search_batched_parallel
API Definition
search_batched_parallel(queries: numpy.ndarray, final_num_neighbors: int, pre_reorder_num_neighbors:int, leaves_to_search: int, batch_size: int) -> tuple(index, distance)
Function
Perform parallel batch-query search, which is concurrently executed by multiple threads. It adds a new parameter batch_size to the open source algorithm API.
Parameters
Parameter |
Description |
Data Type |
Value Range |
|---|---|---|---|
queries |
Queries in a batch. |
numpy.ndarray |
The value cannot be null. |
final_num_neighbors |
Number of returned results (Top K). |
int |
[1, number_of_base_libraries] |
pre_reorder_num_neighbors |
Number of results saved before reordering. |
int |
[final_num_neighbors, number_of_base_libraries] |
leaves_to_search |
Number of subspaces to be searched. |
int |
[1, num_leaves], where num_leaves indicates the total number of subspaces in the IVF index partition. |
batch_size |
Size of the preferred batch during automatic batching in parallel mode. The default value is 256. |
int |
≥ 1 |
Return Value
Data Type |
Description |
|---|---|
tuple(index, distance) |
index is the numpy.ndarray type data that contains final_num_neighbors base library IDs. distance is the numpy.ndarray type data that contains final_num_neighbors distances. |