code: def test_exhaustive_random_values(self):
      # Most other tests use small and crafted predictions and labels.
      # This test exhaustively generates many data points.
      data_points = 420
      pb = self.compute_and_check_summary_pb(
          name="foo",
          labels=np.random.uniform(size=(data_points,)) > 0.5,
          predictions=np.float32(
              np.random.uniform(size=(data_points,))
          ),
          num_thresholds=5,
      )
      expected = [
          [218.0, 162.0, 111.0, 55.0, 0.0],
          [202.0, 148.0, 98.0, 51.0, 0.0],
          [0.0, 54.0, 104.0, 151.0, 202.0],
          [0.0, 56.0, 107.0, 163.0, 218.0],
          [0.5190476, 0.5225806, 0.5311005, 0.5188679, 0.0],
          [1.0, 0.7431192, 0.5091743, 0.2522936, 0.0],
      ]
      values = tensor_util.make_ndarray(pb.value[0].tensor)
      self.verify_float_arrays_are_equal(expected, values)
  
imports: import numpy
  import tensorflow
  from tensorboard.compat.proto import summary_pb2
  from tensorboard.plugins.pr_curve import metadata
  from tensorboard.plugins.pr_curve import summary
  from tensorboard.util import tensor_util
  from tensorboard.util import test_util
label_desc: Use image node_id 13 for calling the PrCurveTest obj's underlying member method code with example usage: obj.test_exhaustive_random_values() without return types