ai.h2o.automl.leaderboard.ScoringTimePerRow Maven / Gradle / Ivy

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H2O AutoML
There is a newer version: 3.46.0.6
package ai.h2o.automl.leaderboard;

import hex.Model;
import water.Iced;
import water.Key;
import water.fvec.Frame;

/**
 * A cell computing lazily the average time needed to score a single row with the model.
 * If there is a leaderboard frame available, this average time will be computed by scoring the entire frame.
 * Otherwise, the training frame will be used.
 */
public class ScoringTimePerRow extends Iced implements LeaderboardCell {

    public static final LeaderboardColumn COLUMN = new LeaderboardColumn("predict_time_per_row_ms", "double", "%.6f");

    private final Key _modelId;
    private final Key _leaderboardFrameId;
    private final Key _trainingFrameId;

    private Double _scoringTimePerRowMillis;

    public ScoringTimePerRow(Model model, Frame leaderboardFrame, Frame trainingFrame) {
        this(model._key,
             leaderboardFrame == null ? null : leaderboardFrame._key,
             trainingFrame == null ? null : trainingFrame._key
        );
    }

    public ScoringTimePerRow(Key modelId, Key leaderboardFrameId, Key trainingFrameId) {
        _modelId = modelId;
        _leaderboardFrameId = leaderboardFrameId;
        _trainingFrameId = trainingFrameId;
    }

    @Override
    public LeaderboardColumn getColumn() {
        return COLUMN;
    }

    @Override
    public Key getModelId() {
        return _modelId;
    }

    @Override
    public Double getValue() {
        return _scoringTimePerRowMillis;
    }

    @Override
    public void setValue(Double value) {
        _scoringTimePerRowMillis = value;
    }

    @Override
    public boolean isNA() {
        return getValue() == null || getValue() < 0;
    }

    @Override
    public Double fetch() {
        if (getValue() == null) {
            try {
                Model model = _modelId.get();
                Frame scoringFrame = _leaderboardFrameId != null ? _leaderboardFrameId.get()
                                : _trainingFrameId != null ? _trainingFrameId.get()
                                : null;
                if (scoringFrame != null) {
                    long nrows = scoringFrame.numRows();
                    long start = System.nanoTime();
                    model.score(scoringFrame).delete();
                    long stop = System.nanoTime();
                    setValue((stop-start)/nrows/1e6);
                } else {
                    setValue(-1d);
                }
            } catch (Exception e) {
                setValue(-1d);
            }
        }
        return getValue();
    }
}