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mpscnnsoftmax(3) [mojave man page]

MPSCNNSoftMax(3)					 MetalPerformanceShaders.framework					  MPSCNNSoftMax(3)

NAME
MPSCNNSoftMax SYNOPSIS
#import <MPSCNNSoftMax.h> Inherits MPSCNNKernel. Additional Inherited Members Detailed Description This depends on Metal.framework The softMax filter is a neural transfer function and is useful for classification tasks. The softMax filter is applied across feature channels and in a convolutional manner at all spatial locations. The softMax filter can be seen as the combination of an activation function (exponential) and a normalization operator. For each feature channel per pixel in an image in a feature map, the softMax filter computes the following: result channel in pixel = exp(pixel(x,y,k))/sum(exp(pixel(x,y,0)) ... exp(pixel(x,y,N-1)) where N is the number of feature channels Author Generated automatically by Doxygen for MetalPerformanceShaders.framework from the source code. Version MetalPerformanceShaders-100 Thu Feb 8 2018 MPSCNNSoftMax(3)

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MPSCNNLogSoftMaxGradient(3)				 MetalPerformanceShaders.framework			       MPSCNNLogSoftMaxGradient(3)

NAME
MPSCNNLogSoftMaxGradient SYNOPSIS
#import <MPSCNNSoftMax.h> Inherits MPSCNNGradientKernel. Instance Methods (nonnull instancetype) - initWithDevice: (nullable instancetype) - initWithCoder:device: Additional Inherited Members Detailed Description This depends on Metal.framework The logSoftMax gradient filter calculates the gradient to be backpropagated. The logSoftMax gradient just as the log softMax filter, is applied across feature channels and at all spatial locations. It computes the gradient for a given output generated by the corresponding logSoftMax (i.e. MPSCNNLogSoftMax) layer and the gradient computed by the previous layer in the back- propagation pass. For each feature channel per pixel in an image in a feature map, the logSoftMax gradient filter computes the following: result gradient channel in pixel outputGradient(x,y,k) = inputGradient(x,y,k) - exp(logSoftMax(x,y,k)) * sum(inputGradient(x,y,0) ... inputGradient(x,y,N-1)) where N is the number of feature channels The incoming gradient is the primary source. The original output of corresponding logSoftMax is the secondary source. 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 MPSCNNGradientKernel. - (nonnull instancetype) initWithDevice: (nonnull id< MTLDevice >) device Initializes a MPSCNNLogSoftMaxGradient function Parameters: device The MTLDevice on which this MPSCNNLogSoftMaxGradient filter will be used Returns: A valid MPSCNNLogSoftMaxGradient object or nil, if failure. Reimplemented from MPSCNNGradientKernel. Author Generated automatically by Doxygen for MetalPerformanceShaders.framework from the source code. Version MetalPerformanceShaders-100 Thu Feb 8 2018 MPSCNNLogSoftMaxGradient(3)

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