org.nd4j.linalg.factory.Nd4j.clearNans()方法的使用及代码示例

x33g5p2x  于2022-01-24 转载在 其他  
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本文整理了Java中org.nd4j.linalg.factory.Nd4j.clearNans()方法的一些代码示例,展示了Nd4j.clearNans()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.clearNans()方法的具体详情如下:
包路径:org.nd4j.linalg.factory.Nd4j
类名称:Nd4j
方法名:clearNans

Nd4j.clearNans介绍

[英]Clear nans from an ndarray
[中]把南斯从黑暗中清除出去

代码示例

代码示例来源:origin: deeplearning4j/nd4j

@Override
public INDArray rsubi(Number n, INDArray result) {
  if (Double.isNaN(n.doubleValue()))
    n = Nd4j.EPS_THRESHOLD;
  Nd4j.getExecutioner().exec(new ScalarReverseSubtraction(this, null, result, result.lengthLong(), n));
  if (Nd4j.ENFORCE_NUMERICAL_STABILITY)
    Nd4j.clearNans(result);
  return result;
}

代码示例来源:origin: deeplearning4j/nd4j

@Override
public INDArray rdivi(Number n, INDArray result) {
  if (Double.isNaN(n.doubleValue()))
    n = Nd4j.EPS_THRESHOLD;
  Nd4j.getExecutioner().exec(new ScalarReverseDivision(this, null, result, result.length(), n));
  if (Nd4j.ENFORCE_NUMERICAL_STABILITY)
    Nd4j.clearNans(result);
  return result;
}

代码示例来源:origin: deeplearning4j/nd4j

@Override
public INDArray divi(Number n, INDArray result) {
  if (Double.isNaN(n.doubleValue()))
    n = Nd4j.EPS_THRESHOLD;
  Nd4j.getExecutioner().exec(new ScalarDivision(this, null, result, result.lengthLong(), n));
  if (Nd4j.ENFORCE_NUMERICAL_STABILITY)
    Nd4j.clearNans(result);
  return result;
}

代码示例来源:origin: deeplearning4j/nd4j

@Override
public INDArray muli(Number n, INDArray result) {
  if (Double.isNaN(n.doubleValue()))
    n = Nd4j.EPS_THRESHOLD;
  Nd4j.getExecutioner().exec(new ScalarMultiplication(this, null, result, result.lengthLong(), n));
  if (Nd4j.ENFORCE_NUMERICAL_STABILITY)
    Nd4j.clearNans(result);
  return result;
}

代码示例来源:origin: deeplearning4j/nd4j

@Override
public INDArray subi(Number n, INDArray result) {
  if (Double.isNaN(n.doubleValue()))
    n = Nd4j.EPS_THRESHOLD;
  Nd4j.getExecutioner().exec(new ScalarSubtraction(this, null, result, result.lengthLong(), n));
  if (Nd4j.ENFORCE_NUMERICAL_STABILITY)
    Nd4j.clearNans(result);
  return result;
}

代码示例来源:origin: deeplearning4j/nd4j

/**
 * in place subtraction of two matrices
 *
 * @param other  the second ndarray to subtract
 * @param result the result ndarray
 * @return the result of the subtraction
 */
@Override
public INDArray subi(INDArray other, INDArray result) {
  if (other.isScalar()) {
    return subi(other.getDouble(0), result);
  }
  if (isScalar()) {
    return other.rsubi(getDouble(0), result);
  }
  if(!Shape.shapeEquals(this.shape(),other.shape())) {
    int[] broadcastDimensions = Shape.getBroadcastDimensions(this.shape(),other.shape());
    Nd4j.getExecutioner().exec(new BroadcastSubOp(this,other,result,broadcastDimensions),broadcastDimensions);
    return result;
  }
  LinAlgExceptions.assertSameShape(other, result);
  Nd4j.getExecutioner().exec(new OldSubOp(this, other,result));
  if (Nd4j.ENFORCE_NUMERICAL_STABILITY)
    Nd4j.clearNans(result);
  return result;
}

