MapDataset

public class MapDataset

Public Constructors

MapDataset(Dataset other, Function<List<Operand<?>>, List<Operand<?>>> mapper)

Public Methods

DatasetIterator	makeInitializeableIterator() Creates a `DatasetIterator` that can be used to iterate over elements of this dataset.
DatasetIterator	makeOneShotIterator() Creates a `DatasetIterator` that can be used to iterate over elements of this dataset.

Inherited Methods

From class org.tensorflow.framework.data.Dataset

final Dataset	batch(long batchSize, boolean dropLastBatch) Groups elements of this dataset into batches.
final Dataset	batch(long batchSize) Groups elements of this dataset into batches.
static Dataset	fromTensorSlices(Ops tf, List<Operand<?>> tensors, List<Class<? extends TType>> outputTypes) Creates an in-memory `Dataset` whose elements are slices of the given tensors.
Ops	getOpsInstance()
List<Shape>	getOutputShapes() Get a list of shapes for each component of this dataset.
List<Class<? extends TType>>	getOutputTypes() Get a list of output types for each component of this dataset.
Operand<?>	getVariant() Get the variant tensor representing this dataset.
Iterator<List<Operand<?>>>	iterator() Creates an iterator which iterates through all batches of this Dataset in an eager fashion.
DatasetIterator	makeInitializeableIterator() Creates a `DatasetIterator` that can be used to iterate over elements of this dataset.
DatasetIterator	makeOneShotIterator() Creates a `DatasetIterator` that can be used to iterate over elements of this dataset.
Dataset	map(Function<List<Operand<?>>, List<Operand<?>>> mapper) Returns a new Dataset which maps a function over all elements returned by this dataset.
Dataset	mapAllComponents(Function<Operand<?>, Operand<?>> mapper) Returns a new Dataset which maps a function across all elements from this dataset, on all components of each element.
Dataset	mapOneComponent(int index, Function<Operand<?>, Operand<?>> mapper) Returns a new Dataset which maps a function across all elements from this dataset, on a single component of each element.
final Dataset	skip(long count) Returns a new `Dataset` which skips `count` initial elements from this dataset
final Dataset	take(long count) Returns a new `Dataset` with only the first `count` elements from this dataset.
static Dataset	textLineDataset(Ops tf, String filename, String compressionType, long bufferSize)
static Dataset	tfRecordDataset(Ops tf, String filename, String compressionType, long bufferSize)
String	toString()

From class java.lang.Object

boolean	equals(Object arg0)
final Class<?>	getClass()
int	hashCode()
final void	notify()
final void	notifyAll()
String	toString()
final void	wait(long arg0, int arg1)
final void	wait(long arg0)
final void	wait()

From interface java.lang.Iterable

abstract void	forEach(Consumer<? super T> arg0)
abstract Iterator<List<Operand<?>>>	iterator()
abstract Spliterator<List<Operand<?>>>	spliterator()

Public Constructors

public MapDataset (Dataset other, Function<List<Operand<?>>, List<Operand<?>>> mapper)

Public Methods

public DatasetIterator makeInitializeableIterator ()

Creates a `DatasetIterator` that can be used to iterate over elements of this dataset.

This iterator will have to be initialized with a call to `iterator.makeInitializer(Dataset)` before elements can be retreived in a loop.

Returns

A new `DatasetIterator` based on this dataset's structure.

public DatasetIterator makeOneShotIterator ()

Creates a `DatasetIterator` that can be used to iterate over elements of this dataset. Using `makeOneShotIterator` ensures that the iterator is automatically initialized on this dataset. skips In graph mode, the initializer op will be added to the Graph's intitializer list, which must be run via `tf.init()`:

Ex:

     try (Session session = new Session(graph) {
         // Immediately run initializers
         session.run(tf.init());
     }

In eager mode, the initializer will be run automatically as a result of this call.

Returns

A new `DatasetIterator` based on this dataset's structure.