本文整理了Java中org.nd4j.linalg.factory.Nd4j.createBuffer()方法的一些代码示例，展示了Nd4j.createBuffer()的具体用法。这些代码示例主要来源于Github/Stackoverflow/Maven等平台，是从一些精选项目中提取出来的代码，具有较强的参考意义，能在一定程度帮忙到你。Nd4j.createBuffer()方法的具体详情如下：
包路径：org.nd4j.linalg.factory.Nd4j
类名称：Nd4j
方法名：createBuffer

Nd4j.createBuffer介绍

[英]Creates a buffer of the specified length based on the data opType
[中]基于数据类型创建指定长度的缓冲区

代码示例

代码示例来源：origin: deeplearning4j/nd4j

/**
 * Creates a buffer of the specified length based on the data opType
 *
 * @param length the length of te buffer
 * @return the buffer to create
 */
public static DataBuffer createBuffer(long length) {
  return createBuffer(length, true);
}

代码示例来源：origin: deeplearning4j/nd4j

public BaseComplexNDArray(float[] data, long[] shape, long[] stride, long offset, Character order) {
  this.data = Nd4j.createBuffer(data);
  /*   this.stride = ArrayUtil.copy(stride);
  this.offset = offset;
  this.ordering = order;
  init(shape);*/
  throw new UnsupportedOperationException();
}

代码示例来源：origin: deeplearning4j/nd4j

/**
 * @param data
 * @param shape
 * @param offset
 * @return
 */
@Override
public IComplexNDArray createComplex(double[] data, int[] shape, long offset) {
  return createComplex(Nd4j.createBuffer(data), shape, offset);
}

代码示例来源：origin: deeplearning4j/nd4j

/**
 * Construct an ndarray of the specified shape.
 *
 * @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 BaseNDArray(int[] shape, int[] stride, long offset, char ordering, boolean initialize) {
  this(Nd4j.createBuffer(ArrayUtil.prodLong(shape), initialize), shape, stride, offset, ordering);
}

代码示例来源：origin: deeplearning4j/nd4j

/**
 * @param data
 * @param shape
 * @param offset
 * @param ordering
 * @return
 */
@Override
public IComplexNDArray createComplex(double[] data, int[] shape, long offset, char ordering) {
  return createComplex(Nd4j.createBuffer(data), shape, offset, ordering);
}

代码示例来源：origin: deeplearning4j/nd4j

/**
 * Get the shape from
 * the given int buffer
 * @param buffer the buffer to get the shape information for
 * @return
 */
public static DataBuffer stride(DataBuffer buffer) {
  int rank = rank(buffer);
  return Nd4j.createBuffer(buffer, 1 + rank, rank);
}

代码示例来源：origin: deeplearning4j/nd4j

private void setIndexes(BaseSparseNDArrayCOO coo, boolean oneBased) {
  int incr = oneBased ? 1 : 0;
  int[] idx = coo.getIncludedIndices().asInt();
  int[] rows = new int[nnz];
  int[] cols = new int[nnz];
  for (int i = 0; i < nnz; i++) {
    rows[i] = idx[i * 2] + incr;
    cols[i] = idx[(i * 2) + 1] + incr;
  }
  rowInd = Nd4j.createBuffer(rows);
  colInd = Nd4j.createBuffer(cols);
}

代码示例来源：origin: deeplearning4j/nd4j

/**
 * Get the shape from
 * the given int buffer
 * @param buffer the buffer to get the shape information for
 * @return
 */
public static DataBuffer shapeOf(DataBuffer buffer) {
  int rank = (int) buffer.getLong(0);
  return Nd4j.createBuffer(buffer, 1, rank);
}

代码示例来源：origin: deeplearning4j/nd4j

/**
 * 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 BaseNDArray(int[] shape, int[] stride, long offset, char ordering) {
  this(Nd4j.createBuffer(ArrayUtil.prodLong(shape)), shape, stride, offset, ordering);
}

代码示例来源：origin: deeplearning4j/nd4j

/**
 *
 * @param shape
 * @param offset
 * @param ordering
 */
public BaseComplexNDArray(int[] shape, long offset, char ordering) {
  this(Nd4j.createBuffer(ArrayUtil.prodLong(shape) * 2), shape, Nd4j.getComplexStrides(shape, ordering), offset,
          ordering);
}

代码示例来源：origin: deeplearning4j/nd4j

/**
 *
 * @param shape
 */
public BaseComplexNDArray(int[] shape) {
  this(Nd4j.createBuffer(ArrayUtil.prodLong(shape) * 2), shape, Nd4j.getComplexStrides(shape));
}

