def DEFAULT_PRUNING(cls) -> PassPipeline:
        """Create a default sparsification pipeline to convert a compressed source model"""
        pipeline = cls.get_pipeline("default_sparsification")

        # set default sparsification
        config = OptimizationConfig(
            global_config=OpThresholdPrunerConfig(
                threshold=1e-12,
            )
        )
        pipeline.set_options("compression::prune_weights", {"config": config})
        return pipeline
Create a default sparsification pipeline to convert a compressed source model
coremltools/converters/mil/mil/passes/pass_pipeline.py