class SparseMiniBatch[T] extends ArrayTensorMiniBatch[T]

SparseMiniBatch is a MiniBatch type for TensorSample. And SparseMiniBatch could deal with SparseTensors in TensorSample.

T

Numeric type

Linear Supertypes
ArrayTensorMiniBatch[T], MiniBatch[T], Serializable, Serializable, AnyRef, Any
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Inherited
  1. SparseMiniBatch
  2. ArrayTensorMiniBatch
  3. MiniBatch
  4. Serializable
  5. Serializable
  6. AnyRef
  7. Any
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Visibility
  1. Public
  2. All

Instance Constructors

  1. new SparseMiniBatch(inputData: Array[Tensor[T]], targetData: Array[Tensor[T]])(implicit arg0: ClassTag[T], ev: TensorNumeric[T])

    inputData

    a set of input tensor

    targetData

    a set of target tensor

Value Members

  1. final def !=(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  2. final def ##(): Int
    Definition Classes
    AnyRef → Any
  3. final def ==(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  4. final def asInstanceOf[T0]: T0
    Definition Classes
    Any
  5. var batchSize: Int
    Attributes
    protected
    Definition Classes
    ArrayTensorMiniBatch
  6. def clone(): AnyRef
    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @native() @throws( ... )
  7. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  8. def equals(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  9. val featurePadding: Option[Array[Tensor[T]]]
    Definition Classes
    ArrayTensorMiniBatch
  10. val featurePaddingStrategy: PaddingStrategy
    Definition Classes
    ArrayTensorMiniBatch
  11. def finalize(): Unit
    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  12. final def getClass(): Class[_]
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  13. def getInput(): Activity

    Get input in this MiniBatch.

    Get input in this MiniBatch.

    returns

    input Activity

    Definition Classes
    SparseMiniBatch → ArrayTensorMiniBatch → MiniBatch
  14. def getTarget(): Activity

    Get target in this MiniBatch

    Get target in this MiniBatch

    returns

    target Activity

    Definition Classes
    SparseMiniBatch → ArrayTensorMiniBatch → MiniBatch
  15. def hashCode(): Int
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  16. def init(features: Array[Tensor[T]], labels: Array[Tensor[T]]): Unit
  17. val inputData: Array[Tensor[T]]
    Definition Classes
    ArrayTensorMiniBatch
  18. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  19. val labelPadding: Option[Array[Tensor[T]]]
    Definition Classes
    ArrayTensorMiniBatch
  20. val labelPaddingStrategy: PaddingStrategy
    Definition Classes
    ArrayTensorMiniBatch
  21. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  22. final def notify(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  23. final def notifyAll(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  24. def set(samples: Seq[Sample[T]])(implicit ev: TensorNumeric[T]): SparseMiniBatch.this.type

    Replace the original content of the miniBatch with a set of Sample.

    Replace the original content of the miniBatch with a set of Sample.

    samples

    a set of Sample

    returns

    self

    Definition Classes
    SparseMiniBatch → ArrayTensorMiniBatch → MiniBatch
  25. def size(): Int

    Get the number of samples in this MiniBatch

    Get the number of samples in this MiniBatch

    returns

    size How many samples in this MiniBatch

    Definition Classes
    ArrayTensorMiniBatch → MiniBatch
  26. def slice(offset: Int, length: Int): MiniBatch[T]

    Slice this MiniBatch to a smaller MiniBatch with offset and length

    Slice this MiniBatch to a smaller MiniBatch with offset and length

    offset

    offset, counted from 1

    length

    length

    returns

    A smaller MiniBatch

    Definition Classes
    ArrayTensorMiniBatch → MiniBatch
  27. final def synchronized[T0](arg0: ⇒ T0): T0
    Definition Classes
    AnyRef
  28. val targetData: Array[Tensor[T]]
    Definition Classes
    ArrayTensorMiniBatch
  29. def toString(): String
    Definition Classes
    AnyRef → Any
  30. var unlabeled: Boolean
    Attributes
    protected
    Definition Classes
    ArrayTensorMiniBatch
  31. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  32. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  33. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @native() @throws( ... )

Deprecated Value Members

  1. def data(): Tensor[T]

    An deprecated function for single-input/single-target MiniBatch.

    An deprecated function for single-input/single-target MiniBatch. You don't need to override this, because we have add a default implement to throw exception.

    Definition Classes
    ArrayTensorMiniBatch → MiniBatch
    Annotations
    @deprecated
    Deprecated

    (Since version 0.2.0) Old interface

  2. def labels(): Tensor[T]

    An deprecated function for single-input/single-target MiniBatch.

    An deprecated function for single-input/single-target MiniBatch. You don't need to override this, because we have add a default implement to throw exception.

    Definition Classes
    ArrayTensorMiniBatch → MiniBatch
    Annotations
    @deprecated
    Deprecated

    (Since version 0.2.0) Old interface

Inherited from ArrayTensorMiniBatch[T]

Inherited from MiniBatch[T]

Inherited from Serializable

Inherited from Serializable

Inherited from AnyRef

Inherited from Any

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