TensorSample

Value Members

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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