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add missing files
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@ -316,7 +316,7 @@ pub struct ProductQuantizer {
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}
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// chunk * centroid_index
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pub struct DistanceLUT(Vec<f32>);
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pub struct QueryLUT(Vec<f32>);
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impl ProductQuantizer {
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pub fn apply_transform(&self, x: &[f32]) -> Vec<f32> {
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@ -366,7 +366,7 @@ impl ProductQuantizer {
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}
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// not particularly performance-sensitive right now; do unbatched
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pub fn preprocess_query(&self, query: &[f32]) -> DistanceLUT {
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pub fn preprocess_query(&self, query: &[f32]) -> QueryLUT {
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let transformed = self.apply_transform(query);
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let n_chunks = self.n_dims / self.n_dims_per_code;
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let n_centroids = self.centroids.len() / self.n_dims;
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@ -382,11 +382,11 @@ impl ProductQuantizer {
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}
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}
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DistanceLUT(lut)
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QueryLUT(lut)
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}
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// compute dot products of query against product-quantized vectors
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pub fn asymmetric_dot_product(&self, query: &DistanceLUT, pq_vectors: &[u8]) -> Vec<i64> {
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pub fn asymmetric_dot_product(&self, query: &QueryLUT, pq_vectors: &[u8]) -> Vec<i64> {
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let n_chunks = self.n_dims / self.n_dims_per_code;
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let n_vectors = pq_vectors.len() / n_chunks;
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let mut scores = vec![0.0; n_vectors];
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@ -1,5 +1,5 @@
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{
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"backend_url": "http://localhost:1707/",
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"image_path": "http://localhost:7858/",
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"thumb_path": "http://localhost:7857/"
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}
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"backend_url": "http://localhost:5601/",
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"image_path": "",
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"thumb_path": null
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}
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