代码示例来源:origin: deeplearning4j/nd4j

/**
 * in place (element wise) multiplication of two matrices
 *
 * @param other  the second ndarray to multiply
 * @param result the result ndarray
 * @return the result of the multiplication
 */
@Override
public INDArray muli(INDArray other, INDArray result) {
  if (other.isScalar()) {
    return muli(other.getDouble(0), result);
  }
  if (isScalar()) {
    return other.muli(getDouble(0), result);
  }
  if(!Shape.shapeEquals(this.shape(),other.shape())) {
    int[] broadcastDimensions = Shape.getBroadcastDimensions(this.shape(),other.shape());
    Nd4j.getExecutioner().exec(new BroadcastMulOp(this,other,result,broadcastDimensions),broadcastDimensions);
    return result;
  }
  LinAlgExceptions.assertSameShape(other, result);
  Nd4j.getExecutioner().exec(new OldMulOp(this, other, result, length()));
  if (Nd4j.ENFORCE_NUMERICAL_STABILITY)
    Nd4j.clearNans(result);
  return result;
}

代码示例来源:origin: deeplearning4j/nd4j

/**
 * in place (element wise) division of two matrices
 *
 * @param other  the second ndarray to divide
 * @param result the result ndarray
 * @return the result of the divide
 */
@Override
public INDArray divi(INDArray other, INDArray result) {
  if (other.isScalar()) {
    return divi(other.getDouble(0), result);
  }
  if (isScalar()) {
    return other.rdivi(getDouble(0), result);
  }
  if(!Shape.shapeEquals(this.shape(),other.shape())) {
    int[] broadcastDimensions = Shape.getBroadcastDimensions(this.shape(),other.shape());
    Nd4j.getExecutioner().exec(new BroadcastDivOp(this,other,result,broadcastDimensions),broadcastDimensions);
    return result;
  }
  LinAlgExceptions.assertSameShape(other, result);
  Nd4j.getExecutioner().exec(new OldDivOp(this, other, result, length()));
  if (Nd4j.ENFORCE_NUMERICAL_STABILITY)
    Nd4j.clearNans(result);
  return result;
}

代码示例来源:origin: deeplearning4j/nd4j

/**
 * in place addition of two matrices
 *
 * @param other  the second ndarray to add
 * @param result the result ndarray
 * @return the result of the addition
 */
@Override
public INDArray addi(INDArray other, INDArray result) {
  if (other.isScalar()) {
    return result.addi(other.getDouble(0), result);
  }
  if (isScalar()) {
    return other.addi(getDouble(0), result);
  }
  if(!Shape.shapeEquals(this.shape(),other.shape())) {
    int[] broadcastDimensions = Shape.getBroadcastDimensions(this.shape(),other.shape());
    result = Nd4j.createUninitialized(Shape.broadcastOutputShape(this.shape(),other.shape()));
    Nd4j.getExecutioner().exec(new BroadcastAddOp(this,other,result,broadcastDimensions),broadcastDimensions);
    return result;
  }
  LinAlgExceptions.assertSameShape(other, result);
  Nd4j.getExecutioner().exec(new OldAddOp(this, other, result, length()));
  if (Nd4j.ENFORCE_NUMERICAL_STABILITY)
    Nd4j.clearNans(result);
  return result;
}

代码示例来源:origin: deeplearning4j/nd4j

Nd4j.clearNans(result);

代码示例来源:origin: deeplearning4j/nd4j

Nd4j.clearNans(result);
return result;

代码示例来源:origin: org.nd4j/nd4j-api

@Override
public INDArray rsubi(Number n, INDArray result) {
  if (Double.isNaN(n.doubleValue()))
    n = Nd4j.EPS_THRESHOLD;
  Nd4j.getExecutioner().exec(new ScalarReverseSubtraction(this, null, result, result.lengthLong(), n));
  if (Nd4j.ENFORCE_NUMERICAL_STABILITY)
    Nd4j.clearNans(result);
  return result;
}

代码示例来源:origin: org.nd4j/nd4j-api

@Override
public INDArray divi(Number n, INDArray result) {
  if (Double.isNaN(n.doubleValue()))
    n = Nd4j.EPS_THRESHOLD;
  Nd4j.getExecutioner().exec(new ScalarDivision(this, null, result, result.lengthLong(), n));
  if (Nd4j.ENFORCE_NUMERICAL_STABILITY)
    Nd4j.clearNans(result);
  return result;
}

