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@@ 727-751 (lines=25) @@
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| 724 |
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assert result[1][0].id in ids |
| 725 |
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assert result[1][0].distance <= epsilon |
| 726 |
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|
| 727 |
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def _test_search_distance_tanimoto_flat_index(self, connect, binary_collection): |
| 728 |
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''' |
| 729 |
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target: search binary_collection, and check the result: distance |
| 730 |
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method: compare the return distance value with value computed with Inner product |
| 731 |
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expected: the return distance equals to the computed value |
| 732 |
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''' |
| 733 |
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# from scipy.spatial import distance |
| 734 |
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nprobe = 512 |
| 735 |
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int_vectors, vectors, ids = self.init_binary_data(connect, binary_collection, nb=2) |
| 736 |
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index_type = "FLAT" |
| 737 |
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index_param = { |
| 738 |
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"nlist": 16384, |
| 739 |
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"metric_type": "TANIMOTO" |
| 740 |
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} |
| 741 |
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connect.create_index(binary_collection, binary_field_name, index_param) |
| 742 |
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logging.getLogger().info(connect.get_collection_info(binary_collection)) |
| 743 |
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logging.getLogger().info(connect.get_index_info(binary_collection)) |
| 744 |
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query_int_vectors, query_vecs, tmp_ids = self.init_binary_data(connect, binary_collection, nb=1, insert=False) |
| 745 |
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distance_0 = tanimoto(query_int_vectors[0], int_vectors[0]) |
| 746 |
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distance_1 = tanimoto(query_int_vectors[0], int_vectors[1]) |
| 747 |
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search_param = get_search_param(index_type) |
| 748 |
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status, result = connect.search(binary_collection, top_k, query_vecs, params=search_param) |
| 749 |
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logging.getLogger().info(status) |
| 750 |
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logging.getLogger().info(result) |
| 751 |
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assert abs(result[0][0].distance - min(distance_0, distance_1)) <= epsilon |
| 752 |
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|
| 753 |
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@pytest.mark.timeout(30) |
| 754 |
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def test_search_concurrent_multithreads(self, connect, args): |
|
@@ 671-695 (lines=25) @@
|
| 668 |
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assert result[1][0].distance <= epsilon |
| 669 |
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assert result[1][0].id == ids[1] |
| 670 |
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|
| 671 |
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def _test_search_distance_superstructure_flat_index(self, connect, binary_collection): |
| 672 |
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''' |
| 673 |
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target: search binary_collection, and check the result: distance |
| 674 |
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method: compare the return distance value with value computed with Inner product |
| 675 |
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expected: the return distance equals to the computed value |
| 676 |
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''' |
| 677 |
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# from scipy.spatial import distance |
| 678 |
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nprobe = 512 |
| 679 |
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int_vectors, vectors, ids = self.init_binary_data(connect, binary_collection, nb=2) |
| 680 |
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index_type = "FLAT" |
| 681 |
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index_param = { |
| 682 |
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"nlist": 16384, |
| 683 |
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"metric_type": "SUBSTRUCTURE" |
| 684 |
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} |
| 685 |
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connect.create_index(binary_collection, binary_field_name, index_param) |
| 686 |
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logging.getLogger().info(connect.get_collection_info(binary_collection)) |
| 687 |
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logging.getLogger().info(connect.get_index_info(binary_collection)) |
| 688 |
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query_int_vectors, query_vecs, tmp_ids = self.init_binary_data(connect, binary_collection, nb=1, insert=False) |
| 689 |
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distance_0 = superstructure(query_int_vectors[0], int_vectors[0]) |
| 690 |
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distance_1 = superstructure(query_int_vectors[0], int_vectors[1]) |
| 691 |
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search_param = get_search_param(index_type) |
| 692 |
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status, result = connect.search(binary_collection, top_k, query_vecs, params=search_param) |
| 693 |
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logging.getLogger().info(status) |
| 694 |
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logging.getLogger().info(result) |
| 695 |
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assert len(result[0]) == 0 |
| 696 |
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|
| 697 |
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def _test_search_distance_superstructure_flat_index_B(self, connect, binary_collection): |
| 698 |
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''' |
|
@@ 615-639 (lines=25) @@
|
| 612 |
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res = connect.search(binary_collection, query_entities) |
| 613 |
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assert abs(res[0][0].distance - min(distance_0, distance_1).astype(float)) <= epsilon |
| 614 |
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|
| 615 |
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def _test_search_distance_substructure_flat_index(self, connect, binary_collection): |
| 616 |
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''' |
| 617 |
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target: search binary_collection, and check the result: distance |
| 618 |
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method: compare the return distance value with value computed with Inner product |
| 619 |
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expected: the return distance equals to the computed value |
| 620 |
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''' |
| 621 |
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# from scipy.spatial import distance |
| 622 |
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nprobe = 512 |
| 623 |
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int_vectors, vectors, ids = self.init_binary_data(connect, binary_collection, nb=2) |
| 624 |
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index_type = "FLAT" |
| 625 |
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index_param = { |
| 626 |
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"nlist": 16384, |
| 627 |
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"metric_type": "SUBSTRUCTURE" |
| 628 |
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} |
| 629 |
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connect.create_index(binary_collection, binary_field_name, index_param) |
| 630 |
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logging.getLogger().info(connect.get_collection_info(binary_collection)) |
| 631 |
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logging.getLogger().info(connect.get_index_info(binary_collection)) |
| 632 |
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query_int_vectors, query_vecs, tmp_ids = self.init_binary_data(connect, binary_collection, nb=1, insert=False) |
| 633 |
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distance_0 = substructure(query_int_vectors[0], int_vectors[0]) |
| 634 |
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distance_1 = substructure(query_int_vectors[0], int_vectors[1]) |
| 635 |
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search_param = get_search_param(index_type) |
| 636 |
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status, result = connect.search(binary_collection, top_k, query_vecs, params=search_param) |
| 637 |
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logging.getLogger().info(status) |
| 638 |
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logging.getLogger().info(result) |
| 639 |
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assert len(result[0]) == 0 |
| 640 |
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|
| 641 |
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def _test_search_distance_substructure_flat_index_B(self, connect, binary_collection): |
| 642 |
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''' |
milvus-io /
milvus
