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Functions | |
| cumlError_t | knn_search (const cumlHandle_t handle, float **input, int *size, int n_params, int D, float *search_items, int n, int64_t *res_I, float *res_D, int k, bool rowMajorIndex, bool rowMajorQuery, int metric_type, float metric_arg, bool expanded) |
| Flat C API function to perform a brute force knn on a series of input arrays and combine the results into a single output array for indexes and distances. More... | |
Function Documentation
◆ knn_search()
| cumlError_t knn_search | ( | const cumlHandle_t | handle, |
| float ** | input, | ||
| int * | size, | ||
| int | n_params, | ||
| int | D, | ||
| float * | search_items, | ||
| int | n, | ||
| int64_t * | res_I, | ||
| float * | res_D, | ||
| int | k, | ||
| bool | rowMajorIndex, | ||
| bool | rowMajorQuery, | ||
| int | metric_type, | ||
| float | metric_arg, | ||
| bool | expanded | ||
| ) |
Flat C API function to perform a brute force knn on a series of input arrays and combine the results into a single output array for indexes and distances.
- Parameters
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[in] handle the cuml handle to use [in] input an array of pointers to the input arrays [in] size an array of sizes of input arrays [in] n_params array size of input and sizes [in] D the dimensionality of the arrays [in] search_items array of items to search of dimensionality D [in] n number of rows in search_items [out] res_I the resulting index array of size n * k [out] res_D the resulting distance array of size n * k [in] k the number of nearest neighbors to return [in] rowMajorIndex is the index array in row major layout? [in] rowMajorQuery is the query array in row major layout? [in] metric_type the type of distance metric to use. This corresponds to the value in the cuvs::distance::DistanceType enum. Default is Euclidean (L2). [in] metric_arg the value of pfor Minkowski (l-p) distances. This is ignored if the metric_type is not Minkowski.[in] expanded should lp-based distances be returned in their expanded form (e.g., without raising to the 1/p power).
