mpscnnconvolutiondatasource-p(3) [mojave man page]
<MPSCNNConvolutionDataSource>(3) MetalPerformanceShaders.framework <MPSCNNConvolutionDataSource>(3) NAME
<MPSCNNConvolutionDataSource> SYNOPSIS
#include <MPSCNNConvolution.h> Detailed Description Provides convolution filter weights and bias terms The MPSCNNConvolutionDataSource protocol declares the methods that an instance of MPSCNNConvolution uses to obtain the weights and bias terms for the CNN convolution filter. Why? CNN weights can be large. If multiple copies of all the weights for all the convolutions are available unpacked in memory at the same time, some devices can run out of memory. The MPSCNNConvolutionDataSource is used to encapsulate a reference to the weights such as a file path, so that unpacking can be deferred until needed, then purged soon thereafter so that not all of the data must be in memory at the same time. MPS does not provide a class that conforms to this protocol. It is up to the developer to craft his own to encapsulate his data. Batch normalization and the neuron activation function are handled using the -descriptor method. Thread safety: The MPSCNNConvolutionDataSource object can be called by threads that are not the main thread. If you will be creating multiple MPSNNGraph objects concurrently in multiple threads and these share MPSCNNConvolutionDataSources, then the data source objects may be called reentrantly. Author Generated automatically by Doxygen for MetalPerformanceShaders.framework from the source code. Version MetalPerformanceShaders-100 Thu Feb 8 2018 <MPSCNNConvolutionDataSource>(3)
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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)