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package org.deeplearning4j.models.embeddings.learning;

import org.deeplearning4j.models.embeddings.WeightLookupTable;
import org.deeplearning4j.models.embeddings.loader.VectorsConfiguration;
import org.deeplearning4j.models.sequencevectors.interfaces.SequenceIterator;
import org.deeplearning4j.models.sequencevectors.sequence.Sequence;
import org.deeplearning4j.models.sequencevectors.sequence.SequenceElement;
import org.deeplearning4j.models.word2vec.wordstore.VocabCache;
import org.nd4j.linalg.api.ndarray.INDArray;

import java.util.concurrent.atomic.AtomicLong;

/**
 * Implementations of this interface should contain sequence-related learning algorithms. Like dbow or dm.
 *
 * @author [email protected]
 */
public interface SequenceLearningAlgorithm {

    String getCodeName();

    void configure(VocabCache vocabCache, WeightLookupTable lookupTable, VectorsConfiguration configuration);

    void pretrain(SequenceIterator iterator);

    /**
     * This method does training over the sequence of elements passed into it
     *
     * @param sequence
     * @param nextRandom
     * @param learningRate
     * @return average score for this sequence
     */
    double learnSequence(Sequence sequence, AtomicLong nextRandom, double learningRate);

    boolean isEarlyTerminationHit();

    /**
     * This method does training on previously unseen paragraph, and returns inferred vector
     *
     * @param sequence
     * @param nextRandom
     * @param learningRate
     * @return
     */
    INDArray inferSequence(Sequence sequence, long nextRandom, double learningRate, double minLearningRate,
                    int iterations);

    ElementsLearningAlgorithm getElementsLearningAlgorithm();

    void finish();
}