code: def setUp(self):
      num_points = 1000
      num_centers = 2000
      num_dim = 100
      max_k = 5
      # Construct a small number of random points and later tile them.
      points_per_tile = 10
      assert num_points % points_per_tile == 0
      points = np.random.standard_normal(
          [points_per_tile, num_dim]
      ).astype(np.float32)
      # Construct random centers.
      self._centers = np.random.standard_normal(
          [num_centers, num_dim]
      ).astype(np.float32)
  
      # Exhaustively compute expected nearest neighbors.
      def squared_distance(x, y):
          return np.linalg.norm(x - y, ord=2) ** 2
  
      nearest_neighbors = [
          sorted(
              [
                  (squared_distance(point, self._centers[j]), j)
                  for j in range(num_centers)
              ]
          )[:max_k]
          for point in points
      ]
      expected_nearest_neighbor_indices = np.array(
          [[i for _, i in nn] for nn in nearest_neighbors]
      )
      expected_nearest_neighbor_squared_distances = np.array(
          [[dist for dist, _ in nn] for nn in nearest_neighbors]
      )
      # Tile points and expected results to reach requested size (num_points)
      (
          self._points,
          self._expected_nearest_neighbor_indices,
          self._expected_nearest_neighbor_squared_distances,
      ) = (
          np.tile(x, (int(num_points / points_per_tile), 1))
          for x in (
              points,
              expected_nearest_neighbor_indices,
              expected_nearest_neighbor_squared_distances,
          )
      )
  
imports: import numpy
  from tensorflow.python.framework import test_util
  from tensorflow.python.ops import clustering_ops
  from tensorflow.python.platform import test
label_desc: Use image node_id 1 for calling the NearestCentersLargeTest obj's underlying member method code with example usage: obj.setUp() and returns: unknown