mirror of https://github.com/milvus-io/milvus.git
51 lines
1.3 KiB
Go
51 lines
1.3 KiB
Go
package clustering
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import (
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"encoding/binary"
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"math"
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"github.com/milvus-io/milvus-proto/go-api/v2/schemapb"
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"github.com/milvus-io/milvus/pkg/util/distance"
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"github.com/milvus-io/milvus/pkg/util/merr"
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)
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func CalcVectorDistance(dim int64, dataType schemapb.DataType, left []byte, right []float32, metric string) ([]float32, error) {
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switch dataType {
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case schemapb.DataType_FloatVector:
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distance, err := distance.CalcFloatDistance(dim, DeserializeFloatVector(left), right, metric)
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if err != nil {
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return nil, err
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}
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return distance, nil
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// todo support other vector type
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case schemapb.DataType_BinaryVector:
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case schemapb.DataType_Float16Vector:
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case schemapb.DataType_BFloat16Vector:
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default:
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return nil, merr.ErrParameterInvalid
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}
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return nil, nil
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}
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func DeserializeFloatVector(data []byte) []float32 {
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vectorLen := len(data) / 4 // Each float32 occupies 4 bytes
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fv := make([]float32, vectorLen)
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for i := 0; i < vectorLen; i++ {
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bits := binary.LittleEndian.Uint32(data[i*4 : (i+1)*4])
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fv[i] = math.Float32frombits(bits)
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}
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return fv
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}
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func SerializeFloatVector(fv []float32) []byte {
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data := make([]byte, 0, 4*len(fv)) // float32 occupies 4 bytes
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buf := make([]byte, 4)
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for _, f := range fv {
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binary.LittleEndian.PutUint32(buf, math.Float32bits(f))
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data = append(data, buf...)
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}
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return data
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}
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