#include <IndexPQ.h>
Public Types | |
| enum | Search_type_t { ST_PQ, ST_HE, ST_generalized_HE, ST_SDC, ST_polysemous, ST_polysemous_generalize } |
| how to perform the search in search_core More... | |
Public Types inherited from faiss::Index | |
| typedef long | idx_t |
| all indices are this type | |
Public Member Functions | |
| IndexPQ (int d, size_t M, size_t nbits, MetricType metric=METRIC_L2) | |
| virtual void | set_typename () override |
| virtual void | train (idx_t n, const float *x) override |
| virtual void | add (idx_t n, const float *x) override |
| virtual void | search (idx_t n, const float *x, idx_t k, float *distances, idx_t *labels) const override |
| virtual void | reset () override |
| removes all elements from the database. | |
| virtual void | reconstruct_n (idx_t i0, idx_t ni, float *recons) const override |
| virtual void | reconstruct (idx_t key, float *recons) const override |
| void | search_core_polysemous (idx_t n, const float *x, idx_t k, float *distances, idx_t *labels) const |
| void | hamming_distance_histogram (idx_t n, const float *x, idx_t nb, const float *xb, long *dist_histogram) |
| void | hamming_distance_table (idx_t n, const float *x, int32_t *dis) const |
Public Member Functions inherited from faiss::Index | |
| Index (idx_t d=0, MetricType metric=METRIC_INNER_PRODUCT) | |
| virtual void | add_with_ids (idx_t n, const float *x, const long *xids) |
| virtual void | range_search (idx_t n, const float *x, float radius, RangeSearchResult *result) const |
| void | assign (idx_t n, const float *x, idx_t *labels, idx_t k=1) |
| virtual long | remove_ids (const IDSelector &sel) |
| void | compute_residual (const float *x, float *residual, idx_t key) const |
| void | display () const |
| virtual std::string | get_typename () const |
Public Attributes | |
| ProductQuantizer | pq |
| The product quantizer used to encode the vectors. | |
| std::vector< uint8_t > | codes |
| Codes. Size ntotal * pq.code_size. | |
| bool | do_polysemous_training |
| false = standard PQ | |
| PolysemousTraining | polysemous_training |
| parameters used for the polysemous training | |
| Search_type_t | search_type |
| bool | encode_signs |
| int | polysemous_ht |
| Hamming threshold used for polysemy. | |
Public Attributes inherited from faiss::Index | |
| std::string | index_typename |
| int | d |
| vector dimension | |
| idx_t | ntotal |
| total nb of indexed vectors | |
| bool | verbose |
| verbosity level | |
| bool | is_trained |
| set if the Index does not require training, or if training is done already | |
| MetricType | metric_type |
| type of metric this index uses for search | |
Index based on a product quantizer. Stored vectors are approximated by PQ codes.
how to perform the search in search_core
| faiss::IndexPQ::IndexPQ | ( | int | d, |
| size_t | M, | ||
| size_t | nbits, | ||
| MetricType | metric = METRIC_L2 |
||
| ) |
Constructor.
| d | dimensionality of the input vectors |
| M | number of subquantizers |
| nbits | number of bit per subvector index |
| d | dimensionality of the input vectors |
| M | number of subquantizers |
| nbits | number of bit per subvector index |
Definition at line 33 of file IndexPQ.cpp.
|
overridevirtual |
Add n vectors of dimension d to the index.
Vectors are implicitly assigned labels ntotal .. ntotal + n - 1 This function slices the input vectors in chuncks smaller than blocksize_add and calls add_core.
| x | input matrix, size n * d |
Implements faiss::Index.
Definition at line 88 of file IndexPQ.cpp.
| void faiss::IndexPQ::hamming_distance_histogram | ( | idx_t | n, |
| const float * | x, | ||
| idx_t | nb, | ||
| const float * | xb, | ||
| long * | dist_histogram | ||
| ) |
prepare query for a polysemous search, but instead of computing the result, just get the histogram of Hamming distances. May be computed on a provided dataset if xb != NULL
| dist_histogram | (M * nbits + 1) |
Definition at line 394 of file IndexPQ.cpp.
| void faiss::IndexPQ::hamming_distance_table | ( | idx_t | n, |
| const float * | x, | ||
| int32_t * | dis | ||
| ) | const |
compute pairwise distances between queries and database
| n | nb of query vectors |
| x | query vector, size n * d |
| dis | output distances, size n * ntotal |
Definition at line 381 of file IndexPQ.cpp.
|
overridevirtual |
Reconstruct a stored vector (or an approximation if lossy coding)
this function may not be defined for some indexes
| key | id of the vector to reconstruct |
| recons | reconstucted vector (size d) |
Reimplemented from faiss::Index.
Definition at line 114 of file IndexPQ.cpp.
Reconstruct vectors i0 to i0 + ni - 1
this function may not be defined for some indexes
| recons | reconstucted vector (size ni * d) |
Reimplemented from faiss::Index.
Definition at line 104 of file IndexPQ.cpp.
|
overridevirtual |
query n vectors of dimension d to the index.
return at most k vectors. If there are not enough results for a query, the result array is padded with -1s.
| x | input vectors to search, size n * d |
| labels | output labels of the NNs, size n*k |
| distances | output pairwise distances, size n*k |
Implements faiss::Index.
Definition at line 134 of file IndexPQ.cpp.
|
overridevirtual |
Perform training on a representative set of vectors
| n | nb of training vectors |
| x | training vecors, size n * d |
Reimplemented from faiss::Index.
Definition at line 64 of file IndexPQ.cpp.
1.8.5