Java Code Examples for org.nd4j.linalg.api.shape.Shape#getOffset()
The following examples show how to use
org.nd4j.linalg.api.shape.Shape#getOffset() .
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Example 1
| Source File: BaseNDArray.java From nd4j with Apache License 2.0 | 6 votes |
|
@Override
public INDArray putScalar(int[] indexes, double value) {
Nd4j.getCompressor().autoDecompress(this);
for (int i = 0; i < indexes.length; i++) {
if (indexes[i] < 0)
indexes[i] += rank();
}
if (indexes.length == 1) {
return putScalar(indexes[0], value);
} else if (indexes.length == 2) {
return putScalar(indexes[0], indexes[1], value);
} else if (indexes.length == 3) {
return putScalar(indexes[0], indexes[1], indexes[2], value);
} else if (indexes.length == 4) {
return putScalar(indexes[0], indexes[1], indexes[2], indexes[3], value);
} else {
autoProcessScalarCall();
long offset = Shape.getOffset(javaShapeInformation, indexes);
data.put(offset, value);
}
return this;
}
Example 2
| Source File: BaseNDArray.java From nd4j with Apache License 2.0 | 6 votes |
|
@Override
public INDArray putScalar(long[] indexes, double value) {
Nd4j.getCompressor().autoDecompress(this);
for (int i = 0; i < indexes.length; i++) {
if (indexes[i] < 0)
indexes[i] += rank();
}
if (indexes.length == 1) {
return putScalar(indexes[0], value);
} else if (indexes.length == 2) {
return putScalar(indexes[0], indexes[1], value);
} else if (indexes.length == 3) {
return putScalar(indexes[0], indexes[1], indexes[2], value);
} else if (indexes.length == 4) {
return putScalar(indexes[0], indexes[1], indexes[2], indexes[3], value);
} else {
autoProcessScalarCall();
long offset = Shape.getOffset(javaShapeInformation, indexes);
data.put(offset, value);
}
return this;
}
Example 3
| Source File: BaseNDArray.java From deeplearning4j with Apache License 2.0 | 5 votes |
|
@Override
public INDArray putScalar(int[] indexes, double value) {
Nd4j.getCompressor().autoDecompress(this);
Preconditions.checkArgument(dataType() != DataType.BOOL || value == 0.0 || value == 1.0, "Cannot put value %s into boolean array" +
" - only putScalar with values 0 or 1 is allowed on boolean arrays", value);
for (int i = 0; i < indexes.length; i++) {
if (indexes[i] < 0)
indexes[i] += this.size(i);
}
if (indexes.length == 1) {
return putScalar(indexes[0], value);
} else if (indexes.length == 2) {
return putScalar(indexes[0], indexes[1], value);
} else if (indexes.length == 3) {
return putScalar(indexes[0], indexes[1], indexes[2], value);
} else if (indexes.length == 4) {
return putScalar(indexes[0], indexes[1], indexes[2], indexes[3], value);
} else {
autoProcessScalarCall();
long offset = Shape.getOffset(jvmShapeInfo.javaShapeInformation, indexes);
data.put(offset, value);
}
return this;
}
Example 4
| Source File: BaseNDArray.java From deeplearning4j with Apache License 2.0 | 5 votes |
|
@Override
public INDArray putScalar(long[] indexes, double value) {
Nd4j.getCompressor().autoDecompress(this);
Preconditions.checkArgument(dataType() != DataType.BOOL || value == 0.0 || value == 1.0, "Cannot put value %s into boolean array" +
" - only putScalar with values 0 or 1 is allowed on boolean arrays", value);
for (int i = 0; i < indexes.length; i++) {
if (indexes[i] < 0)
indexes[i] += size(i);
}
if (indexes.length == 1) {
return putScalar(indexes[0], value);
} else if (indexes.length == 2) {
return putScalar(indexes[0], indexes[1], value);
} else if (indexes.length == 3) {
return putScalar(indexes[0], indexes[1], indexes[2], value);
} else if (indexes.length == 4) {
return putScalar(indexes[0], indexes[1], indexes[2], indexes[3], value);
} else {
autoProcessScalarCall();
long offset = Shape.getOffset(jvmShapeInfo.javaShapeInformation, indexes);
