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mpsmatrixfullyconnected(3) [mojave man page]

MPSMatrixFullyConnected(3)				 MetalPerformanceShaders.framework				MPSMatrixFullyConnected(3)

NAME
MPSMatrixFullyConnected SYNOPSIS
#import <MPSMatrixFullyConnected.h> Inherits MPSMatrixBinaryKernel. Instance Methods (void) - setNeuronType:parameterA:parameterB:parameterC: (MPSCNNNeuronType) - neuronType (float) - neuronParameterA (float) - neuronParameterB (float) - neuronParameterC (nonnull instancetype) - initWithDevice: (void) - encodeToCommandBuffer:inputMatrix:weightMatrix:biasVector:resultMatrix: (nullable instancetype) - initWithCoder:device: (nonnull instancetype) - copyWithZone:device: Properties NSUInteger sourceNumberOfFeatureVectors NSUInteger sourceInputFeatureChannels NSUInteger sourceOutputFeatureChannels double alpha Additional Inherited Members Detailed Description This depends on Metal.framework. Applies a fully connected neural network layer by performing a a matrix multiplication, adding a bias vector, scaling, and applying a neuron activation function. A MPSMatrixFullyConnected object computes: y = neuron(alpha * x * W + bias) y is the output matrix, x and W are input matrices corresponding to a collection of input vectors and weights respectively, and bias is a vector which is broadcast and accumulated to each row of the product. alpha is a scale factor applied to the product. neuron() is a pointwise function applied to the intermediate result. Method Documentation - (nonnull instancetype) copyWithZone: (nullable NSZone *) zone(nullable id< MTLDevice >) device Make a copy of this kernel for a new device - See also: MPSKernel Parameters: zone The NSZone in which to allocate the object device The device for the new MPSKernel. If nil, then use self.device. Returns: A pointer to a copy of this MPSKernel. This will fail, returning nil if the device is not supported. Devices must be MTLFeatureSet_iOS_GPUFamily2_v1 or later. Reimplemented from MPSKernel. - (void) encodeToCommandBuffer: (nonnull id< MTLCommandBuffer >) commandBuffer(MPSMatrix *__nonnull) inputMatrix(MPSMatrix *__nonnull) weightMatrix(MPSVector *__nullable) biasVector(MPSMatrix *__nonnull) resultMatrix Encode a MPSMatrixFullyConnected object to a command buffer. Parameters: commandBuffer A valid MTLCommandBuffer to receive the encoded kernel. inputMatrix A valid MPSMatrix object which specifies the input array. weightMatrix A valid MPSMatrix object which specifies the weight array. biasVector A valid MPSVector object which specifies the bias values, or a null object to indicate that no bias is to be applied. resultMatrix A valid MPSMatrix object which specifies the output array. Encodes the operation to the specified command buffer. resultMatrix must be large enough to hold a MIN(sourceNumberOfInputs, inputMatrix.rows - primarySourceMatrixOrigin.x) x MIN(sourceOutputFeatureChannels, weightMatrix.columns - secondarySourceMatrixOrigin.y) array. The bias vector must contain at least MIN(sourceOutputFeatureChannels, weightMatrix.columns - secondarySourceMatrixOrigin.y) elements. - (nullable instancetype) initWithCoder: (NSCoder *__nonnull) aDecoder(nonnull id< MTLDevice >) device NSSecureCoding compatability See MPSKernel::initWithCoder. Parameters: aDecoder The NSCoder subclass with your serialized MPSMatrixFullyConnected device The MTLDevice on which to make the MPSMatrixFullyConnected object. Returns: A new MPSMatrixFullyConnected object, or nil if failure. Reimplemented from MPSKernel. - (nonnull instancetype) initWithDevice: (nonnull id< MTLDevice >) device Standard init with default properties per filter type Parameters: device The device that the filter will be used on. May not be NULL. Returns: a 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. Reimplemented from MPSKernel. - (float) neuronParameterA Getter funtion for neuronType set using setNeuronType:parameterA:parameterB:parameterC method - (float) neuronParameterB Getter funtion for neuronType set using setNeuronType:parameterA:parameterB:parameterC method - (float) neuronParameterC Getter funtion for neuronType set using setNeuronType:parameterA:parameterB:parameterC method - (MPSCNNNeuronType) neuronType Getter funtion for neuronType set using setNeuronType:parameterA:parameterB:parameterC method - (void) setNeuronType: (MPSCNNNeuronType) neuronType(float) parameterA(float) parameterB(float) parameterC Specifies a neuron activation function to be used. This method can be used to add a neuron activation funtion of given type with associated scalar parameters A, B, and C that are shared across all output values. Note that this method can only be used to specify neurons which are specified by three (or fewer) parameters shared across all output values (or channels, in CNN nomenclature). It is an error to call this method for neuron activation functions like MPSCNNNeuronTypePReLU, which require per-channel parameter values. For those kind of neuron activation functions, use appropriate setter functions. An MPSMatrixFullyConnected kernel is initialized with a default neuron function of MPSCNNNeuronTypeNone. Parameters: neuronType Type of neuron activation function. For full list see MPSCNNNeuronType.h parameterA parameterA of neuron activation that is shared across all output values. parameterB parameterB of neuron activation that is shared across all output values. parameterC parameterC of neuron activation that is shared across all output values. Property Documentation - alpha [read], [write], [nonatomic], [assign] The scale factor to apply to the product. Specified in double precision. Will be converted to the appropriate precision in the implementation subject to rounding and/or clamping as necessary. Defaults to 1.0 at initialization time. - sourceInputFeatureChannels [read], [write], [nonatomic], [assign] The input size to to use in the operation. This is equivalent to the number of columns and the number of rows in the primary (input array) and secondary (weight array) source matrices respectively. This property is modifiable and defaults to NSUIntegerMax. At encode time the larger of this property or the available input size is used. The value of NSUIntegerMax thus indicates that all available columns in the input array (beginning at primarySourceMatrixOrigin.y) and all available rows in the weight array (beginning at secondarySourceMatrixOrigin.x) should be considered. Note: The value used in the operation will be MIN(MIN(inputMatrix.columns - primarySourceMatrixOrigin.y, weightMatrix.rows - secondarySourceMatrixOrigin.x), sourceInputFeatureChannels) - sourceNumberOfFeatureVectors [read], [write], [nonatomic], [assign] The number of input vectors which make up the input array. This is equivalent to the number of rows to consider from the primary source matrix. This property is modifiable and defaults to NSUIntegerMax. At encode time the larger of this property or the available number of inputs is used. The value of NSUIntegerMax thus indicates that all available input rows (beginning at primarySourceMatrixOrigin.x) should be considered. - sourceOutputFeatureChannels [read], [write], [nonatomic], [assign] The output size to to use in the operation. This is equivalent to the number of columns to consider in the weight array, or the secondary source matrix. This property is modifiable and defaults to NSUIntegerMax. At encode time the larger of this property or the available output size is used. The value of NSUIntegerMax thus indicates that all available columns in the weight array (beginning at secondarySourceMatrixOrigin.y) should be considered. Author Generated automatically by Doxygen for MetalPerformanceShaders.framework from the source code. Version MetalPerformanceShaders-100 Thu Feb 8 2018 MPSMatrixFullyConnected(3)
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