本文整理了Java中org.nd4j.linalg.factory.Nd4j.getNDArrayFactory()方法的一些代码示例，展示了Nd4j.getNDArrayFactory()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.getNDArrayFactory()方法的具体详情如下：
包路径：org.nd4j.linalg.factory.Nd4j
类名称：Nd4j
方法名：getNDArrayFactory

Nd4j.getNDArrayFactory介绍

暂无

代码示例

代码示例来源：origin: deeplearning4j/nd4j

/**
 * Sort an ndarray along a particular dimension<br>
 * Note that the input array is modified in-place.
 *
 * @param ndarray   the ndarray to sort
 * @param dimension the dimension to sort
 * @return the sorted ndarray
 */
public static INDArray sort(INDArray ndarray, int dimension, boolean ascending) {
  return getNDArrayFactory().sort(ndarray, !ascending, dimension);
}

代码示例来源：origin: deeplearning4j/nd4j

public static INDArray sort(INDArray ndarray, boolean ascending) {
  return getNDArrayFactory().sort(ndarray, !ascending);
}

代码示例来源：origin: deeplearning4j/nd4j

@Override
public DataBuffer compress(DataBuffer buffer) {
  DataBuffer result = Nd4j.getNDArrayFactory().convertDataEx(getBufferTypeEx(buffer), buffer,
          DataBuffer.TypeEx.FLOAT16);
  return result;
}

代码示例来源：origin: deeplearning4j/nd4j

@Override
public DataBuffer compress(DataBuffer buffer) {
  DataBuffer result = Nd4j.getNDArrayFactory().convertDataEx(getBufferTypeEx(buffer), buffer,
          DataBuffer.TypeEx.INT16);
  return result;
}

代码示例来源：origin: deeplearning4j/nd4j

@Override
public DataBuffer decompress(DataBuffer buffer) {
  val type = getGlobalTypeEx();
  DataBuffer result = Nd4j.getNDArrayFactory().convertDataEx(DataBuffer.TypeEx.FLOAT16, buffer, type);
  return result;
}

代码示例来源：origin: deeplearning4j/nd4j

@Override
public DataBuffer decompress(DataBuffer buffer) {
  DataBuffer result = Nd4j.getNDArrayFactory().convertDataEx(DataBuffer.TypeEx.UINT8, buffer, getGlobalTypeEx());
  return result;
}

代码示例来源：origin: deeplearning4j/nd4j

@Override
public DataBuffer compress(DataBuffer buffer) {
  DataBuffer result = Nd4j.getNDArrayFactory().convertDataEx(getBufferTypeEx(buffer), buffer,
          DataBuffer.TypeEx.UINT8);
  return result;
}

代码示例来源：origin: deeplearning4j/nd4j

@Override
public DataBuffer compress(DataBuffer buffer) {
  DataBuffer result = Nd4j.getNDArrayFactory().convertDataEx(getBufferTypeEx(buffer), buffer,
          DataBuffer.TypeEx.FLOAT8);
  return result;
}

代码示例来源：origin: deeplearning4j/nd4j

@Override
public DataBuffer decompress(DataBuffer buffer) {
  DataBuffer result = Nd4j.getNDArrayFactory().convertDataEx(DataBuffer.TypeEx.INT8, buffer, getGlobalTypeEx());
  return result;
}

代码示例来源：origin: deeplearning4j/nd4j

@Override
public DataBuffer decompress(DataBuffer buffer) {
  DataBuffer result = Nd4j.getNDArrayFactory().convertDataEx(DataBuffer.TypeEx.FLOAT8, buffer, getGlobalTypeEx());
  return result;
}

代码示例来源：origin: deeplearning4j/nd4j

@Override
public DataBuffer compress(DataBuffer buffer) {
  DataBuffer result =
          Nd4j.getNDArrayFactory().convertDataEx(getBufferTypeEx(buffer), buffer, DataBuffer.TypeEx.INT8);
  return result;
}

代码示例来源：origin: deeplearning4j/nd4j

@Override
public DataBuffer decompress(DataBuffer buffer) {
  DataBuffer result = Nd4j.getNDArrayFactory().convertDataEx(DataBuffer.TypeEx.INT16, buffer, getGlobalTypeEx());
  return result;
}

代码示例来源：origin: deeplearning4j/nd4j

@Override
public INDArray percentile(Number quantile, int... dimension) {
  if (quantile.doubleValue() < 0 || quantile.doubleValue() > 100)
    throw new ND4JIllegalStateException("Percentile value should be in 0...100 range");
  if (isScalar())
    return Nd4j.scalar(this.getDouble(0));
  INDArray sorted = Nd4j.getNDArrayFactory().sort(this.dup(this.ordering()), false, dimension);
  // there's no practical sense doing this on GPU, stride will be just size of TAD.
  INDArray ret = Nd4j.createUninitialized(sorted.tensorssAlongDimension(dimension));
  for (int i = 0; i < ret.length(); i++) {
    ret.putScalar(i, getPercentile(quantile, sorted.tensorAlongDimension(i, dimension)));
  }
  return ret;
}

