code: def _select_and_gather_add_batching_rule(
      batched_args,
      batch_dims,
      *,
      select_prim,
      window_dimensions,
      window_strides,
      padding,
      base_dilation,
      window_dilation,
  ):
      t, x = batched_args
      t_bdim, x_bdim = batch_dims
      size = next(
          a.shape[bdim]
          for a, bdim in zip(batched_args, batch_dims)
          if bdim is not None
      )
      t = batching.bdim_at_front(t, t_bdim, size)
      x = batching.bdim_at_front(x, x_bdim, size)
      window_dimensions = (1,) + window_dimensions
      window_strides = (1,) + window_strides
      padding = ((0, 0),) + padding
      base_dilation = (1,) + base_dilation
      window_dilation = (1,) + window_dilation
      out = _select_and_gather_add(
          t,
          x,
          select_prim,
          window_dimensions,
          window_strides,
          padding,
          base_dilation,
          window_dilation,
      )
      return (out, 0)
  
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 33 for calling a global function with example usage: _select_and_gather_add_batching_rule(batched_args, batch_dims) and returns: out,  int