code: def testDistanceWithTransformButNoSumOverAxis(self):
      source = np.array(
          [[1, 1], [2, 2], [0, 2], [10, -10]], dtype="float32"
      )
      target = np.array(
          [[0, 0], [0, 2], [1, 3], [3, 3]], dtype="float32"
      )
  
      distance_config = configs.DistanceConfig(
          distance_type="l1",
          reduction=tf.compat.v1.losses.Reduction.NONE,
          transform_fn="softmax",
      )
      distance_tensor = distances.pairwise_distance_wrapper(
          tf.constant(source),
          tf.constant(target),
          distance_config=distance_config,
      )
  
      expected_distance = np.abs(
          self._softmax_func(source) - self._softmax_func(target)
      )
      with self.cached_session() as sess:
          distance = sess.run(distance_tensor)
          self.assertAllClose(distance, expected_distance)
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import neural_structured_learning.configs
  from neural_structured_learning.lib import distances
  import numpy
  import tensorflow
label_desc: Use image node_id 21 for calling the DistancesTest obj's underlying member method code with example usage: obj.testDistanceWithTransformButNoSumOverAxis() without return types