org.datavec.api.writable.Writable类的使用及代码示例

x33g5p2x  于2022-02-03 转载在 其他  
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本文整理了Java中org.datavec.api.writable.Writable类的一些代码示例，展示了Writable类的具体用法。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。Writable类的具体详情如下：
包路径：org.datavec.api.writable.Writable
类名称：Writable

Writable介绍

暂无

代码示例

代码示例来源：origin: org.datavec/datavec-spark_2.11

switch (schema.getColumnTypes().get(i)) {
  case Double:
    values[i + 2] = step.get(i).toDouble();
    break;
  case Integer:
    values[i + 2] = step.get(i).toInt();
    break;
  case Long:
    values[i + 2] = step.get(i).toLong();
    break;
  case Float:
    values[i + 2] = step.get(i).toFloat();
    break;
  default:

代码示例来源：origin: org.datavec/datavec-data-nlp

protected String toString(Collection<Writable> record) {
  ByteArrayOutputStream bos = new ByteArrayOutputStream();
  DataOutputStream dos = new DataOutputStream(bos);
  for (Writable w : record) {
    if (w instanceof Text) {
      try {
        w.write(dos);
      } catch (IOException e) {
        e.printStackTrace();
      }
    }
  }
  return new String(bos.toByteArray());
}

代码示例来源：origin: org.deeplearning4j/deeplearning4j-datavec-iterators

int classIdx = w.toInt();
  if (classIdx >= details.oneHotNumClasses) {
    throw new IllegalStateException("Cannot convert sequence writables to one-hot: class index " + classIdx
        "indexed, thus only values 0 to nClasses-1 are valid)");
  arr.putScalar(i, w.toInt(), 1.0);
} else {
        k += toPut.length();
      } else {
        arr.putScalar(i, k, w.toDouble());
        k++;

代码示例来源：origin: org.datavec/datavec-spark_2.11

@Override
  public double call(Writable writable) throws Exception {
    return writable.toDouble();
  }
}

代码示例来源：origin: org.datavec/datavec-spark

@Override
  public int compare(List<Writable> o1, List<Writable> o2) {
    return Integer.compare(o1.get(1).toInt(), o2.get(1).toInt());
  }
});

代码示例来源：origin: org.datavec/datavec-spark

@Override
public LongAnalysisCounter add(Writable writable) {
  long value = writable.toLong();
  if (value == 0)
    countZero++;
  if (value == getMinValueSeen())
    countMinValue++;
  else if (value < getMinValueSeen()) {
    countMinValue = 1;
  }
  if (value == getMaxValueSeen())
    countMaxValue++;
  else if (value > getMaxValueSeen()) {
    countMaxValue = 1;
  }
  if (value >= 0) {
    countPositive++;
  } else {
    countNegative++;
  } ;
  counter.merge((double) value);
  return this;
}

代码示例来源：origin: org.deeplearning4j/deeplearning4j-core

int classIdx = w.toInt();
  if (classIdx >= details.oneHotNumClasses) {
    throw new DL4JException("Cannot convert sequence writables to one-hot: class index " + classIdx
            + " >= numClass (" + details.oneHotNumClasses + ")");
  arr.putScalar(i, w.toInt(), 1.0);
} else {
        k += toPut.length();
      } else {
        arr.putScalar(i, k, w.toDouble());
        k++;

代码示例来源：origin: org.datavec/datavec-spark

@Override
  public double call(Writable writable) throws Exception {
    return writable.toDouble();
  }
}

代码示例来源：origin: org.datavec/datavec-spark

@Override
  public int compare(List<Writable> o1, List<Writable> o2) {
    return Integer.compare(o1.get(1).toInt(), o2.get(1).toInt());
  }
});

代码示例来源：origin: org.datavec/datavec-spark_2.11

@Override
public LongAnalysisCounter add(Writable writable) {
  long value = writable.toLong();
  if (value == 0)
    countZero++;
  if (value == getMinValueSeen())
    countMinValue++;
  else if (value < getMinValueSeen()) {
    countMinValue = 1;
  }
  if (value == getMaxValueSeen())
    countMaxValue++;
  else if (value > getMaxValueSeen()) {
    countMaxValue = 1;
  }
  if (value >= 0) {
    countPositive++;
  } else {
    countNegative++;
  } ;
  counter.merge((double) value);
  return this;
}

