1 files changed, 0 insertions, 220 deletions
diff --git a/linguistics/src/main/java/com/yahoo/language/sentencepiece/SentencePieceEncoder.java b/linguistics/src/main/java/com/yahoo/language/sentencepiece/SentencePieceEncoder.java
deleted file mode 100644
index b6659ebeaa3..00000000000
--- a/linguistics/src/main/java/com/yahoo/language/sentencepiece/SentencePieceEncoder.java
+++ /dev/null
@@ -1,220 +0,0 @@
-// Copyright Yahoo. Licensed under the terms of the Apache 2.0 license. See LICENSE in the project root.
-package com.yahoo.language.sentencepiece;
-
-import com.google.common.annotations.Beta;
-import com.google.inject.Inject;
-import com.yahoo.language.Language;
-import com.yahoo.language.process.Encoder;
-import com.yahoo.language.process.Segmenter;
-import com.yahoo.tensor.Tensor;
-import com.yahoo.tensor.TensorAddress;
-import com.yahoo.tensor.TensorType;
-
-import java.nio.file.Path;
-import java.util.ArrayList;
-import java.util.Collections;
-import java.util.HashMap;
-import java.util.List;
-import java.util.Map;
-import java.util.stream.Collectors;
-
-/**
- * Integration with https://github.com/google/sentencepiece
- * through http://docs.djl.ai/extensions/sentencepiece/index.html
- *
- * SentencePiece is a language-agnostic tokenizer for neural nets.
- *
- * @author bratseth
- */
-@Beta
-public class SentencePieceEncoder implements Segmenter, Encoder {
-
-    private final Map<Language, Model> models;
-
-    private final SentencePieceAlgorithm algorithm;
-
-    @Inject
-    public SentencePieceEncoder(SentencePieceConfig config) {
-        this(new Builder(config));
-    }
-
-    public SentencePieceEncoder(Builder builder) {
-        algorithm = new SentencePieceAlgorithm(builder.collapseUnknowns, builder.getScoring());
-
-        models = builder.getModels().entrySet()
-                        .stream()
-                        .map(e -> new Model(e.getKey(), e.getValue()))
-                        .collect(Collectors.toUnmodifiableMap(m -> m.language, m -> m));
-        if (models.isEmpty())
-            throw new IllegalArgumentException("SentencePieceEncoder requires at least one model configured");
-    }
-
-    /**
-     * Segments the given text into token segments using the SentencePiece algorithm
-     *
-     * @param rawInput the text to segment. Any sequence of BMP (Unicode-16 the True Unicode) is supported.
-     * @param language the model to use, or Language.UNKNOWN to use the default model if any
-     * @return the list of zero or more tokens resulting from segmenting the input text
-     */
-    @Override
-    public List<String> segment(String rawInput, Language language) {
-        String input = normalize(rawInput);
-        var resultBuilder = new ResultBuilder<List<String>>(new ArrayList<>()) {
-            public void add(int segmentStart, int segmentEnd, SentencePieceAlgorithm.SegmentEnd[] segmentEnds) {
-                result().add(input.substring(segmentStart, segmentEnd));
-            }
-        };
-        segment(input, language, resultBuilder);
-        Collections.reverse(resultBuilder.result());
-        return resultBuilder.result();
-    }
-
-    /**
-     * Segments the given text into token segments using the SentencePiece algorithm and returns the segment ids.
-     *
-     * @param rawInput the text to segment. Any sequence of BMP (Unicode-16 the True Unicode) is supported.