代码示例来源：origin: deeplearning4j/nd4j

@Override
public INDArray create(long[] shape, long[] stride, long offset, char ordering) {
  if (shape.length == 1 && shape[0] == 0) {
    shape = new long[] {1, 1};
  }
  return create(Nd4j.createBuffer(ArrayUtil.prodLong(shape)), shape, stride, offset, ordering);
}

代码示例来源：origin: deeplearning4j/nd4j

@Override
public INDArray create(float[] data, char order) {
  int[] shape = new int[] {1, data.length};
  return create(Nd4j.createBuffer(data), shape, Nd4j.getStrides(shape, order), order, 0);
}

代码示例来源：origin: deeplearning4j/nd4j

public BaseNDArray(double[] data, long[] shape, long[] stride, long offset, char ordering) {
  setShapeInformation(Nd4j.getShapeInfoProvider().createShapeInformation(shape, stride, offset,
      Shape.elementWiseStride(shape, stride, ordering == 'f'), ordering));
  if (data != null && data.length > 0) {
    this.data = Nd4j.createBuffer(data, offset);
    if (offset >= data.length)
      throw new IllegalArgumentException("invalid offset: must be < data.length");
  }
  init(shape, stride);
}

代码示例来源：origin: deeplearning4j/nd4j

public BaseNDArray(float[] data, long[] shape, long[] stride, long offset, char ordering) {
  setShapeInformation(Nd4j.getShapeInfoProvider().createShapeInformation(shape, stride, offset,
      Shape.elementWiseStride(shape, stride, ordering == 'f'), ordering));
  if (data != null && data.length > 0) {
    this.data = Nd4j.createBuffer(data, offset);
    if (offset >= data.length)
      throw new IllegalArgumentException("invalid offset: must be < data.length");
  }
  init(shape, stride);
}

代码示例来源：origin: deeplearning4j/nd4j

protected void read(ObjectInputStream s) {
  shapeInformation = Nd4j.createBuffer(new int[Shape.shapeInfoLength(rank())], 0);
  shapeInformation.read(s);
  setShapeInformation(Pair.create(shapeInformation, shapeInformation.asLong()));
  data = Nd4j.createBuffer(length(), false);
  data().read(s);
}

代码示例来源：origin: deeplearning4j/nd4j

protected static DataBuffer internalCreateBuffer(float[] data) {
  val perfX = PerformanceTracker.getInstance().helperStartTransaction();
  val buffer = Nd4j.createBuffer(data);
  PerformanceTracker.getInstance().helperRegisterTransaction(0, perfX, data.length * Nd4j.sizeOfDataType(), MemcpyDirection.HOST_TO_HOST);
  return buffer;
}

代码示例来源：origin: deeplearning4j/nd4j

protected static DataBuffer internalCreateBuffer(int[] data) {
  val perfX = PerformanceTracker.getInstance().helperStartTransaction();
  val buffer = Nd4j.createBuffer(data);
  PerformanceTracker.getInstance().helperRegisterTransaction(0, perfX, data.length * Nd4j.sizeOfDataType(), MemcpyDirection.HOST_TO_HOST);
  return buffer;
}

代码示例来源：origin: deeplearning4j/nd4j

public BaseNDArray(DataBuffer buffer, long[] shape, long[] stride, long offset, char ordering) {
  this.data = offset > 0 ? Nd4j.createBuffer(buffer, offset, ArrayUtil.prodLong(shape)) : buffer;
  setShapeInformation(Nd4j.getShapeInfoProvider().createShapeInformation(shape, stride, offset,
      Shape.elementWiseStride(shape, stride, ordering == 'f'), ordering));
  init(shape, stride);
  // Shape.setElementWiseStride(this.shapeInfo(),Shape.elementWiseStride(shape, stride, ordering == 'f'));
}

代码示例来源：origin: deeplearning4j/nd4j

@Override
public INDArray convertToFloats() {
  if (data.dataType() == DataBuffer.Type.FLOAT)
    return this;
  val factory = Nd4j.getNDArrayFactory();
  val buffer = Nd4j.createBuffer(new long[]{this.length()}, DataBuffer.Type.FLOAT);
  factory.convertDataEx(convertType(data.dataType()), this.data().addressPointer(), DataBuffer.TypeEx.FLOAT, buffer.addressPointer(), buffer.length());
  return Nd4j.createArrayFromShapeBuffer(buffer, this.shapeInformation);
}