/
util.go
111 lines (99 loc) · 2.65 KB
/
util.go
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//
// Copyright (C) 2019-2024 vdaas.org vald team <vald@vdaas.org>
//
// Licensed under the Apache License, Version 2.0 (the "License");
// You may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// https://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
//
// Package strategy provides benchmark strategy
package strategy
import (
"context"
"github.com/vdaas/vald/hack/benchmark/internal/assets"
"github.com/vdaas/vald/hack/benchmark/internal/core/algorithm"
"github.com/vdaas/vald/internal/errors"
)
const (
bulkInsertCnt = 1000
)
func wrapErrors(errs []error) (wrapped error) {
for _, err := range errs {
if err != nil {
if wrapped == nil {
wrapped = err
} else {
wrapped = errors.Wrap(wrapped, err.Error())
}
}
}
return
}
func insertAndCreateIndex32(ctx context.Context, c algorithm.Bit32, dataset assets.Dataset) (ids []uint, err error) {
ids = make([]uint, 0, dataset.TrainSize()*bulkInsertCnt)
n := 0
for i := 0; i < bulkInsertCnt; i++ {
train := make([][]float32, 0, dataset.TrainSize()/bulkInsertCnt)
for j := 0; j < len(train); j++ {
v, err := dataset.Train(n)
if err != nil {
n = 0
break
}
train = append(train, v.([]float32))
n++
}
inserted, errs := c.BulkInsert(train)
err = wrapErrors(errs)
if err != nil {
return nil, err
}
ids = append(ids, inserted...)
}
err = c.CreateIndex(uint32((dataset.TrainSize() * bulkInsertCnt) / 100))
if err != nil {
return nil, err
}
return
}
func insertAndCreateIndex64(ctx context.Context, c algorithm.Bit64, dataset assets.Dataset) (ids []uint, err error) {
ids = make([]uint, 0, dataset.TrainSize()*bulkInsertCnt)
n := 0
for i := 0; i < bulkInsertCnt; i++ {
train := make([][]float64, 0, dataset.TrainSize()/bulkInsertCnt)
for j := 0; j < len(train); j++ {
v, err := dataset.Train(n)
if err != nil {
n = 0
break
}
train = append(train, float32To64(v.([]float32)))
n++
}
inserted, errs := c.BulkInsert(train)
err = wrapErrors(errs)
if err != nil {
return nil, err
}
ids = append(ids, inserted...)
}
err = c.CreateIndex(uint32((dataset.TrainSize() * bulkInsertCnt) / 100))
if err != nil {
return nil, err
}
return
}
func float32To64(x []float32) (y []float64) {
y = make([]float64, len(x))
for i, a := range x {
y[i] = float64(a)
}
return y
}