[ci] Allows build project with JDK 21

api/src/main/java/ai/djl/modality/Classifications.java

@@ -53,7 +53,7 @@ public class Classifications implements JsonSerializable, Ensembleable<Classific
     @SuppressWarnings("serial")
     protected List<Double> probabilities;
 
-    private int topK;
+    protected int topK;
 
     /**
      * Constructs a {@code Classifications} using a parallel list of classNames and probabilities.

api/src/main/java/ai/djl/modality/cv/output/CategoryMask.java

@@ -43,7 +43,7 @@ public class CategoryMask implements JsonSerializable {
                     .registerTypeAdapter(CategoryMask.class, new SegmentationSerializer())
                     .create();
 
-    private List<String> classes;
+    private transient List<String> classes;
     private int[][] mask;
 
     /**

api/src/main/java/ai/djl/modality/cv/output/DetectedObjects.java

@@ -48,7 +48,7 @@ public DetectedObjects(
             List<String> classNames, List<Double> probabilities, List<BoundingBox> boundingBoxes) {
         super(classNames, probabilities);
         this.boundingBoxes = boundingBoxes;
-        setTopK(Integer.MAX_VALUE);
+        this.topK = Integer.MAX_VALUE;
     }
 
     /** {@inheritDoc} */

api/src/main/java/ai/djl/modality/nlp/Decoder.java

@@ -42,6 +42,7 @@ public abstract class Decoder extends AbstractBlock {
      * @param block the block to be used to decode
      * @param version the version to use for parameter and metadata serialization
      */
+    @SuppressWarnings("this-escape")
     public Decoder(byte version, Block block) {
         super(version);
         this.block = addChildBlock("Block", block);

api/src/main/java/ai/djl/modality/nlp/Encoder.java

@@ -40,6 +40,7 @@ public abstract class Encoder extends AbstractBlock {
      * @param version the version to use for parameter and metadata serialization
      * @param block the encoder block
      */
+    @SuppressWarnings("this-escape")
     public Encoder(byte version, Block block) {
         super(version);
         this.block = addChildBlock("Block", block);

api/src/main/java/ai/djl/modality/nlp/EncoderDecoder.java

@@ -46,6 +46,7 @@ public class EncoderDecoder extends AbstractBlock {
      * @param encoder the {@link Encoder}
      * @param decoder the {@link Decoder}
      */
+    @SuppressWarnings("this-escape")
     public EncoderDecoder(Encoder encoder, Decoder decoder) {
         super(VERSION);
         this.encoder = addChildBlock("Encoder", encoder);

api/src/main/java/ai/djl/modality/nlp/embedding/TrainableTextEmbedding.java

@@ -38,6 +38,7 @@ public class TrainableTextEmbedding extends AbstractBlock implements TextEmbeddi
      *
      * @param wordEmbedding the word embedding to embed each word
      */
+    @SuppressWarnings("this-escape")
     public TrainableTextEmbedding(TrainableWordEmbedding wordEmbedding) {
         this.trainableWordEmbedding = addChildBlock("trainableWordEmbedding", wordEmbedding);
     }

api/src/main/java/ai/djl/ndarray/BaseNDManager.java

@@ -53,6 +53,7 @@ public abstract class BaseNDManager implements NDManager {
     protected AtomicBoolean closed = new AtomicBoolean(false);
     protected AtomicBoolean capped = new AtomicBoolean(false);
 
+    @SuppressWarnings("this-escape")
     protected BaseNDManager(NDManager parent, Device device) {
         this.parent = parent;
         this.device = device == null ? defaultDevice() : device;

api/src/main/java/ai/djl/ndarray/NDScope.java

@@ -30,6 +30,7 @@ public class NDScope implements AutoCloseable {
     private IdentityHashMap<NDArray, NDArray> resources;
 
