Trait faiss::index::Index

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pub trait Index {
Show 14 methods    // Required methods
    fn is_trained(&self) -> bool;
    fn ntotal(&self) -> u64;
    fn d(&self) -> u32;
    fn metric_type(&self) -> MetricType;
    fn add(&mut self, x: &[f32]) -> Result<()>;
    fn add_with_ids(&mut self, x: &[f32], xids: &[Idx]) -> Result<()>;
    fn train(&mut self, x: &[f32]) -> Result<()>;
    fn assign(&mut self, q: &[f32], k: usize) -> Result<AssignSearchResult>;
    fn search(&mut self, q: &[f32], k: usize) -> Result<SearchResult>;
    fn range_search(
        &mut self,
        q: &[f32],
        radius: f32
    ) -> Result<RangeSearchResult>;
    fn reset(&mut self) -> Result<()>;
    fn remove_ids(&mut self, sel: &IdSelector) -> Result<usize>;
    fn verbose(&self) -> bool;
    fn set_verbose(&mut self, value: bool);
}

Expand description

Interface for a Faiss index. Most methods in this trait match the ones in the native library, whereas some others serve as getters to the index’ parameters.

Although all methods appear to be available for all index implementations, some methods may not be supported. For instance, a FlatIndex stores vectors sequentially, and so does not support add_with_ids nor remove_ids. Users are advised to read the Faiss wiki pages in order to understand which index algorithms support which operations.

Required Methods§

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fn is_trained(&self) -> bool

Whether the Index does not require training, or if training is done already

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fn ntotal(&self) -> u64

The total number of vectors indexed

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fn d(&self) -> u32

The dimensionality of the indexed vectors

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fn metric_type(&self) -> MetricType

The metric type assumed by the index

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fn add(&mut self, x: &[f32]) -> Result<()>

Add new data vectors to the index. This assumes a C-contiguous memory slice of vectors, where the total number of vectors is x.len() / d.

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fn add_with_ids(&mut self, x: &[f32], xids: &[Idx]) -> Result<()>

Add new data vectors to the index with IDs. This assumes a C-contiguous memory slice of vectors, where the total number of vectors is x.len() / d. Not all index types may support this operation.

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