code: def reference(self):
      binary_op = self.__class__.binary_op_np_func
      unary_op = self.__class__.unary_op_np_func
      [d1, d2, d3, d4] = [
          self.numpy(d) for d in [self.d1, self.d2, self.d3, self.d4]
      ]
      return self._eval(d1, d2, d3, d4, binary_op, unary_op)
  
imports: import itertools
  import operator
  import numpy
  import torch
  from .None import benchmark
label_desc: Use image node_id 4 for calling the BroadcastBench obj's underlying member method code with example usage: obj.reference() and returns: self