     /** Constructs a new {@code NDScope} instance. */
+    @SuppressWarnings("this-escape")
     public NDScope() {
         resources = new IdentityHashMap<>();
         SCOPE_STACK.get().addLast(this);

api/src/main/java/ai/djl/nn/ParallelBlock.java

@@ -62,6 +62,7 @@ public ParallelBlock(Function<List<NDList>, NDList> function) {
      * @param function the function to define how the parallel branches are combined
      * @param blocks the blocks that form each of the parallel branches
      */
+    @SuppressWarnings("this-escape")
     public ParallelBlock(Function<List<NDList>, NDList> function, List<Block> blocks) {
         super(VERSION);
         this.function = function;
@@ -74,6 +75,7 @@ public ParallelBlock(Function<List<NDList>, NDList> function, List<Block> blocks
      * @param blocks the array of blocks to add
      * @return this block
      */
+    @SuppressWarnings("this-escape")
     public final ParallelBlock addAll(Block... blocks) {
         return addAll(Arrays.asList(blocks));
     }

api/src/main/java/ai/djl/nn/convolutional/Convolution.java

@@ -89,6 +89,7 @@ public abstract class Convolution extends AbstractBlock {
      *
      * @param builder the {@code Builder} that has the necessary configurations
      */
+    @SuppressWarnings("this-escape")
     public Convolution(ConvolutionBuilder<?> builder) {
         super(VERSION);
         kernelShape = builder.kernelShape;

api/src/main/java/ai/djl/nn/convolutional/Deconvolution.java

@@ -62,6 +62,7 @@ public abstract class Deconvolution extends AbstractBlock {
      *
      * @param builder the {@code Builder} that has the necessary configurations
      */
+    @SuppressWarnings("this-escape")
     public Deconvolution(DeconvolutionBuilder<?> builder) {
         kernelShape = builder.kernelShape;
         stride = builder.stride;

api/src/main/java/ai/djl/nn/core/ConstantEmbedding.java

@@ -38,6 +38,7 @@ public class ConstantEmbedding extends AbstractBlock implements AbstractIndexedE
      *
      * @param embedding the value to return for all embeddings
      */
+    @SuppressWarnings("this-escape")
     public ConstantEmbedding(NDArray embedding) {
         this.embedding = embedding;
         freezeParameters(true);

api/src/main/java/ai/djl/nn/core/Embedding.java

@@ -49,6 +49,7 @@ public abstract class Embedding<T> extends AbstractBlock implements AbstractInde
 
     protected Parameter embedding;
 
+    @SuppressWarnings("this-escape")
     protected Embedding(BaseBuilder<T, ?> baseBuilder) {
         super(VERSION);
         embeddingSize = baseBuilder.embeddingSize;
@@ -91,6 +92,7 @@ protected Embedding(NDArray embedding) {
      * @param embedding the embedding array
      * @param format whether to compute row sparse gradient in the backward calculation
      */
+    @SuppressWarnings("this-escape")
     protected Embedding(NDArray embedding, SparseFormat format) {
         super(VERSION);
         numEmbeddings = Math.toIntExact(embedding.getShape().get(0));

api/src/main/java/ai/djl/nn/core/Linear.java

@@ -62,6 +62,7 @@ public class Linear extends AbstractBlock {
     private Parameter weight;
     private Parameter bias;
 
+    @SuppressWarnings("this-escape")
     protected Linear(Builder builder) {
         super(VERSION);
         units = builder.units;

api/src/main/java/ai/djl/nn/core/Prelu.java

@@ -41,6 +41,7 @@ public class Prelu extends AbstractBlock {
     private Parameter alpha;
 
     /** Creates a Parametric ReLU Block. */
+    @SuppressWarnings("this-escape")
     public Prelu() {
         super(VERSION);
         alpha =

api/src/main/java/ai/djl/nn/norm/LayerNorm.java

@@ -66,6 +66,7 @@ public class LayerNorm extends AbstractBlock {
     protected Parameter gamma;
     protected Parameter beta;
 
