Class

ml.dmlc.mxnet

CustomOpProp

Related Doc: package mxnet

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abstract class CustomOpProp extends AnyRef

Base class for operator property class implemented in Scala. MXNET_CPU_WORKER_NTHREADS must be greater than 1 for custom op to work on CPU

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Instance Constructors

  1. new CustomOpProp(needTopGrad: Boolean = false)

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    needTopGrad

    : Boolean The default declareBackwardDependency function use this value to determine whether this operator needs gradient input for above.

Abstract Value Members

  1. abstract def createOperator(ctx: String, inShapes: Array[Array[Int]], inDtypes: Array[Int]): CustomOp

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    Create an operator that carries out the real computation given the context, input shapes, and input data types.

Concrete Value Members

  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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  6. def declareBackwardDependency(outGrad: Array[Int], inData: Array[Int], outData: Array[Int]): Array[Int]

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    Declare dependencies of this operator for backward pass.

    Declare dependencies of this operator for backward pass.

    outGrad

    : array of Int ids of outGrad blobs.

    inData

    : array of Int ids of inData blobs.

    outData

    : array of Int ids of outData blobs.

    returns

    deps : array of Int ids of the needed blobs.

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

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  8. def equals(arg0: Any): Boolean

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  9. def finalize(): Unit

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

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  11. def hashCode(): Int

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  12. def inferShape(inShape: Array[Shape]): (Array[Shape], Array[Shape], Array[Shape])

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    inferShape interface.

    inferShape interface. override to create new operators

    inShape

    : array of Shape list of argument shapes in the same order as declared in listArguments().

    returns

    inShapes : array of Shape array of argument shapes. Can be modified from inShape. outShapes : array of Shape array of output shapes calculated from inShape, in the same order as declared in listOutputs(). auxShapes : Optional, array of Shape array of aux shapes calculated from inShape, in the same order as declared in listAuxiliaryStates().

  13. def inferType(inType: Array[DType]): (Array[DType], Array[DType], Array[DType])

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    inferType interface.

    inferType interface. override to create new operators

    inType

    : array of DType list of argument types in the same order as declared in listArguments().

    returns

    inTypes : array of DType array of argument types. Can be modified from inType. outTypes : array of DType array of output types calculated from inType, in the same order as declared in listOutputs(). auxTypes : Optional, array of DType array of aux types calculated from inType, in the same order as declared in listAuxiliaryStates().

  14. final def isInstanceOf[T0]: Boolean

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  15. var kwargs: Map[String, String]

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    Attributes
    protected
  16. def listArguments(): Array[String]

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    listArguments interface.

    listArguments interface. override to create new operators

    returns

    arguments : array of String list of argument blob names.

  17. def listAuxiliaryStates(): Array[String]

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    listAuxiliaryStates interface.

    listAuxiliaryStates interface. override to create new operators

    returns

    auxs : array of String list of auxiliary state blob names.

  18. def listOutputs(): Array[String]

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    listOutputs interface.

    listOutputs interface. override to create new operators

    returns

    outputs : array of String list of output blob names.

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

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  20. final def notify(): Unit

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  21. final def notifyAll(): Unit

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

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  23. def toString(): String

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  24. final def wait(): Unit

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

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

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