SequenceRecordReaderDataSetIterator (deeplearning4j 1.0.0-beta7 API)

java.lang.Object
- org.deeplearning4j.datasets.datavec.SequenceRecordReaderDataSetIterator

All Implemented Interfaces:

Serializable, Iterator<DataSet>, DataSetIterator

Direct Known Subclasses:

UciSequenceDataSetIterator
```
public class SequenceRecordReaderDataSetIterator
extends Object
implements DataSetIterator
```
Sequence record reader data set iterator.
Given a record reader (and optionally another record reader for the labels) generate time series (sequence) data sets.
Supports padding for one-to-many and many-to-one type data loading (i.e., with different number of inputs vs. labels via the SequenceRecordReaderDataSetIterator.AlignmentMode mode.

Author:

Alex Black

See Also:

Serialized Form

Nested Class Summary

Nested Classes
Modifier and Type	Class and Description
`static class`	`SequenceRecordReaderDataSetIterator.AlignmentMode` Alignment mode for dealing with input/labels of differing lengths (for example, one-to-many and many-to-one type situations).

Constructor Summary

Constructors
Constructor and Description
`SequenceRecordReaderDataSetIterator(SequenceRecordReader reader, int miniBatchSize, int numPossibleLabels, int labelIndex)` Constructor where features and labels come from the SAME RecordReader (i.e., target/label is a column in the same data as the features).
`SequenceRecordReaderDataSetIterator(SequenceRecordReader reader, int miniBatchSize, int numPossibleLabels, int labelIndex, boolean regression)` Constructor where features and labels come from the SAME RecordReader (i.e., target/label is a column in the same data as the features)
`SequenceRecordReaderDataSetIterator(SequenceRecordReader featuresReader, SequenceRecordReader labels, int miniBatchSize, int numPossibleLabels)` Constructor where features and labels come from different RecordReaders (for example, different files), and labels are for classification.
`SequenceRecordReaderDataSetIterator(SequenceRecordReader featuresReader, SequenceRecordReader labels, int miniBatchSize, int numPossibleLabels, boolean regression)` Constructor where features and labels come from different RecordReaders (for example, different files)
`SequenceRecordReaderDataSetIterator(SequenceRecordReader featuresReader, SequenceRecordReader labels, int miniBatchSize, int numPossibleLabels, boolean regression, SequenceRecordReaderDataSetIterator.AlignmentMode alignmentMode)` Constructor where features and labels come from different RecordReaders (for example, different files)

Method Summary

All Methods Instance Methods Concrete Methods
Modifier and Type	Method and Description
`boolean`	`asyncSupported()` Does this DataSetIterator support asynchronous prefetching of multiple DataSet objects?
`int`	`batch()` Batch size
`List<String>`	`getLabels()` Get dataset iterator class labels, if any.
`boolean`	`hasNext()`
`int`	`inputColumns()` Input columns for the dataset
`DataSet`	`loadFromMetaData(List<RecordMetaData> list)` Load a multiple sequence examples to a DataSet, using the provided RecordMetaData instances.
`DataSet`	`loadFromMetaData(RecordMetaData recordMetaData)` Load a single sequence example to a DataSet, using the provided RecordMetaData.
`DataSet`	`next()`
`DataSet`	`next(int num)` Like the standard next method but allows a customizable number of examples returned
`void`	`remove()`
`void`	`reset()` Resets the iterator back to the beginning
`boolean`	`resetSupported()` Is resetting supported by this DataSetIterator?
`void`	`setPreProcessor(DataSetPreProcessor preProcessor)` Set a pre processor
`int`	`totalOutcomes()` The number of labels for the dataset

Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Methods inherited from interface org.nd4j.linalg.dataset.api.iterator.DataSetIterator
getPreProcessor

Methods inherited from interface java.util.Iterator
forEachRemaining

- Constructor Detail
  - SequenceRecordReaderDataSetIterator
```
public SequenceRecordReaderDataSetIterator(SequenceRecordReader featuresReader,
                                           SequenceRecordReader labels,
                                           int miniBatchSize,
                                           int numPossibleLabels)
```
    Constructor where features and labels come from different RecordReaders (for example, different files), and labels are for classification.
    
