code: def squared_pairwise_distance(
      x: tf.Tensor,
      y: tf.Tensor,
      a_min: float = 1e-30,
      a_max: float = 1e30,
  ) -> tf.Tensor:
      """
      TensorFlow pairwise squared Euclidean distance between samples x and y.
  
      Parameters
      ----------
      x
          Batch of instances of shape [Nx, features].
      y
          Batch of instances of shape [Ny, features].
      a_min
          Lower bound to clip distance values.
      a_max
          Upper bound to clip distance values.
  
      Returns
      -------
      Pairwise squared Euclidean distance [Nx, Ny].
      """
      x2 = tf.reduce_sum(x**2, axis=-1, keepdims=True)
      y2 = tf.reduce_sum(y**2, axis=-1, keepdims=True)
      dist = (
          x2
          + tf.transpose(y2, (1, 0))
          - 2.0 * x @ tf.transpose(y, (1, 0))
      )
      return tf.clip_by_value(dist, a_min, a_max)
  
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 1 for calling a global function with example usage: squared_pairwise_distance(x, y, a_min, a_max) and returns: tf