Kotlin friendly names (Shape.get)

Author: rnett

.gitignore

@@ -1,2 +1,3 @@
 *.iml
+.idea
 target

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

@@ -17,7 +17,9 @@
 
 package org.tensorflow.ndarray;
 
+import java.util.ArrayList;
 import java.util.Arrays;
+import java.util.List;
 
 /**
  * The shape of a Tensor or {@link NdArray}.
@@ -74,8 +76,8 @@ public static Shape scalar() {
    * Shape scalar = Shape.of()
    * }</pre>
    *
-   * @param dimensionSizes number of elements in each dimension of this shape, if any, or
-   *                       {@link Shape#UNKNOWN_SIZE} if unknown.
+   * @param dimensionSizes number of elements in each dimension of this shape, if any, or {@link
+   *     Shape#UNKNOWN_SIZE} if unknown.
    * @return a new shape
    */
   public static Shape of(long... dimensionSizes) {
@@ -108,13 +110,34 @@ public long size() {
    * an unknown size, {@link Shape#UNKNOWN_SIZE} is returned.
    *
    * @param i the index of the dimension to get the size for. If this Shape has a known number of
-   *     dimensions, it must be &lt; {@link Shape#numDimensions()}. The index may be negative, in which
-   *     case the position is counted from the end of the shape. E.g.: {@code size(-1)} returns the
-   *     size of the last dimension, {@code size(-2)} the size of the second to last dimension etc.
+   *     dimensions, it must be &lt; {@link Shape#numDimensions()}. The index may be negative, in
+   *     which case the position is counted from the end of the shape. E.g.: {@code size(-1)}
+   *     returns the size of the last dimension, {@code size(-2)} the size of the second to last
+   *     dimension etc.
    * @return The size of the dimension with the given index if known, {@link Shape#UNKNOWN_SIZE}
    *     otherwise.
+   * @deprecated Renamed to {@link #get(int)}.
    */
-  public long size(int i) {
+  @Deprecated
+  public long size(int i){
+    return get(i);
+  }
+
+  /**
+   * The size of the dimension with the given index.
+   *
+   * <p>If {@link Shape#isUnknown()} is true or the size of the dimension with the given index has
+   * an unknown size, {@link Shape#UNKNOWN_SIZE} is returned.
+   *
+   * @param i the index of the dimension to get the size for. If this Shape has a known number of
+   *     dimensions, it must be &lt; {@link Shape#numDimensions()}. The index may be negative, in
+   *     which case the position is counted from the end of the shape. E.g.: {@code size(-1)}
+   *     returns the size of the last dimension, {@code size(-2)} the size of the second to last
+   *     dimension etc.
+   * @return The size of the dimension with the given index if known, {@link Shape#UNKNOWN_SIZE}
+   *     otherwise.
+   */
+  public long get(int i) {
     if (dimensionSizes == null) {
       return UNKNOWN_SIZE;
     } else if (i >= 0) {
@@ -177,6 +200,24 @@ public long[] asArray() {
     }
   }
 
+  /**
+   * Returns a defensive copy of the this Shape's axes. Changes to the returned list do not change
+   * this Shape's state. Returns null if {@link Shape#isUnknown()} is true.
+   */
+  public List<Long> toListOrNull() {
+    long[] array = asArray();
+    if (array == null) {
+      return null;
+    }
+
+    List<Long> list = new ArrayList<>(array.length);
+    for (long l : array) {
+      list.add(l);
+    }
+
+    return list;
+  }
+
   @Override
   public int hashCode() {
     return dimensionSizes != null ? Arrays.hashCode(dimensionSizes) : super.hashCode();
@@ -186,6 +227,7 @@ public int hashCode() {
    * Equals implementation for Shapes. Two Shapes are considered equal iff:
    *
    * <p>
+   *
    * <ul>
    *   <li>the number of dimensions is defined and equal for both
    *   <li>the size of each dimension is defined and equal for both
@@ -236,7 +278,8 @@ public Shape head() {
    * Returns an n-dimensional Shape with the dimensions matching the first n dimensions of this
    * shape
    *
-   * @param n the number of leading dimensions to get, must be &lt;= than {@link Shape#numDimensions()}
+   * @param n the number of leading dimensions to get, must be &lt;= than {@link
+   *     Shape#numDimensions()}
    * @return an n-dimensional Shape with the first n dimensions matching the first n dimensions of
    *     this Shape
    */
@@ -252,7 +295,9 @@ public Shape take(int n) {
 
