Struct faiss::IndexResidualQuantizer

struct faiss::IndexResidualQuantizer : public faiss::IndexAdditiveQuantizer

Index based on a residual quantizer. Stored vectors are approximated by residual quantization codes. Can also be used as a codec

Public Types

using Search_type_t = AdditiveQuantizer::Search_type_t
using idx_t = int64_t

all indices are this type

using component_t = float
using distance_t = float

Public Functions

IndexResidualQuantizer(int d, size_t M, size_t nbits, MetricType metric = METRIC_L2, Search_type_t search_type = AdditiveQuantizer::ST_decompress)

Constructor.

Parameters
  • 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

IndexResidualQuantizer(int d, const std::vector<size_t> &nbits, MetricType metric = METRIC_L2, Search_type_t search_type = AdditiveQuantizer::ST_decompress)
IndexResidualQuantizer()
virtual void train(idx_t n, const float *x) override

Perform training on a representative set of vectors

Parameters
  • n – nb of training vectors

  • x – training vecors, size n * d

virtual void search(idx_t n, const float *x, idx_t k, float *distances, idx_t *labels) const override

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.

Parameters
  • x – input vectors to search, size n * d

  • labels – output labels of the NNs, size n*k

  • distances – output pairwise distances, size n*k

virtual void reset() override

removes all elements from the database.

virtual void add(idx_t n, const float *x) override

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 chunks smaller than blocksize_add and calls add_core.

Parameters

x – input matrix, size n * d

virtual size_t sa_code_size() const override

size of the produced codes in bytes

virtual void sa_encode(idx_t n, const float *x, uint8_t *bytes) const override

encode a set of vectors

Parameters
  • n – number of vectors

  • x – input vectors, size n * d

  • bytes – output encoded vectors, size n * sa_code_size()

virtual void sa_decode(idx_t n, const uint8_t *bytes, float *x) const override

encode a set of vectors

Parameters
  • n – number of vectors

  • bytes – input encoded vectors, size n * sa_code_size()

  • x – output vectors, size n * d

virtual void add_with_ids(idx_t n, const float *x, const idx_t *xids)

Same as add, but stores xids instead of sequential ids.

The default implementation fails with an assertion, as it is not supported by all indexes.

Parameters

xids – if non-null, ids to store for the vectors (size n)

virtual void range_search(idx_t n, const float *x, float radius, RangeSearchResult *result) const

query n vectors of dimension d to the index.

return all vectors with distance < radius. Note that many indexes do not implement the range_search (only the k-NN search is mandatory).

Parameters
  • x – input vectors to search, size n * d

  • radius – search radius

  • result – result table

virtual void assign(idx_t n, const float *x, idx_t *labels, idx_t k = 1) const

return the indexes of the k vectors closest to the query x.

This function is identical as search but only return labels of neighbors.

Parameters
  • x – input vectors to search, size n * d

  • labels – output labels of the NNs, size n*k

virtual size_t remove_ids(const IDSelector &sel)

removes IDs from the index. Not supported by all indexes. Returns the number of elements removed.

virtual void reconstruct(idx_t key, float *recons) const

Reconstruct a stored vector (or an approximation if lossy coding)

this function may not be defined for some indexes

Parameters
  • key – id of the vector to reconstruct

  • recons – reconstucted vector (size d)

virtual void reconstruct_n(idx_t i0, idx_t ni, float *recons) const

Reconstruct vectors i0 to i0 + ni - 1

this function may not be defined for some indexes

Parameters

recons – reconstucted vector (size ni * d)

virtual void search_and_reconstruct(idx_t n, const float *x, idx_t k, float *distances, idx_t *labels, float *recons) const

Similar to search, but also reconstructs the stored vectors (or an approximation in the case of lossy coding) for the search results.

If there are not enough results for a query, the resulting arrays is padded with -1s.

Parameters

recons – reconstructed vectors size (n, k, d)

virtual void compute_residual(const float *x, float *residual, idx_t key) const

Computes a residual vector after indexing encoding.

The residual vector is the difference between a vector and the reconstruction that can be decoded from its representation in the index. The residual can be used for multiple-stage indexing methods, like IndexIVF’s methods.

Parameters
  • x – input vector, size d

  • residual – output residual vector, size d

  • key – encoded index, as returned by search and assign

virtual void compute_residual_n(idx_t n, const float *xs, float *residuals, const idx_t *keys) const

Computes a residual vector after indexing encoding (batch form). Equivalent to calling compute_residual for each vector.

The residual vector is the difference between a vector and the reconstruction that can be decoded from its representation in the index. The residual can be used for multiple-stage indexing methods, like IndexIVF’s methods.

Parameters
  • n – number of vectors

  • xs – input vectors, size (n x d)

  • residuals – output residual vectors, size (n x d)

  • keys – encoded index, as returned by search and assign

virtual DistanceComputer *get_distance_computer() const

Get a DistanceComputer (defined in AuxIndexStructures) object for this kind of index.

DistanceComputer is implemented for indexes that support random access of their vectors.

Public Members

ResidualQuantizer rq

The residual quantizer used to encode the vectors.

AdditiveQuantizer *aq
size_t code_size

size of residual quantizer codes + norms

std::vector<uint8_t> codes

Codes. Size ntotal * rq.code_size.

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

float metric_arg

argument of the metric type