data.put(offset, value);
}
return this;
}
Example 5
| Source File: BaseNDArray.java From deeplearning4j with Apache License 2.0 | 5 votes |
|
@Override
public INDArray getScalar(int[] indexes) {
if (indexes.length > rank())
throw new ND4JIllegalStateException("Indexes can't be longer then array rank");
for (int i = 0; i < indexes.length; i++) {
if (indexes[i] < 0)
indexes[i] += this.size(i);
}
long idx = Shape.getOffset(jvmShapeInfo.javaShapeInformation, indexes);
val buffer = Nd4j.createBuffer(this.data(), idx, 1);
val shape = Nd4j.getShapeInfoProvider().createShapeInformation(new long[0], new long[0],1, 'c', this.dataType(), false);
return Nd4j.createArrayFromShapeBuffer(buffer, shape);
}
Example 6
| Source File: BaseNDArray.java From deeplearning4j with Apache License 2.0 | 5 votes |
|
@Override
public INDArray getScalar(long... indexes) {
if (indexes.length > rank())
throw new ND4JIllegalStateException("Indexes can't be longer then array rank");
for (int i = 0; i < indexes.length; i++) {
if (indexes[i] < 0)
indexes[i] += this.size(i);
}
long idx = Shape.getOffset(jvmShapeInfo.javaShapeInformation, indexes);
val buffer = Nd4j.createBuffer(this.data(), idx, 1);
val shape = Nd4j.getShapeInfoProvider().createShapeInformation(new long[0], new long[0],1,'c', this.dataType(), false);
return Nd4j.createArrayFromShapeBuffer(buffer, shape);
}
Example 7
| Source File: StaticShapeTests.java From nd4j with Apache License 2.0 | 4 votes |
|
@Test
public void testBufferToIntShapeStrideMethods() {
//Specifically: Shape.shape(IntBuffer), Shape.shape(DataBuffer)
//.isRowVectorShape(DataBuffer), .isRowVectorShape(IntBuffer)
//Shape.size(DataBuffer,int), Shape.size(IntBuffer,int)
//Also: Shape.stride(IntBuffer), Shape.stride(DataBuffer)
//Shape.stride(DataBuffer,int), Shape.stride(IntBuffer,int)
List<List<Pair<INDArray, String>>> lists = new ArrayList<>();
lists.add(NDArrayCreationUtil.getAllTestMatricesWithShape(3, 4, 12345));
lists.add(NDArrayCreationUtil.getAllTestMatricesWithShape(1, 4, 12345));
lists.add(NDArrayCreationUtil.getAllTestMatricesWithShape(3, 1, 12345));
lists.add(NDArrayCreationUtil.getAll3dTestArraysWithShape(12345, 3, 4, 5));
lists.add(NDArrayCreationUtil.getAll4dTestArraysWithShape(12345, 3, 4, 5, 6));
lists.add(NDArrayCreationUtil.getAll4dTestArraysWithShape(12345, 3, 1, 5, 1));
lists.add(NDArrayCreationUtil.getAll5dTestArraysWithShape(12345, 3, 4, 5, 6, 7));
lists.add(NDArrayCreationUtil.getAll6dTestArraysWithShape(12345, 3, 4, 5, 6, 7, 8));
val shapes = new long[][] {{3, 4}, {1, 4}, {3, 1}, {3, 4, 5}, {3, 4, 5, 6}, {3, 1, 5, 1}, {3, 4, 5, 6, 7},
{3, 4, 5, 6, 7, 8}};
for (int i = 0; i < shapes.length; i++) {
List<Pair<INDArray, String>> list = lists.get(i);
val shape = shapes[i];
for (Pair<INDArray, String> p : list) {
INDArray arr = p.getFirst();
assertArrayEquals(shape, arr.shape());
val thisStride = arr.stride();
val ib = arr.shapeInfo();
DataBuffer db = arr.shapeInfoDataBuffer();
//Check shape calculation
assertEquals(shape.length, Shape.rank(ib));
assertEquals(shape.length, Shape.rank(db));
assertArrayEquals(shape, Shape.shape(ib));
assertArrayEquals(shape, Shape.shape(db));
for (int j = 0; j < shape.length; j++) {
assertEquals(shape[j], Shape.size(ib, j));
assertEquals(shape[j], Shape.size(db, j));
assertEquals(thisStride[j], Shape.stride(ib, j));
assertEquals(thisStride[j], Shape.stride(db, j));
}
//Check base offset
assertEquals(Shape.offset(ib), Shape.offset(db));
//Check offset calculation:
NdIndexIterator iter = new NdIndexIterator(shape);
while (iter.hasNext()) {
val next = iter.next();
long offset1 = Shape.getOffset(ib, next);
assertEquals(offset1, Shape.getOffset(db, next));
