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Full Discussion: Using regex in find command
Top Forums UNIX for Dummies Questions & Answers Using regex in find command Post 302513176 by Zucriy Amsuna on Tuesday 12th of April 2011 02:03:30 PM
Old 04-12-2011
But that finds things like assign##.o and assign##.cpp. Why won't the variations work so it would just find what I want?

Or would I just have to pipe that into something else (I don't know what) to get the plain assign# or assign##?
 

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MPSCNNLossDescriptor(3) 				 MetalPerformanceShaders.framework				   MPSCNNLossDescriptor(3)

NAME
MPSCNNLossDescriptor SYNOPSIS
#import <MPSCNNLoss.h> Inherits NSObject, and <NSCopying>. Instance Methods (nonnull instancetype) - init Class Methods (nullable MPSCNNLossDescriptor *) + cnnLossDescriptorWithType:reductionType: Properties MPSCNNLossType lossType MPSCNNReductionType reductionType float weight float labelSmoothing NSUInteger numberOfClasses float epsilon float delta Detailed Description This depends on Metal.framework. The MPSCNNLossDescriptor specifies a loss filter descriptor. The same descriptor can be used to initialize both the MPSCNNLoss and the MPSCNNLossGradient filters. Method Documentation + (nullable MPSCNNLossDescriptor*) cnnLossDescriptorWithType: (MPSCNNLossType) lossType(MPSCNNReductionType) reductionType Make a descriptor for a MPSCNNLoss or MPSCNNLossGradient object. Parameters: lossType The type of a loss filter. reductionType The type of a reduction operation to apply. This argument is ignored in the MPSCNNLossGradient filter. Returns: A valid MPSCNNLossDescriptor object or nil, if failure. - (nonnull instancetype) init Property Documentation - delta [read], [write], [nonatomic], [assign] The delta parameter. The default value is 1.0f. This parameter is valid only for the loss functions of the following type(s): MPSCNNLossTypeHuber. Given predictions and labels (ground truth), it is applied in the following way: if (|predictions - labels| <= delta, loss = 0.5f * predictions^2 if (|predictions - labels| > delta, loss = 0.5 * delta^2 + delta * (|predictions - labels| - delta) - epsilon [read], [write], [nonatomic], [assign] The epsilon parameter. The default value is 1e-7. This parameter is valid only for the loss functions of the following type(s): MPSCNNLossTypeLog. Given predictions and labels (ground truth), it is applied in the following way: -(labels * log(predictions + epsilon)) - ((1 - labels) * log(1 - predictions + epsilon)) - labelSmoothing [read], [write], [nonatomic], [assign] The label smoothing parameter. The default value is 0.0f. This parameter is valid only for the loss functions of the following type(s): MPSCNNLossFunctionTypeSoftmaxCrossEntropy, MPSCNNLossFunctionTypeSigmoidCrossEntropy. MPSCNNLossFunctionTypeSoftmaxCrossEntropy: given labels (ground truth), it is applied in the following way: labels = labelSmoothing > 0 ? labels * (1 - labelSmoothing) + labelSmoothing / numberOfClasses : labels MPSCNNLossFunctionTypeSigmoidCrossEntropy: given labels (ground truth), it is applied in the following way: labels = labelSmoothing > 0 ? labels * (1 - labelSmoothing) + 0.5 * labelSmoothing : labels - lossType [read], [write], [nonatomic], [assign] The type of a loss filter. This parameter specifies the type of a loss filter. - numberOfClasses [read], [write], [nonatomic], [assign] The number of classes parameter. The default value is 1. This parameter is valid only for the loss functions of the following type(s): MPSCNNLossFunctionTypeSoftmaxCrossEntropy. Given labels (ground truth), it is applied in the following way: labels = labelSmoothing > 0 ? labels * (1 - labelSmoothing) + labelSmoothing / numberOfClasses : labels - reductionType [read], [write], [nonatomic], [assign] The type of a reduction operation performed in the loss filter. This parameter specifies the type of a reduction operation performed in the loss filter. - weight [read], [write], [nonatomic], [assign] The scale factor to apply to each element of a result. Each element of a result is multiplied by the weight value. The default value is 1.0f. Author Generated automatically by Doxygen for MetalPerformanceShaders.framework from the source code. Version MetalPerformanceShaders-100 Thu Feb 8 2018 MPSCNNLossDescriptor(3)
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