Package apple.metalperformanceshaders

Class MPSMatrixNeuronGradient

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

    • Constructor Detail

      • MPSMatrixNeuronGradient

        protected MPSMatrixNeuronGradient​(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)

      • alpha

        public double alpha()
        [@property] alpha The scale factor to apply to the input.

      • 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()

      • encodeToCommandBufferGradientMatrixInputMatrixBiasVectorResultGradientForDataMatrixResultGradientForBiasVector

        public void encodeToCommandBufferGradientMatrixInputMatrixBiasVectorResultGradientForDataMatrixResultGradientForBiasVector​(MTLCommandBuffer commandBuffer,
                                                                                                                           MPSMatrix gradientMatrix,
                                                                                                                           MPSMatrix inputMatrix,
                                                                                                                           MPSVector biasVector,
                                                                                                                           MPSMatrix resultGradientForDataMatrix,
                                                                                                                           MPSVector resultGradientForBiasVector)
        Encode a MPSMatrixNeuronGradient 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 MPSMatrixNeuron operation.
        inputMatrix - A matrix containing the inputs to a forward MPSMatrixNeuron operation for which the gradient values are to be computed.
        biasVector - A vector containing the bias terms.
        resultGradientForDataMatrix - The matrix containing the resulting gradient values.
        resultGradientForBiasVector - If non-NULL the vector containing gradients for the bias terms.

      • hash_static

        public static long hash_static()

      • initWithCoderDevice

        public MPSMatrixNeuronGradient 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 MPSMatrixNeuronGradient
        device - The MTLDevice on which to make the MPSMatrixNeuronGradient object.
        Returns:
        A new MPSMatrixNeuronGradient object, or nil if failure.

      • initWithDevice

        public MPSMatrixNeuronGradient 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)

      • setAlpha

        public void setAlpha​(double value)
        [@property] alpha The scale factor to apply to the input.

      • setNeuronToPReLUWithParametersA

        public void setNeuronToPReLUWithParametersA​(NSData A)
        Add per output value neuron parameters A for PReLu neuron activation functions. This method sets the neuron to PReLU, zeros parameters A and B and sets the per output value neuron parameters A to an array containing a unique value of A for each output value. If the neuron function is f(v,a,b), it will apply resultMatrix(i, j) = f( input(i, j), A[j], B[j] ) where j in [0, sourceInputFeatureChannels] See https://arxiv.org/pdf/1502.01852.pdf for details. All other neuron types, where parameter A and parameter B are shared across output values must be set using -setNeuronType:parameterA:parameterB:
        Parameters:
        A - An array containing float values for neuron parameter A. Number of entries must be equal to MIN(inputMatrix.columns - sourceMatrixOrigin.y, sourceInputFeatureChannels)

      • 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. For those kind of neuron activation functions, use appropriate setter functions. An MPSMatrixNeuron 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()