code: def test_floats_60000():
      data = np.fromfile(
          os.path.join(os.getcwd(), "hnsw_data", "floats_60000"),
          dtype=np.dtype("float32"),
      )
      dimension = 40
      distance = EDistance.DotProduct
      data = data.reshape((data.size // dimension, dimension))
      estimator = HnswEstimator(
          distance=distance,
          level_size_decay=2,
          max_neighbors=5,
          search_neighborhood_size=30,
          batch_size=10,
          upper_level_batch_size=10,
          num_exact_candidates=10,
      )
      estimator.fit(data)
      neighbor_distances, neighbor_ids = estimator.kneighbors(
          [data[0]], n_neighbors=20, search_neighborhood_size=40
      )
  
imports: import os
  import numpy
  from catboost.hnsw import HnswEstimator, EDistance
label_desc: Use image node_id 1 for calling a global function with example usage: test_floats_60000() without return types