code: def relative_euclidean_distance(
      x: tf.Tensor, y: tf.Tensor, eps: float = 1e-12, axis: int = -1
  ) -> tf.Tensor:
      """
      Relative Euclidean distance.
  
      Parameters
      ----------
      x
          Tensor used in distance computation.
      y
          Tensor used in distance computation.
      eps
          Epsilon added to denominator for numerical stability.
      axis
          Axis used to compute distance.
  
      Returns
      -------
      Tensor with relative Euclidean distance across specified axis.
      """
      denom = tf.concat(
          [
              tf.reshape(tf.norm(x, ord=2, axis=axis), (-1, 1)),
              tf.reshape(tf.norm(y, ord=2, axis=axis), (-1, 1)),
          ],
          axis=1,
      )
      dist = tf.norm(x - y, ord=2, axis=axis) / (
          tf.reduce_min(denom, axis=axis) + eps
      )
      return dist
  
file_path: alibi-detect/alibi_detect/utils/tensorflow/distance.py
imports: import logging
  import numpy
  import tensorflow
  from typing import Callable, Tuple, List, Optional, Union
label_desc: Use image node_id 5 for calling a global function with example usage: relative_euclidean_distance(x, y, eps, axis) and returns: dist