Package apple.metalperformanceshaders

Class MPSMatrixBatchNormalizationGradient

  • All Implemented Interfaces:
    NSCoding, NSCopying, NSSecureCoding, NSObject
    public class MPSMatrixBatchNormalizationGradient
extends MPSMatrixBinaryKernel
    MPSMatrixBatchNormalizationGradient [@dependency] This depends on Metal.framework. A kernel to compute the gradient of the batch normalization operation. A MPSMatrixBatchNormalizationGradient object computes the results of backpropagating the gradients of a loss function with respect to the outputs of an MPSMatrixBatchNormalization object. The corresponding properties and data used by the MPSMatrixBatchNormalizationGradient object should correspond to those used by the forward MPSMatrixBatchNormalization object for which the gradient is being computed.

    • Constructor Detail

      • MPSMatrixBatchNormalizationGradient

        protected MPSMatrixBatchNormalizationGradient​(org.moe.natj.general.Pointer peer)

    • Method Detail

      • accessInstanceVariablesDirectly

        public static boolean accessInstanceVariablesDirectly()

      • allocWithZone

        public static java.lang.Object allocWithZone​(org.moe.natj.general.ptr.VoidPtr zone)

      • automaticallyNotifiesObserversForKey

        public static boolean automaticallyNotifiesObserversForKey​(java.lang.String key)

      • cancelPreviousPerformRequestsWithTarget

        public static void cancelPreviousPerformRequestsWithTarget​(java.lang.Object aTarget)

      • cancelPreviousPerformRequestsWithTargetSelectorObject

        public static void cancelPreviousPerformRequestsWithTargetSelectorObject​(java.lang.Object aTarget,
                                                                         org.moe.natj.objc.SEL aSelector,
                                                                         java.lang.Object anArgument)

      • classFallbacksForKeyedArchiver

        public static NSArray<java.lang.String> classFallbacksForKeyedArchiver()

      • classForKeyedUnarchiver

        public static org.moe.natj.objc.Class classForKeyedUnarchiver()

      • copyWithZoneDevice

        public java.lang.Object copyWithZoneDevice​(org.moe.natj.general.ptr.VoidPtr zone,
                                           MTLDevice device)
        Make a copy of this kernel for a new device - @see MPSKernel
        Overrides:
        copyWithZoneDevice in class MPSKernel
        Parameters:
        zone - The NSZone in which to allocate the object
        device - The device for the new MPSKernel. If nil, then use self.device.
        Returns:
        A pointer to a copy of this MPSKernel. This will fail, returning nil if the device is not supported. Devices must be MTLFeatureSet_iOS_GPUFamily2_v1 or later.

      • debugDescription_static

        public static java.lang.String debugDescription_static()

      • description_static

        public static java.lang.String description_static()

      • encodeToCommandBufferGradientMatrixInputMatrixMeanVectorVarianceVectorGammaVectorBetaVectorResultGradientForDataMatrixResultGradientForGammaVectorResultGradientForBetaVector

        public void encodeToCommandBufferGradientMatrixInputMatrixMeanVectorVarianceVectorGammaVectorBetaVectorResultGradientForDataMatrixResultGradientForGammaVectorResultGradientForBetaVector​(MTLCommandBuffer commandBuffer,
                                                                                                                                                                                          MPSMatrix gradientMatrix,
                                                                                                                                                                                          MPSMatrix inputMatrix,
                                                                                                                                                                                          MPSVector meanVector,
                                                                                                                                                                                          MPSVector varianceVector,
                                                                                                                                                                                          MPSVector gammaVector,
                                                                                                                                                                                          MPSVector betaVector,
                                                                                                                                                                                          MPSMatrix resultGradientForDataMatrix,
                                                                                                                                                                                          MPSVector resultGradientForGammaVector,
                                                                                                                                                                                          MPSVector resultGradientForBetaVector)
        Encode a MPSMatrixBatchNormalizationGradient object to a command buffer and compute its gradient with respect to its input data.
        Parameters:
        commandBuffer - The commandBuffer on which to encode the operation.
        gradientMatrix - A matrix whose values represent the gradient of a loss function with respect to the results of a forward MPSMatrixBatchNormalization operation.
        inputMatrix - A matrix containing the inputs to a forward MPSMatrixBatchNormalization operation for which the gradient values are to be computed.
        meanVector - A vector containing the batch mean values. Should contain either the specified values used to compute the forward result, or the computed values resulting from the forward kernel execution.
        varianceVector - A vector containing the batch variance values. Should contain either the specified values used to compute the forward result, or the computed values resulting from the forward kernel execution.
        gammaVector - A vector containing the gamma terms. Should be the same values as used when computing the forward result.
        betaVector - A vector containing the beta terms. Should be the same values as used when computing the forward result.
        resultGradientForDataMatrix - The matrix containing the resulting gradient values.
        resultGradientForGammaVector - If non-NULL the vector containing gradients for the gamma terms.
        resultGradientForBetaVector - If non-NULL the vector containing gradients for the beta terms.

      • epsilon

        public float epsilon()
        [@property] epsilon A small term added to the variance when normalizing the input.

