05-16-2014
Because I already have a tcsh file that does what I need and outputs a text file with the mean and stdev numbers. Now all I am trying to do is add a line or two at the very end so when I concatenate all subjects' files, I can keep the values and the subject id in good order.
thanks.
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LEARN ABOUT MOJAVE
mpsrnndescriptor
MPSRNNDescriptor(3) MetalPerformanceShaders.framework MPSRNNDescriptor(3)
NAME
MPSRNNDescriptor
SYNOPSIS
#import <MPSRNNLayer.h>
Inherits NSObject.
Inherited by MPSGRUDescriptor, MPSLSTMDescriptor, and MPSRNNSingleGateDescriptor.
Properties
NSUInteger inputFeatureChannels
NSUInteger outputFeatureChannels
BOOL useLayerInputUnitTransformMode
BOOL useFloat32Weights
MPSRNNSequenceDirection layerSequenceDirection
Detailed Description
This depends on Metal.framework The MPSRNNDescriptor specifies a Recursive neural network block/layer descriptor.
Property Documentation
- inputFeatureChannels [read], [write], [nonatomic], [assign]
The number of feature channels per pixel in the input image or number of rows in the input matrix.
- layerSequenceDirection [read], [write], [nonatomic], [assign]
When the layer specified with this descriptor is used to process a sequence of inputs by calling
See also:
encodeBidirectionalSequenceToCommandBuffer then this parameter defines in which direction the sequence is processed. The operation of
the layer is: (yt, ht, ct) = f(xt,ht-1,ct-1) for MPSRNNSequenceDirectionForward and (yt, ht, ct) = f(xt,ht+1,ct+1) for
MPSRNNSequenceDirectionBackward, where xt is the output of the previous layer that encodes in the same direction as this layer, (or the
input image or matrix if this is the first layer in stack with this direction).
MPSRNNImageInferenceLayer and
MPSRNNMatrixInferenceLayer.
- outputFeatureChannels [read], [write], [nonatomic], [assign]
The number of feature channels per pixel in the destination image or number of rows in the destination matrix.
- useFloat32Weights [read], [write], [nonatomic], [assign]
If YES, then MPSRNNMatrixInferenceLayer uses 32-bit floating point numbers internally for weights when computing matrix transformations. If
NO, then 16-bit, half precision floating point numbers are used. Currently MPSRNNImageInferenceLayer ignores this property and the
convolution operations always convert FP32 weights into FP16 for better performance. Defaults to NO.
- useLayerInputUnitTransformMode [read], [write], [nonatomic], [assign]
if YES then use identity transformation for all weights (W, Wr, Wi, Wf, Wo, Wc) affecting input x_j in this layer, even if said weights are
specified as nil. For example 'W_ij * x_j' is replaced by 'x_j' in formulae defined in MPSRNNSingleGateDescriptor. Defaults to NO.
Author
Generated automatically by Doxygen for MetalPerformanceShaders.framework from the source code.
Version MetalPerformanceShaders-100 Thu Feb 8 2018 MPSRNNDescriptor(3)