code: def test_positive_distances():
      """Test that the pairwise distances are always positive."""
  
      # Create embeddings very close to each other in [1.0 - 2e-7, 1.0 + 2e-7]
      # This will encourage errors in the computation
      embeddings = 1.0 + 2e-7 * tf.random.uniform(
          [64, 6], dtype=tf.float32
      )
      distances = pairwise_distance(embeddings, squared=False)
      assert np.all(distances >= 0)
  
file_path: addons/tensorflow_addons/losses/tests/metric_test.py
imports: import pytest
  import numpy
  import tensorflow
  from tensorflow_addons.losses.metric_learning import pairwise_distance
label_desc: Use image node_id 2 for calling a global function with example usage: test_positive_distances() without return types