com.intel.analytics.bigdl.dataset

SampleToBatch

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

Annotations
@deprecated
Deprecated

(Since version 0.2.0) Use SampleToMiniBatch instead

Linear Supertypes
Transformer[Sample[T], MiniBatch[T]], Serializable, Serializable, AnyRef, Any
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Instance Constructors

  1. new SampleToBatch(totalBatch: Int, featurePadding: Option[Tensor[T]] = scala.None, labelPadding: Option[T] = scala.None, fixedLength: Option[Int] = scala.None, partitionNum: Option[Int] = scala.None)(implicit arg0: ClassTag[T], ev: TensorNumeric[T])

    totalBatch

    total batch size

    featurePadding

    feature padding value (by default None, meaning no feature padding)

    labelPadding

    label padding value (by default None, meaning no label padding)

    fixedLength

    if padding, it specifies the length of feature/label after padding (by default None, meaning the length after padding is set to the max length of feature/label in a mini-batch)

    partitionNum

    partition number of dataset, default means partitionNum equals Engine.nodeNumber()

Value Members

  1. final def !=(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef

  2. final def !=(arg0: Any): Boolean

    Definition Classes
    Any

  3. final def ##(): Int

    Definition Classes
    AnyRef → Any

  4. def ->[C](other: Transformer[MiniBatch[T], C]): Transformer[Sample[T], C]

    Definition Classes
    Transformer

  5. final def ==(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef

  6. final def ==(arg0: Any): Boolean

    Definition Classes
    Any

  7. def apply(prev: Iterator[Sample[T]]): Iterator[MiniBatch[T]]

    Definition Classes
    SampleToBatch → Transformer

  8. def apply(dataset: RDD[Sample[T]])(implicit evidence: ClassTag[MiniBatch[T]]): RDD[MiniBatch[T]]

    Apply this transformer to rdd

    Apply this transformer to rdd

    dataset

    Definition Classes
    Transformer

  9. final def asInstanceOf[T0]: T0

    Definition Classes
    Any

  10. def clone(): AnyRef

    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

  11. def cloneTransformer(): Transformer[Sample[T], MiniBatch[T]]

    Definition Classes
    Transformer

  12. final def eq(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef

  13. def equals(arg0: Any): Boolean

    Definition Classes
    AnyRef → Any

  14. def finalize(): Unit

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    protected[java.lang]
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    @throws( classOf[java.lang.Throwable] )

  15. final def getClass(): Class[_]

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    AnyRef → Any

  16. def hashCode(): Int

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    AnyRef → Any

  17. final def isInstanceOf[T0]: Boolean

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    Any

  18. final def ne(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef

  19. final def notify(): Unit

    Definition Classes
    AnyRef

  20. final def notifyAll(): Unit

    Definition Classes
    AnyRef

  21. final def synchronized[T0](arg0: ⇒ T0): T0

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  22. def toString(): String

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    AnyRef → Any

  23. final def wait(): Unit

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    @throws( ... )

  24. final def wait(arg0: Long, arg1: Int): Unit

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    @throws( ... )

  25. final def wait(arg0: Long): Unit

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    @throws( ... )

Inherited from Transformer[Sample[T], MiniBatch[T]]

Inherited from Serializable

Inherited from Serializable

Inherited from AnyRef

Inherited from Any

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