code: def _reduce_window(
      *args,
      jaxpr,
      consts,
      window_dimensions,
      window_strides,
      padding,
      base_dilation,
      window_dilation,
      _in_avals: Sequence[core.ShapedArray],
      _out_aval: tuple[core.ShapedArray, ...],
  ) -> tuple[TfVal, ...]:
      assert (
          len(consts) == 0
      ), "Reduction computation cannot have constants"
      operands, init_values = util.split_list(args, [len(args) // 2])
  
      if len(operands) != 1 or len(init_values) != 1:
          raise _reduce_error(
              "jax2tf does not support variadic reduce_window"
          )
  
      operand, init_value = operands[0], init_values[0]
      # Infer operation type from jaxpr.
      if (
          len(jaxpr.eqns) != 1
          or len(jaxpr.eqns[0].invars) != 2
          or len(jaxpr.eqns[0].outvars) != 1
          or jaxpr.eqns[0].primitive.name not in ["min", "max", "add"]
      ):
          raise _reduce_error(
              "Reduction function should be either min, max, or add."
          )
  
      computation_name = jaxpr.eqns[0].primitive.name
      result = _reduce_monoid(
          operand,
          window_dimensions=window_dimensions,
          window_strides=window_strides,
          padding=padding,
          base_dilation=base_dilation,
          window_dilation=window_dilation,
          computation_name=computation_name,
          _in_avals=(_in_avals[0],),  # Don't pass init_value.
          _out_aval=_out_aval[0],
      )  # Returns single value.
  
      reduce_fn = {
          "min": tf.minimum,
          "max": tf.maximum,
          "add": tf.add,
      }[computation_name]
      result = reduce_fn(result, init_value)
  
      # The output is expected to be wrapped in a tuple, and since we don't use
      # variadic reductions, this tuple always contains a single element.
      return (result,)
  
imports: from __future__ import annotations
  import builtins
  from collections.abc import Sequence
  import dataclasses
  from functools import partial, wraps
  import math
  import string
  from typing import Any, Callable, Optional
  from jax._src import core
  from jax import lax
  from jax._src.lax import slicing
  from jax._src import dtypes
  from jax._src import util
  from jax.experimental.jax2tf import jax2tf
  import numpy
  import tensorflow
label_desc: Use image node_id 23 for calling a global function with example usage: _reduce_window() and returns: result