   /** Returns a new Shape, with this Shape's first dimension removed. */
   public Shape tail() {
-    if (dimensionSizes.length < 2) return Shape.of();
+    if (dimensionSizes.length < 2) {
+      return Shape.of();
+    }
     return Shape.of(Arrays.copyOfRange(dimensionSizes, 1, dimensionSizes.length));
   }
 
@@ -276,15 +321,21 @@ public Shape takeLast(int n) {
   }
 
   /**
-   * Return a {@code end - begin} dimensional shape with dimensions matching this Shape from {@code begin} to {@code end}.
+   * Return a {@code end - begin} dimensional shape with dimensions matching this Shape from {@code
+   * begin} to {@code end}.
+   *
    * @param begin Where to start the sub-shape.
    * @param end Where to end the sub-shape, exclusive.
    * @return the sub-shape bounded by begin and end.
    */
-  public Shape subShape(int begin, int end){
+  public Shape subShape(int begin, int end) {
     if (end > numDimensions()) {
       throw new ArrayIndexOutOfBoundsException(
-          "End index " + end + " out of bounds: shape only has " + numDimensions() + " dimensions.");
+          "End index "
+              + end
+              + " out of bounds: shape only has "
+              + numDimensions()
+              + " dimensions.");
     }
     if (begin < 0) {
       throw new ArrayIndexOutOfBoundsException(
@@ -423,7 +474,7 @@ public boolean isCompatibleWith(Shape shape) {
         return false;
       }
       for (int i = 0; i < numDimensions(); i++) {
-        if (!isCompatible(size(i), shape.size(i))) {
+        if (!isCompatible(get(i), shape.get(i))) {
           return false;
         }
       }

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

@@ -3798,9 +3798,9 @@ private static int[] computeArrayDims(NdArray<?> ndArray, int expectedRank) {
     }
     int[] arrayShape = new int[expectedRank];
     for (int i = 0; i < expectedRank; ++i) {
-      long dimSize = shape.size(i);
+      long dimSize = shape.get(i);
       if (dimSize > Integer.MAX_VALUE) {
-        throw new IllegalArgumentException("Dimension " + i + " is too large to fit in a standard array (" + shape.size(i) + ")");
+        throw new IllegalArgumentException("Dimension " + i + " is too large to fit in a standard array (" + shape.get(i) + ")");
       }
       arrayShape[i] = (int)dimSize;
     }

ndarray/src/main/java/org/tensorflow/ndarray/impl/dimension/DimensionalSpace.java

@@ -28,7 +28,7 @@ public static DimensionalSpace create(Shape shape) {
 
     // Start from the last dimension, where all elements are continuous
     for (int i = dimensions.length - 1, elementSize = 1; i >= 0; --i) {
-      dimensions[i] = new Axis(shape.size(i), elementSize);
+      dimensions[i] = new Axis(shape.get(i), elementSize);
       elementSize *= dimensions[i].numElements();
     }
     return new DimensionalSpace(dimensions, shape);
@@ -189,7 +189,9 @@ public long positionOf(long[] coords) {
     return position;
   }
 
-  /** Succinct description of the shape meant for debugging. */
+  /**
+   * Succinct description of the shape meant for debugging.
+   */
   @Override
   public String toString() {
     return Arrays.toString(dimensions);

ndarray/src/test/java/org/tensorflow/ndarray/NdArrayTestBase.java

@@ -24,10 +24,10 @@
 import static org.tensorflow.ndarray.index.Indices.at;
 import static org.tensorflow.ndarray.index.Indices.even;
 import static org.tensorflow.ndarray.index.Indices.flip;
-import static org.tensorflow.ndarray.index.Indices.sliceFrom;
 import static org.tensorflow.ndarray.index.Indices.odd;
 import static org.tensorflow.ndarray.index.Indices.range;
 import static org.tensorflow.ndarray.index.Indices.seq;
+import static org.tensorflow.ndarray.index.Indices.sliceFrom;
 import static org.tensorflow.ndarray.index.Indices.sliceTo;
 
