calculate sensitivities.
version: 1.0
pruners:
    pruner_1:
        class: 'StructurePruner'
        pruning_axis:
            '*': 0
        criterions:
            '*': 'l1_norm'
strategies:
    sensitive_pruning_strategy:
        class: 'SensitivePruneStrategy'
        pruner: 'pruner_1'
        start_epoch: 0
        delta_rate: 0.1
        target_ratio: 0.3
        num_steps: 1
        eval_rate: 0.5
        pruned_params: '.*_sep_weights'
        sensitivities_file: 'mobilenet_acc_top1_sensitive.data'
        metric_name: 'acc_top1'
compressor:
    epoch: 120
    checkpoint_path: './checkpoints/'
    strategies:
        - sensitive_pruning_strategy
