MPSCNNFullyConnected(3)

NAME

       MPSCNNFullyConnected

SYNOPSIS

       #import <MPSCNNConvolution.h>

       Inherits MPSCNNConvolution.

   Instance Methods
       (nonnull instancetype) -
           initWithDevice:convolutionDescriptor:kernelWeights:biasTerms:flags:
       (nonnull instancetype) - initWithDevice:weights:
       (nullable instancetype) - initWithCoder:device:
       (nonnull instancetype) - initWithDevice:

   Additional Inherited Members

Detailed Description

       This depends on Metal.framework  The MPSCNNFullyConnected specifies a
       fully connected convolution layer a.k.a. Inner product layer. A fully
       connected CNN layer is one where every input channel is connected to
       every output channel. The kernel width is equal to width of source
       image and the kernel height is equal to the height of source image.
       Width and height of the output is 1x1. Thus, it takes a srcW x srcH x
       Ni MPSCNNImage, convolves it with Weights[No][SrcW][srcH][Ni] and
       produces a 1 x 1 x No output. The following must be true:

       kernelWidth  == source.width
       kernelHeight == source.height
       clipRect.size.width == 1
       clipRect.size.height == 1


        One can think of a fully connected layer as a matrix multiplication
       that flattens an image into a vector of length srcW*srcH*Ni. The
       weights are arragned in a matrix of dimension No x (srcW*srcH*Ni) for
       product output vectors of length No. The strideInPixelsX,
       strideInPixelsY, and group must be 1. Offset is not applicable and is
       ignored. Since clipRect is clamped to the destination image bounds, if
       the destination is 1x1, one doesn't need to set the clipRect.

       Note that one can implement an inner product using MPSCNNConvolution by
       setting

       offset = (kernelWidth/2,kernelHeight/2)
       clipRect.origin = (ox,oy), clipRect.size = (1,1)
       strideX = strideY = group = 1


        However, using the MPSCNNFullyConnected for this is better for
       performance as it lets us choose the most performant method which may
       not be possible when using a general convolution. For example, we may
       internally use matrix multiplication or special reduction kernels for a
       specific platform.

Method Documentation

   - (nullable instancetype) initWithCoder: (NSCoder *__nonnull)
       aDecoder(nonnull id< MTLDevice >) 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.

       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.



       Reimplemented from MPSCNNConvolution.

   - (nonnull instancetype) initWithDevice: (nonnull id< MTLDevice >) device
       Standard init with default properties per filter type

       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.



       Reimplemented from MPSCNNConvolution.

   - (nonnull instancetype) initWithDevice: (nonnull id< MTLDevice >)
       device(const MPSCNNConvolutionDescriptor *__nonnull)
       fullyConnectedDescriptor(const float *__nonnull) kernelWeights(const
       float *__nullable) biasTerms(MPSCNNConvolutionFlags) flags
       Initializes a fully connected kernel.

       Parameters:
           device The MTLDevice on which this MPSCNNFullyConnected filter will
           be used
           fullyConnectedDescriptor A pointer to a
           MPSCNNConvolutionDescriptor. strideInPixelsX, strideInPixelsY and
           group properties of fullyConnectedDescriptor must be set to 1
           (default).
           kernelWeights A pointer to a weights array. Each entry is a float
           value. The number of entries is = inputFeatureChannels *
           outputFeatureChannels * kernelHeight * kernelWidth The layout of
           filter weight is so that it can be reinterpreted as 4D tensor
           (array) weight[ outputChannels ][ kernelHeight ][ kernelWidth ][
           inputChannels / groups ] Weights are converted to half float (fp16)
           internally for best performance.
           biasTerms A pointer to bias terms to be applied to the convolution
           output. Each entry is a float value. The number of entries is =
           numberOfOutputFeatureMaps
           flags Currently unused. Pass MPSCNNConvolutionFlagsNone

       Returns:
           A valid MPSCNNConvolution object or nil, if failure.



       Reimplemented from MPSCNNConvolution.

   - (nonnull instancetype) initWithDevice: (nonnull id< MTLDevice >)
       device(nonnull id< MPSCNNConvolutionDataSource >) weights
       Initializes a fully connected kernel

       Parameters:
           device The MTLDevice on which this MPSCNNFullyConnected filter will
           be used
           weights A pointer to a object that conforms to the
           MPSCNNConvolutionDataSource protocol. The
           MPSCNNConvolutionDataSource protocol declares the methods that an
           instance of MPSCNNFullyConnected uses to obtain the weights and
           bias terms for the CNN fully connected filter.

       Returns:
           A valid MPSCNNFullyConnected object or nil, if failure.



       Reimplemented from MPSCNNConvolution.

Author

       Generated automatically by Doxygen for
       MetalPerformanceShaders.framework from the source code.





Version MetalPerformanceShaders-Thu2Jul 13 2017        MPSCNNFullyConnected(3)


Mac OS X 10.13.1 - Generated Mon Nov  6 16:26:24 CST 2017