class_docstr: Detect the ``reduce_sum`` ---> ``mul/real_div`` pattern than can be mapped to ``reduce_mean``.
  That is, the operation ``reduce_sum/count == reduce_mean``.
  
  `Input graph`
  
  .. code-block::
  
                                  const (scalar)
                                      |
      input ----> reduce_sum ----> mul/real_div -----------> output
  
  
  `Output graph`
  
  .. code-block::
  
      input --------> reduce_mean ---------> output
code: def apply(self, prog):
      for f in prog.functions.values():
          block_changed = True
          while block_changed:
              block_changed = self._fuse_reduce_mean_block(f)
  
file_path: coremltools/coremltools/converters/mil/mil/passes/defs/cleanup/fuse_reduce_mean.py
imports: from coremltools.converters.mil.mil import Builder
  from coremltools.converters.mil.mil.passes.graph_pass import AbstractGraphPass
  from coremltools.converters.mil.mil.passes.helper import _check_child_op_type, _check_var_scalar_value, block_context_manager
  from coremltools.converters.mil.mil.passes.pass_registry import register_pass
  from coremltools.converters.mil.mil.types.symbolic import is_symbolic
label_desc: Use image node_id 1 for calling the fuse_reduce_mean obj's underlying member method code with example usage: obj.apply(prog) without return types