-     * @param language the model to use, or Language.UNKNOWN to use the default model if any
-     * @return the list of zero or more token ids resulting from segmenting the input text
-     */
-    @Override
-    public List<Integer> encode(String rawInput, Language language) {
-        var resultBuilder = new ResultBuilder<List<Integer>>(new ArrayList<>()) {
-            public void add(int segmentStart, int segmentEnd, SentencePieceAlgorithm.SegmentEnd[] segmentEnds) {
-                result().add(segmentEnds[segmentEnd].id);
-            }
-        };
-        segment(normalize(rawInput), language, resultBuilder);
-        Collections.reverse(resultBuilder.result());
-        return resultBuilder.result();
-    }
-
-    /**
-     * <p>Encodes directly to a tensor.</p>
-     *
-     * <p>If the tensor type is indexed 1-d (bound or unbound) this will return a tensor containing the token ids in the order
-     * they were encountered in the text. If the dimension is bound and too large it will be zero padded, if too small
-     * it will be truncated.</p>
-     *
-     * <p>If the tensor type is1-d sparse this will return a tensor containing the token strings as keys and the token
-     * position as value.</p>
-     *
-     * <p>If the tensor is any other type IllegalArgumentException is thrown.</p>
-     */
-    @Override
-    public Tensor encode(String rawInput, Language language, TensorType type) {
-        if (type.dimensions().size() == 1 && type.dimensions().get(0).isIndexed()) {
-            // Build to a list first since we can't reverse a tensor builder
-            List<Integer> values = encode(rawInput, language);
-
-            long maxSize = values.size();
-            if (type.dimensions().get(0).size().isPresent())
-                maxSize = Math.min(maxSize, type.dimensions().get(0).size().get());
-
-            Tensor.Builder builder = Tensor.Builder.of(type);
-            for (int i = 0; i < maxSize; i++)
-                builder.cell(values.get(i), i);
-            return builder.build();
-        }
-        else if (type.dimensions().size() == 1 && type.dimensions().get(0).isMapped()) {
-            // Build to a list first since we can't reverse a tensor builder
-            List<String> values = segment(rawInput, language);
-
-            Tensor.Builder builder = Tensor.Builder.of(type);
-            for (int i = 0; i < values.size(); i++)
-                builder.cell(TensorAddress.ofLabels(values.get(i)), i);
-            return builder.build();
-        }
-        else {
-            throw new IllegalArgumentException("Don't know how to encode with SentencePiece into " + type);
-        }
-    }
-
-    private <RESULTTYPE> void segment(String input, Language language,
-                                      ResultBuilder<RESULTTYPE> resultBuilder) {
-        Model model = resolveFrom(language);
-        algorithm.segment(input, resultBuilder, model);
-    }
-
-    private Model resolveFrom(Language language) {
-        // Disregard language if there is default model
-        if (models.size() == 1 && models.containsKey(Language.UNKNOWN)) return models.get(Language.UNKNOWN);
-        if (models.containsKey(language)) return models.get(language);
-        throw new IllegalArgumentException("No SentencePiece model for language " + language + " is configured");
-    }
-
-    public String normalize(String s) {
-        StringBuilder b = new StringBuilder(s.length() + 1);
-        boolean queuedSpace = true; // Always start by one space
-        for (int i = 0; i < s.length(); i++) {
-            char c = s.charAt(i);
-            if (s.charAt(i) == ' ') {
-                queuedSpace = true;
-            }
-            else {
-                if (queuedSpace) {
-                    b.append(SentencePieceAlgorithm.spaceSymbol);
-                    queuedSpace = false;
-                }
-                b.append(c);
-            }
-        }
-        return b.toString();
-    }
-
-    public static class Builder {
-
-        private final Map<Language, Path> models = new HashMap<>();
-        private boolean collapseUnknowns = true;
-        private Scoring scoring = Scoring.fewestSegments;
-
-        public Builder() {
-        }
-
-        private Builder(SentencePieceConfig config) {
-            collapseUnknowns = config.collapseUnknowns();
-            scoring = config.scoring() == SentencePieceConfig.Scoring.fewestSegments ? Scoring.fewestSegments
-                                                                                     : Scoring.highestScore;
-            for (SentencePieceConfig.Model model : config.model()) {
-                addModel(Language.fromLanguageTag(model.language()), model.path());
-            }
-        }
-
-        public void addModel(Language language, Path model) {
-            models.put(language, model);
-        }
-
-        /**
-         * Adds the model that will be used if the language is unknown, OR only one model is specified.
-         * The same as addModel(Language.UNKNOWN, model).
-         */
-        public Builder addDefaultModel(Path model) {
-            addModel(Language.UNKNOWN, model);
-            return this;
-        }
-        public Map<Language, Path> getModels() { return models; }
-
-        /**
-         * Sets whether consecutive unknown character should be collapsed into one large unknown token (default)
-         * or be returned as single character tokens.
-         */
-        public Builder setCollapseUnknowns(boolean collapseUnknowns) {
-            this.collapseUnknowns = collapseUnknowns;
-            return this;
-        }
-        public boolean getCollapseUnknowns() { return collapseUnknowns; }
-
-        /** Sets the scoring strategy to use when picking a segmentation. Default: fewestSegments. */
-        public Builder setScoring(Scoring scoring) {
-            this.scoring = scoring;
-            return this;
-        }
-        public Scoring getScoring() { return scoring; }
-
-        public SentencePieceEncoder build() {
-            if (models.isEmpty()) throw new IllegalStateException("At least one model must be supplied");
-            return new SentencePieceEncoder(this);
-        }
-
-    }
-
-}