code: def _get_monoid_window_reducer(
      monoid_op: Callable, xs: Sequence[Array]
  ) -> Callable | None:
      if len(xs) != 1:
          return None
      (x,) = xs
      aval = core.get_aval(x)
      if (type(aval) is ConcreteArray) and aval.shape == ():
          if monoid_op is lax.add:
              return aval.val == 0 and _reduce_window_sum
          elif monoid_op is lax.max:
              return (
                  aval.val == lax._get_max_identity(aval.dtype)
                  and _reduce_window_max
              )
          elif monoid_op is lax.min:
              return (
                  aval.val == lax._get_min_identity(aval.dtype)
                  and _reduce_window_min
              )
      return None
  
imports: from __future__ import annotations
  from collections.abc import Sequence
  from functools import partial
  from typing import Callable
  import warnings
  import numpy
  from jax import tree_util
  from jax._src import ad_util
  from jax._src import core
  from jax._src import dispatch
  from jax._src import dtypes
  from jax._src import util
  from jax._src.core import ShapedArray, ConcreteArray
  from jax._src.interpreters import ad
  from jax._src.interpreters import batching
  from jax._src.interpreters import mlir
  from jax._src.lax import lax
  from jax._src.lax import convolution
  from jax._src.lax import slicing
  from jax._src.lib.mlir import ir
  from jax._src.lib.mlir.dialects import hlo
  from jax._src.numpy.ufuncs import logaddexp
  from jax._src.typing import Array
label_desc: Use image node_id 2 for calling a global function with example usage: _get_monoid_window_reducer(monoid_op, xs) and returns: None, None, unknown, unknown, unknown