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https://github.com/meilisearch/MeiliSearch
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rename the ArroyReader to an ArroyWrapper since it can read and write
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5 changed files with 13 additions and 13 deletions
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@ -21,7 +21,7 @@ use crate::heed_codec::{BEU16StrCodec, FstSetCodec, StrBEU16Codec, StrRefCodec};
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use crate::order_by_map::OrderByMap;
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use crate::proximity::ProximityPrecision;
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use crate::vector::parsed_vectors::RESERVED_VECTORS_FIELD_NAME;
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use crate::vector::{ArroyReader, Embedding, EmbeddingConfig};
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use crate::vector::{ArroyWrapper, Embedding, EmbeddingConfig};
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use crate::{
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default_criteria, CboRoaringBitmapCodec, Criterion, DocumentId, ExternalDocumentsIds,
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FacetDistribution, FieldDistribution, FieldId, FieldIdMapMissingEntry, FieldIdWordCountCodec,
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@ -1615,9 +1615,9 @@ impl Index {
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rtxn: &'a RoTxn<'a>,
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embedder_id: u8,
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quantized: bool,
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) -> impl Iterator<Item = Result<ArroyReader>> + 'a {
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) -> impl Iterator<Item = Result<ArroyWrapper>> + 'a {
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crate::vector::arroy_db_range_for_embedder(embedder_id).map_while(move |k| {
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let reader = ArroyReader::new(self.vector_arroy, k, quantized);
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let reader = ArroyWrapper::new(self.vector_arroy, k, quantized);
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// Here we don't care about the dimensions, but we want to know if we can read
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// in the database or if its medata are missing.
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match reader.dimensions(rtxn) {
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@ -1654,7 +1654,7 @@ impl Index {
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let mut embeddings = Vec::new();
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'vectors: for i in 0..=u8::MAX {
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let reader = ArroyReader::new(
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let reader = ArroyWrapper::new(
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self.vector_arroy,
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embedder_id | (i as u16),
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config.config.quantized(),
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