code: def testTrueNegativesAtThresholds(self, distribution):
      def _metric_fn(x):
          labels = x["labels"]
          predictions = x["predictions"]
          return metrics.true_negatives_at_thresholds(
              labels, predictions, [0.5]
          )
  
      def _expected_fn(num_batches):
          return [[0.0], [1.0], [2.0], [3.0]][num_batches - 1]
  
      self._test_metric(
          distribution, _threshold_dataset_fn, _metric_fn, _expected_fn
      )
  
imports: from absl.testing import parameterized
  from tensorflow.python.data.ops import dataset_ops
  from tensorflow.python.distribute import combinations
  from tensorflow.python.distribute import strategy_combinations
  from tensorflow.python.distribute import strategy_test_lib
  from tensorflow.python.eager import test
  from tensorflow.python.framework import ops
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import metrics
  from tensorflow.python.ops import variables
label_desc: Use image node_id 12 for calling the MetricsV1Test obj's underlying member method code with example usage: obj.testTrueNegativesAtThresholds(distribution) and returns: metrics, list