How to use the chunkflow.block_inference_engine.BlockInferenceEngine function in chunkflow

def _inference(self):
        # prepare for inference
        from chunkflow.block_inference_engine import BlockInferenceEngine
        from chunkflow.frameworks.pznet_patch_inference_engine import PZNetPatchInferenceEngine
        patch_engine = PZNetPatchInferenceEngine(self.convnet_path)
        self.block_inference_engine = BlockInferenceEngine(
            patch_inference_engine=patch_engine,
            patch_size=self.patch_size,
            overlap=self.patch_overlap,
            output_key=self.output_key,
            output_channels=self.num_output_channels)


        # inference engine input is a OffsetArray rather than normal numpy array
        # it is actually a numpy array with global offset
        from chunkflow.offset_array import OffsetArray

        input_offset = tuple(s.start for s in self.input_slices)
        input_chunk = OffsetArray(self.image, global_offset=input_offset)
        self.output = self.block_inference_engine(input_chunk)