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

Nd4j.getExecutioner介绍

[英]Get the operation executioner instance
[中]获取操作执行器实例

代码示例

代码示例来源：origin: deeplearning4j/nd4j

@Override
public INDArray nextFloat(char order, int[] shape) {
  INDArray array = Nd4j.createUninitialized(shape, order);
  UniformDistribution op = new UniformDistribution(array, 0.0, 1.0);
  Nd4j.getExecutioner().exec(op, this);
  return array;
}

代码示例来源：origin: deeplearning4j/nd4j

/**
 * Sin function
 * @param in
 * @param copy
 * @return
 */
public static INDArray sin(INDArray in, boolean copy) {
  return Nd4j.getExecutioner().execAndReturn(new Sin((copy ? in.dup() : in)));
}

代码示例来源：origin: deeplearning4j/nd4j

@Override
public INDArray getActivation(INDArray in, boolean training) {
  Nd4j.getExecutioner().execAndReturn(new SoftSign(in));
  return in;
}

代码示例来源：origin: deeplearning4j/nd4j

/**
 * Returns non-normalized Shannon entropy along dimension
 * @param dimension
 * @return
 */
@Override
public INDArray shannonEntropy(int... dimension) {
  return Nd4j.getExecutioner().exec(new ShannonEntropy(this), dimension);
}

代码示例来源：origin: deeplearning4j/nd4j

public static void checkForInf(INDArray z) {
  if (Nd4j.getExecutioner().getProfilingMode() != OpExecutioner.ProfilingMode.INF_PANIC
          && Nd4j.getExecutioner().getProfilingMode() != OpExecutioner.ProfilingMode.ANY_PANIC)
    return;
  int match = 0;
  if (!z.isScalar()) {
    MatchCondition condition = new MatchCondition(z, Conditions.isInfinite());
    match = Nd4j.getExecutioner().exec(condition, Integer.MAX_VALUE).getInt(0);
  } else {
    if (z.data().dataType() == DataBuffer.Type.DOUBLE) {
      if (Double.isInfinite(z.getDouble(0)))
        match = 1;
    } else {
      if (Float.isInfinite(z.getFloat(0)))
        match = 1;
    }
  }
  if (match > 0)
    throw new ND4JIllegalStateException("P.A.N.I.C.! Op.Z() contains " + match + " Inf value(s)");
}

代码示例来源：origin: deeplearning4j/nd4j

@Override
public INDArray compress(INDArray array) {
  INDArray dup = array.dup(array.ordering());
  Nd4j.getExecutioner().commit();
  dup.setData(compress(dup.data()));
  dup.markAsCompressed(true);
  return dup;
}

代码示例来源：origin: deeplearning4j/nd4j

/**
 * Log on arbitrary base
 *
 * @param ndArray
 * @param base
 * @return
 */
public static INDArray log(INDArray ndArray, double base, boolean duplicate) {
  return Nd4j.getExecutioner().exec(new LogX(duplicate ? ndArray.dup(ndArray.ordering()) : ndArray, base)).z();
}

代码示例来源：origin: deeplearning4j/nd4j

@Override
public int iamax(long n, INDArray arr, int stride) {
  if (Nd4j.getExecutioner().getProfilingMode() == OpExecutioner.ProfilingMode.ALL)
    OpProfiler.getInstance().processBlasCall(false, arr);
  if (arr.data().dataType() == DataBuffer.Type.DOUBLE) {
    DefaultOpExecutioner.validateDataType(DataBuffer.Type.DOUBLE, arr);
    return idamax(n, arr, stride);
  } else {
    DefaultOpExecutioner.validateDataType(DataBuffer.Type.FLOAT, arr);
    return isamax(n, arr, stride);
  }
}

代码示例来源：origin: deeplearning4j/nd4j

/**
 * Atan2 operation, new INDArray instance will be returned
 * Note the order of x and y parameters is opposite to that of java.lang.Math.atan2
 *
 * @param x the abscissa coordinate
 * @param y the ordinate coordinate
 * @return the theta from point (r, theta) when converting (x,y) from to cartesian to polar coordinates
 */
public static INDArray atan2(@NonNull INDArray x, @NonNull INDArray y) {
  return Nd4j.getExecutioner()
          .execAndReturn(new OldAtan2Op(x, y, Nd4j.createUninitialized(x.shape(), x.ordering())));
}

代码示例来源：origin: deeplearning4j/nd4j

/**
 * Sin function
 * @param in
 * @param copy
 * @return
 */
public static INDArray atanh(INDArray in, boolean copy) {
  return Nd4j.getExecutioner().execAndReturn(new ATanh((copy ? in.dup() : in)));
}

代码示例来源：origin: deeplearning4j/nd4j

/**
 * Negate each element (in-place).
 */
@Override
public INDArray negi() {
  Nd4j.getExecutioner().exec(new Negative(this));
  return this;
}

