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)

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)