SparseMiniBatch

final def !=(arg0: AnyRef): Boolean

final def !=(arg0: Any): Boolean

final def ##(): Int

final def ==(arg0: AnyRef): Boolean

final def ==(arg0: Any): Boolean

final def asInstanceOf[T0]: T0

var batchSize: Int

def clone(): AnyRef

final def eq(arg0: AnyRef): Boolean

def equals(arg0: Any): Boolean

val featurePadding: Option[Array[Tensor[T]]]

val featurePaddingStrategy: PaddingStrategy

def finalize(): Unit

final def getClass(): Class[_]

def getInput(): Activity

Get input in this MiniBatch.

def getTarget(): Activity

Get target in this MiniBatch

def hashCode(): Int

def init(features: Array[Tensor[T]], labels: Array[Tensor[T]]): Unit

final def isInstanceOf[T0]: Boolean

val labelPadding: Option[Array[Tensor[T]]]

val labelPaddingStrategy: PaddingStrategy

final def ne(arg0: AnyRef): Boolean

final def notify(): Unit

final def notifyAll(): Unit

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.

def size(): Int

Get the number of samples in this MiniBatch

def slice(offset: Int, length: Int): MiniBatch[T]

Slice this MiniBatch to a smaller MiniBatch with offset and length

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

def toString(): String

var unlabeled: Boolean

final def wait(): Unit

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

final def wait(arg0: Long): Unit

def data(): Tensor[T]

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

def labels(): Tensor[T]

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