code: def angular_distance_np(feature):
      """Computes the angular distance matrix in numpy.
      Args:
        feature: 2-D numpy array of size [number of data, feature dimension]
      Returns:
        angular_distances: 2-D numpy array of size
          [number of data, number of data].
      """
  
      # l2-normalize all features
      normed = feature / np.linalg.norm(
          feature, ord=2, axis=1, keepdims=True
      )
      cosine_similarity = normed @ normed.T
      inverse_cos_sim = 1 - cosine_similarity
  
      return inverse_cos_sim
  
file_path: addons/tensorflow_addons/losses/tests/triplet_test.py
imports: import pytest
  import numpy
  import tensorflow
  from tensorflow_addons.losses import triplet
  from tensorflow_addons.utils import test_utils
label_desc: Use image node_id 4 for calling a global function with example usage: angular_distance_np(feature) and returns: inverse_cos_sim