Many resources are needed to download a project. Please understand that we have to compensate our server costs. Thank you in advance. Project price only 1 $
You can buy this project and download/modify it how often you want.
/*******************************************************************************
* Copyright (c) 2015-2018 Skymind, Inc.
*
* This program and the accompanying materials are made available under the
* terms of the Apache License, Version 2.0 which is available at
* https://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.
*
* SPDX-License-Identifier: Apache-2.0
******************************************************************************/
package org.nd4j.linalg.cpu.nativecpu;
import lombok.val;
import org.bytedeco.javacpp.Pointer;
import org.nd4j.linalg.api.buffer.DataBuffer;
import org.nd4j.linalg.api.buffer.DoubleBuffer;
import org.nd4j.linalg.api.buffer.FloatBuffer;
import org.nd4j.linalg.api.buffer.LongBuffer;
import org.nd4j.linalg.api.ndarray.BaseNDArray;
import org.nd4j.linalg.api.ndarray.BaseNDArrayProxy;
import org.nd4j.linalg.api.ndarray.INDArray;
import org.nd4j.linalg.api.ndarray.JvmShapeInfo;
import org.nd4j.linalg.api.ops.performance.PerformanceTracker;
import org.nd4j.linalg.factory.Nd4j;
import org.nd4j.linalg.memory.MemcpyDirection;
import org.nd4j.linalg.workspace.WorkspaceUtils;
import java.util.List;
/**
* NDArray: (think numpy)
*
* A few things of note.
*
* An NDArray can have any number of dimensions.
*
* An NDArray is accessed via strides.
*
* Strides are how to index over
* a contiguous block of data.
*
* This block of data has 2 orders(as of right now):
* fortran and c
*
* @author Adam Gibson
*/
public class NDArray extends BaseNDArray {
static {
//invoke the override
Nd4j.getBlasWrapper();
}
public NDArray() {
super();
}
public NDArray(DataBuffer buffer, LongBuffer shapeInfo, long[] javaShapeInfo) {
this.jvmShapeInfo = new JvmShapeInfo(javaShapeInfo);
this.shapeInformation = shapeInfo;
this.data = buffer;
}
public NDArray(DataBuffer buffer) {
super(buffer);
}
public NDArray(DataBuffer buffer, int[] shape, int[] stride, long offset, char ordering) {
super(buffer, shape, stride, offset, ordering);
}
public NDArray(DataBuffer buffer, long[] shape, long[] stride, long offset, char ordering) {
super(buffer, shape, stride, offset, ordering);
}
public NDArray(double[][] data) {
super(data);
}
public NDArray(double[][] data, char ordering) {
super(data, ordering);
}
/**
* Create this ndarray with the given data and shape and 0 offset
*
* @param data the data to use
* @param shape the shape of the ndarray
* @param ordering
*/
public NDArray(float[] data, int[] shape, char ordering) {
super(data, shape, ordering);
}
/**
* @param data the data to use
* @param shape the shape of the ndarray
* @param offset the desired offset
* @param ordering the ordering of the ndarray
*/
public NDArray(float[] data, int[] shape, long offset, char ordering) {
super(data, shape, offset, ordering);
}
public NDArray(float[] data, long[] shape, long offset, char ordering) {
super(data, shape, offset, ordering);
}
public NDArray(float[] data, long[] shape, long[] stride, long offset, char ordering) {
super(data, shape, stride, offset, ordering);
}
public NDArray(double[] data, long[] shape, long[] stride, long offset, char ordering) {
super(data, shape, stride, offset, ordering);
}
public NDArray(double[] data, long[] shape, long offset, char ordering) {
super(data, shape, offset, ordering);
}
/**
* Construct an ndarray of the specified shape
* with an empty data array
*
* @param shape the shape of the ndarray
* @param stride the stride of the ndarray
* @param offset the desired offset
* @param ordering the ordering of the ndarray
*/
public NDArray(int[] shape, int[] stride, long offset, char ordering) {
super(shape, stride, offset, ordering);
}
public NDArray(long[] shape, long[] stride, long offset, char ordering) {
super(shape, stride, offset, ordering);
}
/**
* Construct an ndarray of the specified shape, with optional initialization
*
* @param shape the shape of the ndarray
* @param stride the stride of the ndarray
* @param offset the desired offset
* @param ordering the ordering of the ndarray
* @param initialize Whether to initialize the INDArray. If true: initialize. If false: don't.
