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

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