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| Original file line number | Diff line number | Diff line change |
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| // Copyright 2024 gorse Project Authors | ||
| // | ||
| // 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 | ||
| // | ||
| // http://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 search | ||
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| import ( | ||
| "github.com/samber/lo" | ||
| ) | ||
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| type Index interface { | ||
| Add(v []float32) (int, error) | ||
| SearchIndex(q, k int, prune0 bool) ([]lo.Tuple2[int, float32], error) | ||
| SearchVector(q []float32, k int, prune0 bool) ([]lo.Tuple2[int, float32], error) | ||
| } |
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| Original file line number | Diff line number | Diff line change |
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| @@ -0,0 +1,148 @@ | ||
| // Copyright 2024 gorse Project Authors | ||
| // | ||
| // 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 | ||
| // | ||
| // http://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 search | ||
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| import ( | ||
| "bufio" | ||
| mapset "github.com/deckarep/golang-set/v2" | ||
| "github.com/samber/lo" | ||
| "github.com/stretchr/testify/assert" | ||
| "github.com/zhenghaoz/gorse/base/floats" | ||
| "github.com/zhenghaoz/gorse/common/dataset" | ||
| "github.com/zhenghaoz/gorse/common/util" | ||
| "os" | ||
| "path/filepath" | ||
| "strconv" | ||
| "strings" | ||
| "testing" | ||
| ) | ||
|
|
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| const ( | ||
| trainSize = 6000 | ||
| testSize = 1000 | ||
| ) | ||
|
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| func recall(gt, pred []lo.Tuple2[int, float32]) float64 { | ||
| s := mapset.NewSet[int]() | ||
| for _, pair := range gt { | ||
| s.Add(pair.A) | ||
| } | ||
| hit := 0 | ||
| for _, pair := range pred { | ||
| if s.Contains(pair.A) { | ||
| hit++ | ||
| } | ||
| } | ||
| return float64(hit) / float64(len(gt)) | ||
| } | ||
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| type MNIST struct { | ||
| TrainImages [][]float32 | ||
| TrainLabels []uint8 | ||
| TestImages [][]float32 | ||
| TestLabels []uint8 | ||
| } | ||
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| func mnist() (*MNIST, error) { | ||
| // Download and unzip dataset | ||
| path, err := dataset.DownloadAndUnzip("mnist") | ||
| if err != nil { | ||
| return nil, err | ||
| } | ||
| // Open dataset | ||
| m := new(MNIST) | ||
| m.TrainImages, m.TrainLabels, err = m.openFile(filepath.Join(path, "train.libfm")) | ||
| if err != nil { | ||
| return nil, err | ||
| } | ||
| m.TestImages, m.TestLabels, err = m.openFile(filepath.Join(path, "test.libfm")) | ||
| if err != nil { | ||
| return nil, err | ||
| } | ||
| return m, nil | ||
| } | ||
|
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| func (m *MNIST) openFile(path string) ([][]float32, []uint8, error) { | ||
| // Open file | ||
| f, err := os.Open(path) | ||
| if err != nil { | ||
| return nil, nil, err | ||
| } | ||
| defer f.Close() | ||
| // Read data line by line | ||
| var ( | ||
| images [][]float32 | ||
| labels []uint8 | ||
| ) | ||
| scanner := bufio.NewScanner(f) | ||
| for scanner.Scan() { | ||
| line := scanner.Text() | ||
| splits := strings.Split(line, " ") | ||
| // Parse label | ||
| label, err := util.ParseUInt8(splits[0]) | ||
| if err != nil { | ||
| return nil, nil, err | ||
| } | ||
| labels = append(labels, label) | ||
| // Parse image | ||
| image := make([]float32, 784) | ||
| for _, split := range splits[1:] { | ||
| kv := strings.Split(split, ":") | ||
| index, err := strconv.Atoi(kv[0]) | ||
| if err != nil { | ||
| return nil, nil, err | ||
| } | ||
| value, err := util.ParseFloat32(kv[1]) | ||
| if err != nil { | ||
| return nil, nil, err | ||
| } | ||
| image[index] = value | ||
| } | ||
| images = append(images, image) | ||