代码示例来源：origin: deeplearning4j/nd4j

@Override
public INDArray nextGaussian(char order, int[] shape) {
  INDArray array = Nd4j.createUninitialized(shape, order);
  GaussianDistribution op = new GaussianDistribution(array, 0.0, 1.0);
  Nd4j.getExecutioner().exec(op, this);
  return array;
}

代码示例来源：origin: deeplearning4j/nd4j

@Override
public INDArray getActivation(INDArray in, boolean training) {
  Nd4j.getExecutioner().execAndReturn(new RectifiedTanh(in));
  return in;
}

代码示例来源：origin: deeplearning4j/nd4j

public static void checkForNaN(INDArray z) {
  if (Nd4j.getExecutioner().getProfilingMode() != OpExecutioner.ProfilingMode.NAN_PANIC
          && Nd4j.getExecutioner().getProfilingMode() != OpExecutioner.ProfilingMode.ANY_PANIC)
    return;
  int match = 0;
  if (!z.isScalar()) {
    MatchCondition condition = new MatchCondition(z, Conditions.isNan());
    match = Nd4j.getExecutioner().exec(condition, Integer.MAX_VALUE).getInt(0);
  } else {
    if (z.data().dataType() == DataBuffer.Type.DOUBLE) {
      if (Double.isNaN(z.getDouble(0)))
        match = 1;
    } else {
      if (Float.isNaN(z.getFloat(0)))
        match = 1;
    }
  }
  if (match > 0)
    throw new ND4JIllegalStateException("P.A.N.I.C.! Op.Z() contains " + match + " NaN value(s): ");
}

代码示例来源：origin: deeplearning4j/nd4j

/**
 * swaps a vector with another vector.
 *
 * @param x
 * @param y
 */
@Override
public void copy(INDArray x, INDArray y) {
  if (Nd4j.getExecutioner().getProfilingMode() == OpExecutioner.ProfilingMode.ALL)
    OpProfiler.getInstance().processBlasCall(false, x, y);
  if (x.isSparse() || y.isSparse()) {
    Nd4j.getSparseBlasWrapper().level1().copy(x, y);
    return;
  }
  if (x.data().dataType() == DataBuffer.Type.DOUBLE) {
    DefaultOpExecutioner.validateDataType(DataBuffer.Type.DOUBLE, x, y);
    dcopy(x.length(), x, BlasBufferUtil.getBlasStride(x), y, BlasBufferUtil.getBlasStride(y));
  } else {
    DefaultOpExecutioner.validateDataType(DataBuffer.Type.FLOAT, x, y);
    scopy(x.length(), x, BlasBufferUtil.getBlasStride(x), y, BlasBufferUtil.getBlasStride(y));
  }
}

代码示例来源：origin: deeplearning4j/nd4j

/**
 *
 * @param in
 * @param copy
 * @return
 */
public static INDArray cos(INDArray in, boolean copy) {
  return Nd4j.getExecutioner().execAndReturn(new Cos((copy ? in.dup() : in)));
}

代码示例来源：origin: deeplearning4j/nd4j

/**
 * Returns the product along a given dimension
 *
 * @param dimension the dimension to getScalar the product along
 * @return the product along the specified dimension
 */
@Override
public INDArray prod(int... dimension) {
  return Nd4j.getExecutioner().exec(new Prod(this), dimension);
}

代码示例来源：origin: deeplearning4j/nd4j

@Override
public INDArray nextGaussian(char order, long[] shape) {
  INDArray array = Nd4j.createUninitialized(shape, order);
  GaussianDistribution op = new GaussianDistribution(array, 0.0, 1.0);
  Nd4j.getExecutioner().exec(op, this);
  return array;
}

代码示例来源：origin: deeplearning4j/nd4j

@Override
public INDArray getActivation(INDArray in, boolean training) {
  Nd4j.getExecutioner().execAndReturn(new Swish(in));
  return in;
}

代码示例来源：origin: deeplearning4j/nd4j

/**
 * computes a vector by a scalar product.
 *
 * @param N
 * @param alpha
 * @param X
 */
@Override
public void scal(long N, double alpha, INDArray X) {
  if (Nd4j.getExecutioner().getProfilingMode() == OpExecutioner.ProfilingMode.ALL)
    OpProfiler.getInstance().processBlasCall(false, X);
  if (X.isSparse()) {
    Nd4j.getSparseBlasWrapper().level1().scal(N, alpha, X);
  } else if (X.data().dataType() == DataBuffer.Type.DOUBLE)
    dscal(N, alpha, X, BlasBufferUtil.getBlasStride(X));
  else if (X.data().dataType() == DataBuffer.Type.FLOAT)
    sscal(N, (float) alpha, X, BlasBufferUtil.getBlasStride(X));
  else if (X.data().dataType() == DataBuffer.Type.HALF)
    Nd4j.getExecutioner().exec(new ScalarMultiplication(X, alpha));
}