type MaxSimPackedMatrix struct {
// contains filtered or unexported fields
}Construct it with NewMaxSimPackedMatrixF32.
MaxSim is the late-interaction primitive used by systems such as ColBERT.
It computes the sum of per-query-token maximum cosine similarities across document tokens.
The result is an angular distance: sum(1 - max_cosine).
The MaxSimPackedMatrix struct wraps packed vectors with their metadata.
package main
import (
"fmt"
nk "github.com/ashvardanian/NumKong/golang"
)
func main() {
queryTokens, docTokens, depth := 4, 8, 16
queries := make([]float32, queryTokens*depth)
docs := make([]float32, docTokens*depth)
for i := range queries { queries[i] = float32(i%5) + 1 }
for i := range docs { docs[i] = float32(i%3) + 1 }
// Pack both sides
qPacked := nk.NewMaxSimPackedMatrixF32(queries, queryTokens, depth)
dPacked := nk.NewMaxSimPackedMatrixF32(docs, docTokens, depth)
// Compute MaxSim score
score := nk.MaxSimF32(qPacked, dPacked)
fmt.Println("MaxSim score:", score)
}API
StructMaxSimPackedMatrixMaxSimPackedMatrix holds a set of vectors packed once for MaxSimF32.5
NewMaxSimPackedMatrixF32NewMaxSimPackedMatrixF32 packs vectorsCount float32 vectors of depth dimensions for MaxSimF32.
func NewMaxSimPackedMatrixF32(
vectorsData []float32,
vectorsCount, depth int,
) MaxSimPackedMatrixThe slice vectorsData holds at least vectorsCount * depth values.
BytesBytes returns the packed buffer.
func (p MaxSimPackedMatrix) Bytes() []byteDepthDepth returns the number of dimensions per packed vector.
func (p MaxSimPackedMatrix) Depth() intShapeShape reads the vector count and depth back from the header of the packed buffer.
func (p MaxSimPackedMatrix) Shape() (vectors, depth int)VectorsVectors returns the number of packed vectors.
func (p MaxSimPackedMatrix) Vectors() intFunctions
MaxSimF32MaxSimF32 sums, over the query vectors, the angular distance from each to its nearest document vector.
func MaxSimF32(query, document MaxSimPackedMatrix) float64Both matrices must have the same depth.