+    @SuppressWarnings("this-escape")
     protected LayerNorm(Builder builder) {
         epsilon = builder.epsilon;
         scale = builder.scale;

api/src/main/java/ai/djl/nn/recurrent/RecurrentBlock.java

@@ -58,6 +58,7 @@ public abstract class RecurrentBlock extends AbstractBlock {
      *
      * @param builder the {@code Builder} that has the necessary configurations
      */
+    @SuppressWarnings("this-escape")
     public RecurrentBlock(BaseBuilder<?> builder) {
         super(VERSION);
         stateSize = builder.stateSize;

api/src/main/java/ai/djl/nn/transformer/BertMaskedLanguageModelBlock.java

@@ -46,6 +46,7 @@ public class BertMaskedLanguageModelBlock extends AbstractBlock {
      * @param bertBlock the bert block to create the task for
      * @param hiddenActivation the activation to use for the hidden layer
      */
+    @SuppressWarnings("this-escape")
     public BertMaskedLanguageModelBlock(
             BertBlock bertBlock, Function<NDArray, NDArray> hiddenActivation) {
         super(VERSION);

api/src/main/java/ai/djl/nn/transformer/BertNextSentenceBlock.java

@@ -29,6 +29,7 @@ public class BertNextSentenceBlock extends AbstractBlock {
     private Linear binaryClassifier;
 
     /** Creates a next sentence block. */
+    @SuppressWarnings("this-escape")
     public BertNextSentenceBlock() {
         binaryClassifier =
                 addChildBlock(

api/src/main/java/ai/djl/nn/transformer/BertPretrainingBlock.java

@@ -36,6 +36,7 @@ public class BertPretrainingBlock extends AbstractBlock {
      *
      * @param builder a builder with a bert configuration
      */
+    @SuppressWarnings("this-escape")
     public BertPretrainingBlock(final BertBlock.Builder builder) {
         this.bertBlock = addChildBlock("Bert", builder.build());
         this.mlBlock =

api/src/main/java/ai/djl/nn/transformer/PointwiseFeedForwardBlock.java

@@ -31,6 +31,7 @@ public class PointwiseFeedForwardBlock extends SequentialBlock {
      * @param activationFunction the activation function to use for the hidden layers (not applied
      *     to output)
      */
+    @SuppressWarnings("this-escape")
     public PointwiseFeedForwardBlock(
             List<Integer> hiddenSizes,
             int outputSize,

api/src/main/java/ai/djl/nn/transformer/TransformerEncoderBlock.java

@@ -51,6 +51,7 @@ public class TransformerEncoderBlock extends AbstractBlock {
      * @param dropoutProbability dropout probability
      * @param activationFunction activation function
      */
+    @SuppressWarnings("this-escape")
     public TransformerEncoderBlock(
             int embeddingSize,
             int headCount,

api/src/main/java/ai/djl/repository/zoo/DefaultModelZoo.java

@@ -29,6 +29,7 @@ public class DefaultModelZoo extends ModelZoo {
     private static final Logger logger = LoggerFactory.getLogger(DefaultModelZoo.class);
 
     /** Constructs a new {@code LocalModelZoo} instance. */
+    @SuppressWarnings("this-escape")
     public DefaultModelZoo() {
         String locations = System.getProperty("ai.djl.repository.zoo.location");
         if (locations != null) {
@@ -41,6 +42,7 @@ public DefaultModelZoo() {
      *
      * @param locations a comma separated urls where the models to be loaded from
      */
+    @SuppressWarnings("this-escape")
     public DefaultModelZoo(String locations) {
         parseLocation(locations);
     }

api/src/main/java/ai/djl/training/Trainer.java

@@ -86,6 +86,7 @@ public class Trainer implements AutoCloseable {
      * @param model the model the trainer will train on
      * @param trainingConfig the configuration used by the trainer
      */
+    @SuppressWarnings("this-escape")
     public Trainer(Model model, TrainingConfig trainingConfig) {
         this.model = model;
         manager = model.getNDManager().newSubManager();

api/src/main/java/ai/djl/translate/PaddingStackBatchifier.java

@@ -29,10 +29,10 @@ public final class PaddingStackBatchifier implements Batchifier {
 
     private static final long serialVersionUID = 1L;
 
