Presage (formerly known as Soothsayer) is an intelligent predictive text entry platform. It exploits redundant information embedded in natural languages to generate predictions. Its modular and pluggable architecture allows its language model to be extended and customized to utilize statistical, syntactic, and semantic information sources. License: GNU General Public License (GPL) Changes:
This version is able to learn "on the fly" from the context and the text currently being entered. The smoothed n-gram predictive plugin dynamically learns from the current context, while generating new predictions. An n-gram count consistency bug triggered by the dynamic learning capability of the smoothed n-gram predictive plugin has been fixed in this release. Completion validation routine case sensitiveness, various compilation warnings, and prompter UTF8 encoding were fixed.
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
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Version MetalPerformanceShaders-100 Thu Feb 8 2018 MPSCNNLossDescriptor(3)