Java DataSetPreProcessor类代码示例

import org.nd4j.linalg.dataset.api.DataSetPreProcessor; //导入依赖的package包/类
/**
 * Pre process a dataset sequentially
 *
 * @param toPreProcess the data set to pre process
 */
@Override
public void preProcess(DataSet toPreProcess) {
    for (DataSetPreProcessor preProcessor : preProcessors) {
        preProcessor.preProcess(toPreProcess);
    }
}
 

import org.nd4j.linalg.dataset.api.DataSetPreProcessor; //导入依赖的package包/类
/**
 * Main constructor, including for multi-label regression
 *
 * @param labelIndexFrom    Index of the first target
 * @param labelIndexTo      Index of the last target, inclusive (for classification or single-output regression: same as labelIndexFrom)
 * @param numPossibleLabels Unused for regression, or number of classes for classification
 * @param regression        If true: regression. false: classification
 */
public DataVecDataSetFunction(int labelIndexFrom, int labelIndexTo, int numPossibleLabels, boolean regression,
                DataSetPreProcessor preProcessor, WritableConverter converter) {
    this.labelIndex = labelIndexFrom;
    this.labelIndexTo = labelIndexTo;
    this.numPossibleLabels = numPossibleLabels;
    this.regression = regression;
    this.preProcessor = preProcessor;
    this.converter = converter;
}
 

import org.nd4j.linalg.dataset.api.DataSetPreProcessor; //导入依赖的package包/类
/**
 * @param labelIndex Index of the label column
 * @param numPossibleLabels Number of classes for classification  (not used if regression = true)
 * @param batchSize size of examples in DataSet. Pass in total examples if including all
 * @param byteFileLen number of bytes per individual file
 * @param regression False for classification, true for regression
 * @param preProcessor DataSetPreprocessor (may be null)
 */
public DataVecByteDataSetFunction(int labelIndex, int numPossibleLabels, int batchSize, int byteFileLen,
                boolean regression, DataSetPreProcessor preProcessor) {
    this.labelIndex = labelIndex;
    this.numPossibleLabels = numPossibleLabels;
    this.batchSize = batchSize;
    this.byteFileLen = byteFileLen;
    this.regression = regression;
    this.preProcessor = preProcessor;

}
 

import org.nd4j.linalg.dataset.api.DataSetPreProcessor; //导入依赖的package包/类
/**
 * @param numPossibleLabels Number of classes for classification  (not used if regression = true)
 * @param regression False for classification, true for regression
 * @param alignmentMode Alignment mode for data. See {@link DataVecSequencePairDataSetFunction.AlignmentMode}
 * @param preProcessor DataSetPreprocessor (may be null)
 * @param converter WritableConverter (may be null)
 */
public DataVecSequencePairDataSetFunction(int numPossibleLabels, boolean regression, AlignmentMode alignmentMode,
                DataSetPreProcessor preProcessor, WritableConverter converter) {
    this.numPossibleLabels = numPossibleLabels;
    this.regression = regression;
    this.alignmentMode = alignmentMode;
    this.preProcessor = preProcessor;
    this.converter = converter;
}
 

import org.nd4j.linalg.dataset.api.DataSetPreProcessor; //导入依赖的package包/类
/**
 * @param labelIndex Index of the label column
 * @param numPossibleLabels Number of classes for classification  (not used if regression = true)
 * @param regression False for classification, true for regression
 * @param preProcessor DataSetPreprocessor (may be null)
 * @param converter WritableConverter (may be null)
 */
public DataVecSequenceDataSetFunction(int labelIndex, int numPossibleLabels, boolean regression,
                DataSetPreProcessor preProcessor, WritableConverter converter) {
    this.labelIndex = labelIndex;
    this.numPossibleLabels = numPossibleLabels;
    this.regression = regression;
    this.preProcessor = preProcessor;
    this.converter = converter;
}
 

import org.nd4j.linalg.dataset.api.DataSetPreProcessor; //导入依赖的package包/类
public void setPreProcessor(DataSetPreProcessor preProcessor) {
    throw new UnsupportedOperationException("Not implemented");
}
 

import org.nd4j.linalg.dataset.api.DataSetPreProcessor; //导入依赖的package包/类
@Override
public DataSetPreProcessor getPreProcessor() {
    throw new UnsupportedOperationException("Not implemented");
}
 

import org.nd4j.linalg.dataset.api.DataSetPreProcessor; //导入依赖的package包/类
@Override public void setPreProcessor(DataSetPreProcessor dataSetPreProcessor) {
    throw new UnsupportedOperationException("Not Implemented");
}
 

import org.nd4j.linalg.dataset.api.DataSetPreProcessor; //导入依赖的package包/类
@Override
public void setPreProcessor(DataSetPreProcessor preProcessor) {
	throw new UnsupportedOperationException();
}
 

import org.nd4j.linalg.dataset.api.DataSetPreProcessor; //导入依赖的package包/类
@Override
public  DataSetPreProcessor getPreProcessor() {
	throw new UnsupportedOperationException("Not implemented");
}
 

import org.nd4j.linalg.dataset.api.DataSetPreProcessor; //导入依赖的package包/类
public void setPreProcessor(DataSetPreProcessor preProcessor)
   {
throw new UnsupportedOperationException("Not implemented");
   }
 

import org.nd4j.linalg.dataset.api.DataSetPreProcessor; //导入依赖的package包/类
@Override
public void setPreProcessor(DataSetPreProcessor preProcessor) {
  throw new UnsupportedOperationException();
}
 

import org.nd4j.linalg.dataset.api.DataSetPreProcessor; //导入依赖的package包/类
@Override
public DataSetPreProcessor getPreProcessor() {
  throw new UnsupportedOperationException("Not implemented");
}
 

import org.nd4j.linalg.dataset.api.DataSetPreProcessor; //导入依赖的package包/类
@Override
public void setPreProcessor(DataSetPreProcessor preProcessor) {
  this.dataSetPreProcessor = preProcessor;
}
 

import org.nd4j.linalg.dataset.api.DataSetPreProcessor; //导入依赖的package包/类
@Override
public DataSetPreProcessor getPreProcessor() {
  return dataSetPreProcessor;
}