[−][src]Trait finalfusion::embeddings::Quantize

pub trait Quantize<V> {
    fn quantize_using<T, R>(
        &self, 
        n_subquantizers: usize, 
        n_subquantizer_bits: u32, 
        n_iterations: usize, 
        n_attempts: usize, 
        normalize: bool, 
        rng: &mut R
    ) -> Embeddings<V, QuantizedArray>
    where
        T: TrainPQ<f32>,
        R: Rng;

    fn quantize<T>(
        &self, 
        n_subquantizers: usize, 
        n_subquantizer_bits: u32, 
        n_iterations: usize, 
        n_attempts: usize, 
        normalize: bool
    ) -> Embeddings<V, QuantizedArray>
    where
        T: TrainPQ<f32>,
    { ... }
}

Quantizable embedding matrix.

Required methods

fn quantize_using<T, R>(
    &self,
    n_subquantizers: usize,
    n_subquantizer_bits: u32,
    n_iterations: usize,
    n_attempts: usize,
    normalize: bool,
    rng: &mut R
) -> Embeddings<V, QuantizedArray> where
    T: TrainPQ<f32>,
    R: Rng, 

Quantize the embedding matrix using the provided RNG.

This method trains a quantizer for the embedding matrix and then quantizes the matrix using this quantizer.

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Provided methods

fn quantize<T>(
    &self,
    n_subquantizers: usize,
    n_subquantizer_bits: u32,
    n_iterations: usize,
    n_attempts: usize,
    normalize: bool
) -> Embeddings<V, QuantizedArray> where
    T: TrainPQ<f32>, 

Quantize the embedding matrix.

This method trains a quantizer for the embedding matrix and then quantizes the matrix using this quantizer.

The xorshift PRNG is used for picking the initial quantizer centroids.

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Implementors

impl<V, S> Quantize<V> for Embeddings<V, S> where
    V: Vocab,
    S: StorageView, [src]

fn quantize<T>(
    &self,
    n_subquantizers: usize,
    n_subquantizer_bits: u32,
    n_iterations: usize,
    n_attempts: usize,
    normalize: bool
) -> Embeddings<V, QuantizedArray> where
    T: TrainPQ<f32>, [src]

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