Package apple.metalperformanceshaders

Class MPSCNNBinaryFullyConnected

  • All Implemented Interfaces:
    NSCoding, NSCopying, NSSecureCoding, NSObject
    public class MPSCNNBinaryFullyConnected
extends MPSCNNBinaryConvolution
    MPSCNNBinaryFullyConnected [@dependency] This depends on Metal.framework The MPSCNNBinaryFullyConnected specifies a fully connected convolution layer with binary weights and optionally binarized input image. See @ref MPSCNNFullyConnected for details on the fully connected layer and MPSCNNBinaryConvolution for binary convolutions. The default padding policy for MPSCNNBinaryConvolution is different from most filters. It uses MPSNNPaddingMethodSizeValidOnly instead of MPSNNPaddingMethodSizeSame.

    • Constructor Detail

      • MPSCNNBinaryFullyConnected

        protected MPSCNNBinaryFullyConnected​(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()

      • description_static

        public static java.lang.String description_static()

      • hash_static

        public static long hash_static()

      • initWithCoderDevice

        public MPSCNNBinaryFullyConnected initWithCoderDevice​(NSCoder aDecoder,
                                                      java.lang.Object device)
        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 MPSCNNBinaryConvolution
        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 MPSCNNBinaryFullyConnected initWithDevice​(java.lang.Object device)
        Description copied from class: MPSCNNKernel
        Standard init with default properties per filter type
        Overrides:
        initWithDevice in class MPSCNNBinaryConvolution
        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.

      • initWithDeviceConvolutionDataOutputBiasTermsOutputScaleTermsInputBiasTermsInputScaleTermsTypeFlags

        public MPSCNNBinaryFullyConnected initWithDeviceConvolutionDataOutputBiasTermsOutputScaleTermsInputBiasTermsInputScaleTermsTypeFlags​(MTLDevice device,
                                                                                                                                     MPSCNNConvolutionDataSource convolutionData,
                                                                                                                                     org.moe.natj.general.ptr.ConstFloatPtr outputBiasTerms,
                                                                                                                                     org.moe.natj.general.ptr.ConstFloatPtr outputScaleTerms,
                                                                                                                                     org.moe.natj.general.ptr.ConstFloatPtr inputBiasTerms,
                                                                                                                                     org.moe.natj.general.ptr.ConstFloatPtr inputScaleTerms,
                                                                                                                                     long type,
                                                                                                                                     long flags)
        Initializes a binary fully connected kernel with binary weights as well as both pre and post scaling terms.
        Overrides:
        initWithDeviceConvolutionDataOutputBiasTermsOutputScaleTermsInputBiasTermsInputScaleTermsTypeFlags in class MPSCNNBinaryConvolution
        Parameters:
        device - The MTLDevice on which this MPSCNNBinaryFullyConnected filter will be used
        convolutionData - A pointer to a object that conforms to the MPSCNNConvolutionDataSource protocol. The MPSCNNConvolutionDataSource protocol declares the methods that an instance of MPSCNNBinaryFullyConnected uses to obtain the weights and the convolution descriptor. Each entry in the convolutionData:weights array is a 32-bit unsigned integer value and each bit represents one filter weight (given in machine byte order). The featurechannel indices increase from the least significant bit within the 32-bits. The number of entries is = ceil( inputFeatureChannels/32.0 ) * outputFeatureChannels * kernelHeight * kernelWidth The layout of filter weight is so that it can be reinterpreted as a 4D tensor (array) weight[ outputChannels ][ kernelHeight ][ kernelWidth ][ ceil( inputChannels / 32.0 ) ] (The ordering of the reduction from 4D tensor to 1D is per C convention. The index based on inputchannels varies most rapidly, followed by kernelWidth, then kernelHeight and finally outputChannels varies least rapidly.)
        outputBiasTerms - A pointer to bias terms to be applied to the convolution output. Each entry is a float value. The number of entries is = numberOfOutputFeatureMaps. If nil then 0.0 is used for bias. The values stored in the pointer are copied in and the array can be freed after this function returns.
        outputScaleTerms - A pointer to scale terms to be applied to binary convolution results per output feature channel. Each entry is a float value. The number of entries is = numberOfOutputFeatureMaps. If nil then 1.0 is used. The values stored in the pointer are copied in and the array can be freed after this function returns.
        inputBiasTerms - A pointer to offset terms to be applied to the input before convolution and before input scaling. Each entry is a float value. The number of entries is 'inputFeatureChannels'. If NULL then 0.0 is used for bias. The values stored in the pointer are copied in and the array can be freed after this function returns.
        inputScaleTerms - A pointer to scale terms to be applied to the input before convolution, but after input biasing. Each entry is a float value. The number of entries is 'inputFeatureChannels'. If nil then 1.0 is used. The values stored in the pointer are copied in and the array can be freed after this function returns.
        type - What kind of binarization strategy is to be used.
        flags - See documentation above and documentation of MPSCNNBinaryConvolutionFlags.
        Returns:
        A valid MPSCNNBinaryFullyConnected object or nil, if failure.

      • initWithDeviceConvolutionDataScaleValueTypeFlags

        public MPSCNNBinaryFullyConnected initWithDeviceConvolutionDataScaleValueTypeFlags​(MTLDevice device,
                                                                                   MPSCNNConvolutionDataSource convolutionData,
                                                                                   float scaleValue,
                                                                                   long type,
                                                                                   long flags)
        Initializes a binary fully connected kernel with binary weights and a single scaling term.
        Overrides:
        initWithDeviceConvolutionDataScaleValueTypeFlags in class MPSCNNBinaryConvolution
        Parameters:
        device - The MTLDevice on which this MPSCNNBinaryFullyConnected filter will be used
        convolutionData - A pointer to a object that conforms to the MPSCNNConvolutionDataSource protocol. The MPSCNNConvolutionDataSource protocol declares the methods that an instance of MPSCNNBinaryFullyConnected uses to obtain the weights and bias terms as well as the convolution descriptor. Each entry in the convolutionData:weights array is a 32-bit unsigned integer value and each bit represents one filter weight (given in machine byte order). The featurechannel indices increase from the least significant bit within the 32-bits. The number of entries is = ceil( inputFeatureChannels/32.0 ) * outputFeatureChannels * kernelHeight * kernelWidth The layout of filter weight is so that it can be reinterpreted as a 4D tensor (array) weight[ outputChannels ][ kernelHeight ][ kernelWidth ][ ceil( inputChannels / 32.0 ) ] (The ordering of the reduction from 4D tensor to 1D is per C convention. The index based on inputchannels varies most rapidly, followed by kernelWidth, then kernelHeight and finally outputChannels varies least rapidly.)
        scaleValue - A single floating point value used to scale the entire convolution. Each entry is a float value. The number of entries is 'inputFeatureChannels'. If nil then 1.0 is used.
        type - What kind of binarization strategy is to be used.
        flags - See documentation above and documentation of MPSCNNBinaryConvolutionFlags.
        Returns:
        A valid MPSCNNBinaryFullyConnected 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 MPSCNNBinaryConvolution

      • version_static

        public static long version_static()