Struct cuvsIvfFlatIndexParams 

#[repr(C)]
pub struct cuvsIvfFlatIndexParams {
    pub metric: cuvsDistanceType,
    pub metric_arg: f32,
    pub add_data_on_build: bool,
    pub n_lists: u32,
    pub kmeans_n_iters: u32,
    pub kmeans_trainset_fraction: f64,
    pub adaptive_centers: bool,
    pub conservative_memory_allocation: bool,
}

@defgroup ivf_flat_c_index_params IVF-Flat index build parameters @{ / /** @brief Supplemental parameters to build IVF-Flat Index

Fields

metric: cuvsDistanceType

Distance type.

metric_arg: f32

The argument used by some distance metrics.

add_data_on_build: bool

Whether to add the dataset content to the index, i.e.:

• true means the index is filled with the dataset vectors and ready to search after calling build.
• false means build only trains the underlying model (e.g. quantizer or clustering), but the index is left empty; you’d need to call extend on the index afterwards to populate it.

n_lists: u32

The number of inverted lists (clusters)

kmeans_n_iters: u32

The number of iterations searching for kmeans centers (index building).

kmeans_trainset_fraction: f64

The fraction of data to use during iterative kmeans building.

adaptive_centers: bool

By default (adaptive_centers = false), the cluster centers are trained in ivf_flat::build, and never modified in ivf_flat::extend. As a result, you may need to retrain the index from scratch after invoking (ivf_flat::extend) a few times with new data, the distribution of which is no longer representative of the original training set.

The alternative behavior (adaptive_centers = true) is to update the cluster centers for new data when it is added. In this case, index.centers() are always exactly the centroids of the data in the corresponding clusters. The drawback of this behavior is that the centroids depend on the order of adding new data (through the classification of the added data); that is, index.centers() “drift” together with the changing distribution of the newly added data.

conservative_memory_allocation: bool

By default, the algorithm allocates more space than necessary for individual clusters (list_data). This allows to amortize the cost of memory allocation and reduce the number of data copies during repeated calls to extend (extending the database).

The alternative is the conservative allocation behavior; when enabled, the algorithm always allocates the minimum amount of memory required to store the given number of records. Set this flag to true if you prefer to use as little GPU memory for the database as possible.

Trait Implementations

impl Clone for cuvsIvfFlatIndexParams

fn clone(&self) -> cuvsIvfFlatIndexParams

Returns a duplicate of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Copy for cuvsIvfFlatIndexParams

impl Debug for cuvsIvfFlatIndexParams

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.