org.nd4j.shade.jackson.databind.DeserializationContext Java Examples

@Override
public IntegerDistribution deserialize(JsonParser p, DeserializationContext ctxt) throws IOException {
    JsonNode node = p.getCodec().readTree(p);
    String simpleName = node.get("distribution").asText();

    switch (simpleName) {
        case "BinomialDistribution":
            return new BinomialDistribution(node.get("trials").asInt(), node.get("p").asDouble());
        case "GeometricDistribution":
            return new GeometricDistribution(node.get("p").asDouble());
        case "HypergeometricDistribution":
            return new HypergeometricDistribution(node.get("populationSize").asInt(),
                            node.get("numberOfSuccesses").asInt(), node.get("sampleSize").asInt());
        case "PascalDistribution":
            return new PascalDistribution(node.get("r").asInt(), node.get("p").asDouble());
        case "PoissonDistribution":
            return new PoissonDistribution(node.get("p").asDouble());
        case "UniformIntegerDistribution":
            return new UniformIntegerDistribution(node.get("lower").asInt(), node.get("upper").asInt());
        case "ZipfDistribution":
            return new ZipfDistribution(node.get("numElements").asInt(), node.get("exponent").asDouble());
        default:
            throw new RuntimeException("Unknown or not supported distribution: " + simpleName);
    }
}
 

@Override
public int[] deserialize(JsonParser jp, DeserializationContext deserializationContext) throws IOException, JsonProcessingException {
    JsonNode n = jp.getCodec().readTree(jp);
    if(n.isArray()){
        ArrayNode an = (ArrayNode)n;
        int size = an.size();
        int[] out = new int[size];
        for( int i=0; i<size; i++ ){
            out[i] = an.get(i).asInt();
        }
        return out;
    } else if(n.isNumber()){
        int v = n.asInt();
        return new int[]{v,v};
    } else {
        throw new IllegalStateException("Could not deserialize value: " + n);
    }
}
 

@Override
public DataFormat deserialize(JsonParser jp, DeserializationContext deserializationContext) throws IOException, JsonProcessingException {
    JsonNode node = jp.getCodec().readTree(jp);
    String text = node.textValue();
    switch (text){
        case "NCHW":
            return CNN2DFormat.NCHW;
        case "NHWC":
            return CNN2DFormat.NHWC;
        case "NCW":
            return RNNFormat.NCW;
        case "NWC":
            return RNNFormat.NWC;
        default:
            return null;
    }
}
 

@Override
public INDArray deserialize(JsonParser jp, DeserializationContext deserializationContext) throws IOException {
    JsonNode node = jp.getCodec().readTree(jp);
    JsonNode arr = node.get("dataBuffer");
    int rank = node.get("rankField").asInt();
    int numElements = node.get("numElements").asInt();
    int offset = node.get("offsetField").asInt();
    JsonNode shape = node.get("shapeField");
    JsonNode stride = node.get("strideField");
    String type = node.get("typeField").asText();
    int[] realShape = new int[rank];
    int[] realStride = new int[rank];
    DataBuffer buff = Nd4j.createBuffer(numElements);
    for (int i = 0; i < numElements; i++) {
        buff.put(i, arr.get(i).asDouble());
    }

    String ordering = node.get("orderingField").asText();
    for (int i = 0; i < rank; i++) {
        realShape[i] = shape.get(i).asInt();
        realStride[i] = stride.get(i).asInt();
    }

    INDArray ret = type.equals("real") ? Nd4j.create(buff, realShape, realStride, offset, ordering.charAt(0))
                    : Nd4j.createComplex(buff, realShape, realStride, offset, ordering.charAt(0));
    return ret;
}
 

@Override
public INDArray deserialize(JsonParser jp, DeserializationContext deserializationContext) throws IOException, JsonProcessingException {
    JsonNode node = jp.getCodec().readTree(jp);
    if(node.has("dataBuffer")){
        //Must be legacy format serialization
        JsonNode arr = node.get("dataBuffer");
        int rank = node.get("rankField").asInt();
        int numElements = node.get("numElements").asInt();
        int offset = node.get("offsetField").asInt();
        JsonNode shape = node.get("shapeField");
        JsonNode stride = node.get("strideField");
        int[] shapeArr = new int[rank];
        int[] strideArr = new int[rank];
        DataBuffer buff = Nd4j.createBuffer(numElements);
        for (int i = 0; i < numElements; i++) {
            buff.put(i, arr.get(i).asDouble());
        }

