Package apple.metalperformanceshaders

Class MPSMatrixBatchNormalization

  • All Implemented Interfaces:
    NSCoding, NSCopying, NSSecureCoding, NSObject
    public class MPSMatrixBatchNormalization
extends MPSMatrixUnaryKernel
    MPSMatrixBatchNormalization [@dependency] This depends on Metal.framework. Applies a batch normalization to a matrix. A MPSMatrixBatchNormalization object computes the batch normalization of a collection of feature vectors stored in an MPSMatrix. Feature vectors are stored in a row of the supplied input matrix and the normalization is performed along columns: y[i,j] = gamma[j] * (x[i,j] - mean(x[:,j])) / (variance(x[:,j]) + epsilon) + beta[j] where gamma and beta are supplied weight and bias factors and epsilon is a small value added to the variance. Optionally a neuron activation function may be applied to the result.

    • Constructor Detail

      • MPSMatrixBatchNormalization

        protected MPSMatrixBatchNormalization​(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()

      • computeStatistics

        public boolean computeStatistics()
        [@property] computeStatistics If YES the batch statistics will be computed prior to performing the normalization. Otherwise the provided statistics will be used. Defaults to NO at initialization time.

      • 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()

      • encodeToCommandBufferInputMatrixMeanVectorVarianceVectorGammaVectorBetaVectorResultMatrix

        public void encodeToCommandBufferInputMatrixMeanVectorVarianceVectorGammaVectorBetaVectorResultMatrix​(MTLCommandBuffer commandBuffer,
                                                                                                      MPSMatrix inputMatrix,
                                                                                                      MPSVector meanVector,
                                                                                                      MPSVector varianceVector,
                                                                                                      MPSVector gammaVector,
                                                                                                      MPSVector betaVector,
                                                                                                      MPSMatrix resultMatrix)
        Encode a MPSMatrixBatchNormalization object to a command buffer. Encodes the operation to the specified command buffer. resultMatrix must be large enough to hold a MIN(sourceNumberOfFeatureVectors, inputMatrix.rows - sourceMatrixOrigin.x) x MIN(inputMatrix.columns - sourceMatrixOrigin.y, sourceInputFeatureChannels) array. Let numChannels = MIN(inputMatrix.columns - sourceMatrixOrigin.y, sourceInputFeatureChannels) The gamma, beta, mean, and variance vectors must contain at least numChannels elements.
        Parameters:
        commandBuffer - A valid MTLCommandBuffer to receive the encoded kernel.
        inputMatrix - A valid MPSMatrix object which specifies the input array.
        meanVector - A valid MPSVector object containing batch mean values to be used to normalize the inputs if computeStatistics is NO. If computeStatistics is YES the resulting batch mean values will be returned in this array.
        varianceVector - A valid MPSVector object containing batch variance values to be used to normalize the inputs if computeStatistics is NO. If computeStatistics is YES the resulting batch variance values will be returned in this array.
        gammaVector - A valid MPSVector object which specifies the gamma terms, or a null object to indicate that no scaling is to be applied.
        betaVector - A valid MPSVector object which specifies the beta terms, or a null object to indicate that no values are to be added.
        resultMatrix - A valid MPSMatrix object which specifies the output array.

      • epsilon

        public float epsilon()
        [@property] epsilon A small value to add to the variance when normalizing the inputs. Defaults to FLT_MIN upon initialization.

      • hash_static

        public static long hash_static()

      • initWithCoderDevice

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

      • initWithDevice

        public MPSMatrixBatchNormalization initWithDevice​(java.lang.Object device)
        Description copied from class: MPSKernel
        Standard init with default properties per filter type
        Overrides:
        initWithDevice in class MPSMatrixUnaryKernel
        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)

      • setComputeStatistics

        public void setComputeStatistics​(boolean value)
        [@property] computeStatistics If YES the batch statistics will be computed prior to performing the normalization. Otherwise the provided statistics will be used. Defaults to NO at initialization time.

      • setEpsilon

        public void setEpsilon​(float value)
        [@property] epsilon A small value to add to the variance when normalizing the inputs. Defaults to FLT_MIN upon initialization.

      • 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 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 input size to to use in the operation. This is equivalent to the number of columns in the primary (input array) source matrix to consider and the number of channels to produce for the output matrix. This property is modifiable and defaults to NSUIntegerMax. At encode time the larger of this property or the available input size is used. The value of NSUIntegerMax thus indicates that all available columns in the input array (beginning at sourceMatrixOrigin.y) should be considered. Defines also the number of output feature channels. Note: The value used in the operation will be MIN(inputMatrix.columns - sourceMatrixOrigin.y, sourceInputFeatureChannels)

      • setSourceNumberOfFeatureVectors

        public void setSourceNumberOfFeatureVectors​(long value)
        [@property] sourceNumberOfFeatureVectors The number of input vectors which make up the input array. This is equivalent to the number of rows to consider from the primary source matrix. This property is modifiable and defaults to NSUIntegerMax. At encode time the larger of this property or the available number of inputs is used. The value of NSUIntegerMax thus indicates that all available input rows (beginning at sourceMatrixOrigin.x) should be considered.

      • setVersion_static

        public static void setVersion_static​(long aVersion)

      • sourceInputFeatureChannels

        public long sourceInputFeatureChannels()
        [@property] sourceInputFeatureChannels The input size to to use in the operation. This is equivalent to the number of columns in the primary (input array) source matrix to consider and the number of channels to produce for the output matrix. This property is modifiable and defaults to NSUIntegerMax. At encode time the larger of this property or the available input size is used. The value of NSUIntegerMax thus indicates that all available columns in the input array (beginning at sourceMatrixOrigin.y) should be considered. Defines also the number of output feature channels. Note: The value used in the operation will be MIN(inputMatrix.columns - sourceMatrixOrigin.y, sourceInputFeatureChannels)

      • sourceNumberOfFeatureVectors

        public long sourceNumberOfFeatureVectors()
        [@property] sourceNumberOfFeatureVectors The number of input vectors which make up the input array. This is equivalent to the number of rows to consider from the primary source matrix. This property is modifiable and defaults to NSUIntegerMax. At encode time the larger of this property or the available number of inputs is used. The value of NSUIntegerMax thus indicates that all available input rows (beginning at sourceMatrixOrigin.x) should be considered.

      • 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 MPSMatrixUnaryKernel

      • version_static

        public static long version_static()