| } | ||
| return images, labels, nil | ||
| } | ||
|
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| func TestMNIST(t *testing.T) { | ||
| dat, err := mnist() | ||
| assert.NoError(t, err) | ||
|
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| // Create brute-force index | ||
| bf := NewBruteforce(floats.Euclidean) | ||
| for _, image := range dat.TrainImages[:trainSize] { | ||
| _, err := bf.Add(image) | ||
| assert.NoError(t, err) | ||
| } | ||
|
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| // Create HNSW index | ||
| hnsw := NewHNSW(floats.Euclidean) | ||
| for _, image := range dat.TrainImages[:trainSize] { | ||
| _, err := hnsw.Add(image) | ||
| assert.NoError(t, err) | ||
| } | ||
|
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| // Test search | ||
| r := 0.0 | ||
| for _, image := range dat.TestImages[:testSize] { | ||
| gt, err := bf.SearchVector(image, 100, false) | ||
| assert.NoError(t, err) | ||
| assert.Len(t, gt, 100) | ||
| scores, err := hnsw.SearchVector(image, 100, false) | ||
| assert.NoError(t, err) | ||
| assert.Len(t, scores, 100) | ||
| r += recall(gt, scores) | ||
| } | ||
| assert.Greater(t, r, 0.99) | ||
| } |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,90 @@ | ||
| // Copyright 2024 gorse Project Authors | ||
| // | ||
| // 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 | ||
| // | ||
| // http://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 search | ||
|
|
||
| import ( | ||
| "github.com/juju/errors" | ||
| "github.com/samber/lo" | ||
| "github.com/zhenghaoz/gorse/base/heap" | ||
| ) | ||
|
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| // Bruteforce is a naive implementation of vector index. | ||
| type Bruteforce[T any] struct { | ||
| distanceFunc func(a, b []T) float32 | ||
| dimension int | ||
| vectors [][]T | ||
| } | ||
|
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| func NewBruteforce[T any](distanceFunc func(a, b []T) float32) *Bruteforce[T] { | ||
| return &Bruteforce[T]{distanceFunc: distanceFunc} | ||
| } | ||
|
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| func (b *Bruteforce[T]) Add(v []T) (int, error) { | ||
| // Check dimension | ||
| if b.dimension == 0 { | ||
| b.dimension = len(v) | ||
| } else if b.dimension != len(v) { | ||
| return 0, errors.Errorf("dimension mismatch: %v != %v", b.dimension, len(v)) | ||
| } | ||
| // Add vector | ||
| b.vectors = append(b.vectors, v) | ||
| return len(b.vectors) - 1, nil | ||
| } | ||
|
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| func (b *Bruteforce[T]) SearchIndex(q, k int, prune0 bool) ([]lo.Tuple2[int, float32], error) { | ||
| // Check index | ||
| if q < 0 || q >= len(b.vectors) { | ||
| return nil, errors.Errorf("index out of range: %v", q) | ||
| } | ||
| // Search | ||
| pq := heap.NewPriorityQueue(true) | ||
| for i, vec := range b.vectors { | ||
| if i != q { | ||
| pq.Push(int32(i), b.distanceFunc(b.vectors[q], vec)) | ||
| if pq.Len() > k { | ||
| pq.Pop() | ||
| } | ||
| } | ||
| } | ||
| pq = pq.Reverse() | ||
| scores := make([]lo.Tuple2[int, float32], 0) | ||
| for pq.Len() > 0 { | ||
| value, score := pq.Pop() | ||
| if !prune0 || score < 0 { | ||
| scores = append(scores, lo.Tuple2[int, float32]{A: int(value), B: score}) | ||
| } | ||
| } | ||
| return scores, nil | ||
| } | ||
|
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| func (b *Bruteforce[T]) SearchVector(q []T, k int, prune0 bool) ([]lo.Tuple2[int, float32], error) { | ||
| // Search | ||
| pq := heap.NewPriorityQueue(true) | ||
| for i, vec := range b.vectors { | ||
| pq.Push(int32(i), b.distanceFunc(q, vec)) | ||
| if pq.Len() > k { | ||
| pq.Pop() | ||
| } | ||
| } | ||
| pq = pq.Reverse() | ||
| scores := make([]lo.Tuple2[int, float32], 0) | ||
| for pq.Len() > 0 { | ||
| value, score := pq.Pop() | ||
| if !prune0 || score < 0 { | ||
| scores = append(scores, lo.Tuple2[int, float32]{A: int(value), B: score}) | ||
| } | ||
| } | ||
| return scores, nil | ||
| } |
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