com.intel.analytics.bigdl

dataset

package dataset

Visibility
  1. Public
  2. All

Type Members

  1. trait AbstractDataSet[D, DataSequence] extends AnyRef

    A set of data which is used in the model optimization process.

  2. class ArraySample[T] extends Sample[T]

    A kind of sample who use only one array

  3. case class ByteRecord(data: Array[Byte], label: Float) extends Product with Serializable

    A byte array and a label.

  4. class CachedDistriDataSet[T] extends DistributedDataSet[T]

    Wrap a RDD as a DataSet.

  5. class ChainedTransformer[A, B, C] extends Transformer[A, C]

    A transformer chain two transformer together.

  6. class DefaultPadding extends PaddingStrategy

  7. trait DistributedDataSet[T] extends AbstractDataSet[T, RDD[T]]

    Represent a distributed data.

  8. case class FixedLength(fixedLength: Array[Int]) extends PaddingStrategy with Product with Serializable

    Set the first dimension's length to fixed length.

  9. class Identity[A] extends Transformer[A, A]

    Just transform the input to output.

  10. abstract class Image extends Serializable

    Represent an image

  11. trait Label[T] extends AnyRef

    Represent a label

  12. class LocalArrayDataSet[T] extends LocalDataSet[T]

    Wrap an array as a DataSet.

  13. trait LocalDataSet[T] extends AbstractDataSet[T, Iterator[T]]

    Manage some 'local' data, e.

  14. class LocalImagePath extends AnyRef

    Represent a local file path of an image file

  15. case class LocalSeqFilePath(path: Path) extends Product with Serializable

    Represent a local file path of a hadoop sequence file

  16. trait MiniBatch[T] extends Serializable

    A interface for MiniBatch.

  17. case class PaddingLongest(paddingLength: Array[Int]) extends PaddingStrategy with Product with Serializable

    Add an constant length to longest feature in the first dimension

  18. case class PaddingParam[T](paddingTensor: Option[Array[Tensor[T]]] = scala.None, paddingStrategy: PaddingStrategy = new DefaultPadding())(implicit evidence$14: ClassTag[T]) extends Serializable with Product

    Feature Padding param for MiniBatch.

  19. abstract class PaddingStrategy extends Serializable

  20. abstract class Sample[T] extends Serializable

    Class that represents the features and labels of a data sample.

  21. class SampleToMiniBatch[T] extends Transformer[Sample[T], MiniBatch[T]]

    Convert a sequence of Sample to a sequence of MiniBatch through function toMiniBatch.

  22. abstract class Sentence[T] extends Serializable

    Represent a sentence

  23. class SparseMiniBatch[T] extends ArrayTensorMiniBatch[T]

    SparseMiniBatch is a MiniBatch type for TensorSample.

  24. class TensorSample[T] extends Sample[T]

    A kind of Sample who hold both DenseTensor and SparseTensor as features.

  25. trait Transformer[A, B] extends Serializable

    Transform a data stream of type A to type B.

  26. class SampleToBatch[T] extends Transformer[Sample[T], MiniBatch[T]]

    Convert a sequence of single-feature and single-label Sample to a sequence of MiniBatch, optionally padding all the features (or labels) in the mini-batch to the same length

Value Members

  1. object ArraySample extends Serializable

  2. object DataSet

    Common used DataSet builder.

  3. object Identity extends Serializable

  4. object MiniBatch extends Serializable

  5. object Sample extends Serializable

  6. object SampleToBatch extends Serializable

    Convert a sequence of Sample to a sequence of MiniBatch, optionally padding all the features (or labels) in the mini-batch to the same length

  7. object SampleToMiniBatch extends Serializable

  8. object SparseMiniBatch extends Serializable

  9. object TensorSample extends Serializable

  10. object Utils

  11. package datamining

  12. package image

  13. package segmentation

  14. package text

Ungrouped