9d468d2c742491af2d2f506c648ddc95ffea6a64,src/sdk/pynni/nni/compression/tensorflow/builtin_pruners.py,SensitivityPruner,calc_mask,#SensitivityPruner#Any#Any#Any#,94

Before Change

    def calc_mask(self, weight, config, op_name, **kwargs):
        target_sparsity = config["sparsity"] * tf.math.reduce_std(weight) 
        mask = tf.get_variable(op_name + "_mask", initializer=tf.ones(weight.shape), trainable=False)
        self.layer_mask[op_name] = mask

        weight_assign_handler = tf.assign(weight, mask*weight)
        // use control_dependencies so that weight_assign_handler will be executed before mask_update_handler

After Change

        self.assign_handler = []

    def calc_mask(self, weight, config, op_name, **kwargs):
        start_epoch = config.get("start_epoch", 0)
        freq = config.get("frequency", 1)
        if self.now_epoch >= start_epoch and self.if_init_list.get(op_name, True) and (
                self.now_epoch - start_epoch) % freq == 0:
            target_sparsity = self.compute_target_sparsity(config)

Instances