        String ordering = node.get("orderingField").asText();
        for (int i = 0; i < rank; i++) {
            shapeArr[i] = shape.get(i).asInt();
            strideArr[i] = stride.get(i).asInt();
        }

        return Nd4j.create(buff, shapeArr, strideArr, offset, ordering.charAt(0));
    }
    //Standard/new format
    return new NDArrayTextDeSerializer().deserialize(node);
}
 

@Override
public INDArray deserialize(JsonParser jsonParser, DeserializationContext deserializationContext)
                throws IOException {
    JsonNode node = jsonParser.getCodec().readTree(jsonParser);
    if (node == null)
        return null;
    int size = node.size();
    double[] d = new double[size];
    for (int i = 0; i < size; i++) {
        d[i] = node.get(i).asDouble();
    }

    return Nd4j.create(d);
}
 

@Override
public ConfusionMatrix<Integer> deserialize(JsonParser jp, DeserializationContext ctxt)
                throws IOException, JsonProcessingException {
    JsonNode n = jp.getCodec().readTree(jp);

    //Get class names/labels
    ArrayNode classesNode = (ArrayNode) n.get("classes");
    List<Integer> classes = new ArrayList<>();
    for (JsonNode cn : classesNode) {
        classes.add(cn.asInt());
    }

    ConfusionMatrix<Integer> cm = new ConfusionMatrix<>(classes);

    ObjectNode matrix = (ObjectNode) n.get("matrix");
    Iterator<Map.Entry<String, JsonNode>> matrixIter = matrix.fields();
    while (matrixIter.hasNext()) {
        Map.Entry<String, JsonNode> e = matrixIter.next();

        int actualClass = Integer.parseInt(e.getKey());
        ArrayNode an = (ArrayNode) e.getValue();

        ArrayNode innerMultiSetKey = (ArrayNode) an.get(0);
        ArrayNode innerMultiSetCount = (ArrayNode) an.get(1);

        Iterator<JsonNode> iterKey = innerMultiSetKey.iterator();
        Iterator<JsonNode> iterCnt = innerMultiSetCount.iterator();
        while (iterKey.hasNext()) {
            int predictedClass = iterKey.next().asInt();
            int count = iterCnt.next().asInt();

            cm.add(actualClass, predictedClass, count);
        }
    }

    return cm;
}
 

@Override
public DateTimeFieldType deserialize(JsonParser jsonParser, DeserializationContext deserializationContext)
                throws IOException, JsonProcessingException {
    JsonNode node = jsonParser.getCodec().readTree(jsonParser);
    String value = node.get("fieldType").textValue();
    return map.get(value);
}
 

@Override
public TDigest deserialize(JsonParser jp, DeserializationContext d) throws IOException, JsonProcessingException {
    JsonNode node = (JsonNode)jp.getCodec().readTree(jp);
    String field = node.get("digest").asText();
    Base64 b = new Base64();
    byte[] bytes = b.decode(field);
    try(ObjectInputStream ois = new ObjectInputStream(new ByteArrayInputStream(bytes))){
        return (TDigest) ois.readObject();
    } catch (Exception e){
        throw new RuntimeException("Error deserializing TDigest object from JSON", e);
    }
}
 

@Override
public INDArray deserialize(JsonParser jp, DeserializationContext deserializationContext) throws IOException {
    JsonNode node = jp.getCodec().readTree(jp);
    String field = node.get("array").asText();
    INDArray ret = Nd4jBase64.fromBase64(field.toString());
    return ret;