    Parameters:
    
    featuresReader - SequenceRecordReader for the features
    
    labels - Labels: assume single value per time step, where values are integers in the range 0 to numPossibleLables-1
    
    miniBatchSize - Minibatch size for each call of next()
    
    numPossibleLabels - Number of classes for the labels
  - SequenceRecordReaderDataSetIterator
```
public SequenceRecordReaderDataSetIterator(SequenceRecordReader featuresReader,
                                           SequenceRecordReader labels,
                                           int miniBatchSize,
                                           int numPossibleLabels,
                                           boolean regression)
```
    Constructor where features and labels come from different RecordReaders (for example, different files)
  - SequenceRecordReaderDataSetIterator
```
public SequenceRecordReaderDataSetIterator(SequenceRecordReader featuresReader,
                                           SequenceRecordReader labels,
                                           int miniBatchSize,
                                           int numPossibleLabels,
                                           boolean regression,
                                           SequenceRecordReaderDataSetIterator.AlignmentMode alignmentMode)
```
    Constructor where features and labels come from different RecordReaders (for example, different files)
  - SequenceRecordReaderDataSetIterator
```
public SequenceRecordReaderDataSetIterator(SequenceRecordReader reader,
                                           int miniBatchSize,
                                           int numPossibleLabels,
                                           int labelIndex)
```
    Constructor where features and labels come from the SAME RecordReader (i.e., target/label is a column in the same data as the features). Defaults to regression = false - i.e., for classification
    
    Parameters:
    
    reader - SequenceRecordReader with data
    
    miniBatchSize - size of each minibatch
    
    numPossibleLabels - number of labels/classes for classification
    
    labelIndex - index in input of the label index. If in regression mode and numPossibleLabels > 1, labelIndex denotes the first index for labels. Everything before that index will be treated as input(s) and everything from that index (inclusive) to the end will be treated as output(s)
  - SequenceRecordReaderDataSetIterator
```
public SequenceRecordReaderDataSetIterator(SequenceRecordReader reader,
                                           int miniBatchSize,
                                           int numPossibleLabels,
                                           int labelIndex,
                                           boolean regression)
```
    Constructor where features and labels come from the SAME RecordReader (i.e., target/label is a column in the same data as the features)
    
    Parameters:
    
    reader - SequenceRecordReader with data
    
    miniBatchSize - size of each minibatch
    
    numPossibleLabels - number of labels/classes for classification
    
    labelIndex - index in input of the label index. If in regression mode and numPossibleLabels > 1, labelIndex denotes the first index for labels. Everything before that index will be treated as input(s) and everything from that index (inclusive) to the end will be treated as output(s)
    
    regression - Whether output is for regression or classification
- Method Detail
  - hasNext
```
public boolean hasNext()
```
    Specified by:
    
    hasNext in interface Iterator<DataSet>
  - next
```
public DataSet next()
```
    Specified by:
    
    next in interface Iterator<DataSet>
  - next
```
public DataSet next(int num)
```
    Description copied from interface: DataSetIterator
    
    Like the standard next method but allows a customizable number of examples returned
    
    Specified by:
    
    next in interface DataSetIterator
    
    Parameters:
    
    num - the number of examples
    
    Returns:
    
    the next data applyTransformToDestination
  - inputColumns
```
public int inputColumns()
```
    Description copied from interface: DataSetIterator
    
    Input columns for the dataset
    
    Specified by:
    
    inputColumns in interface DataSetIterator
    
    Returns:
  - totalOutcomes
```
public int totalOutcomes()
```
    Description copied from interface: DataSetIterator
    
    The number of labels for the dataset
    
    Specified by:
    
    totalOutcomes in interface DataSetIterator
    
    Returns:
  - resetSupported
```
public boolean resetSupported()
```
    Description copied from interface: DataSetIterator
    
