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com.intel.analytics.bigdl.tensor

SparseTensorBLAS

object SparseTensorBLAS

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  1. final def !=(arg0: Any): Boolean
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  2. final def ##(): Int
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  3. final def ==(arg0: Any): Boolean
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  4. final def asInstanceOf[T0]: T0
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  5. def clone(): AnyRef
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    @native() @throws( ... )
  6. def coomm[T](alpha: T, mat1: Tensor[T], mat2: Tensor[T], beta: T, r: Tensor[T])(implicit ev: TensorNumeric[T]): Unit
  7. def coomv[T](alpha: T, mat: Tensor[T], vec: Tensor[T], beta: T, r: Tensor[T])(implicit ev: TensorNumeric[T]): Unit

    Perform r := beta * r + alpha * mat * vec mat should be a 2D SparseTensor, vec should be a 1D DenseTensor, r should be a 2D DenseTensor.

    Perform r := beta * r + alpha * mat * vec mat should be a 2D SparseTensor, vec should be a 1D DenseTensor, r should be a 2D DenseTensor.

    T

    numeric type

    alpha

    alpha

    mat

    a 2D SparseTensor

    vec

    a 1D DenseTensor

    beta

    beta

    r

    result, 2D DenseTensor

    ev

    tensor numeric

  8. final def eq(arg0: AnyRef): Boolean
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  10. def finalize(): Unit
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  11. final def getClass(): Class[_]
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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
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  19. def vdot[T](vec1: DenseTensor[T], vec2: SparseTensor[T]): T

    Perform vector dot product of vec1, and vec2

  20. final def wait(): Unit
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  21. final def wait(arg0: Long, arg1: Int): Unit
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  22. final def wait(arg0: Long): Unit
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