Uses of Interface
org.deeplearning4j.datasets.iterator.callbacks.DataSetCallback

Packages that use DataSetCallback

Package	Description
org.deeplearning4j.datasets.iterator
org.deeplearning4j.datasets.iterator.callbacks

Uses of DataSetCallback in org.deeplearning4j.datasets.iterator

Fields in org.deeplearning4j.datasets.iterator declared as DataSetCallback

Modifier and Type	Field and Description
protected DataSetCallback	AsyncDataSetIterator.callback
protected DataSetCallback	AsyncMultiDataSetIterator.callback

Constructors in org.deeplearning4j.datasets.iterator with parameters of type DataSetCallback

Constructor and Description
AsyncDataSetIterator(org.nd4j.linalg.dataset.api.iterator.DataSetIterator iterator, int queueSize, BlockingQueue<org.nd4j.linalg.dataset.DataSet> queue, boolean useWorkspace, DataSetCallback callback)
AsyncDataSetIterator(org.nd4j.linalg.dataset.api.iterator.DataSetIterator iterator, int queueSize, BlockingQueue<org.nd4j.linalg.dataset.DataSet> queue, boolean useWorkspace, DataSetCallback callback, Integer deviceId)
AsyncDataSetIterator(org.nd4j.linalg.dataset.api.iterator.DataSetIterator baseIterator, int queueSize, boolean useWorkspace, DataSetCallback callback)
AsyncMultiDataSetIterator(org.nd4j.linalg.dataset.api.iterator.MultiDataSetIterator iterator, int queueSize, BlockingQueue<org.nd4j.linalg.dataset.api.MultiDataSet> queue, boolean useWorkspace, DataSetCallback callback)
AsyncMultiDataSetIterator(org.nd4j.linalg.dataset.api.iterator.MultiDataSetIterator iterator, int queueSize, BlockingQueue<org.nd4j.linalg.dataset.api.MultiDataSet> queue, boolean useWorkspace, DataSetCallback callback, Integer deviceId)

Uses of DataSetCallback in org.deeplearning4j.datasets.iterator.callbacks

Classes in org.deeplearning4j.datasets.iterator.callbacks that implement DataSetCallback

Modifier and Type	Class and Description
class	DefaultCallback This callback ensures that memory on device is up-to-date with host memory.
class	InterleavedDataSetCallback This callback migrates incoming datasets in round-robin manner, to ensure TDA for ParallelWrapper