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/*
 * Copyright (c) "Neo4j"
 * Neo4j Sweden AB [http://neo4j.com]
 *
 * This file is part of Neo4j.
 *
 * Neo4j is free software: you can redistribute it and/or modify
 * it under the terms of the GNU General Public License as published by
 * the Free Software Foundation, either version 3 of the License, or
 * (at your option) any later version.
 *
 * This program is distributed in the hope that it will be useful,
 * but WITHOUT ANY WARRANTY; without even the implied warranty of
 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
 * GNU General Public License for more details.
 *
 * You should have received a copy of the GNU General Public License
 * along with this program.  If not, see .
 */
package org.neo4j.gds.ml.linkmodels.pipeline;

import org.neo4j.gds.core.model.Model;
import org.neo4j.gds.core.model.ModelCatalog;
import org.neo4j.gds.ml.api.TrainingMethod;
import org.neo4j.gds.ml.models.Classifier;
import org.neo4j.gds.ml.pipeline.linkPipeline.LinkPredictionModelInfo;
import org.neo4j.gds.ml.pipeline.linkPipeline.train.LinkPredictionTrainConfig;
import org.neo4j.gds.procedures.pipelines.TrainedLPPipelineModel;

import java.util.List;
import java.util.Map;

public final class LinkPredictionPipelineCompanion {

    public static final String PREDICT_DESCRIPTION = "Predicts relationships for all non-connected node pairs based on a previously trained LinkPrediction model.";
    public static final String ESTIMATE_PREDICT_DESCRIPTION = "Estimates memory for predicting relationships for all non-connected node pairs based on a previously trained LinkPrediction model";

    static final Map>> DEFAULT_PARAM_SPACE = Map.of(
        TrainingMethod.LogisticRegression.toString(), List.of(),
        TrainingMethod.RandomForestClassification.toString(), List.of(),
        TrainingMethod.MLPClassification.toString(), List.of()
    );

    private LinkPredictionPipelineCompanion() {}

    public static Model getTrainedLPPipelineModel(
        ModelCatalog modelCatalog,
        String pipelineName,
        String username
    ) {
        return new TrainedLPPipelineModel(modelCatalog).get(pipelineName, username);
    }
}