MPSCNNArithmeticGradient(3)				 MetalPerformanceShaders.framework			       MPSCNNArithmeticGradient(3)

NAME

       MPSCNNArithmeticGradient

SYNOPSIS

       #import <MPSCNNMath.h>

       Inherits MPSCNNGradientKernel.

       Inherited by MPSCNNAddGradient, MPSCNNMultiplyGradient, and MPSCNNSubtractGradient.

   Instance Methods
       (nonnull instancetype) - initWithDevice:

   Properties
       float primaryScale
       float secondaryScale
       float bias
       NSUInteger secondaryStrideInFeatureChannels
       float minimumValue
       float maximumValue
       bool isSecondarySourceFilter

   Additional Inherited Members
Detailed Description
       This depends on Metal.framework	The MPSCNNArithmeticGradient filter is the backward filter for the MPSCNNArithmetic forward filter.

       The forward filter takes two inputs, primary and secondary source images, and produces a single output image. Thus, going backwards
       requires two separate filters (one for the primary source image and one for the secondary source image) that take multiple inputs and
       produce a single output. The secondarySourceFilter property is used to indicate whether the filter is operating on the primary or secondary
       source image from the forward pass.

       All the arithmetic gradient filters require the following inputs: gradient image from the previous layer (going backwards) and all the
       applicable input source images from the forward pass.

       The forward filter takes the following additional parameters:

       o primaryStrideInPixelsX, primaryStrideInPixelsY, primaryStrideInFeatureChannels

       o secondaryStrideInPixelsX, secondaryStrideInPixelsY, secondaryStrideInFeatureChannels These parameters can be used in the forward filter
	 to control broadcasting for the data stored in the primary and secondary source images. For example, setting all strides for the primary
	 source image to 0 will result in the primarySource image being treated as a single pixel. The only supported values are 0 or 1. The
	 default value of these parameters is 1.

       The first input to the backward filter is the gradient image from the previous layer (going backwards), so there are no broadcasting
       parameters for this input. For the backward filter, the broadcasting parameters for the second input must match the broadcasting parameters
       set for the same image in the forward filter.

       In the backward pass, broadcasting results in a reduction operation (sum) across all of the applicable broadcasting dimensions (rows,
       columns, feature channels, or any combination thereof) to produce the destination image of the size that matches the primary/secondary
       input images used in the forward pass.

       In the case of no broadcasting, the following arithmetic gradient operations are copy operations (that can be optimized away by the graph
       interface):

       o Add (primarySource, secondarySource)

       o Subtract (primarySource)

       Similarly to the forward filter, this backward filter takes additional parameters: primaryScale, secondaryScale, and bias. The default
       value for primaryScale and secondaryScale is 1.0f. The default value for bias is 0.0f. This filter applies primaryScale to the primary
       source image, applies the secondaryScale to the secondary source image, where appropriate, and applies bias to the result, i.e.: result =
       ((primaryScale * x) [insert operation] (secondaryScale * y)) + bias.

       The subtraction gradient filter for the secondary source image requires that the primaryScale property is set to -1.0f (for x - y, d/dy(x -
       y) = -1).

       In the forward filter, there is support for clamping the result of the available operations, where result = clamp(result, minimumValue,
       maximumValue). The clamp backward operation is not supported in the arithmetic gradient filters. If you require this functionality, it can
       be implemented by performing a clamp backward operation before calling the arithmetic gradient filters. You would need to apply the
       following function on the incomping gradient input image: f(x) = ((minimumValue < x) && (x < maximumValue)) ? 1 : 0, where x is the
       original result (before clamping) of the forward arithmetic filter.

       The number of output feature channels remains the same as the number of input feature channels.

       You must use one of the sub-classes of MPSImageArithmeticGradient.

Method Documentation
   - (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 MPSCNNGradientKernel.

       Reimplemented in MPSCNNAddGradient, MPSCNNSubtractGradient, and MPSCNNMultiplyGradient.

Property Documentation
   - (float) bias [read],  [write],  [nonatomic],  [assign]
   - isSecondarySourceFilter [read],  [write],	[nonatomic],  [assign]
       The isSecondarySourceFilter property is used to indicate whether the arithmetic gradient filter is operating on the primary or secondary
       source image from the forward pass. The default value of isSecondarySourceFilter is NO.

   - maximumValue [read],  [write],  [nonatomic],  [assign]
       maximumValue is used to clamp the result of an arithmetic operation: result = clamp(result, minimumValue, maximumValue). The default value
       of maximumValue is FLT_MAX.

   - minimumValue [read],  [write],  [nonatomic],  [assign]
       minimumValue is to clamp the result of an arithmetic operation: result = clamp(result, minimumValue, maximumValue). The default value of
       minimumValue is -FLT_MAX.

   - (float) primaryScale [read],  [write],  [nonatomic],  [assign]
   - (float) secondaryScale [read],  [write],  [nonatomic],  [assign]
   - (NSUInteger) secondaryStrideInFeatureChannels [read],  [write],  [nonatomic],  [assign]
Author
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Version MetalPerformanceShaders-100				  Thu Feb 8 2018				       MPSCNNArithmeticGradient(3)