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mpscnnbinaryfullyconnectednode(3) [mojave man page]

MPSCNNBinaryFullyConnectedNode(3)			 MetalPerformanceShaders.framework			 MPSCNNBinaryFullyConnectedNode(3)

NAME
MPSCNNBinaryFullyConnectedNode SYNOPSIS
#import <MPSNNGraphNodes.h> Inherits MPSCNNBinaryConvolutionNode. Instance Methods (nonnull instancetype) - initWithSource:weights:scaleValue:type:flags: (nonnull instancetype) - initWithSource:weights:outputBiasTerms:outputScaleTerms:inputBiasTerms:inputScaleTerms:type:flags: Class Methods (nonnull instancetype) + nodeWithSource:weights:scaleValue:type:flags: (nonnull instancetype) + nodeWithSource:weights:outputBiasTerms:outputScaleTerms:inputBiasTerms:inputScaleTerms:type:flags: Additional Inherited Members Detailed Description A MPSNNFilterNode representing a MPSCNNBinaryFullyConnected kernel Method Documentation - (nonnull instancetype) initWithSource: (MPSNNImageNode *__nonnull) sourceNode(nonnull id< MPSCNNConvolutionDataSource >) weights(const float *__nullable) outputBiasTerms(const float *__nullable) outputScaleTerms(const float *__nullable) inputBiasTerms(const float *__nullable) inputScaleTerms(MPSCNNBinaryConvolutionType) type(MPSCNNBinaryConvolutionFlags) flags Init a node representing a MPSCNNBinaryFullyConnected kernel Parameters: sourceNode The MPSNNImageNode representing the source MPSImage for the filter weights A pointer to a valid object conforming to the MPSCNNConvolutionDataSource protocol. This object is provided by you to encapsulate storage for convolution weights and biases. outputBiasTerms A pointer to bias terms to be applied to the convolution output. See MPSCNNBinaryConvolution for more details. outputScaleTerms A pointer to scale terms to be applied to binary convolution results per output feature channel. See MPSCNNBinaryConvolution for more details. inputBiasTerms A pointer to offset terms to be applied to the input before convolution and before input scaling. See MPSCNNBinaryConvolution for more details. inputScaleTerms A pointer to scale terms to be applied to the input before convolution, but after input biasing. See MPSCNNBinaryConvolution for more details. type What kind of binarization strategy is to be used. flags See documentation of MPSCNNBinaryConvolutionFlags. Returns: A new MPSNNFilter node for a MPSCNNBinaryFullyConnected kernel. Implements MPSCNNBinaryConvolutionNode. - (nonnull instancetype) initWithSource: (MPSNNImageNode *__nonnull) sourceNode(nonnull id< MPSCNNConvolutionDataSource >) weights(float) scaleValue(MPSCNNBinaryConvolutionType) type(MPSCNNBinaryConvolutionFlags) flags Init a node representing a MPSCNNBinaryFullyConnected kernel Parameters: sourceNode The MPSNNImageNode representing the source MPSImage for the filter weights A pointer to a valid object conforming to the MPSCNNConvolutionDataSource protocol. This object is provided by you to encapsulate storage for convolution weights and biases. scaleValue A floating point value used to scale the entire convolution. type What kind of binarization strategy is to be used. flags See documentation of MPSCNNBinaryConvolutionFlags. Returns: A new MPSNNFilter node for a MPSCNNBinaryFullyConnected kernel. Implements MPSCNNBinaryConvolutionNode. + (nonnull instancetype) nodeWithSource: (MPSNNImageNode *__nonnull) sourceNode(nonnull id< MPSCNNConvolutionDataSource >) weights(const float *__nullable) outputBiasTerms(const float *__nullable) outputScaleTerms(const float *__nullable) inputBiasTerms(const float *__nullable) inputScaleTerms(MPSCNNBinaryConvolutionType) type(MPSCNNBinaryConvolutionFlags) flags Init an autoreleased node representing a MPSCNNBinaryFullyConnected kernel Parameters: sourceNode The MPSNNImageNode representing the source MPSImage for the filter weights A pointer to a valid object conforming to the MPSCNNConvolutionDataSource protocol. This object is provided by you to encapsulate storage for convolution weights and biases. outputBiasTerms A pointer to bias terms to be applied to the convolution output. See MPSCNNBinaryConvolution for more details. outputScaleTerms A pointer to scale terms to be applied to binary convolution results per output feature channel. See MPSCNNBinaryConvolution for more details. inputBiasTerms A pointer to offset terms to be applied to the input before convolution and before input scaling. See MPSCNNBinaryConvolution for more details. inputScaleTerms A pointer to scale terms to be applied to the input before convolution, but after input biasing. See MPSCNNBinaryConvolution for more details. type What kind of binarization strategy is to be used. flags See documentation of MPSCNNBinaryConvolutionFlags. Returns: A new MPSNNFilter node for a MPSCNNBinaryFullyConnected kernel. Implements MPSCNNBinaryConvolutionNode. + (nonnull instancetype) nodeWithSource: (MPSNNImageNode *__nonnull) sourceNode(nonnull id< MPSCNNConvolutionDataSource >) weights(float) scaleValue(MPSCNNBinaryConvolutionType) type(MPSCNNBinaryConvolutionFlags) flags Init an autoreleased node representing a MPSCNNBinaryFullyConnected kernel Parameters: sourceNode The MPSNNImageNode representing the source MPSImage for the filter weights A pointer to a valid object conforming to the MPSCNNConvolutionDataSource protocol. This object is provided by you to encapsulate storage for convolution weights and biases. scaleValue A floating point value used to scale the entire convolution. type What kind of binarization strategy is to be used. flags See documentation of MPSCNNBinaryConvolutionFlags. Returns: A new MPSNNFilter node for a MPSCNNBinaryFullyConnected kernel. Implements MPSCNNBinaryConvolutionNode. Author Generated automatically by Doxygen for MetalPerformanceShaders.framework from the source code. Version MetalPerformanceShaders-100 Thu Feb 8 2018 MPSCNNBinaryFullyConnectedNode(3)
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