Package apple.metalperformanceshaders

Class MPSNNOptimizerRMSProp

  • All Implemented Interfaces:
    NSCoding, NSCopying, NSSecureCoding, NSObject
    public class MPSNNOptimizerRMSProp
extends MPSNNOptimizer
    MPSNNOptimizerRMSProp The MPSNNOptimizerRMSProp performs an RMSProp Update RMSProp is also known as root mean square propagation. s[t] = decay * s[t-1] + (1 - decay) * (g ^ 2) variable = variable - learningRate * g / (sqrt(s[t]) + epsilon) where, g is gradient of error wrt variable s[t] is weighted sum of squares of gradients

    • Constructor Detail

      • MPSNNOptimizerRMSProp

        protected MPSNNOptimizerRMSProp​(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()

      • debugDescription_static

        public static java.lang.String debugDescription_static()

      • decay

        public double decay()
        [@property] decay The decay at which we update sumOfSquares Default value is 0.9

      • description_static

        public static java.lang.String description_static()

      • encodeToCommandBufferBatchNormalizationGradientStateBatchNormalizationSourceStateInputSumOfSquaresVectorsResultState

        public void encodeToCommandBufferBatchNormalizationGradientStateBatchNormalizationSourceStateInputSumOfSquaresVectorsResultState​(MTLCommandBuffer commandBuffer,
                                                                                                                                 MPSCNNBatchNormalizationState batchNormalizationGradientState,
                                                                                                                                 MPSCNNBatchNormalizationState batchNormalizationSourceState,
                                                                                                                                 NSArray<? extends MPSVector> inputSumOfSquaresVectors,
                                                                                                                                 MPSCNNNormalizationGammaAndBetaState resultState)
        Encode an MPSNNOptimizerRMSProp object to a command buffer to perform out of place update The following operations would be applied s[t] = decay * s[t-1] + (1 - decay) * (g ^ 2) variable = variable - learningRate * g / (sqrt(s[t]) + epsilon) where, g is gradient of error wrt variable s[t] is weighted sum of squares of gradients
        Parameters:
        commandBuffer - A valid MTLCommandBuffer to receive the encoded kernel.
        batchNormalizationGradientState - A valid MPSCNNBatchNormalizationState object which specifies the input state with gradients for this update.
        batchNormalizationSourceState - A valid MPSCNNBatchNormalizationState object which specifies the input state with original gamma/beta for this update.
        inputSumOfSquaresVectors - An array MPSVector object which specifies the gradient sumOfSquares vectors which will be updated and overwritten. The index 0 corresponds to gamma, index 1 corresponds to beta, array can be of size 1 in which case beta won't be updated
        resultState - A valid MPSCNNNormalizationGammaAndBetaState object which specifies the resultValues state which will be updated and overwritten.

      • encodeToCommandBufferBatchNormalizationStateInputSumOfSquaresVectorsResultState

        public void encodeToCommandBufferBatchNormalizationStateInputSumOfSquaresVectorsResultState​(MTLCommandBuffer commandBuffer,
                                                                                            MPSCNNBatchNormalizationState batchNormalizationState,
                                                                                            NSArray<? extends MPSVector> inputSumOfSquaresVectors,
                                                                                            MPSCNNNormalizationGammaAndBetaState resultState)
        Encode an MPSNNOptimizerRMSProp object to a command buffer to perform out of place update The following operations would be applied s[t] = decay * s[t-1] + (1 - decay) * (g ^ 2) variable = variable - learningRate * g / (sqrt(s[t]) + epsilon) where, g is gradient of error wrt variable s[t] is weighted sum of squares of gradients
        Parameters:
        commandBuffer - A valid MTLCommandBuffer to receive the encoded kernel.
        batchNormalizationState - A valid MPSCNNBatchNormalizationState object which specifies the input state with gradients and original gamma/beta for this update.
        inputSumOfSquaresVectors - An array MPSVector object which specifies the gradient sumOfSquares vectors which will be updated and overwritten. The index 0 corresponds to gamma, index 1 corresponds to beta, array can be of size 1 in which case beta won't be updated
        resultState - A valid MPSCNNNormalizationGammaAndBetaState object which specifies the resultValues state which will be updated and overwritten.

      • encodeToCommandBufferConvolutionGradientStateConvolutionSourceStateInputSumOfSquaresVectorsResultState