*/
public NDArray(int[] shape, int[] stride, long offset, char ordering, boolean initialize) {
super(shape, stride, offset, ordering, initialize);
}
public NDArray(long[] shape, long[] stride, long offset, char ordering, boolean initialize) {
super(shape, stride, offset, ordering, initialize);
}
/**
* Create the ndarray with
* the specified shape and stride and an offset of 0
*
* @param shape the shape of the ndarray
* @param stride the stride of the ndarray
* @param ordering the ordering of the ndarray
*/
public NDArray(int[] shape, int[] stride, char ordering) {
super(shape, stride, ordering);
}
public NDArray(int[] shape, long offset, char ordering) {
super(shape, offset, ordering);
}
public NDArray(int[] shape) {
super(shape);
}
/**
* Creates a new n times mDoubleMatrix.
*
* @param newRows the number of rows (n) of the new matrix.
* @param newColumns the number of columns (m) of the new matrix.
* @param ordering
*/
public NDArray(int newRows, int newColumns, char ordering) {
super(newRows, newColumns, ordering);
}
public NDArray(long newRows, long newColumns, char ordering) {
super(newRows, newColumns, ordering);
}
/**
* Create an ndarray from the specified slices.
* This will go through and merge all of the
* data from each slice in to one ndarray
* which will then take the specified shape
*
* @param slices the slices to merge
* @param shape the shape of the ndarray
* @param ordering
*/
public NDArray(List slices, int[] shape, char ordering) {
super(slices, shape, ordering);
}
public NDArray(List slices, long[] shape, char ordering) {
super(slices, shape, ordering);
}
/**
* Create an ndarray from the specified slices.
* This will go through and merge all of the
* data from each slice in to one ndarray
* which will then take the specified shape
*
* @param slices the slices to merge
* @param shape the shape of the ndarray
* @param stride
* @param ordering
*/
public NDArray(List slices, int[] shape, int[] stride, char ordering) {
super(slices, shape, stride, ordering);
}
public NDArray(float[] data, int[] shape, int[] stride, char ordering) {
super(data, shape, stride, ordering);
}
public NDArray(float[] data, int[] shape, int[] stride, long offset, char ordering) {
super(data, shape, stride, offset, ordering);
}
/**
* Create this ndarray with the given data and shape and 0 offset
*
* @param data the data to use
* @param shape the shape of the ndarray
*/
public NDArray(float[] data, int[] shape) {
super(data, shape);
}
public NDArray(float[] data, int[] shape, long offset) {
super(data, shape, offset);
}
/**
* Construct an ndarray of the specified shape
* with an empty data array
*
* @param shape the shape of the ndarray
* @param stride the stride of the ndarray
* @param offset the desired offset
*/
public NDArray(int[] shape, int[] stride, long offset) {
super(shape, stride, offset);
}
public NDArray(long[] shape, long[] stride, long offset) {
super(shape, stride, offset);
}
/**
* Create the ndarray with
* the specified shape and stride and an offset of 0
*
* @param shape the shape of the ndarray
* @param stride the stride of the ndarray
*/
public NDArray(int[] shape, int[] stride) {
super(shape, stride);
}
public NDArray(int[] shape, long offset) {
super(shape, offset);
}
public NDArray(int[] shape, char ordering) {
super(shape, ordering);
}
/**
* Creates a new n times mDoubleMatrix.
*
* @param newRows the number of rows (n) of the new matrix.
* @param newColumns the number of columns (m) of the new matrix.
*/
public NDArray(int newRows, int newColumns) {
super(newRows, newColumns);
}
public NDArray(long newRows, long newColumns) {
super(newRows, newColumns);
}
/**
* Create an ndarray from the specified slices.
