code: def _dynamic_slice(
      operand,
      *start_indices,
      slice_sizes: core.Shape,
      _in_avals: Sequence[core.ShapedArray],
      _out_aval: core.ShapedArray,
  ):
      start_indices = tf.stack(start_indices)
      slice_sizes_tf = jax2tf._eval_shape(slice_sizes)
  
      operand_shape = jax2tf._eval_shape(_in_avals[0].shape)
      start_indices = _clip(
          operand_shape, start_indices, slice_sizes_tf
      )
      return tf.slice(operand, start_indices, size=slice_sizes_tf)
  
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 36 for calling a global function with example usage: _dynamic_slice(operand) and returns: tf