code: def _phi(r: FloatTensorLike, order: int) -> FloatTensorLike:
      """Coordinate-wise nonlinearity used to define the order of the
      interpolation.
  
      See https://en.wikipedia.org/wiki/Polyharmonic_spline for the definition.
  
      Args:
        r: input op.
        order: interpolation order.
  
      Returns:
        `phi_k` evaluated coordinate-wise on `r`, for `k = r`.
      """
  
      # using EPSILON prevents log(0), sqrt0), etc.
      # sqrt(0) is well-defined, but its gradient is not
      with tf.name_scope("phi"):
          if order == 1:
              r = tf.maximum(r, EPSILON)
              r = tf.sqrt(r)
              return r
          elif order == 2:
              return 0.5 * r * tf.math.log(tf.maximum(r, EPSILON))
          elif order == 4:
              return (
                  0.5
                  * tf.square(r)
                  * tf.math.log(tf.maximum(r, EPSILON))
              )
          elif order % 2 == 0:
              r = tf.maximum(r, EPSILON)
              return 0.5 * tf.pow(r, 0.5 * order) * tf.math.log(r)
          else:
              r = tf.maximum(r, EPSILON)
              return tf.pow(r, 0.5 * order)
  
file_path: addons/tensorflow_addons/image/interpolate_spline.py
imports: import tensorflow
  from tensorflow_addons.utils.types import FloatTensorLike, TensorLike
label_desc: Use image node_id 5 for calling a global function with example usage: _phi(r, order) and returns: r, unknown, unknown, unknown, tf