Trait

toolkit.neuralnetwork

GradientPropagation

Related Doc: package neuralnetwork

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trait GradientPropagation extends AnyRef

Self Type
DifferentiableField
Linear Supertypes
AnyRef, Any
Known Subclasses
AplusBXtoN, Bias, ByteDataSource, ByteLabelSource, CrossEntropy, CrossEntropySoftmax, CrossEntropySoftmaxes, DifferentiableField, Downsample, FullyConnected, MaxPooling, RandomSource, ReLU, RightCrop, RightPad, Softmax, SpatialConvolution, StackFeatures, Subspace, SumOfSquares, Tanh, TrainableState, ZeroPad
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  1. GradientPropagation
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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. def activateSGD(initField: libcog.Field = ScalarField(1f), invokeCallbacks: Boolean = true): Unit

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  5. final def asInstanceOf[T0]: T0

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  6. def clone(): AnyRef

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  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. final def isInstanceOf[T0]: Boolean

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

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  14. final def notify(): Unit

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  15. final def notifyAll(): Unit

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

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  17. def toString(): String

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  18. def totalDerivative(): libcog.Field

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  19. final def wait(): Unit

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

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

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