code: def unique_inverse(
      x: Union[tf.Tensor, tf.Variable],
      /,
      *,
      axis: Optional[int] = None,
  ) -> Tuple[
      Union[tf.Tensor, tf.Variable], Union[tf.Tensor, tf.Variable]
  ]:
      Results = namedtuple("Results", ["values", "inverse_indices"])
      if axis is None:
          x = tf.reshape(x, shape=(-1,))
          axis = 0
  
      flat_tensor = tf.reshape(x, -1)
      values = tf.unique(tf.sort(flat_tensor))[0]
      values = tf.cast(values, dtype=x.dtype)
  
      values_list = values.numpy().tolist()
      inverse_indices = [
          values_list.index(val) for val in flat_tensor.numpy().tolist()
      ]
      inverse_indices = tf.reshape(
          tf.convert_to_tensor(inverse_indices), x.shape
      )
      inverse_indices = tf.cast(inverse_indices, dtype=tf.int64)
      return Results(values, inverse_indices)
  
file_path: ivy/ivy/functional/backends/tensorflow/set.py
imports: import tensorflow
  from typing import Tuple, Union, Optional
  from collections import namedtuple
  from ivy.func_wrapper import with_unsupported_dtypes
  from .None import backend_version
label_desc: Use image node_id 3 for calling a global function with example usage: unique_inverse() and returns: Results