Sparse tensor (#3)

Author: JimClarke5

ndarray/src/main/java/org/tensorflow/ndarray/NdArrays.java

@@ -0,0 +1,50 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+=======================================================================*/
+package org.tensorflow.ndarray;
+
+/**
+ * Interface for Sparse Arrays
+ *
+ * @param <T> the type that the array contains
+ * @param <U> the type of dense NdArray
+ */
+public interface SparseNdArray<T, U extends NdArray<T>> extends NdArray<T> {
+  /**
+   * Gets the Indices
+   *
+   * <p>Indices are a A 2-D long array of shape {@code [N, ndims]}, that specifies the indices of
+   * the elements in the sparse array that contain nonzero values (elements are zero-indexed).
+   *
+   * <p>For example, {@code indices=[[1,3], [2,4]]} specifies that the elements with indexes of
+   * coordinates {@code [1,3]} and {@code [2,4]} have nonzero values.
+   *
+   * @return the Indices
+   */
+  LongNdArray getIndices();
+
+  /**
+   * Gets the values.
+   *
+   * <p>Values are a 1-D array of any type and shape {@code [N]}, that supplies the values for each
+   * element in indices.
+   *
+   * <p>For example, given {@code indices=[[1,3], [2,4]]}, and {@code values=[18, 3.6]} specifies
+   * that element {@code [1,3]} of the sparse array has a value of {@code 18}, and element {@code
+   * [2,4]} of the sparse array has a value of {@code 3.6}.
+   *
+   * @return the values
+   */
+  U getValues();
+}

ndarray/src/main/java/org/tensorflow/ndarray/SparseNdArray.java

@@ -1,30 +1,38 @@
 /*
- Copyright 2019 The TensorFlow Authors. All Rights Reserved.
+Copyright 2019 The TensorFlow Authors. All Rights Reserved.
 
- Licensed under the Apache License, Version 2.0 (the "License");
- you may not use this file except in compliance with the License.
- You may obtain a copy of the License at
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
 
-     http://www.apache.org/licenses/LICENSE-2.0
+    http://www.apache.org/licenses/LICENSE-2.0
 
- Unless required by applicable law or agreed to in writing, software
- distributed under the License is distributed on an "AS IS" BASIS,
- WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- See the License for the specific language governing permissions and
- limitations under the License.
- =======================================================================
- */
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+=======================================================================
+*/
 package org.tensorflow.ndarray.impl;
 
-import java.util.Iterator;
 import org.tensorflow.ndarray.NdArray;
 import org.tensorflow.ndarray.NdArraySequence;
 import org.tensorflow.ndarray.Shape;
 import org.tensorflow.ndarray.impl.dimension.DimensionalSpace;
 
+import java.util.Iterator;
+import java.util.Objects;
+
 @SuppressWarnings("unchecked")
 public abstract class AbstractNdArray<T, U extends NdArray<T>> implements NdArray<T> {
 
+  protected final DimensionalSpace dimensions;
+
+  protected AbstractNdArray(DimensionalSpace dimensions) {
+    this.dimensions = dimensions;
+  }
+
   public abstract U slice(long position, DimensionalSpace dimensions);
 
   public DimensionalSpace dimensions() {
@@ -39,7 +47,7 @@ public Shape shape() {
   @Override
   public NdArraySequence<U> scalars() {
     // negative if this array is a scalar, should be handled in `elements(dimIdx)`
-    return (NdArraySequence<U>)elements(shape().numDimensions() - 1);
+    return (NdArraySequence<U>) elements(shape().numDimensions() - 1);
   }
 
   @Override
@@ -55,11 +63,7 @@ public boolean equals(Object obj) {
     if (!(obj instanceof NdArray)) {
       return false;
     }
-    return slowEquals((NdArray<?>)obj);
-  }
-
-  protected AbstractNdArray(DimensionalSpace dimensions) {
-    this.dimensions = dimensions;
+    return slowEquals((NdArray<?>) obj);
   }
 
   protected void slowCopyTo(NdArray<T> array) {
@@ -77,16 +81,19 @@ protected int slowHashCode() {
   }
 
   protected boolean slowEquals(NdArray<?> array) {
-    if (!shape().equals(array.shape())) {  // this guarantees also that we have the same number of scalar values
+    if (!shape()
+        .equals(
+            array.shape())) { // this guarantees also that we have the same number of scalar values
       return false;
     }
-    for (Iterator<? extends NdArray<?>> thisIter = scalars().iterator(), otherIter = array.scalars().iterator(); thisIter.hasNext();) {
-      if (!thisIter.next().getObject().equals(otherIter.next().getObject())) {
+    for (Iterator<? extends NdArray<?>> thisIter = scalars().iterator(),
+            otherIter = array.scalars().iterator();
+        thisIter.hasNext(); ) {
+      // Use Object.equals to handle nulls.
+      if (!Objects.equals(thisIter.next().getObject(), otherIter.next().getObject())) {
         return false;
       }
     }
     return true;
   }
-
-  protected final DimensionalSpace dimensions;
 }