-    private List<Integer> arraysToPad;
-    private List<Integer> dimsToPad;
+    private transient List<Integer> arraysToPad;
+    private transient List<Integer> dimsToPad;
     private transient List<NDArraySupplier> paddingSuppliers;
-    private List<Integer> paddingSizes;
+    private transient List<Integer> paddingSizes;
     private boolean includeValidLengths;
 
     private PaddingStackBatchifier(Builder builder) {

basicdataset/src/main/java/ai/djl/basicdataset/tabular/ListFeatures.java

@@ -44,6 +44,7 @@ public ListFeatures(int initialCapacity) {
      *
      * @param source the source list
      */
+    @SuppressWarnings("this-escape")
     public ListFeatures(List<String> source) {
         super(source.size());
         addAll(source);

engines/ml/lightgbm/src/main/java/ai/djl/ml/lightgbm/LgbmSymbolBlock.java

@@ -46,6 +46,7 @@ public class LgbmSymbolBlock extends AbstractSymbolBlock implements AutoCloseabl
      * @param iterations the number of iterations the model was trained for
      * @param handle the Booster handle
      */
+    @SuppressWarnings("this-escape")
     public LgbmSymbolBlock(LgbmNDManager manager, int iterations, SWIGTYPE_p_p_void handle) {
         this.handle = new AtomicReference<>(handle);
         this.iterations = iterations;

engines/ml/xgboost/src/main/java/ai/djl/ml/xgboost/XgbSymbolBlock.java

@@ -45,6 +45,7 @@ public class XgbSymbolBlock extends AbstractSymbolBlock implements AutoCloseable
      * @param manager the manager to use for the block
      * @param handle the Booster handle
      */
+    @SuppressWarnings("this-escape")
     public XgbSymbolBlock(XgbNDManager manager, long handle) {
         this.handle = new AtomicReference<>(handle);
         this.manager = manager;

engines/mxnet/jnarator/build.gradle

@@ -17,6 +17,11 @@ dependencies {
 checkstyleMain.source = 'src/main/java'
 pmdMain.source = 'src/main/java'
 
+compileJava {
+    options.compilerArgs.clear()
+    options.compilerArgs << "--release" << "11" << "-proc:none" << "-Xlint:all,-options,-static"
+}
+
 jar {
     manifest {
         attributes (

engines/mxnet/jnarator/src/main/java/ai/djl/mxnet/jnarator/JnaGenerator.java

@@ -276,6 +276,7 @@ public void writeNativeSize() throws IOException {
             writer.append("    public NativeSizeByReference() {\n");
             writer.append("        this(new NativeSize(0));\n");
             writer.append("    }\n\n");
+            writer.append("    @SuppressWarnings(\"this-escape\")\n");
             writer.append("    public NativeSizeByReference(NativeSize value) {\n");
             writer.append("        super(NativeSize.SIZE);\n");
             writer.append("        setValue(value);\n");

engines/mxnet/mxnet-engine/src/main/java/ai/djl/mxnet/engine/CachedOp.java

@@ -63,6 +63,7 @@ public class CachedOp extends NativeResource<Pointer> {
      * @param dataIndices the input data names required by the model and their corresponding
      *     location
      */
+    @SuppressWarnings("this-escape")
     public CachedOp(
             Pointer handle,
             MxNDManager manager,

engines/mxnet/mxnet-engine/src/main/java/ai/djl/mxnet/engine/MxParameterServer.java

@@ -40,6 +40,7 @@ public class MxParameterServer extends NativeResource<Pointer> implements Parame
      *
      * @param optimizer the optimizer to use for the parameter server updates
      */
+    @SuppressWarnings("this-escape")
     public MxParameterServer(Optimizer optimizer) {
         super(createdKVStore());
         callback = new OptimizerCallback(optimizer);

engines/onnxruntime/onnxruntime-engine/src/main/java/ai/djl/onnxruntime/engine/OrtSymbolBlock.java

@@ -59,6 +59,7 @@ public class OrtSymbolBlock extends AbstractSymbolBlock implements AutoCloseable
      * @param session the {@link OrtSession} contains the model information
      * @param manager the {@link NDManager} to holds the NDArray
      */
+    @SuppressWarnings("this-escape")
     public OrtSymbolBlock(OrtSession session, OrtNDManager manager) {
         this.session = session;
         this.manager = manager;

engines/pytorch/pytorch-engine/src/main/java/ai/djl/pytorch/engine/PtNDArray.java

