code: def test_dice_score_nosquare_weights(self):
      with self.cached_session():
          weights = tf.constant(
              [[1, 1, 0, 0]], dtype=tf.float32, name="weights"
          )
          predicted = tf.constant(
              [[0, 10], [10, 0], [10, 0], [10, 0]],
              dtype=tf.float32,
              name="predicted",
          )
          labels = tf.constant(
              [[1, 0, 0, 0]], dtype=tf.int64, name="labels"
          )
          predicted, labels = [
              tf.expand_dims(x, axis=0) for x in (predicted, labels)
          ]
  
          test_loss_func = LossFunction(2, loss_type="Dice_NS")
          one_minus_dice_score = test_loss_func(
              predicted, labels, weight_map=weights
          )
          self.assertAllClose(
              one_minus_dice_score.eval(), 0.0, atol=1e-4
          )
  
imports: from __future__ import absolute_import, print_function
  import numpy
  import tensorflow
  from niftynet.layer.loss_segmentation import LossFunction, labels_to_one_hot
  from tests.niftynet_testcase import NiftyNetTestCase
label_desc: Use image node_id 2 for calling the DiceTestNoSquare obj's underlying member method code with example usage: obj.test_dice_score_nosquare_weights() without return types