code: def _reduce_window_lower(
      reduce_op,
      init_value,
      ctx,
      operand,
      *,
      window_dimensions,
      window_strides,
      padding,
      base_dilation,
      window_dilation,
  ):
      (operand_aval,) = ctx.avals_in
      scalar_aval = operand_aval.update(shape=())
  
      return mlir.reduce_window(
          ctx,
          reducer_name=f"reduce_window_{scalar_aval.dtype}_reducer",
          reducer_body=lambda reducer: [reduce_op(*reducer.arguments)],
          operands=[operand],
          init_values=[
              mlir.full_like_aval(
                  ctx, init_value(scalar_aval.dtype), scalar_aval
              )
          ],
          init_values_avals=[scalar_aval],
          out_avals=ctx.avals_out,
          window_dimensions=window_dimensions,
          window_strides=window_strides,
          base_dilation=base_dilation,
          window_dilation=window_dilation,
          padding=padding,
      )
  
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 20 for calling a global function with example usage: _reduce_window_lower(reduce_op, init_value, ctx, operand) and returns: mlir