com.intel.analytics.bigdl.dataset

Sample

abstract class Sample[T] extends Serializable

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

T

numeric type

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Instance Constructors

  1. new Sample()(implicit arg0: ClassTag[T])

Abstract Value Members

  1. abstract def feature(index: Int)(implicit ev: TensorNumeric[T]): Tensor[T]

    Get feature tensor for given index

    Get feature tensor for given index

    index

    index of specific sample

  2. abstract def feature()(implicit ev: TensorNumeric[T]): Tensor[T]

    Get feature tensor, for one feature Sample only.

    Get feature tensor, for one feature Sample only. You don't need to override this, because we have add a default implement to throw exception.

    returns

    feature tensor

  3. abstract def featureLength(index: Int): Int

    First dimension length of index-th feature.

    First dimension length of index-th feature. This function could be used to sort samples in DataSet.

    returns

  4. abstract def getData(): Array[T]

    Get data

    Get data

    returns

    data

  5. abstract def getFeatureSize(): Array[Array[Int]]

    Get feature sizes

    Get feature sizes

    returns

    feature sizes

  6. abstract def getLabelSize(): Array[Array[Int]]

    Get label sizes

    Get label sizes

    returns

    label sizes

  7. abstract def label(index: Int)(implicit ev: TensorNumeric[T]): Tensor[T]

    Get label tensor for given index

    Get label tensor for given index

    index

    index of specific sample

  8. abstract def label()(implicit ev: TensorNumeric[T]): Tensor[T]

    Get label tensor, for one label Sample only.

    Get label tensor, for one label Sample only. You don't need to override this, because we have add a default implement to throw exception.

    returns

    label tensor

  9. abstract def labelLength(index: Int): Int

    First dimension length of index-th label.

    First dimension length of index-th label. This function could be used to find the longest label.

    returns

  10. abstract def numFeature(): Int

    Number of tensors in feature

    Number of tensors in feature

    returns

    number of tensors in feature

  11. abstract def numLabel(): Int

    Number of tensors in label

    Number of tensors in label

    returns

    number of tensors in label

Concrete Value Members

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

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

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  3. final def ##(): Int

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

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

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  6. final def asInstanceOf[T0]: T0

    Definition Classes
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  7. def clone(): Sample.this.type

    returns

    A deep clone

    Definition Classes
    Sample → AnyRef
  8. final def eq(arg0: AnyRef): Boolean

    Definition Classes
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  9. def equals(arg0: Any): Boolean

    Definition Classes
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  10. def finalize(): Unit

    Attributes
    protected[java.lang]
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    @throws( classOf[java.lang.Throwable] )
  11. final def getClass(): Class[_]

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  12. def hashCode(): Int

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  13. final def isInstanceOf[T0]: Boolean

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

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  15. final def notify(): Unit

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  16. final def notifyAll(): Unit

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

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  18. def toString(): String

    Definition Classes
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  19. final def wait(): Unit

    Definition Classes
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    @throws( ... )
  20. final def wait(arg0: Long, arg1: Int): Unit

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    @throws( ... )
  21. final def wait(arg0: Long): Unit

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Deprecated Value Members

  1. def set(featureData: Array[T], labelData: Array[T], featureSize: Array[Int], labelSize: Array[Int])(implicit ev: TensorNumeric[T]): Sample[T]

    Set data of feature and label.

    Set data of feature and label.

    featureData
    labelData
    featureSize
    labelSize
    returns

    Annotations
    @deprecated
    Deprecated

    (Since version 0.2.0) Old interface

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