* This will go through and merge all of the
* data from each slice in to one ndarray
* which will then take the specified shape
*
* @param slices the slices to merge
* @param shape the shape of the ndarray
*/
public NDArray(List slices, int[] shape) {
super(slices, shape);
}
public NDArray(List slices, long[] shape) {
super(slices, shape);
}
/**
* Create an ndarray from the specified slices.
* This will go through and merge all of the
* data from each slice in to one ndarray
* which will then take the specified shape
*
* @param slices the slices to merge
* @param shape the shape of the ndarray
* @param stride
*/
public NDArray(List slices, int[] shape, int[] stride) {
super(slices, shape, stride);
}
public NDArray(List slices, long[] shape, long[] stride) {
super(slices, shape, stride);
}
public NDArray(float[] data, int[] shape, int[] stride) {
super(data, shape, stride);
}
public NDArray(float[] data, int[] shape, int[] stride, long offset) {
super(data, shape, stride, offset);
}
public NDArray(float[] data) {
super(data);
}
public NDArray(double[] data, int[] shape, int[] stride, long offset) {
super(data, shape, stride, offset);
}
public NDArray(float[][] floats) {
super(floats);
}
public NDArray(float[][] data, char ordering) {
super(data, ordering);
}
public NDArray(DataBuffer data, int[] shape, int[] stride, long offset) {
super(data, shape, stride, offset);
}
public NDArray(int[] data, int[] shape, int[] strides) {
super(data, shape, strides);
}
public NDArray(DataBuffer data, int[] shape) {
super(data, shape);
}
public NDArray(DataBuffer data, long[] shape) {
super(data, shape);
}
public NDArray(DataBuffer buffer, int[] shape, long offset) {
super(buffer, shape, offset);
}
public NDArray(DataBuffer buffer, int[] shape, char ordering) {
super(buffer, shape, ordering);
}
public NDArray(double[] data, int[] shape, char ordering) {
super(data, shape, ordering);
}
public NDArray(double[] data, long[] shape, char ordering) {
super(data, shape, ordering);
}
public NDArray(double[] data, int[] shape, int[] stride, long offset, char ordering) {
super(data, shape, stride, offset, ordering);
}
public NDArray(float[] data, char order) {
super(data, order);
}
public NDArray(FloatBuffer floatBuffer, char order) {
super(floatBuffer, order);
}
public NDArray(DataBuffer buffer, int[] shape, int[] strides) {
super(buffer, shape, strides);
}
public NDArray(DoubleBuffer buffer, int[] shape, char ordering) {
super(buffer, shape, 0, ordering);
}
public NDArray(DoubleBuffer buffer, int[] shape, long offset) {
super(buffer, shape, offset);
}
public NDArray(int[] shape, DataBuffer buffer) {
super(shape, buffer);
}
private Object writeReplace() throws java.io.ObjectStreamException {
return new BaseNDArrayProxy(this);
}
/**
* This method does direct array copy. Impossible to use on views or mixed orders.
*
* PLEASE NOTE: YOU SHOULD NEVER USE THIS METHOD, UNLESS YOU 100% CLEAR ABOUT IT
*
* @return
*/
@Override
public INDArray unsafeDuplication() {
WorkspaceUtils.assertValidArray(this, "Cannot duplicate array");
if (isView())
return this.dup(this.ordering());
DataBuffer rb = Nd4j.getMemoryManager().getCurrentWorkspace() == null ? Nd4j.getDataBufferFactory().createSame(this.data, false) : Nd4j.getDataBufferFactory().createSame(this.data, false, Nd4j.getMemoryManager().getCurrentWorkspace());
INDArray ret = Nd4j.createArrayFromShapeBuffer(rb, this.shapeInfoDataBuffer());
val perfD = PerformanceTracker.getInstance().helperStartTransaction();
Pointer.memcpy(ret.data().addressPointer(), this.data().addressPointer(), this.data().length() * this.data().getElementSize());
PerformanceTracker.getInstance().helperRegisterTransaction(0, perfD, this.data().length() * this.data().getElementSize(), MemcpyDirection.HOST_TO_HOST);
return ret;
}
@Override
public INDArray unsafeDuplication(boolean blocking) {
return unsafeDuplication();
}
}