代码示例来源：origin: org.datavec/datavec-spark

switch (schema.getColumnTypes().get(i)) {
  case Double:
    values[i + 2] = step.get(i).toDouble();
    break;
  case Integer:
    values[i + 2] = step.get(i).toInt();
    break;
  case Long:
    values[i + 2] = step.get(i).toLong();
    break;
  case Float:
    values[i + 2] = step.get(i).toFloat();
    break;
  default:

代码示例来源：origin: org.deeplearning4j/deeplearning4j-datavec-iterators

j += row.length();
  } else {
    arr.putScalar(i, j, k, w.toDouble());
    j++;
    w = iter.next();
int classIdx = w.toInt();
if (classIdx >= details.oneHotNumClasses) {
  throw new IllegalStateException("Cannot convert sequence writables to one-hot: class index " + classIdx
    arr.putScalar(i, l++, k, w.toDouble());

代码示例来源：origin: org.datavec/datavec-spark_2.11

@Override
public HistogramCounter add(Writable w) {
  double d = w.toDouble();
  //Not super efficient, but linear search on 20-50 items should be good enough
  int idx = -1;
  for (int i = 0; i < nBins; i++) {
    if (d >= bins[i] && d < bins[i + 1]) {
      idx = i;
      break;
    }
  }
  if (idx == -1)
    idx = nBins - 1;
  binCounts[idx]++;
  return this;
}

代码示例来源：origin: org.datavec/datavec-spark_2.11

@Override
  public int compare(List<Writable> o1, List<Writable> o2) {
    return Integer.compare(o1.get(1).toInt(), o2.get(1).toInt());
  }
});

代码示例来源：origin: org.datavec/datavec-hadoop

for (Writable writable : record) {
  Writable newWritable;
  if (writable.getType() == WritableType.Text) {
    switch (convertTextTo) {
      case Byte:
        newWritable = new ByteWritable((byte) writable.toInt());
        break;
      case Double:
        newWritable = new DoubleWritable(writable.toDouble());
        break;
      case Float:
        newWritable = new FloatWritable(writable.toFloat());
        break;
      case Int:
        newWritable = new IntWritable(writable.toInt());
        break;
      case Long:
        newWritable = new org.datavec.api.writable.LongWritable(writable.toLong());
        break;
      default:

代码示例来源：origin: org.deeplearning4j/deeplearning4j-core

j += row.length();
  } else {
    arr.putScalar(i, j, k, w.toDouble());
    j++;
    w = iter.next();
int classIdx = w.toInt();
if (classIdx >= details.oneHotNumClasses) {
  throw new DL4JException("Cannot convert sequence writables to one-hot: class index " + classIdx
    arr.putScalar(i, l++, k, w.toDouble());

代码示例来源：origin: org.datavec/datavec-spark

@Override
public HistogramCounter add(Writable w) {
  double d = w.toDouble();
  //Not super efficient, but linear search on 20-50 items should be good enough
  int idx = -1;
  for (int i = 0; i < nBins; i++) {
    if (d >= bins[i] && d < bins[i + 1]) {
      idx = i;
      break;
    }
  }
  if (idx == -1)
    idx = nBins - 1;
  binCounts[idx]++;
  return this;
}

代码示例来源：origin: org.datavec/datavec-spark_2.11

@Override
  public int compare(List<Writable> o1, List<Writable> o2) {
    return Integer.compare(o1.get(1).toInt(), o2.get(1).toInt());
  }
});

代码示例来源：origin: org.datavec/datavec-spark_2.11

switch (schema.getColumnTypes().get(i)) {
  case Double:
    values[i] = v1.get(i).toDouble();
    break;
  case Integer:
    values[i] = v1.get(i).toInt();
    break;
  case Long:
    values[i] = v1.get(i).toLong();
    break;
  case Float:
    values[i] = v1.get(i).toFloat();
    break;
  default:

代码示例来源：origin: org.datavec/datavec-spark_2.11

@Override
public DoubleAnalysisCounter add(Writable writable) {
  double value = writable.toDouble();
  if (value == 0)
    countZero++;
  if (value == Double.NaN)
    countNaN++;
  if (value == getMinValueSeen())
    countMinValue++;
  else if (value < getMinValueSeen()) {
    countMinValue = 1;
  }
  if (value == getMaxValueSeen())
    countMaxValue++;
  else if (value > getMaxValueSeen()) {
    countMaxValue = 1;
  }
  if (value >= 0) {
    countPositive++;
  } else {
    countNegative++;
  } ;
  counter.merge(value);
  return this;
}

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