@@ -60,6 +60,7 @@ public class PtNDArray extends NativeResource<Long> implements NDArray {
      * @param manager the manager to attach the new array to
      * @param handle the pointer to the native PyTorch memory
      */
+    @SuppressWarnings("this-escape")
     public PtNDArray(PtNDManager manager, long handle) {
         super(handle);
         this.manager = manager;
@@ -76,6 +77,7 @@ public PtNDArray(PtNDManager manager, long handle) {
      * @param handle the pointer to the native PyTorch memory
      * @param data the direct buffer of the data
      */
+    @SuppressWarnings("this-escape")
     public PtNDArray(PtNDManager manager, long handle, ByteBuffer data) {
         super(handle);
         this.manager = manager;
@@ -93,6 +95,7 @@ public PtNDArray(PtNDManager manager, long handle, ByteBuffer data) {
      * @param strs the string array
      * @param shape the {@link Shape} of the {@link NDArray}
      */
+    @SuppressWarnings("this-escape")
     public PtNDArray(PtNDManager manager, String[] strs, Shape shape) {
         super(-1L);
         this.manager = manager;

engines/pytorch/pytorch-engine/src/main/java/ai/djl/pytorch/engine/PtSymbolBlock.java

@@ -67,6 +67,7 @@ public class PtSymbolBlock extends AbstractSymbolBlock implements AutoCloseable
      * @param manager the manager to use for the block
      * @param handle the module handle
      */
+    @SuppressWarnings("this-escape")
     public PtSymbolBlock(PtNDManager manager, long handle) {
         this(manager);
         this.handle = new AtomicReference<>(handle);

extensions/fasttext/src/test/java/ai/djl/fasttext/CookingStackExchangeTest.java

@@ -41,6 +41,7 @@
 
 import java.io.IOException;
 import java.io.InputStream;
+import java.net.URI;
 import java.net.URL;
 import java.nio.file.Files;
 import java.nio.file.Path;
@@ -129,7 +130,9 @@ public void testWord2Vec() throws IOException, MalformedModelException, ModelNot
     public void testBlazingText() throws IOException, ModelException {
         TestRequirements.nightly();
 
-        URL url = new URL("https://resources.djl.ai/test-models/blazingtext_classification.bin");
+        URL url =
+                URI.create("https://resources.djl.ai/test-models/blazingtext_classification.bin")
+                        .toURL();
         Path path = Paths.get("build/tmp/model");
         Path modelFile = path.resolve("text_classification.bin");
         if (!Files.exists(modelFile)) {

jacoco/build.gradle

@@ -39,7 +39,9 @@ dependencies {
     jacocoAggregation project(":extensions:tokenizers")
     jacocoAggregation project(":extensions:tablesaw")
     jacocoAggregation project(":extensions:timeseries")
-    jacocoAggregation project(":extensions:spark")
+    if (JavaVersion.current() < JavaVersion.VERSION_19) {
+        jacocoAggregation project(":extensions:spark")
+    }
     jacocoAggregation project(":integration")
     jacocoAggregation project(":model-zoo")
 }

model-zoo/src/main/java/ai/djl/basicmodelzoo/basic/Mlp.java

@@ -56,6 +56,7 @@ public Mlp(int input, int output, int[] hidden) {
      * @param hidden the sizes of all of the hidden layers
      * @param activation the activation function to use
      */
+    @SuppressWarnings("this-escape")
     public Mlp(int input, int output, int[] hidden, Function<NDList, NDList> activation) {
         add(Blocks.batchFlattenBlock(input));
         for (int hiddenSize : hidden) {

settings.gradle

@@ -34,7 +34,9 @@ include ':extensions:sentencepiece'
 include ':extensions:tokenizers'
 include ':extensions:tablesaw'
 include ':extensions:timeseries'
-include ':extensions:spark'
+if (JavaVersion.current() < JavaVersion.VERSION_21) {
+    include ':extensions:spark'
+}
 include ':integration'
 include ':model-zoo'
 include ':testing'