Package org.deeplearning4j.datasets.iterator

Interface Summary

Interface	Description
DataSetFetcher	Deprecated Retained for legacy purposes, will be removed in a future release

Class Summary

Class	Description
AbstractDataSetIterator<T>	This is simple DataSetIterator implementation, that builds DataSetIterator out of INDArray/float[]/double[] pairs.
AsyncDataSetIterator	Deprecated Use AsyncDataSetIterator
AsyncMultiDataSetIterator	Deprecated Use AsyncMultiDataSetIterator
AsyncShieldDataSetIterator	This wrapper takes your existing DataSetIterator implementation and prevents asynchronous prefetch when using methods such as MultiLayerNetwork.fit(DataSetIterator) This is mainly used for debugging purposes; generally an iterator that isn't safe to asynchronously prefetch from should simply return asyncSupported() == false
AsyncShieldMultiDataSetIterator	This wrapper takes your existing MultiDataSetIterator implementation and prevents asynchronous prefetch
BaseDatasetIterator	Baseline implementation includes control over the data fetcher and some basic getters for metadata
CombinedMultiDataSetPreProcessor	Combines various multidataset preprocessors Applied in the order they are specified to in the builder
CombinedMultiDataSetPreProcessor.Builder
CombinedPreProcessor	This is special preProcessor, that allows to combine multiple prerpocessors, and apply them to data sequentially.
CombinedPreProcessor.Builder
DataSetIteratorSplitter	This iterator virtually splits given MultiDataSetIterator into Train and Test parts.
DoublesDataSetIterator	A simple utility iterator for creating a DataSetIterator from an Iterable<Pair<double[], double[]>>.
DummyBlockDataSetIterator	This class provides baseline implementation of BlockDataSetIterator interface
DummyBlockMultiDataSetIterator	This class provides baseline implementation of BlockMultiDataSetIterator interface
DummyPreProcessor	This is special dummy preProcessor, that does nothing.
EarlyTerminationDataSetIterator	Builds an iterator that terminates once the number of minibatches returned with .next() is equal to a specified number.
EarlyTerminationMultiDataSetIterator	Builds an iterator that terminates once the number of minibatches returned with .next() is equal to a specified number. Note that a call to .next(num) is counted as a call to return a minibatch regardless of the value of num This essentially restricts the data to this specified number of minibatches.
ExistingDataSetIterator	This wrapper provides DataSetIterator interface to existing java Iterable<DataSet> and Iterator<DataSet>.
FileSplitDataSetIterator	Simple iterator working with list of files.
FloatsDataSetIterator	A simple utility iterator for creating a DataSetIterator from an Iterable<Pair<float[], float[]>> First value in pair is the features vector, second value in pair is the labels.
INDArrayDataSetIterator	A simple utility iterator for creating a DataSetIterator from an Iterable<Pair<INDArray,INDArray>>.
IteratorDataSetIterator	A DataSetIterator that works on an Iterator<DataSet>, combining and splitting the input DataSet objects as required to get the specified batch size. Typically used in Spark training, but may be used elsewhere. NOTE: reset method is not supported here.
IteratorMultiDataSetIterator	A DataSetIterator that works on an Iterator<MultiDataSet>, combining and splitting the input DataSet objects as required to get a specified batch size. Typically used in Spark training, but may be used elsewhere.
JointMultiDataSetIterator	This dataset iterator combines multiple DataSetIterators into 1 MultiDataSetIterator.
MultiDataSetIteratorSplitter	This iterator virtually splits given MultiDataSetIterator into Train and Test parts.
MultiDataSetWrapperIterator	This class is simple wrapper that takes single-input MultiDataSets and converts them to DataSets on the fly PLEASE NOTE: This only works if number of features/labels/masks is 1
MultipleEpochsIterator	Deprecated Does not properly trigger the incrementing of epoch counts in MultiLayerNetwork/ComputationGraph.
RandomDataSetIterator	RandomDataSetIterator: Generates random values (or zeros, ones, integers, etc) according to some distribution. The type of values produced can be specified by the RandomDataSetIterator.Values enumeration. Note: This is typically used for testing, debugging and benchmarking purposes.
RandomMultiDataSetIterator	RandomMultiDataSetIterator: Generates random values (or zeros, ones, integers, etc) according to some distribution. The type of values produced can be specified by the RandomMultiDataSetIterator.Values enumeration. Note: This is typically used for testing, debugging and benchmarking purposes.
RandomMultiDataSetIterator.Builder
ReconstructionDataSetIterator	Wraps a data set iterator setting the first (feature matrix) as the labels.
SamplingDataSetIterator	A wrapper for a dataset to sample from.
ScrollableDataSetIterator
ScrollableMultiDataSetIterator
WorkspacesShieldDataSetIterator	This iterator detaches/migrates DataSets coming out from backed DataSetIterator, thus providing "safe" DataSets. This is typically used for debugging and testing purposes, and should not be used in general by users

Enum Summary

Enum	Description
RandomDataSetIterator.Values
RandomMultiDataSetIterator.Values