    Is resetting supported by this DataSetIterator? Many DataSetIterators do support resetting, but some don't
    
    Specified by:
    
    resetSupported in interface DataSetIterator
    
    Returns:
    
    true if reset method is supported; false otherwise
  - asyncSupported
```
public boolean asyncSupported()
```
    Description copied from interface: DataSetIterator
    
    Does this DataSetIterator support asynchronous prefetching of multiple DataSet objects? Most DataSetIterators do, but in some cases it may not make sense to wrap this iterator in an iterator that does asynchronous prefetching. For example, it would not make sense to use asynchronous prefetching for the following types of iterators: (a) Iterators that store their full contents in memory already (b) Iterators that re-use features/labels arrays (as future next() calls will overwrite past contents) (c) Iterators that already implement some level of asynchronous prefetching (d) Iterators that may return different data depending on when the next() method is called
    
    Specified by:
    
    asyncSupported in interface DataSetIterator
    
    Returns:
    
    true if asynchronous prefetching from this iterator is OK; false if asynchronous prefetching should not be used with this iterator
  - reset
```
public void reset()
```
    Description copied from interface: DataSetIterator
    
    Resets the iterator back to the beginning
    
    Specified by:
    
    reset in interface DataSetIterator
  - batch
```
public int batch()
```
    Description copied from interface: DataSetIterator
    
    Batch size
    
    Specified by:
    
    batch in interface DataSetIterator
    
    Returns:
  - setPreProcessor
```
public void setPreProcessor(DataSetPreProcessor preProcessor)
```
    Description copied from interface: DataSetIterator
    
    Set a pre processor
    
    Specified by:
    
    setPreProcessor in interface DataSetIterator
    
    Parameters:
    
    preProcessor - a pre processor to set
  - getLabels
```
public List<String> getLabels()
```
    Description copied from interface: DataSetIterator
    
    Get dataset iterator class labels, if any. Note that implementations are not required to implement this, and can simply return null
    
    Specified by:
    
    getLabels in interface DataSetIterator
  - remove
```
public void remove()
```
    Specified by:
    
    remove in interface Iterator<DataSet>
  - loadFromMetaData
```
public DataSet loadFromMetaData(RecordMetaData recordMetaData)
                         throws IOException
```
    Load a single sequence example to a DataSet, using the provided RecordMetaData. Note that it is more efficient to load multiple instances at once, using loadFromMetaData(List)
    
    Parameters:
    
    recordMetaData - RecordMetaData to load from. Should have been produced by the given record reader
    
    Returns:
    
    DataSet with the specified example
    
    Throws:
    
    IOException - If an error occurs during loading of the data
  - loadFromMetaData
```
public DataSet loadFromMetaData(List<RecordMetaData> list)
                         throws IOException
```
    Load a multiple sequence examples to a DataSet, using the provided RecordMetaData instances.
    
    Parameters:
    
    list - List of RecordMetaData instances to load from. Should have been produced by the record reader provided to the SequenceRecordReaderDataSetIterator constructor
    
    Returns:
    
    DataSet with the specified examples
    
    Throws:
    
    IOException - If an error occurs during loading of the data

Class SequenceRecordReaderDataSetIterator

Nested Class Summary

Constructor Summary

Method Summary

Methods inherited from class java.lang.Object

Methods inherited from interface org.nd4j.linalg.dataset.api.iterator.DataSetIterator

Methods inherited from interface java.util.Iterator

Constructor Detail

SequenceRecordReaderDataSetIterator

SequenceRecordReaderDataSetIterator

SequenceRecordReaderDataSetIterator

SequenceRecordReaderDataSetIterator

SequenceRecordReaderDataSetIterator

Method Detail

hasNext

next

next

inputColumns

totalOutcomes

resetSupported

asyncSupported

reset

batch

setPreProcessor

getLabels

remove

loadFromMetaData

loadFromMetaData