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Signed-off-by: Kosuke Morimoto <[email protected]>
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| // | ||
| // Copyright (C) 2019-2023 vdaas.org vald team <[email protected]> | ||
| // | ||
| // 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. | ||
| // | ||
|
|
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| // Package ngt provides implementation of Go API for https://github.com/yahoojapan/NGT | ||
| package main | ||
|
|
||
| import ( | ||
| "context" | ||
| "fmt" | ||
| "os" | ||
| "os/signal" | ||
| "runtime" | ||
| "strings" | ||
| "sync" | ||
| "syscall" | ||
|
|
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| "github.com/vdaas/vald/internal/core/algorithm/ngt" | ||
| "github.com/vdaas/vald/internal/log" | ||
| "gonum.org/v1/hdf5" | ||
| ) | ||
|
|
||
| func main() { | ||
| vectors, _, _ := load("sift-128-euclidean.hdf5") | ||
| n, _ := ngt.New( | ||
| ngt.WithDimension(len(vectors[0])), | ||
| ngt.WithDefaultPoolSize(8), | ||
| ngt.WithObjectType(ngt.Float), | ||
| ngt.WithDistanceType(ngt.L2), | ||
| ) | ||
| pid := os.Getpid() | ||
|
|
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| log.Infof("# of vectors: %v", len(vectors)) | ||
| output := func(header string) { | ||
| status := fmt.Sprintf("/proc/%d/status", pid) | ||
| buf, err := os.ReadFile(status) | ||
| if err != nil { | ||
| log.Fatal(err) | ||
| } | ||
| var vmpeak, vmrss, vmhwm string | ||
| for _, line := range strings.Split(string(buf), "\n") { | ||
| switch { | ||
| case strings.HasPrefix(line, "VmPeak"): | ||
| vmpeak = strings.Fields(line)[1] | ||
| case strings.HasPrefix(line, "VmHWM"): | ||
| vmhwm = strings.Fields(line)[1] | ||
| case strings.HasPrefix(line, "VmRSS"): | ||
| vmrss = strings.Fields(line)[1] | ||
| } | ||
| } | ||
|
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| var m runtime.MemStats | ||
| runtime.ReadMemStats(&m) | ||
| log.Infof("%v\t%v\t%v\t%v\t%v\t%v\t%v\t%v\t%v", header, vmpeak, vmhwm, vmrss, m.Alloc/1024, m.TotalAlloc/1024, m.HeapAlloc/1024, m.HeapSys/1024, m.HeapInuse/1024) | ||
| } | ||
| log.Info(" operation\tVmPeak\tVmHWM\tVmRSS\tAlloc\tTotalAlloc\tHeapAlloc\tHeapSys\tHeapInuse") | ||
| output(" start") | ||
| defer output(" end") | ||
| ctx, cancel := context.WithCancel(context.Background()) | ||
| wg := sync.WaitGroup{} | ||
| wg.Add(1) | ||
| go func() { | ||
| for { | ||
| select { | ||
| case <-ctx.Done(): | ||
| wg.Done() | ||
| return | ||
| default: | ||
| ids := make([]uint, len(vectors)) | ||
| for i, vector := range vectors { | ||
| id, err := n.Insert(vector) | ||
| if err != nil { | ||
| log.Fatal(err) | ||
| } | ||
| ids[i] = id | ||
| } | ||
| output(" insert") | ||
|
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| if err := n.CreateIndex(8); err != nil { | ||
| log.Fatal(err) | ||
| } | ||
| output("create index") | ||
|
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| for _, id := range ids { | ||
| if err := n.Remove(id); err != nil { | ||
| log.Fatal(err) | ||
| } | ||
| } | ||
| output(" remove") | ||
| } | ||
| } | ||
| }() | ||
|
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| ch := make(chan os.Signal) | ||
| signal.Notify(ch, os.Interrupt, syscall.SIGTERM) | ||
|
|
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| <-ch | ||
| cancel() | ||
|
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| wg.Wait() | ||
| } | ||
|
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| // load function loads training and test vector from hdf file. The size of ids is same to the number of training data. | ||
| // Each id, which is an element of ids, will be set a random number. | ||
| func load(path string) (train, test [][]float32, err error) { | ||
| var f *hdf5.File | ||
| f, err = hdf5.OpenFile(path, hdf5.F_ACC_RDONLY) | ||
| if err != nil { | ||
| return nil, nil, err | ||
| } | ||
| defer f.Close() | ||
|
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| // readFn function reads vectors of the hierarchy with the given the name. | ||
| readFn := func(name string) ([][]float32, error) { | ||
| // Opens and returns a named Dataset. | ||
| // The returned dataset must be closed by the user when it is no longer needed. | ||
| d, err := f.OpenDataset(name) | ||
| if err != nil { | ||
| return nil, err | ||
| } | ||
| defer d.Close() | ||
|
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| // Space returns an identifier for a copy of the dataspace for a dataset. | ||
| sp := d.Space() | ||
| defer sp.Close() | ||
|
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| // SimpleExtentDims returns dataspace dimension size and maximum size. | ||
| dims, _, _ := sp.SimpleExtentDims() | ||
| row, dim := int(dims[0]), int(dims[1]) | ||
|
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| // Gets the stored vector. All are represented as one-dimensional arrays. | ||
| // The type of the slice depends on your dataset. | ||
| // For fashion-mnist-784-euclidean.hdf5, the datatype is float32. | ||
| vec := make([]float32, sp.SimpleExtentNPoints()) | ||
| if err := d.Read(&vec); err != nil { | ||
| return nil, err | ||
| } | ||
|
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| // Converts a one-dimensional array to a two-dimensional array. | ||
| // Use the `dim` variable as a separator. | ||
| vecs := make([][]float32, row) | ||
| for i := 0; i < row; i++ { | ||
| vecs[i] = make([]float32, dim) | ||
| for j := 0; j < dim; j++ { | ||
| vecs[i][j] = float32(vec[i*dim+j]) | ||
| } | ||
| } | ||
|
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| return vecs, nil | ||
| } | ||
|
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| // Gets vector of `train` hierarchy. | ||
| train, err = readFn("train") | ||
| if err != nil { | ||
| return nil, nil, err | ||
| } | ||
|
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| // Gets vector of `test` hierarchy. | ||
| test, err = readFn("test") | ||
| if err != nil { | ||
| return nil, nil, err | ||
| } | ||
|
|
||
| return | ||
| } |
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