code: def _generic_reduce_window_batch_rule(
      batched_args,
      batch_dims,
      *,
      jaxpr,
      consts,
      window_dimensions,
      window_strides,
      padding,
      base_dilation,
      window_dilation,
  ):
      num_operands = len(batched_args) // 2
      operands, init_values = util.split_list(
          batched_args, [num_operands]
      )
      operand_bdims, init_value_bdims = util.split_list(
          batch_dims, [num_operands]
      )
  
      if any(init_bdim is not None for init_bdim in init_value_bdims):
          raise NotImplementedError(
              "reduce_window batching is not implemented for "
              "initial values"
          )
  
      size = next(
          x.shape[ax]
          for x, ax in zip(operands, operand_bdims)
          if ax is not None
      )
      operands = [
          batching.bdim_at_front(arg, bdim, size)
          for arg, bdim in zip(operands, operand_bdims)
      ]
      window_dimensions = (1,) + window_dimensions
      window_strides = (1,) + window_strides
      padding = ((0, 0),) + padding
      base_dilation = (1,) + base_dilation
      window_dilation = (1,) + window_dilation
      outs = reduce_window_p.bind(
          *(operands + init_values),
          jaxpr=jaxpr,
          consts=consts,
          window_dimensions=window_dimensions,
          window_strides=window_strides,
          padding=padding,
          base_dilation=base_dilation,
          window_dilation=window_dilation,
      )
      return outs, (0,) * num_operands
  
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 12 for calling a global function with example usage: _generic_reduce_window_batch_rule(batched_args, batch_dims) and returns: outs,  unknown