代码示例来源:origin: org.nd4j/nd4j-api

@Override
public INDArray subi(Number n, INDArray result) {
  if (Double.isNaN(n.doubleValue()))
    n = Nd4j.EPS_THRESHOLD;
  Nd4j.getExecutioner().exec(new ScalarSubtraction(this, null, result, result.lengthLong(), n));
  if (Nd4j.ENFORCE_NUMERICAL_STABILITY)
    Nd4j.clearNans(result);
  return result;
}

代码示例来源:origin: org.nd4j/nd4j-api

@Override
public INDArray rdivi(Number n, INDArray result) {
  if (Double.isNaN(n.doubleValue()))
    n = Nd4j.EPS_THRESHOLD;
  Nd4j.getExecutioner().exec(new ScalarReverseDivision(this, null, result, result.length(), n));
  if (Nd4j.ENFORCE_NUMERICAL_STABILITY)
    Nd4j.clearNans(result);
  return result;
}

代码示例来源:origin: org.nd4j/nd4j-api

@Override
public INDArray muli(Number n, INDArray result) {
  if (Double.isNaN(n.doubleValue()))
    n = Nd4j.EPS_THRESHOLD;
  Nd4j.getExecutioner().exec(new ScalarMultiplication(this, null, result, result.lengthLong(), n));
  if (Nd4j.ENFORCE_NUMERICAL_STABILITY)
    Nd4j.clearNans(result);
  return result;
}

代码示例来源:origin: neo4j-graph-analytics/ml-models

@Override
public INDArray ndOp(INDArray features, INDArray adjacencyMatrix) {
  INDArray mean = adjacencyMatrix
      .mmul(features)
      .diviColumnVector(adjacencyMatrix.sum(1));
  // clear NaNs from div by 0 - these entries should have a 0 instead.
  Nd4j.clearNans(mean);
  return mean;
}

代码示例来源:origin: org.nd4j/nd4j-api

/**
 * in place addition of two matrices
 *
 * @param other  the second ndarray to add
 * @param result the result ndarray
 * @return the result of the addition
 */
@Override
public INDArray addi(INDArray other, INDArray result) {
  if (other.isScalar()) {
    return result.addi(other.getDouble(0), result);
  }
  if (isScalar()) {
    return other.addi(getDouble(0), result);
  }
  LinAlgExceptions.assertSameShape(other, result);
  Nd4j.getExecutioner().exec(new AddOp(this, other, result));
  if (Nd4j.ENFORCE_NUMERICAL_STABILITY)
    Nd4j.clearNans(result);
  return result;
}

代码示例来源:origin: org.nd4j/nd4j-api

/**
 * in place subtraction of two matrices
 *
 * @param other  the second ndarray to subtract
 * @param result the result ndarray
 * @return the result of the subtraction
 */
@Override
public INDArray subi(INDArray other, INDArray result) {
  if (other.isScalar()) {
    return subi(other.getDouble(0), result);
  }
  if (isScalar()) {
    return other.subi(getDouble(0), result);
  }
  LinAlgExceptions.assertSameShape(other, result);
  Nd4j.getExecutioner().exec(new SubOp(this, other, result, length()));
  if (Nd4j.ENFORCE_NUMERICAL_STABILITY)
    Nd4j.clearNans(result);
  return result;
}

代码示例来源:origin: org.nd4j/nd4j-api

/**
 * in place (element wise) division of two matrices
 *
 * @param other  the second ndarray to divide
 * @param result the result ndarray
 * @return the result of the divide
 */
@Override
public INDArray divi(INDArray other, INDArray result) {
  if (other.isScalar()) {
    return divi(other.getDouble(0), result);
  }
  if (isScalar()) {
    return other.divi(getDouble(0), result);
  }
  LinAlgExceptions.assertSameShape(other, result);
  Nd4j.getExecutioner().exec(new DivOp(this, other, result, length()));
  if (Nd4j.ENFORCE_NUMERICAL_STABILITY)
    Nd4j.clearNans(result);
  return result;
}

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