code: def group_reduce(
      l: Iterable[Any],
      key_f=lambda x: x,
      val_f=lambda x: x,
      reducer: Callable[[List[Any]], Any] = None,
  ) -> Iterable[tuple]:
      """Group values by key and then apply reducer on each group"""
  
      # extract key, value pairs
      tuples = to_tuples(l, key_f, val_f)
  
      # we must sort the keys for groupby
      tuples = sorted(tuples, key=operator.itemgetter(0))
      tuples = list(tuples)
      # group by key
      groups = groupby(tuples, key=operator.itemgetter(0))
      # item paert of groups includes whole tuple, separate only the values
      groups = (
          (key, (t1 for t0, t1 in group)) for key, group in groups
      )
      # run reducer on items in each group
      if reducer:
          groups = ((k, reducer(items)) for k, items in groups)
      return groups
  
imports: import math
  import numpy
  import random
  import heapq
  from .None import utils
  from .lv_types import ImageData, PointData
  from collections import OrderedDict
  from itertools import groupby, islice
  import operator
  from typing import Callable, List, Iterable, Any, Sized, Tuple
  from .None import utils
  from .None import tensor_utils
label_desc: Use image node_id 3 for calling a global function with example usage: group_reduce(l, key_f, val_f, reducer) and returns: groups