        public void encodeToCommandBufferConvolutionGradientStateConvolutionSourceStateInputSumOfSquaresVectorsResultState​(MTLCommandBuffer commandBuffer,
                                                                                                                   MPSCNNConvolutionGradientState convolutionGradientState,
                                                                                                                   MPSCNNConvolutionWeightsAndBiasesState convolutionSourceState,
                                                                                                                   NSArray<? extends MPSVector> inputSumOfSquaresVectors,
                                                                                                                   MPSCNNConvolutionWeightsAndBiasesState resultState)
        Encode an MPSNNOptimizerRMSProp object to a command buffer to perform out of place update The following operations would be applied s[t] = decay * s[t-1] + (1 - decay) * (g ^ 2) variable = variable - learningRate * g / (sqrt(s[t]) + epsilon) where, g is gradient of error wrt variable s[t] is weighted sum of squares of gradients
        Parameters:
        commandBuffer - A valid MTLCommandBuffer to receive the encoded kernel.
        convolutionGradientState - A valid MPSCNNConvolutionGradientState object which specifies the input state with gradients for this update.
        convolutionSourceState - A valid MPSCNNConvolutionWeightsAndBiasesState object which specifies the input state with values to be updated.
        inputSumOfSquaresVectors - An array MPSVector object which specifies the gradient sumOfSquares vectors which will be updated and overwritten. The index 0 corresponds to weights, index 1 corresponds to biases, array can be of size 1 in which case biases won't be updated
        resultState - A valid MPSCNNConvolutionWeightsAndBiasesState object which specifies the resultValues state which will be updated and overwritten.

      • encodeToCommandBufferInputGradientMatrixInputValuesMatrixInputSumOfSquaresMatrixResultValuesMatrix

        public void encodeToCommandBufferInputGradientMatrixInputValuesMatrixInputSumOfSquaresMatrixResultValuesMatrix​(MTLCommandBuffer commandBuffer,
                                                                                                               MPSMatrix inputGradientMatrix,
                                                                                                               MPSMatrix inputValuesMatrix,
                                                                                                               MPSMatrix inputSumOfSquaresMatrix,
                                                                                                               MPSMatrix resultValuesMatrix)

      • encodeToCommandBufferInputGradientVectorInputValuesVectorInputSumOfSquaresVectorResultValuesVector

        public void encodeToCommandBufferInputGradientVectorInputValuesVectorInputSumOfSquaresVectorResultValuesVector​(MTLCommandBuffer commandBuffer,
                                                                                                               MPSVector inputGradientVector,
                                                                                                               MPSVector inputValuesVector,
                                                                                                               MPSVector inputSumOfSquaresVector,
                                                                                                               MPSVector resultValuesVector)
        Encode an MPSNNOptimizerRMSProp object to a command buffer to perform out of place update The following operations would be applied s[t] = decay * s[t-1] + (1 - decay) * (g ^ 2) variable = variable - learningRate * g / (sqrt(s[t]) + epsilon) where, g is gradient of error wrt variable s[t] is weighted sum of squares of gradients
        Parameters:
        commandBuffer - A valid MTLCommandBuffer to receive the encoded kernel.
        inputGradientVector - A valid MPSVector object which specifies the input vector of gradients for this update.
        inputValuesVector - A valid MPSVector object which specifies the input vector of values to be updated.
        inputSumOfSquaresVector - A valid MPSVector object which specifies the gradient velocity vector which will be updated and overwritten.
        resultValuesVector - A valid MPSVector object which specifies the resultValues vector which will be updated and overwritten.

      • epsilon

        public float epsilon()
        [@property] epsilon The epsilon at which we update values This value is usually used to ensure to avoid divide by 0, default value is 1e-8

      • hash_static

        public static long hash_static()

      • initWithCoderDevice

        public MPSNNOptimizerRMSProp initWithCoderDevice​(NSCoder aDecoder,
                                                 java.lang.Object device)
        Description copied from class: MPSKernel
        NSSecureCoding compatability While the standard NSSecureCoding/NSCoding method -initWithCoder: should work, since the file can't know which device your data is allocated on, we have to guess and may guess incorrectly. To avoid that problem, use initWithCoder:device instead.
        Overrides:
        initWithCoderDevice in class MPSNNOptimizer
        Parameters:
        aDecoder - The NSCoder subclass with your serialized MPSKernel
        device - The MTLDevice on which to make the MPSKernel
        Returns:
        A new MPSKernel object, or nil if failure.

      • initWithDevice

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

      • initWithDeviceDecayEpsilonOptimizerDescriptor

        public MPSNNOptimizerRMSProp initWithDeviceDecayEpsilonOptimizerDescriptor​(MTLDevice device,
                                                                           double decay,
                                                                           float epsilon,
                                                                           MPSNNOptimizerDescriptor optimizerDescriptor)
        Full initialization for the rmsProp update
        Parameters:
        device - The device on which the kernel will execute.
        decay - The decay to update sumOfSquares
        epsilon - The epsilon which will be applied
        optimizerDescriptor - The optimizerDescriptor which will have a bunch of properties to be applied
        Returns:
        A valid MPSNNOptimizerRMSProp object or nil, if failure.

      • initWithDeviceLearningRate

        public MPSNNOptimizerRMSProp initWithDeviceLearningRate​(MTLDevice device,
                                                        float learningRate)
        Convenience initialization for the RMSProp update
        Parameters:
        device - The device on which the kernel will execute.
        learningRate - The learningRate which will be applied
        Returns:
        A valid MPSNNOptimizerRMSProp object or nil, if failure.

      • 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)

      • 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)

      • setVersion_static

        public static void setVersion_static​(long aVersion)

      • 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 MPSNNOptimizer

      • version_static

        public static long version_static()