com.intel.analytics.bigdl.dataset

TensorSample

object TensorSample extends Serializable

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

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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. def apply[T](featureTensor: Tensor[T], label: T)(implicit arg0: ClassTag[T], ev: TensorNumeric[T]): Sample[T]

  7. def apply[T](featureTensor: Tensor[T], labelTensor: Tensor[T])(implicit arg0: ClassTag[T], ev: TensorNumeric[T]): Sample[T]

  8. def apply[T](featureTensors: Array[Tensor[T]], labelTensor: Tensor[T])(implicit arg0: ClassTag[T], ev: TensorNumeric[T]): Sample[T]

  9. def apply[T](featureTensors: Array[Tensor[T]], labelTensors: Array[Tensor[T]])(implicit arg0: ClassTag[T], ev: TensorNumeric[T]): Sample[T]

  10. def apply[T](featureTensor: Tensor[T])(implicit arg0: ClassTag[T], ev: TensorNumeric[T]): Sample[T]

  11. def apply[T](featureTensors: Array[Tensor[T]])(implicit arg0: ClassTag[T], ev: TensorNumeric[T]): Sample[T]

  12. final def asInstanceOf[T0]: T0

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  13. def clone(): AnyRef

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  14. def create[T](featureTensors: Array[Tensor[_]], labelTensors: Array[Tensor[_]] = null)(implicit arg0: ClassTag[T], ev: TensorNumeric[T]): Sample[T]

    Create a TensorSample which is able to contains Tensors with different types.

    Create a TensorSample which is able to contains Tensors with different types.

    T

    main type

    featureTensors

    feature tensors

    labelTensors

    label tensors, can be null or empty, default value is null

    returns

    TensorSample

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

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  16. def equals(arg0: Any): Boolean

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  17. def finalize(): Unit

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

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  19. def hashCode(): Int

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  20. final def isInstanceOf[T0]: Boolean

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

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  22. final def notify(): Unit

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  23. final def notifyAll(): Unit

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

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  25. def toString(): String

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  26. final def wait(): Unit

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

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

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