def METHOD_NAME(values, axis=-1, direction='ASCENDING', stable=False, name=None):
  """Returns the indices of a tensor that give its sorted order along an axis.
  For a 1D tensor, `tf.gather(values, tf.argsort(values))` is equivalent to
  `tf.sort(values)`. For higher dimensions, the output has the same shape as
  `values`, but along the given axis, values represent the index of the sorted
  element in that slice of the tensor at the given position.
  Usage:
  ```python
  import tensorflow as tf
  a = [1, 10, 26.9, 2.8, 166.32, 62.3]
  b = tf.argsort(a,axis=-1,direction='ASCENDING',stable=False,name=None)
  c = tf.keras.backend.eval(b)
  # Here, c = [0 3 1 2 5 4]
  ```
  Args:
    values: 1-D or higher numeric `Tensor`.
    axis: The axis along which to sort. The default is -1, which sorts the last
      axis.
    direction: The direction in which to sort the values (`'ASCENDING'` or
      `'DESCENDING'`).
    stable: If True, equal elements in the original tensor will not be
      re-ordered in the returned order. Unstable sort is not yet implemented,
      but will eventually be the default for performance reasons. If you require
      a stable order, pass `stable=True` for forwards compatibility.
    name: Optional name for the operation.
  Returns:
    An int32 `Tensor` with the same shape as `values`. The indices that would
        sort each slice of the given `values` along the given `axis`.
  Raises:
    ValueError: If axis is not a constant scalar, or the direction is invalid.
  """
  del stable  # Unused.
  with framework_ops.name_scope(name, 'argsort'):
    return _sort_or_argsort(values, axis, direction, return_argsort=True)