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import pickle
import unittest
import numpy as np
import hnswlib
def get_dist(metric, pt1, pt2):
if metric == 'l2':
return np.sum((pt1-pt2)**2)
elif metric == 'ip':
return 1. - np.sum(np.multiply(pt1, pt2))
elif metric == 'cosine':
return 1. - np.sum(np.multiply(pt1, pt2)) / (np.sum(pt1**2) * np.sum(pt2**2))**.5
def brute_force_distances(metric, items, query_items, k):
dists = np.zeros((query_items.shape[0], items.shape[0]))
for ii in range(items.shape[0]):
for jj in range(query_items.shape[0]):
dists[jj,ii] = get_dist(metric, items[ii, :], query_items[jj, :])
labels = np.argsort(dists, axis=1) # equivalent, but faster: np.argpartition(dists, range(k), axis=1)
dists = np.sort(dists, axis=1) # equivalent, but faster: np.partition(dists, range(k), axis=1)
return labels[:, :k], dists[:, :k]
def check_ann_results(self, metric, items, query_items, k, ann_l, ann_d, err_thresh=0, total_thresh=0, dists_thresh=0):
brute_l, brute_d = brute_force_distances(metric, items, query_items, k)
err_total = 0
for jj in range(query_items.shape[0]):
err = np.sum(np.isin(brute_l[jj, :], ann_l[jj, :], invert=True))
if err > 0:
print(f"Warning: {err} labels are missing from ann results (k={k}, err_thresh={err_thresh})")
if err > err_thresh:
err_total += 1
self.assertLessEqual(err_total, total_thresh, f"Error: knn_query returned incorrect labels for {err_total} items (k={k})")
wrong_dists = np.sum(((brute_d - ann_d)**2.) > 1e-3)
if wrong_dists > 0:
dists_count = brute_d.shape[0]*brute_d.shape[1]
print(f"Warning: {wrong_dists} ann distance values are different from brute-force values (total # of values={dists_count}, dists_thresh={dists_thresh})")
self.assertLessEqual(wrong_dists, dists_thresh, msg=f"Error: {wrong_dists} ann distance values are different from brute-force values")
def test_space_main(self, space, dim):
# Generating sample data
data = np.float32(np.random.random((self.num_elements, dim)))
test_data = np.float32(np.random.random((self.num_test_elements, dim)))
# Declaring index
p = hnswlib.Index(space=space, dim=dim) # possible options are l2, cosine or ip
print(f"Running pickle tests for {p}")
p.num_threads = self.num_threads # by default using all available cores
p0 = pickle.loads(pickle.dumps(p)) # pickle un-initialized Index
p.init_index(max_elements=self.num_elements, ef_construction=self.ef_construction, M=self.M)
p0.init_index(max_elements=self.num_elements, ef_construction=self.ef_construction, M=self.M)
p.ef = self.ef
p0.ef = self.ef
p1 = pickle.loads(pickle.dumps(p)) # pickle Index before adding items
# add items to ann index p,p0,p1
p.add_items(data)
p1.add_items(data)
p0.add_items(data)
p2=pickle.loads(pickle.dumps(p)) # pickle Index before adding items
self.assertTrue(np.allclose(p.get_items(), p0.get_items()), "items for p and p0 must be same")
self.assertTrue(np.allclose(p0.get_items(), p1.get_items()), "items for p0 and p1 must be same")
self.assertTrue(np.allclose(p1.get_items(), p2.get_items()), "items for p1 and p2 must be same")
# Test if returned distances are same
l, d = p.knn_query(test_data, k=self.k)
l0, d0 = p0.knn_query(test_data, k=self.k)
l1, d1 = p1.knn_query(test_data, k=self.k)
l2, d2 = p2.knn_query(test_data, k=self.k)
self.assertLessEqual(np.sum(((d-d0)**2.) > 1e-3), self.dists_err_thresh, msg=f"knn distances returned by p and p0 must match")
self.assertLessEqual(np.sum(((d0-d1)**2.) > 1e-3), self.dists_err_thresh, msg=f"knn distances returned by p0 and p1 must match")
self.assertLessEqual(np.sum(((d1-d2)**2.) > 1e-3), self.dists_err_thresh, msg=f"knn distances returned by p1 and p2 must match")
# check if ann results match brute-force search
# allow for 2 labels to be missing from ann results
check_ann_results(self, space, data, test_data, self.k, l, d,
err_thresh=self.label_err_thresh,
total_thresh=self.item_err_thresh,
dists_thresh=self.dists_err_thresh)
check_ann_results(self, space, data, test_data, self.k, l2, d2,
err_thresh=self.label_err_thresh,
total_thresh=self.item_err_thresh,
dists_thresh=self.dists_err_thresh)
# Check ef parameter value
self.assertEqual(p.ef, self.ef, "incorrect value of p.ef")
self.assertEqual(p0.ef, self.ef, "incorrect value of p0.ef")
self.assertEqual(p2.ef, self.ef, "incorrect value of p2.ef")
self.assertEqual(p1.ef, self.ef, "incorrect value of p1.ef")
# Check M parameter value
self.assertEqual(p.M, self.M, "incorrect value of p.M")
self.assertEqual(p0.M, self.M, "incorrect value of p0.M")
self.assertEqual(p1.M, self.M, "incorrect value of p1.M")
self.assertEqual(p2.M, self.M, "incorrect value of p2.M")
# Check ef_construction parameter value
self.assertEqual(p.ef_construction, self.ef_construction, "incorrect value of p.ef_construction")
self.assertEqual(p0.ef_construction, self.ef_construction, "incorrect value of p0.ef_construction")
self.assertEqual(p1.ef_construction, self.ef_construction, "incorrect value of p1.ef_construction")
self.assertEqual(p2.ef_construction, self.ef_construction, "incorrect value of p2.ef_construction")
class PickleUnitTests(unittest.TestCase):
def setUp(self):
self.ef_construction = 200
self.M = 32
self.ef = 400
self.num_elements = 1000
self.num_test_elements = 100
self.num_threads = 4
self.k = 25
self.label_err_thresh = 5 # max number of missing labels allowed per test item
self.item_err_thresh = 5 # max number of items allowed with incorrect labels
self.dists_err_thresh = 50 # for two matrices, d1 and d2, dists_err_thresh controls max
# number of value pairs that are allowed to be different in d1 and d2
# i.e., number of values that are (d1-d2)**2>1e-3
def test_inner_product_space(self):
test_space_main(self, 'ip', 16)
def test_l2_space(self):
test_space_main(self, 'l2', 53)
def test_cosine_space(self):
test_space_main(self, 'cosine', 32)
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