code: def _gather_with_batch_dim(args: GatherArgs):
      """Implements call to gather with non-empty batch dimensions.
  
      E.g., when doing `jax.vmap(lax.dynamic_slice).
      """
      op_shape = jax2tf._eval_shape(args.op_shape)
      start_indices = _clip(
          op_shape, args.start_indices, args.slice_sizes
      )
      result = tf.map_fn(
          lambda idxs: tf.slice(
              args.operand, begin=idxs, size=args.slice_sizes
          ),
          start_indices,
          fn_output_signature=jax2tf._to_tf_dtype(args.operand.dtype),
      )
      result = tf.reshape(
          result, jax2tf._eval_shape(args.out_aval.shape)
      )
      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 32 for calling a global function with example usage: _gather_with_batch_dim(args) and returns: result