MPSCNNBinaryConvolutionNode
#import <MPSNNGraphNodes.h>
Inherits MPSCNNConvolutionNode.
Inherited by MPSCNNBinaryFullyConnectedNode.
(nonnull instancetype) -
initWithSource:weights:scaleValue:type:flags:
(nonnull instancetype) -
initWithSource:weights:outputBiasTerms:outputScaleTerms:inputBiasTerms:inputScaleTerms:type:flags:
(nonnull instancetype) +
nodeWithSource:weights:scaleValue:type:flags:
(nonnull instancetype) +
nodeWithSource:weights:outputBiasTerms:outputScaleTerms:inputBiasTerms:inputScaleTerms:type:flags:
MPSCNNConvolutionGradientStateNode *
convolutionGradientState
A MPSNNFilterNode representing a
MPSCNNBinaryConvolution kernel
- (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 MPSCNNBinaryConvolution
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
MPSCNNBinaryConvolution kernel.
Implemented in MPSCNNBinaryFullyConnectedNode.
- (nonnull instancetype) initWithSource: (MPSNNImageNode
*__nonnull) sourceNode(nonnull id< MPSCNNConvolutionDataSource >)
weights(float) scaleValue(MPSCNNBinaryConvolutionType)
type(MPSCNNBinaryConvolutionFlags) flags
Init a node representing a MPSCNNBinaryConvolution
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
MPSCNNBinaryConvolution kernel.
Implemented in MPSCNNBinaryFullyConnectedNode.
+ (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
MPSCNNBinaryConvolution 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
MPSCNNBinaryConvolution kernel.
Implemented in MPSCNNBinaryFullyConnectedNode.
+ (nonnull instancetype) nodeWithSource: (MPSNNImageNode
*__nonnull) sourceNode(nonnull id< MPSCNNConvolutionDataSource >)
weights(float) scaleValue(MPSCNNBinaryConvolutionType)
type(MPSCNNBinaryConvolutionFlags) flags
Init an autoreleased node representing a
MPSCNNBinaryConvolution 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
MPSCNNBinaryConvolution kernel.
Implemented in MPSCNNBinaryFullyConnectedNode.
- (MPSCNNConvolutionGradientStateNode*)
convolutionGradientState [read], [nonatomic], [assign]
unavailable
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