code: def _dynamic_update_slice(
      operand,
      update,
      *start_indices,
      _in_avals: Sequence[core.ShapedArray],
      _out_aval: core.ShapedArray,
  ):
      start_indices = tf.stack(start_indices)
  
      op_shape = jax2tf._eval_shape(_in_avals[0].shape)
      op_size = tf.size(operand)
      update_shape_tf = jax2tf._eval_shape(_in_avals[1].shape)
  
      start_indices = _clip(op_shape, start_indices, update_shape_tf)
      end_indices = tf.add(start_indices, update_shape_tf)
  
      # Get the cells to update in `operand` as an array of ids.
      id_tensor = tf.reshape(tf.range(op_size), op_shape)
      scattered_indices = tf.strided_slice(
          id_tensor, start_indices, end_indices
      )
  
      # Create an array containing updates at scattered_indices and zeros otherwise.
      flat_indices = tf.expand_dims(
          tf.nest.flatten(scattered_indices), -1
      )
      flat_update = tf.nest.flatten(update)
      update = tf.scatter_nd(flat_indices, flat_update, (op_size,))
      update = tf.reshape(update, op_shape)
  
      # Create a bool mask that is True only where `operand` should be updated.
      update_mask = tf.ones_like(flat_update, dtype=tf.bool)
      update_mask = tf.scatter_nd(flat_indices, update_mask, (op_size,))
      update_mask = tf.reshape(update_mask, op_shape)
  
      # Use the mask to only update `operand` with `update`.
      return tf.where(update_mask, update, operand)
  
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 37 for calling a global function with example usage: _dynamic_update_slice(operand, update) and returns: tf