Examples with FloatVector com.airbnb.aerosolve.core.util.FloatVector used on opensource projects

Example 11 with FloatVector

use of com.airbnb.aerosolve.core.util.FloatVector in project aerosolve by airbnb.

the class MlpModel method save.

public void save(BufferedWriter writer) throws IOException {
    ModelHeader header = new ModelHeader();
    header.setModelType("multilayer_perceptron");
    header.setNumHiddenLayers(numHiddenLayers);
    ArrayList<Integer> nodeNum = new ArrayList<>();
    for (int i = 0; i < numHiddenLayers + 1; i++) {
        // this includes the number of node at the output layer
        nodeNum.add(layerNodeNumber.get(i));
    }
    header.setNumberHiddenNodes(nodeNum);
    long count = 0;
    for (Map.Entry<String, Map<String, FloatVector>> familyMap : inputLayerWeights.entrySet()) {
        count += familyMap.getValue().entrySet().size();
    }
    // number of record for the input layer weights
    header.setNumRecords(count);
    ModelRecord headerRec = new ModelRecord();
    headerRec.setModelHeader(header);
    writer.write(Util.encode(headerRec));
    writer.newLine();
    // save the input layer weight, one record per feature
    for (Map.Entry<String, Map<String, FloatVector>> familyMap : inputLayerWeights.entrySet()) {
        for (Map.Entry<String, FloatVector> feature : familyMap.getValue().entrySet()) {
            ModelRecord record = new ModelRecord();
            record.setFeatureFamily(familyMap.getKey());
            record.setFeatureName(feature.getKey());
            ArrayList<Double> arrayList = new ArrayList<>();
            for (int i = 0; i < feature.getValue().length(); i++) {
                arrayList.add((double) feature.getValue().values[i]);
            }
            record.setWeightVector(arrayList);
            writer.write(Util.encode(record));
            writer.newLine();
        }
    }
    // save the bias for each layer after input layer, one record per layer
    for (int i = 0; i < numHiddenLayers + 1; i++) {
        ArrayList<Double> arrayList = new ArrayList<>();
        FloatVector layerBias = bias.get(i);
        int n = layerBias.length();
        ModelRecord record = new ModelRecord();
        for (int j = 0; j < n; j++) {
            arrayList.add((double) layerBias.get(j));
        }
        record.setWeightVector(arrayList);
        record.setFunctionForm(activationFunction.get(i));
        writer.write(Util.encode(record));
        writer.newLine();
    }
    // save the hiddenLayerWeights, one record per (layer + node)
    for (int i = 0; i < numHiddenLayers; i++) {
        ArrayList<FloatVector> weights = hiddenLayerWeights.get(i);
        for (int j = 0; j < layerNodeNumber.get(i); j++) {
            FloatVector w = weights.get(j);
            ModelRecord record = new ModelRecord();
            ArrayList<Double> arrayList = new ArrayList<>();
            for (int k = 0; k < w.length(); k++) {
                arrayList.add((double) w.get(k));
            }
            record.setWeightVector(arrayList);
            writer.write(Util.encode(record));
            writer.newLine();
        }
    }
    writer.flush();
}

Example 12 with FloatVector

use of com.airbnb.aerosolve.core.util.FloatVector in project aerosolve by airbnb.

the class MaxoutModel method debugScoreItem.

@Override
public float debugScoreItem(FeatureVector combinedItem, StringBuilder builder) {
    Map<String, Map<String, Double>> flatFeatures = Util.flattenFeature(combinedItem);
    FloatVector response = getResponse(flatFeatures);
    FloatVector.MinMaxResult result = response.getMinMaxResult();
    float sum = result.maxValue - result.minValue;
    PriorityQueue<Map.Entry<String, Float>> scores = new PriorityQueue<>(100, new LinearModel.EntryComparator());
    float[] biasWt = bias.weights.getValues();
    float biasScore = biasWt[result.maxIndex] - biasWt[result.minIndex];
    scores.add(new AbstractMap.SimpleEntry<String, Float>("bias = " + biasScore + " <br>\n", biasScore));
    for (Map.Entry<String, Map<String, Double>> featureFamily : flatFeatures.entrySet()) {
        Map<String, WeightVector> familyWeightMap = weightVector.get(featureFamily.getKey());
        if (familyWeightMap == null)
            continue;
        for (Map.Entry<String, Double> feature : featureFamily.getValue().entrySet()) {
            WeightVector weightVec = familyWeightMap.get(feature.getKey());
            if (weightVec == null)
                continue;
            float val = feature.getValue().floatValue();
            float[] wt = weightVec.weights.getValues();
            float p = wt[result.maxIndex] * weightVec.scale;
            float n = wt[result.minIndex] * weightVec.scale;
            float subscore = val * (p - n);
            String str = featureFamily.getKey() + ":" + feature.getKey() + "=" + val + " * (" + p + " - " + n + ") = " + subscore + "<br>\n";
            scores.add(new AbstractMap.SimpleEntry<String, Float>(str, subscore));
        }
    }
    builder.append("Top 15 scores ===>\n");
    if (!scores.isEmpty()) {
        int count = 0;
        float subsum = 0.0f;
        while (!scores.isEmpty()) {
            Map.Entry<String, Float> entry = scores.poll();
            builder.append(entry.getKey());
            float val = entry.getValue();
            subsum += val;
            count = count + 1;
            if (count >= 15) {
                builder.append("Leftover = " + (sum - subsum) + '\n');
                break;
            }
        }
    }
    builder.append("Total = " + sum + '\n');
    return sum;
}

Example 13 with FloatVector

use of com.airbnb.aerosolve.core.util.FloatVector in project aerosolve by airbnb.

the class MaxoutModel method loadInternal.

