code: def transpose(array, axes=None):
      """
      Framework-agnostic version of `numpy.transpose` that will work on torch/TensorFlow/Jax tensors as well as NumPy
      arrays.
      """
      if is_numpy_array(array):
          return np.transpose(array, axes=axes)
      elif is_torch_tensor(array):
          return array.T if axes is None else array.permute(*axes)
      elif is_tf_tensor(array):
          import tensorflow as tf
  
          return tf.transpose(array, perm=axes)
      elif is_jax_tensor(array):
          return jnp.transpose(array, axes=axes)
      else:
          raise ValueError(
              f"Type not supported for transpose: {type(array)}."
          )
  
imports: import inspect
  import tempfile
  from collections import OrderedDict, UserDict
  from collections.abc import MutableMapping
  from contextlib import ExitStack, contextmanager
  from dataclasses import fields, is_dataclass
  from enum import Enum
  from typing import Any, ContextManager, Iterable, List, Tuple
  import numpy
  from .import_utils import is_flax_available, is_tf_available, is_torch_available, is_torch_fx_proxy
label_desc: Use image node_id 25 for calling a global function with example usage: transpose(array, axes) and returns: np, unknown, tf, jnp