 import java.nio.BufferOverflowException;
@@ -132,15 +132,15 @@ public void iterateElements() {
     long value = 0L;
     for (NdArray<T> matrix : matrix3d.elements(0)) {
       assertEquals(2L, matrix.shape().numDimensions());
-      assertEquals(4L, matrix.shape().size(0));
-      assertEquals(5L, matrix.shape().size(1));
+      assertEquals(4L, matrix.shape().get(0));
+      assertEquals(5L, matrix.shape().get(1));
 
       for (NdArray<T> vector : matrix.elements(0)) {
-        assertEquals(1L, vector.shape().numDimensions()) ;
-        assertEquals(5L, vector.shape().size(0));
+        assertEquals(1L, vector.shape().numDimensions());
+        assertEquals(5L, vector.shape().get(0));
 
         for (NdArray<T> scalar : vector.scalars()) {
-          assertEquals(0L, scalar.shape().numDimensions()) ;
+          assertEquals(0L, scalar.shape().numDimensions());
           scalar.setObject(valueOf(value++));
           try {
             scalar.elements(0);
@@ -162,7 +162,7 @@ public void iterateElements() {
   @Test
   public void slices() {
     NdArray<T> matrix3d = allocate(Shape.of(5, 4, 5));
-    
+
     T val100 = valueOf(100L);
     matrix3d.setObject(val100, 1, 0, 0);
     T val101 = valueOf(101L);
@@ -318,8 +318,8 @@ public void equalsAndHashCode() {
     NdArray<T> array4 = allocate(Shape.of(1, 2, 2));
 
     @SuppressWarnings("unchecked")
-    T[][][] values = (T[][][])(new Object[][][] {
-        { { valueOf(0L), valueOf(1L) }, { valueOf(2L), valueOf(0L) } }
+    T[][][] values = (T[][][]) (new Object[][][]{
+        {{valueOf(0L), valueOf(1L)}, {valueOf(2L), valueOf(0L)}}
     });
 
     StdArrays.copyTo(values[0], array1);

ndarray/src/test/java/org/tensorflow/ndarray/ShapeTest.java

@@ -16,32 +16,38 @@
 */
 package org.tensorflow.ndarray;
 
-import org.junit.jupiter.api.Test;
+import static org.junit.jupiter.api.Assertions.assertArrayEquals;
+import static org.junit.jupiter.api.Assertions.assertEquals;
+import static org.junit.jupiter.api.Assertions.assertFalse;
+import static org.junit.jupiter.api.Assertions.assertNotEquals;
+import static org.junit.jupiter.api.Assertions.assertNotNull;
+import static org.junit.jupiter.api.Assertions.assertTrue;
+import static org.junit.jupiter.api.Assertions.fail;
 
-import static org.junit.jupiter.api.Assertions.*;
+import org.junit.jupiter.api.Test;
 
 public class ShapeTest {
 
   @Test
   public void allKnownDimensions() {
     Shape shape = Shape.of(5, 4, 5);
     assertEquals(3, shape.numDimensions());
-    assertEquals(5, shape.size(0));
-    assertEquals(4, shape.size(1));
-    assertEquals(5, shape.size(2));
+    assertEquals(5, shape.get(0));
+    assertEquals(4, shape.get(1));
+    assertEquals(5, shape.get(2));
     assertEquals(100, shape.size());
-    assertArrayEquals(new long[] {5, 4, 5}, shape.asArray());
+    assertArrayEquals(new long[]{5, 4, 5}, shape.asArray());
     try {
-      shape.size(3);
+      shape.get(3);
       fail();
     } catch (IndexOutOfBoundsException e) {
       // as expected
     }
-    assertEquals(5, shape.size(-1));
-    assertEquals(4, shape.size(-2));
-    assertEquals(5, shape.size(-3));
+    assertEquals(5, shape.get(-1));
+    assertEquals(4, shape.get(-2));
+    assertEquals(5, shape.get(-3));
     try {
-      shape.size(-4);
+      shape.get(-4);
       fail();
     } catch (IndexOutOfBoundsException e) {
       // as expected
@@ -133,7 +139,7 @@ public void testShapeModification() {
     long[] internalShape = one.asArray();
     assertNotNull(internalShape);
     internalShape[0] = 42L;
-    assertEquals(2L, one.size(0));
+    assertEquals(2L, one.get(0));
   }
 
   @Test