@Override
protected void loadInternal(ModelHeader header, BufferedReader reader) throws IOException {
    long rows = header.getNumRecords();
    numHidden = header.getNumHidden();
    weightVector = new HashMap<>();
    for (long i = 0; i < rows; i++) {
        String line = reader.readLine();
        ModelRecord record = Util.decodeModel(line);
        String family = record.getFeatureFamily();
        String name = record.getFeatureName();
        Map<String, WeightVector> inner = weightVector.get(family);
        if (inner == null) {
            inner = new HashMap<>();
            weightVector.put(family, inner);
        }
        WeightVector vec = new WeightVector();
        vec.scale = (float) record.getScale();
        vec.weights = new FloatVector(numHidden);
        for (int j = 0; j < numHidden; j++) {
            vec.weights.values[j] = record.getWeightVector().get(j).floatValue();
        }
        inner.put(name, vec);
    }
    Map<String, WeightVector> special = weightVector.get("$SPECIAL");
    assert (special != null);
    bias = special.get("$BIAS");
    assert (bias != null);
}

Example 14 with FloatVector

use of com.airbnb.aerosolve.core.util.FloatVector in project aerosolve by airbnb.

the class LowRankLinearModelTest method testLoad.

@Test
public void testLoad() {
    CharArrayWriter charWriter = new CharArrayWriter();
    BufferedWriter writer = new BufferedWriter(charWriter);
    ModelHeader header = new ModelHeader();
    header.setModelType("low_rank_linear");
    header.setLabelDictionary(makeLabelDictionary());
    Map<String, FloatVector> labelWeightVector = makeLabelWeightVector();
    Map<String, java.util.List<Double>> labelEmbedding = new HashMap<>();
    for (Map.Entry<String, FloatVector> labelRepresentation : labelWeightVector.entrySet()) {
        float[] values = labelRepresentation.getValue().getValues();
        ArrayList<Double> arrayList = new ArrayList<>();
        for (int i = 0; i < 3; i++) {
            arrayList.add((double) values[i]);
        }
        labelEmbedding.put(labelRepresentation.getKey(), arrayList);
    }
    header.setLabelEmbedding(labelEmbedding);
    header.setNumRecords(4);
    ArrayList<Double> ws = new ArrayList<>();
    ws.add(1.0);
    ws.add(0.0);
    ws.add(0.0);
    ModelRecord record1 = new ModelRecord();
    record1.setModelHeader(header);
    ModelRecord record2 = new ModelRecord();
    record2.setFeatureFamily("a");
    record2.setFeatureName("cat");
    record2.setWeightVector(ws);
    ModelRecord record3 = new ModelRecord();
    record3.setFeatureFamily("a");
    record3.setFeatureName("dog");
    record3.setWeightVector(ws);
    ModelRecord record4 = new ModelRecord();
    record4.setFeatureFamily("a");
    record4.setFeatureName("fish");
    record4.setWeightVector(ws);
    ModelRecord record5 = new ModelRecord();
    record5.setFeatureFamily("a");
    record5.setFeatureName("horse");
    record5.setWeightVector(ws);
    try {
        writer.write(Util.encode(record1) + "\n");
        writer.write(Util.encode(record2) + "\n");
        writer.write(Util.encode(record3) + "\n");
        writer.write(Util.encode(record4) + "\n");
        writer.write(Util.encode(record5) + "\n");
        writer.close();
    } catch (IOException e) {
        assertTrue("Could not write", false);
    }
    String serialized = charWriter.toString();
    assertTrue(serialized.length() > 0);
    StringReader strReader = new StringReader(serialized);
    BufferedReader reader = new BufferedReader(strReader);
    FeatureVector animalFv = makeFeatureVector("animal");
    FeatureVector colorFv = makeFeatureVector("color");
    try {
        Optional<AbstractModel> model = ModelFactory.createFromReader(reader);
        assertTrue(model.isPresent());
        ArrayList<MulticlassScoringResult> s1 = model.get().scoreItemMulticlass(animalFv);
        assertEquals(s1.size(), 3);
        assertEquals(0.0f, s1.get(0).score, 3.0f);
        assertEquals(0.0f, s1.get(1).score, 1e-10f);
        assertEquals(0.0f, s1.get(2).score, 1e-10f);
        ArrayList<MulticlassScoringResult> s2 = model.get().scoreItemMulticlass(colorFv);
        assertEquals(s2.size(), 3);
        assertEquals(0.0f, s2.get(0).score, 1e-10f);
        assertEquals(0.0f, s2.get(1).score, 1e-10f);
        assertEquals(0.0f, s2.get(2).score, 1e-10f);
    } catch (IOException e) {
        assertTrue("Could not read", false);
    }
}

Example 15 with FloatVector

use of com.airbnb.aerosolve.core.util.FloatVector in project aerosolve by airbnb.

the class AbstractModel method scoreToProbability.

// Populates a multiclass result probability using softmax over the scores by default.
// Some models might override this if their scores are already probabilities e.g. random forests.
public void scoreToProbability(ArrayList<MulticlassScoringResult> results) {
    FloatVector vec = new FloatVector(results.size());
    for (int i = 0; i < results.size(); i++) {
        vec.values[i] = (float) results.get(i).score;
    }
    vec.softmax();
    for (int i = 0; i < results.size(); i++) {
        results.get(i).probability = vec.values[i];
    }
}