.TH "MPSCNNNeuronGradient" 3 "Mon Jul 9 2018" "Version MetalPerformanceShaders-119.3" "MetalPerformanceShaders.framework" \" -*- nroff -*-
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.SH NAME
MPSCNNNeuronGradient
.SH SYNOPSIS
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.PP
.PP
\fC#import <MPSCNNNeuron\&.h>\fP
.PP
Inherits \fBMPSCNNGradientKernel\fP\&.
.SS "Instance Methods"

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.RI "(nonnull instancetype) \- \fBinitWithDevice:\fP"
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.RI "(nonnull instancetype) \- \fBinitWithDevice:neuronDescriptor:\fP"
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.RI "(nullable instancetype) \- \fBinitWithCoder:device:\fP"
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.SS "Properties"

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.RI "\fBMPSCNNNeuronType\fP \fBneuronType\fP"
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.RI "float \fBa\fP"
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.RI "float \fBb\fP"
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.RI "float \fBc\fP"
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.RI "NSData * \fBdata\fP"
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.SS "Additional Inherited Members"
.SH "Detailed Description"
.PP 
This depends on Metal\&.framework  This filter is a backward filter for the neuron activation function filter\&.
.PP
The following filter types are supported: MPSCNNNeuronTypeNone ///< df/dx = 1 MPSCNNNeuronTypeLinear ///< df/dx = a MPSCNNNeuronTypeReLU ///< df/dx = [ 1, if x >= 0 [ a, if x < 0 MPSCNNNeuronTypeSigmoid ///< df/dx = e^x / (e^x + 1)^2 MPSCNNNeuronTypeHardSigmoid ///< df/dx = [ a, if (x >= 0) and (x <= 1) [ 0, otherwise MPSCNNNeuronTypeTanH ///< df/dx = a * b * (1 - tanh^2(b * x)) MPSCNNNeuronTypeAbsolute ///< df/dx = sign(x) MPSCNNNeuronTypeSoftPlus ///< df/dx = (a * b * exp(b * x)) / (exp(b * x) + 1) MPSCNNNeuronTypeSoftSign ///< df/dx = 1 / (|x| + 1)^2 MPSCNNNeuronTypeELU ///< df/dx = [ a * exp(x), x < 0 [ 1, x >= 0 MPSCNNNeuronTypePReLU ///< df/dx = [ 1, if x >= 0 [ aV, if x < 0 MPSCNNNeuronTypeReLUN ///< df/dx = [ 1, if x >= 0 [ a, if x < 0 [ b, if x >= b MPSCNNNeuronTypePower ///< df/dx = a * c * (a * x + b)^(c - 1) MPSCNNNeuronTypeExponential ///< df/dx = [ a * exp(a * x + b), if c == -1 [ a * log(c) * c^(a * x + b), if c != -1 MPSCNNNeuronTypeLogarithm ///< df/dx = [ a / (a * in + b), if c == -1 [ a / (log(c) * (a * in + b)), if c != -1
.PP
The result of the above operation is multiplied with the gradient, computed by the preceeding filter (going backwards)\&. 
.SH "Method Documentation"
.PP 
.SS "\- (nullable instancetype) \fBinitWithCoder:\fP (NSCoder *__nonnull) aDecoder(nonnull id< MTLDevice >) device"
\fBNSSecureCoding\fP 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\&. 
.PP
\fBParameters:\fP
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\fIaDecoder\fP The NSCoder subclass with your serialized \fBMPSKernel\fP 
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\fIdevice\fP The MTLDevice on which to make the \fBMPSKernel\fP 
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\fBReturns:\fP
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\fBA\fP new \fBMPSKernel\fP object, or nil if failure\&. 
.RE
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.PP
Reimplemented from \fBMPSCNNGradientKernel\fP\&.
.SS "\- (nonnull instancetype) initWithDevice: (nonnull id< MTLDevice >) device"
Standard init with default properties per filter type 
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\fBParameters:\fP
.RS 4
\fIdevice\fP The device that the filter will be used on\&. May not be NULL\&. 
.RE
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\fBReturns:\fP
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\fBA\fP 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\&. 
.RE
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Reimplemented from \fBMPSCNNGradientKernel\fP\&.
.SS "\- (nonnull instancetype) \fBinitWithDevice:\fP (nonnull id< MTLDevice >) device(\fBMPSNNNeuronDescriptor\fP *_Nonnull) neuronDescriptor"
Initialize the neuron gradient filter with a neuron descriptor\&. 
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\fBParameters:\fP
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\fIdevice\fP The device the filter will run on\&. 
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\fIneuronDescriptor\fP The neuron descriptor\&. For the neuron of type MPSCNNNeuronTypePReLU, the neuron descriptor references an NSData object containing a float array with the per feature channel value of PReLu parameter and, in this case, the \fBMPSCNNNeuronGradient\fP retains the NSData object\&. 
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\fBReturns:\fP
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\fBA\fP valid \fBMPSCNNNeuronGradient\fP object or nil, if failure\&. 
.RE
.PP

.SH "Property Documentation"
.PP 
.SS "\- (float) a\fC [read]\fP, \fC [nonatomic]\fP, \fC [assign]\fP"

.SS "\- (float) b\fC [read]\fP, \fC [nonatomic]\fP, \fC [assign]\fP"

.SS "\- (float) c\fC [read]\fP, \fC [nonatomic]\fP, \fC [assign]\fP"

.SS "\- (NSData*) data\fC [read]\fP, \fC [nonatomic]\fP, \fC [retain]\fP"

.SS "\- (\fBMPSCNNNeuronType\fP) neuronType\fC [read]\fP, \fC [nonatomic]\fP, \fC [assign]\fP"


.SH "Author"
.PP 
Generated automatically by Doxygen for MetalPerformanceShaders\&.framework from the source code\&.