Class/Object

com.intel.analytics.bigdl.dataset

SampleToBatch

Related Docs: object SampleToBatch | package dataset

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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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Visibility
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Instance Constructors

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

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    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: Any): Boolean

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    Definition Classes
    AnyRef → Any

  2. final def ##(): Int

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    AnyRef → Any

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

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    Definition Classes
    Transformer

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

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    AnyRef → Any

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

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    Definition Classes
    SampleToBatch → Transformer

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

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    Apply this transformer to rdd

    Apply this transformer to rdd

    Definition Classes
    Transformer

  7. final def asInstanceOf[T0]: T0

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    Definition Classes
    Any

  8. def clone(): AnyRef

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

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

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    Definition Classes
    Transformer

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

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    Definition Classes
    AnyRef

  11. def equals(arg0: Any): Boolean

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    AnyRef → Any

  12. def finalize(): Unit

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

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

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  14. def hashCode(): Int

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    AnyRef → Any

  15. final def isInstanceOf[T0]: Boolean

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    Any

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

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    AnyRef

  17. final def notify(): Unit

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    AnyRef

  18. final def notifyAll(): Unit

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    AnyRef

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

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  20. def toString(): String

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  21. final def wait(): Unit

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    @throws( ... )

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

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    @throws( ... )

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

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

Inherited from Serializable

Inherited from Serializable

Inherited from AnyRef

Inherited from Any

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