代码示例来源：origin: deeplearning4j/nd4j

@Override
public INDArray percentile(Number quantile, int... dimension) {
  if (quantile.doubleValue() < 0 || quantile.doubleValue() > 100)
    throw new ND4JIllegalStateException("Percentile value should be in 0...100 range");
  if (isScalar())
    return Nd4j.scalar(this.getDouble(0));
  INDArray sorted = Nd4j.getNDArrayFactory().sort(this.dup(this.ordering()), false, dimension);
  // there's no practical sense doing this on GPU, stride will be just size of TAD.
  INDArray ret = Nd4j.createUninitialized(sorted.tensorssAlongDimension(dimension));
  for (int i = 0; i < ret.length(); i++) {
    ret.putScalar(i, getPercentile(quantile, sorted.tensorAlongDimension(i, dimension)));
  }
  return ret;
}

代码示例来源：origin: deeplearning4j/nd4j

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

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);
}

代码示例来源：origin: deeplearning4j/nd4j

@Override
  protected CompressedDataBuffer compressPointer(DataBuffer.TypeEx srcType, Pointer srcPointer, int length,
          int elementSize) {
    BytePointer ptr = new BytePointer(length);
    CompressionDescriptor descriptor = new CompressionDescriptor();
    descriptor.setCompressedLength(length * 1);
    descriptor.setOriginalLength(length * elementSize);
    descriptor.setOriginalElementSize(elementSize);
    descriptor.setNumberOfElements(length);
    descriptor.setCompressionAlgorithm(getDescriptor());
    descriptor.setCompressionType(getCompressionType());
    CompressedDataBuffer buffer = new CompressedDataBuffer(ptr, descriptor);
    Nd4j.getNDArrayFactory().convertDataEx(srcType, srcPointer, DataBuffer.TypeEx.UINT8, ptr, length);
    return buffer;
  }
}

代码示例来源：origin: deeplearning4j/nd4j

@Override
  protected CompressedDataBuffer compressPointer(DataBuffer.TypeEx srcType, Pointer srcPointer, int length,
          int elementSize) {
    BytePointer ptr = new BytePointer(length);
    CompressionDescriptor descriptor = new CompressionDescriptor();
    descriptor.setCompressedLength(length * 1);
    descriptor.setOriginalLength(length * elementSize);
    descriptor.setOriginalElementSize(elementSize);
    descriptor.setNumberOfElements(length);
    descriptor.setCompressionAlgorithm(getDescriptor());
    descriptor.setCompressionType(getCompressionType());
    CompressedDataBuffer buffer = new CompressedDataBuffer(ptr, descriptor);
    Nd4j.getNDArrayFactory().convertDataEx(srcType, srcPointer, DataBuffer.TypeEx.FLOAT8, ptr, length);
    return buffer;
  }
}

代码示例来源：origin: deeplearning4j/nd4j

@Override
  protected CompressedDataBuffer compressPointer(DataBuffer.TypeEx srcType, Pointer srcPointer, int length,
          int elementSize) {
    BytePointer ptr = new BytePointer(length * 2);
    CompressionDescriptor descriptor = new CompressionDescriptor();
    descriptor.setCompressedLength(length * 2);
    descriptor.setOriginalLength(length * elementSize);
    descriptor.setOriginalElementSize(elementSize);
    descriptor.setNumberOfElements(length);
    descriptor.setCompressionAlgorithm(getDescriptor());
    descriptor.setCompressionType(getCompressionType());
    CompressedDataBuffer buffer = new CompressedDataBuffer(ptr, descriptor);
    Nd4j.getNDArrayFactory().convertDataEx(srcType, srcPointer, DataBuffer.TypeEx.INT16, ptr, length);
    return buffer;
  }
}

代码示例来源：origin: deeplearning4j/nd4j

@Override
  protected CompressedDataBuffer compressPointer(DataBuffer.TypeEx srcType, Pointer srcPointer, int length,
          int elementSize) {
    BytePointer ptr = new BytePointer(length * 2);
    CompressionDescriptor descriptor = new CompressionDescriptor();
    descriptor.setCompressedLength(length * 2);
    descriptor.setOriginalLength(length * elementSize);
    descriptor.setOriginalElementSize(elementSize);
    descriptor.setNumberOfElements(length);
    descriptor.setCompressionAlgorithm(getDescriptor());
    descriptor.setCompressionType(getCompressionType());
    CompressedDataBuffer buffer = new CompressedDataBuffer(ptr, descriptor);
    Nd4j.getNDArrayFactory().convertDataEx(srcType, srcPointer, DataBuffer.TypeEx.FLOAT16, ptr, length);
    return buffer;
  }
}