com.intel.analytics.bigdl.nn

MklInt8Convertible

trait MklInt8Convertible extends AnyRef

Trait which provides MKL-DNN functionality to convert from FP32 to INT8

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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. final def asInstanceOf[T0]: T0

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  7. def clone(): AnyRef

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

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  9. def equals(arg0: Any): Boolean

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  10. def finalize(): Unit

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

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  12. def getInputDimMask(): Int

    Get dimension mask of input

    Get dimension mask of input

    returns

    inputDimMask field which stores value of input dimension mask

  13. def getInputScales(): Array[Array[Float]]

    Get input scales

    Get input scales

    returns

    field which stores value of input scales

  14. def getOutputDimMask(): Int

    Get dimension mask of output

    Get dimension mask of output

    returns

    outputDimMask field which stores value of output dimension mask

  15. def getOutputScales(): Array[Array[Float]]

    Get output scales

    Get output scales

    returns

    field which stores value of output scales

  16. def getWeightDimMask(): Int

    Get dimension mask of weight

    Get dimension mask of weight

    returns

    weightDimMask which stores value of weight mask

  17. def getWeightScales(): Array[Array[Float]]

    Get weight scales

    Get weight scales

    returns

    field which stores value of weight scales

  18. def hashCode(): Int

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  19. var inputDimMask: 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. var outputDimMask: Int

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    protected
  25. def setInputDimMask(mask: Int): Unit

    Set dimension mask of input

    Set dimension mask of input

    mask

    value of input dimension mask to be set

    returns

    Unit

  26. def setInputScales(inScales: Array[Array[Float]]): Unit

    Set input scales Clear existing buffer of input scales, and place updated scales into the cleared buffer

    Set input scales Clear existing buffer of input scales, and place updated scales into the cleared buffer

    inScales

    value of input scales to be set

    returns

    Unit

  27. def setOutputDimMask(mask: Int): Unit

    Set dimension mask of output

    Set dimension mask of output

    mask

    value of output dimension mask to be set

    returns

    Unit

  28. def setOutputScales(outScales: Array[Array[Float]]): Unit

    Set output scales Clear existing buffer of output scales, and place updated scales into the cleared buffer

    Set output scales Clear existing buffer of output scales, and place updated scales into the cleared buffer

    outScales

    value of output scales to be set

    returns

    Unit

  29. def setWeightDimMask(mask: Int): Unit

    Set dimension mask of weight

    Set dimension mask of weight

    mask

    value of weight mask to be set

    returns

    Unit

  30. def setWeightScales(weightScales: Array[Array[Float]]): Unit

    Set weight scales Clear existing buffer of weight scales, and place updated scales into the cleared buffer

    Set weight scales Clear existing buffer of weight scales, and place updated scales into the cleared buffer

    weightScales

    value of weight scales to be set

    returns

    Unit

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

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  32. def toString(): String

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  33. def updateInputScales(scale: Array[Float], index: Int): Unit

    Update input scales at specific index with provided new scale

    Update input scales at specific index with provided new scale

    scale

    the new scale

    index

    the index of which the scale need to be updated

    returns

    Unit

  34. def updateOutputScales(scale: Array[Float], index: Int): Unit

    Update output scales at specific index with provided new scale

    Update output scales at specific index with provided new scale

    scale

    the new scale

    index

    the index of which the scale need to be updated

    returns

    Unit

  35. def updateWeightScales(scale: Array[Float], index: Int): Unit

    Update weight scales at specific index with provided new scale

    Update weight scales at specific index with provided new scale

    scale

    the new scale

    index

    the index of which the scale need to be updated

    returns

    Unit

  36. final def wait(): Unit

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

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

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  39. var weightDimMask: Int

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