}
 

@Override
public INDArray deserialize(JsonParser jsonParser, DeserializationContext deserializationContext)
                throws IOException {
    JsonNode node = jsonParser.getCodec().readTree(jsonParser);
    if (node == null)
        return null;
    int size = node.size();
    double[] d = new double[size];
    for (int i = 0; i < size; i++) {
        d[i] = node.get(i).asDouble();
    }

    return Nd4j.create(d);
}
 

@Override
public StorageLevel deserialize(JsonParser jsonParser, DeserializationContext deserializationContext)
                throws IOException, JsonProcessingException {
    JsonNode node = jsonParser.getCodec().readTree(jsonParser);
    String value = node.textValue();
    if (value == null || "null".equals(value)) {
        return null;
    }
    return StorageLevel.fromString(value);
}
 

@Override
public DateTimeFieldType deserialize(JsonParser jsonParser, DeserializationContext deserializationContext)
                throws IOException, JsonProcessingException {
    JsonNode node = jsonParser.getCodec().readTree(jsonParser);
    String value = node.get("fieldType").textValue();
    return map.get(value);
}
 

@Override
public TDigest deserialize(JsonParser jp, DeserializationContext d) throws IOException, JsonProcessingException {
    JsonNode node = (JsonNode)jp.getCodec().readTree(jp);
    String field = node.get("digest").asText();
    Base64 b = new Base64();
    byte[] bytes = b.decode(field);
    try(ObjectInputStream ois = new ObjectInputStream(new ByteArrayInputStream(bytes))){
        return (TDigest) ois.readObject();
    } catch (Exception e){
        throw new RuntimeException("Error deserializing TDigest object from JSON", e);
    }
}
 

@Override
public Point deserialize(JsonParser jp, DeserializationContext dc) throws IOException, JsonProcessingException {
    JsonNode n = jp.getCodec().readTree(jp);
    String lbl = n.has("label") ? n.get("label").textValue() : null;
    Double prob = n.has("probability") ? n.get("probability").doubleValue() : null;
    ArrayNode cn = (ArrayNode)n.get("coords");
    double[] pts = new double[cn.size()];
    for( int i=0; i<pts.length; i++ ){
        pts[i] = cn.get(i).doubleValue();
    }
    return new NDPoint(pts, lbl, prob);
}
 

@Override
public AtomicDouble deserialize(JsonParser jsonParser, DeserializationContext deserializationContext) throws IOException, JsonProcessingException {
    JsonNode node = jsonParser.getCodec().readTree(jsonParser);
    double value = node.asDouble();
    return new AtomicDouble(value);
}
 

@Override
public void resolve(DeserializationContext ctxt) throws JsonMappingException {
    ((ResolvableDeserializer) defaultDeserializer).resolve(ctxt);
}
 

@Override
public abstract T deserialize(JsonParser jp, DeserializationContext ctxt)
                throws IOException, JsonProcessingException;
 

@Override
public RealDistribution deserialize(JsonParser p, DeserializationContext ctxt)
                throws IOException, JsonProcessingException {
    JsonNode node = p.getCodec().readTree(p);
    String simpleName = node.get("distribution").asText();

    switch (simpleName) {
        case "BetaDistribution":
            return new BetaDistribution(node.get("alpha").asDouble(), node.get("beta").asDouble());
        case "CauchyDistribution":
            return new CauchyDistribution(node.get("median").asDouble(), node.get("scale").asDouble());
        case "ChiSquaredDistribution":
            return new ChiSquaredDistribution(node.get("dof").asDouble());
        case "ExponentialDistribution":
            return new ExponentialDistribution(node.get("mean").asDouble());
        case "FDistribution":
            return new FDistribution(node.get("numeratorDof").asDouble(), node.get("denominatorDof").asDouble());
        case "GammaDistribution":
            return new GammaDistribution(node.get("shape").asDouble(), node.get("scale").asDouble());
        case "LevyDistribution":
            return new LevyDistribution(node.get("mu").asDouble(), node.get("c").asDouble());
        case "LogNormalDistribution":
            return new LogNormalDistribution(node.get("scale").asDouble(), node.get("shape").asDouble());
        case "NormalDistribution":
            return new NormalDistribution(node.get("mean").asDouble(), node.get("stdev").asDouble());
        case "ParetoDistribution":
            return new ParetoDistribution(node.get("scale").asDouble(), node.get("shape").asDouble());
        case "TDistribution":
            return new TDistribution(node.get("dof").asDouble());
        case "TriangularDistribution":
            return new TriangularDistribution(node.get("a").asDouble(), node.get("b").asDouble(),
                            node.get("c").asDouble());
        case "UniformRealDistribution":
            return new UniformRealDistribution(node.get("lower").asDouble(), node.get("upper").asDouble());
        case "WeibullDistribution":
            return new WeibullDistribution(node.get("alpha").asDouble(), node.get("beta").asDouble());
        case "LogUniformDistribution":
            return new LogUniformDistribution(node.get("min").asDouble(), node.get("max").asDouble());
        default:
            throw new RuntimeException("Unknown or not supported distribution: " + simpleName);
    }