switch (shape.length) {
case 2:
assertEquals(offset1, Shape.getOffset(ib, next[0], next[1]));
assertEquals(offset1, Shape.getOffset(db, next[0], next[1]));
break;
case 3:
assertEquals(offset1, Shape.getOffset(ib, next[0], next[1], next[2]));
assertEquals(offset1, Shape.getOffset(db, next[0], next[1], next[2]));
break;
case 4:
assertEquals(offset1, Shape.getOffset(ib, next[0], next[1], next[2], next[3]));
assertEquals(offset1, Shape.getOffset(db, next[0], next[1], next[2], next[3]));
break;
case 5:
case 6:
//No 5 and 6d getOffset overloads
break;
default:
throw new RuntimeException();
}
}
}
}
}
Example 8
| Source File: StaticShapeTests.java From deeplearning4j with Apache License 2.0 | 4 votes |
|
@Test
public void testBufferToIntShapeStrideMethods() {
//Specifically: Shape.shape(IntBuffer), Shape.shape(DataBuffer)
//.isRowVectorShape(DataBuffer), .isRowVectorShape(IntBuffer)
//Shape.size(DataBuffer,int), Shape.size(IntBuffer,int)
//Also: Shape.stride(IntBuffer), Shape.stride(DataBuffer)
//Shape.stride(DataBuffer,int), Shape.stride(IntBuffer,int)
List<List<Pair<INDArray, String>>> lists = new ArrayList<>();
lists.add(NDArrayCreationUtil.getAllTestMatricesWithShape(3, 4, 12345, DataType.DOUBLE));
lists.add(NDArrayCreationUtil.getAllTestMatricesWithShape(1, 4, 12345, DataType.DOUBLE));
lists.add(NDArrayCreationUtil.getAllTestMatricesWithShape(3, 1, 12345, DataType.DOUBLE));
lists.add(NDArrayCreationUtil.getAll3dTestArraysWithShape(12345, new long[]{3, 4, 5}, DataType.DOUBLE));
lists.add(NDArrayCreationUtil.getAll4dTestArraysWithShape(12345, new int[]{3, 4, 5, 6}, DataType.DOUBLE));
lists.add(NDArrayCreationUtil.getAll4dTestArraysWithShape(12345, new int[]{3, 1, 5, 1}, DataType.DOUBLE));
lists.add(NDArrayCreationUtil.getAll5dTestArraysWithShape(12345, new int[]{3, 4, 5, 6, 7}, DataType.DOUBLE));
lists.add(NDArrayCreationUtil.getAll6dTestArraysWithShape(12345, new int[]{3, 4, 5, 6, 7, 8}, DataType.DOUBLE));
val shapes = new long[][] {{3, 4}, {1, 4}, {3, 1}, {3, 4, 5}, {3, 4, 5, 6}, {3, 1, 5, 1}, {3, 4, 5, 6, 7}, {3, 4, 5, 6, 7, 8}};
for (int i = 0; i < shapes.length; i++) {
List<Pair<INDArray, String>> list = lists.get(i);
val shape = shapes[i];
for (Pair<INDArray, String> p : list) {
INDArray arr = p.getFirst();
assertArrayEquals(shape, arr.shape());
val thisStride = arr.stride();
val ib = arr.shapeInfo();
DataBuffer db = arr.shapeInfoDataBuffer();
//Check shape calculation
assertEquals(shape.length, Shape.rank(ib));
assertEquals(shape.length, Shape.rank(db));
assertArrayEquals(shape, Shape.shape(ib));
assertArrayEquals(shape, Shape.shape(db));
for (int j = 0; j < shape.length; j++) {
assertEquals(shape[j], Shape.size(ib, j));
assertEquals(shape[j], Shape.size(db, j));
assertEquals(thisStride[j], Shape.stride(ib, j));
assertEquals(thisStride[j], Shape.stride(db, j));
}
//Check base offset
assertEquals(Shape.offset(ib), Shape.offset(db));
//Check offset calculation:
NdIndexIterator iter = new NdIndexIterator(shape);
while (iter.hasNext()) {
val next = iter.next();
long offset1 = Shape.getOffset(ib, next);
assertEquals(offset1, Shape.getOffset(db, next));
switch (shape.length) {
case 2:
assertEquals(offset1, Shape.getOffset(ib, next[0], next[1]));
assertEquals(offset1, Shape.getOffset(db, next[0], next[1]));
break;
case 3:
assertEquals(offset1, Shape.getOffset(ib, next[0], next[1], next[2]));
assertEquals(offset1, Shape.getOffset(db, next[0], next[1], next[2]));
break;
case 4:
assertEquals(offset1, Shape.getOffset(ib, next[0], next[1], next[2], next[3]));
assertEquals(offset1, Shape.getOffset(db, next[0], next[1], next[2], next[3]));
break;
case 5:
case 6:
//No 5 and 6d getOffset overloads
break;
default:
throw new RuntimeException();
}
}
}
}
}
