Minor fixes on duplicated code (#736)

* remove methods that already defined in the NDArrayAdapter

Change-Id: I01cc03a7f5b427bf31c6b3fd8d2136f2a27fe93b

* refactor toString

Change-Id: Iea22b16e1daa9f759b55c1a8b8b85536482e551a

* remove sparse NDArray

Change-Id: Icb44096519775f54cb32cc768c14f49e33dc7ea5

* fix test

Change-Id: Icef580ed77e7bba22864ce44577de3cba51e3e41

Author: lanking520

api/src/main/java/ai/djl/BaseModel.java

@@ -267,6 +267,22 @@ public Path getModelPath() {
         return modelDir;
     }
 
+    /** {@inheritDoc} */
+    @Override
+    public String toString() {
+        StringBuilder sb = new StringBuilder(200);
+        sb.append("Model (\n\tName: ").append(modelName);
+        if (modelDir != null) {
+            sb.append("\n\tModel location: ").append(modelDir.toAbsolutePath());
+        }
+        sb.append("\n\tData Type: ").append(dataType);
+        for (Map.Entry<String, String> entry : properties.entrySet()) {
+            sb.append("\n\t").append(entry.getKey()).append(": ").append(entry.getValue());
+        }
+        sb.append("\n)");
+        return sb.toString();
+    }
+
     /** {@inheritDoc} */
     @SuppressWarnings("deprecation")
     @Override

dlr/dlr-engine/src/main/java/ai/djl/dlr/engine/DlrNDArray.java

@@ -116,18 +116,6 @@ public void detach() {
         manager = DlrNDManager.getSystemManager();
     }
 
-    /** {@inheritDoc} */
-    @Override
-    public boolean hasGradient() {
-        return false;
-    }
-
-    /** {@inheritDoc} */
-    @Override
-    public NDArray stopGradient() {
-        throw new UnsupportedOperationException("Not supported for DLR");
-    }
-
     /** {@inheritDoc} */
     @Override
     public ByteBuffer toByteBuffer() {

integration/src/main/java/ai/djl/integration/tests/ndarray/NDArrayCreationOpTest.java

@@ -70,7 +70,7 @@ public void testCreateCSRMatrix() {
             long[] indptr = {0, 2, 2, 3};
             long[] indices = {0, 2, 1};
             NDArray nd = manager.createCSR(buf, indptr, indices, new Shape(3, 4));
-            float[] array = nd.toFloatArray();
+            float[] array = nd.toDense().toFloatArray();
             Assert.assertEquals(array[0], expected[0]);
             Assert.assertEquals(array[2], expected[1]);
             Assert.assertEquals(array[9], expected[2]);
@@ -85,7 +85,7 @@ public void testCreateRowSparseMatrix() {
             FloatBuffer buf = FloatBuffer.wrap(expected);
             long[] indices = {0, 1, 3};
             NDArray nd = manager.createRowSparse(buf, new Shape(3, 2), indices, new Shape(4, 2));
-            float[] array = nd.toFloatArray();
+            float[] array = nd.toDense().toFloatArray();
             Assert.assertEquals(array[0], expected[0]);
             Assert.assertEquals(array[1], expected[1]);
             Assert.assertEquals(array[2], expected[2]);

mxnet/mxnet-engine/src/main/java/ai/djl/mxnet/engine/MxModel.java

@@ -200,20 +200,4 @@ private void loadParameters(Path paramFile, Map<String, ?> options)
         dataType = paramNDlist.head().getDataType();
         logger.debug("MXNet Model {} ({}) loaded successfully.", paramFile, dataType);
     }
-
-    /** {@inheritDoc} */
-    @Override
-    public String toString() {
-        StringBuilder sb = new StringBuilder(200);
-        sb.append("Model (\n\tName: ").append(modelName);
-        if (modelDir != null) {
-            sb.append("\n\tModel location: ").append(modelDir.toAbsolutePath());
-        }
-        sb.append("\n\tData Type: ").append(dataType);
-        for (Map.Entry<String, String> entry : properties.entrySet()) {
-            sb.append("\n\t").append(entry.getKey()).append(": ").append(entry.getValue());
-        }
-        sb.append("\n)");
-        return sb.toString();
-    }
 }

