code: def store_const_to_top(self, match_result):
      top_node = list(match_result._pattern_to_op.values())[0]
      kwargs = dict()
      for pattern, op in match_result._pattern_to_op.items():
          if pattern.name and pattern.type == "Const":
              if tensor_util.MakeNdarray(
                  op.get_attr("value")
              ).shape == (1,):
                  kwargs[pattern.name] = np.asscalar(
                      tensor_util.MakeNdarray(op.get_attr("value"))
                  )
              else:
                  kwargs[pattern.name] = np.squeeze(
                      tensor_util.MakeNdarray(op.get_attr("value"))
                  )
      if hasattr(top_node, "kwargs"):
          top_node.kwargs.update(kwargs)
      else:
          top_node.kwargs = kwargs
  
imports: from __future__ import division
  from __future__ import print_function
  import numpy
  import tensorflow
  from tensorflow.python.framework import tensor_util
  from tensorflow.core.framework import attr_value_pb2
  import sys
  from mmdnn.conversion.tensorflow.tensorflow_graph import *
  import mmdnn.conversion.common.IR.graph_pb2
  from mmdnn.conversion.rewriter.graph_matcher import *
  from mmdnn.conversion.common.DataStructure import *
  from tensorflow.core.framework.node_def_pb2 import NodeDef
  from mmdnn.conversion.rewriter.rnn_utils import *
label_desc: Use image node_id 5 for calling the UnitRewriterBase obj's underlying member method code with example usage: obj.store_const_to_top(match_result) without return types