      • hash_static

        public static long hash_static()

      • initWithCoderDevice

        public MPSMatrixBatchNormalizationGradient initWithCoderDevice​(NSCoder aDecoder,
                                                               java.lang.Object device)
        NSSecureCoding compatability See @ref MPSKernel#initWithCoder.
        Overrides:
        initWithCoderDevice in class MPSMatrixBinaryKernel
        Parameters:
        aDecoder - The NSCoder subclass with your serialized MPSMatrixBatchNormalizationGradient
        device - The MTLDevice on which to make the MPSMatrixBatchNormalizationGradient object.
        Returns:
        A new MPSMatrixBatchNormalizationGradient object, or nil if failure.

      • initWithDevice

        public MPSMatrixBatchNormalizationGradient initWithDevice​(java.lang.Object device)
        Description copied from class: MPSKernel
        Standard init with default properties per filter type
        Overrides:
        initWithDevice in class MPSMatrixBinaryKernel
        Parameters:
        device - The device that the filter will be used on. May not be NULL.
        Returns:
        a pointer to the newly initialized object. This will fail, returning nil if the device is not supported. Devices must be MTLFeatureSet_iOS_GPUFamily2_v1 or later.

      • instanceMethodSignatureForSelector

        public static NSMethodSignature instanceMethodSignatureForSelector​(org.moe.natj.objc.SEL aSelector)

      • instancesRespondToSelector

        public static boolean instancesRespondToSelector​(org.moe.natj.objc.SEL aSelector)

      • isSubclassOfClass

        public static boolean isSubclassOfClass​(org.moe.natj.objc.Class aClass)

      • keyPathsForValuesAffectingValueForKey

        public static NSSet<java.lang.String> keyPathsForValuesAffectingValueForKey​(java.lang.String key)

      • neuronParameterA

        public float neuronParameterA()
        Getter funtion for neuronType set using setNeuronType:parameterA:parameterB:parameterC method

      • neuronParameterB

        public float neuronParameterB()
        Getter funtion for neuronType set using setNeuronType:parameterA:parameterB:parameterC method

      • neuronParameterC

        public float neuronParameterC()
        Getter funtion for neuronType set using setNeuronType:parameterA:parameterB:parameterC method

      • neuronType

        public int neuronType()
        Getter funtion for neuronType set using setNeuronType:parameterA:parameterB:parameterC method

      • new_objc

        public static java.lang.Object new_objc()

      • resolveClassMethod

        public static boolean resolveClassMethod​(org.moe.natj.objc.SEL sel)

      • resolveInstanceMethod

        public static boolean resolveInstanceMethod​(org.moe.natj.objc.SEL sel)

      • setEpsilon

        public void setEpsilon​(float value)
        [@property] epsilon A small term added to the variance when normalizing the input.

      • setNeuronTypeParameterAParameterBParameterC

        public void setNeuronTypeParameterAParameterBParameterC​(int neuronType,
                                                        float parameterA,
                                                        float parameterB,
                                                        float parameterC)
        Specifies a neuron activation function to be used. This method can be used to add a neuron activation funtion of given type with associated scalar parameters A, B, and C that are shared across all output values. Note that this method can only be used to specify neurons which are specified by three (or fewer) parameters shared across all output values (or channels, in CNN nomenclature). It is an error to call this method for neuron activation functions like MPSCNNNeuronTypePReLU, which require per-channel parameter values. An MPSMatrixBatchNormalizationGradient kernel is initialized with a default neuron function of MPSCNNNeuronTypeNone.
        Parameters:
        neuronType - Type of neuron activation function. For full list see MPSCNNNeuronType.h
        parameterA - parameterA of neuron activation that is shared across all output values.
        parameterB - parameterB of neuron activation that is shared across all output values.
        parameterC - parameterC of neuron activation that is shared across all output values.

      • setSourceInputFeatureChannels

        public void setSourceInputFeatureChannels​(long value)
        [@property] sourceInputFeatureChannels The number of feature channels in the input vectors.

      • setSourceNumberOfFeatureVectors

        public void setSourceNumberOfFeatureVectors​(long value)
        [@property] sourceNumberOfFeatureVectors The number of input vectors which make up the input array.

      • setVersion_static

        public static void setVersion_static​(long aVersion)

      • sourceInputFeatureChannels

        public long sourceInputFeatureChannels()
        [@property] sourceInputFeatureChannels The number of feature channels in the input vectors.

      • sourceNumberOfFeatureVectors

        public long sourceNumberOfFeatureVectors()
        [@property] sourceNumberOfFeatureVectors The number of input vectors which make up the input array.

      • superclass_static

        public static org.moe.natj.objc.Class superclass_static()

      • supportsSecureCoding

        public static boolean supportsSecureCoding()

      • _supportsSecureCoding

        public boolean _supportsSecureCoding()
        Description copied from interface: NSSecureCoding
        This property must return YES on all classes that allow secure coding. Subclasses of classes that adopt NSSecureCoding and override initWithCoder: must also override this method and return YES. The Secure Coding Guide should be consulted when writing methods that decode data.
        Specified by:
        _supportsSecureCoding in interface NSSecureCoding
        Overrides:
        _supportsSecureCoding in class MPSMatrixBinaryKernel

      • version_static

        public static long version_static()