mxnet/mxnet-engine/src/main/java/ai/djl/mxnet/engine/MxNDArray.java

@@ -290,6 +290,9 @@ public String[] toStringArray() {
     /** {@inheritDoc} */
     @Override
     public ByteBuffer toByteBuffer() {
+        if (getSparseFormat() != SparseFormat.DENSE) {
+            throw new IllegalStateException("Require Dense NDArray, actual " + getSparseFormat());
+        }
         Shape sh = getShape();
         DataType dType = getDataType();
         long product = sh.size();

mxnet/mxnet-engine/src/main/java/ai/djl/mxnet/engine/MxNDManager.java

@@ -81,8 +81,8 @@ public MxNDArray create(Pointer handle) {
      * @param fmt the sparse format to use
      * @return the created array
      */
-    public MxSparseNDArray create(Pointer handle, SparseFormat fmt) {
-        return new MxSparseNDArray(this, handle, fmt);
+    public MxNDArray create(Pointer handle, SparseFormat fmt) {
+        return new MxNDArray(this, handle, fmt);
     }
 
     /** {@inheritDoc} */
@@ -97,7 +97,7 @@ public MxNDArray create(Shape shape, DataType dataType) {
 
     /** {@inheritDoc} */
     @Override
-    public MxSparseNDArray createCSR(Buffer data, long[] indptr, long[] indices, Shape shape) {
+    public MxNDArray createCSR(Buffer data, long[] indptr, long[] indices, Shape shape) {
         SparseFormat fmt = SparseFormat.CSR;
         DataType dataType = DataType.fromBuffer(data);
         MxNDArray indptrNd = create(new Shape(indptr.length), DataType.INT64);
@@ -113,7 +113,7 @@ public MxSparseNDArray createCSR(Buffer data, long[] indptr, long[] indices, Sha
                         new DataType[] {indptrNd.getDataType(), indicesNd.getDataType()},
                         new Shape[] {indptrNd.getShape(), indicesNd.getShape()},
                         false);
-        MxSparseNDArray sparse = create(handle, fmt);
+        MxNDArray sparse = create(handle, fmt);
         MxNDArray dataNd = create(new Shape(data.remaining()), dataType);
         dataNd.set(data);
         JnaUtils.ndArraySyncCopyFromNdArray(sparse, dataNd, -1);
@@ -124,8 +124,7 @@ public MxSparseNDArray createCSR(Buffer data, long[] indptr, long[] indices, Sha
 
     /** {@inheritDoc} */
     @Override
-    public MxSparseNDArray createRowSparse(
-            Buffer data, Shape dataShape, long[] indices, Shape shape) {
+    public MxNDArray createRowSparse(Buffer data, Shape dataShape, long[] indices, Shape shape) {
         SparseFormat fmt = SparseFormat.ROW_SPARSE;
         DataType dataType = DataType.fromBuffer(data);
         MxNDArray indicesNd = create(new Shape(indices.length), DataType.INT64);
@@ -139,7 +138,7 @@ public MxSparseNDArray createRowSparse(
                         new DataType[] {indicesNd.getDataType()},
                         new Shape[] {indicesNd.getShape()},
                         false);
-        MxSparseNDArray sparse = create(handle, fmt);
+        MxNDArray sparse = create(handle, fmt);
         MxNDArray dataNd = create(dataShape, dataType);
         dataNd.set(data);
         JnaUtils.ndArraySyncCopyFromNdArray(sparse, dataNd, -1);

mxnet/mxnet-engine/src/main/java/ai/djl/mxnet/engine/MxSparseNDArray.java

@@ -96,22 +96,6 @@ private String[] findModelFile(Path dir) {
         return null;
     }
 
-    /** {@inheritDoc} */
-    @Override
-    public String toString() {
-        StringBuilder sb = new StringBuilder(200);
-        sb.append("Model (\n\tName: ").append(modelName);
-        if (modelDir != null) {
-            sb.append("\n\tModel location: ").append(modelDir.toAbsolutePath());
-        }
-        sb.append("\n\tData Type: ").append(dataType);
-        for (Map.Entry<String, String> entry : properties.entrySet()) {
-            sb.append("\n\t").append(entry.getKey()).append(": ").append(entry.getValue());
-        }
-        sb.append("\n)");
-        return sb.toString();
-    }
-
     /** {@inheritDoc} */
     @Override
     public <I, O> Predictor<I, O> newPredictor(Translator<I, O> translator) {