}
 

@Override
public INDArray deserialize(JsonParser jp, DeserializationContext deserializationContext) throws IOException {
    JsonNode node = jp.getCodec().readTree(jp);
    String field = node.get("array").asText();
    return Nd4jBase64.fromBase64(field);
}
 

@Override
public INDArray deserialize(JsonParser jp, DeserializationContext deserializationContext) throws IOException {
    JsonNode n = jp.getCodec().readTree(jp);
    return deserialize(n);
}
 

@Override
public AtomicBoolean deserialize(JsonParser jsonParser, DeserializationContext deserializationContext) throws IOException, JsonProcessingException {
    JsonNode node = jsonParser.getCodec().readTree(jsonParser);
    boolean value = node.asBoolean();
    return new AtomicBoolean(value);
}
 

@Override
public BoundingBox deserialize(JsonParser jp, DeserializationContext dc) throws IOException, JsonProcessingException {
    JsonNode n = jp.getCodec().readTree(jp);
    return DataJsonDeserializer.deserializeBB(n);
}
 

@Override
public AtomicBoolean deserialize(JsonParser jsonParser, DeserializationContext deserializationContext) throws IOException, JsonProcessingException {
    JsonNode node = jsonParser.getCodec().readTree(jsonParser);
    boolean value = node.asBoolean();
    return new AtomicBoolean(value);
}
 

@Override
public AtomicDouble deserialize(JsonParser jsonParser, DeserializationContext deserializationContext) throws IOException, JsonProcessingException {
    JsonNode node = jsonParser.getCodec().readTree(jsonParser);
    double value = node.asDouble();
    return new AtomicDouble(value);
}
 

@Override
public Data deserialize(JsonParser jp, DeserializationContext dc) throws IOException, JsonProcessingException {
    JsonNode n = jp.getCodec().readTree(jp);
    return deserialize(jp, n);
}
 

@Override
public Pipeline deserialize(JsonParser jp, DeserializationContext dc) throws IOException, JsonProcessingException {
    TreeNode tn = jp.readValueAsTree();
    TreeNode n = tn.get("steps");
    String id = null;
    if(tn.get("id") != null){
        id = ((TextNode)tn.get("id")).asText();
    }

    Trigger asyncTrigger = null;        //If present: it's an async pipeline
    if(tn.get(Data.RESERVED_KEY_ASYNC_TRIGGER) != null){
        TreeNode triggerNode = tn.get(Data.RESERVED_KEY_ASYNC_TRIGGER);
        asyncTrigger = jp.getCodec().treeToValue(triggerNode, Trigger.class);
    }

    Pipeline p;
    if(n.isArray()){
        PipelineStep[] steps = jp.getCodec().treeToValue(n, PipelineStep[].class);
        p = new SequencePipeline(Arrays.asList(steps), id);
    } else if(n.isObject()){
        Map<String, GraphStep> map = new LinkedHashMap<>();

        Iterator<String> f = n.fieldNames();
        while(f.hasNext()) {
            String s = f.next();
            TreeNode pn = n.get(s);
            GraphStep step = jp.getCodec().treeToValue(pn, GraphStep.class);
            step.name(s);
            map.put(s, step);
        }

        String outputStep = ((TextNode)tn.get("outputStep")).asText();

        p = new GraphPipeline(map, outputStep, id);
    } else {
        throw new JsonParseException(jp, "Unable to deserialize Pipeline: Invalid JSON/YAML? Pipeline is neither a SequencePipeline or a GraphPipeline");
    }

    if(asyncTrigger != null ){
        return new AsyncPipeline(p, asyncTrigger);
    }

    return p;
}