code: def _transpose_with_shape(
      x: TfVal, x_shape: core.Shape, permutation
  ) -> tuple[TfVal, core.Shape]:
      """Computes transposition of x and its shape.
  
      x_shape matches x.shape in the known dimensions, and it has dimension
      polynomials elsewhere, while x.shape has None.
      """
      return tf.transpose(x, perm=permutation), tuple(
          x_shape[i] for i in permutation
      )
  
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 4 for calling a global function with example usage: _transpose_with_shape(x, x_shape, permutation) and returns: tf,  tuple