apple.mlcompute

Class MLCBatchNormalizationLayer

java.lang.Object

org.moe.natj.general.NativeObject

org.moe.natj.objc.ObjCObject

apple.NSObject

apple.mlcompute.MLCLayer

apple.mlcompute.MLCBatchNormalizationLayer

All Implemented Interfaces:

NSObject

public class MLCBatchNormalizationLayer
extends MLCLayer

MLCBatchNormalizationLayer

A batch normalizaion layer

Nested Class Summary

Nested classes/interfaces inherited from class apple.NSObject

NSObject.Function_instanceMethodForSelector_ret, NSObject.Function_methodForSelector_ret

Constructor Summary

Constructors

Modifier	Constructor and Description
protected	MLCBatchNormalizationLayer(org.moe.natj.general.Pointer peer)

Method Summary

Modifier and Type	Method and Description
static boolean	accessInstanceVariablesDirectly()
static MLCBatchNormalizationLayer	alloc()
static MLCBatchNormalizationLayer	allocWithZone(org.moe.natj.general.ptr.VoidPtr zone)
static boolean	automaticallyNotifiesObserversForKey(java.lang.String key)
MLCTensor	beta() [@property] beta
MLCTensorParameter	betaParameter() [@property] betaParameter
static void	cancelPreviousPerformRequestsWithTarget(java.lang.Object aTarget)
static void	cancelPreviousPerformRequestsWithTargetSelectorObject(java.lang.Object aTarget, org.moe.natj.objc.SEL aSelector, java.lang.Object anArgument)
static NSArray<java.lang.String>	classFallbacksForKeyedArchiver()
static org.moe.natj.objc.Class	classForKeyedUnarchiver()
static java.lang.String	debugDescription_static()
static java.lang.String	description_static()
long	featureChannelCount() [@property] featureChannelCount
MLCTensor	gamma() [@property] gamma
MLCTensorParameter	gammaParameter() [@property] gammaParameter
static long	hash_static()
MLCBatchNormalizationLayer	init()
static NSObject.Function_instanceMethodForSelector_ret	instanceMethodForSelector(org.moe.natj.objc.SEL aSelector)
static NSMethodSignature	instanceMethodSignatureForSelector(org.moe.natj.objc.SEL aSelector)
static boolean	instancesRespondToSelector(org.moe.natj.objc.SEL aSelector)
static boolean	isSubclassOfClass(org.moe.natj.objc.Class aClass)
static NSSet<java.lang.String>	keyPathsForValuesAffectingValueForKey(java.lang.String key)
static MLCBatchNormalizationLayer	layerWithFeatureChannelCountMeanVarianceBetaGammaVarianceEpsilon(long featureChannelCount, MLCTensor mean, MLCTensor variance, MLCTensor beta, MLCTensor gamma, float varianceEpsilon) Create a batch normalization layer
static MLCBatchNormalizationLayer	layerWithFeatureChannelCountMeanVarianceBetaGammaVarianceEpsilonMomentum(long featureChannelCount, MLCTensor mean, MLCTensor variance, MLCTensor beta, MLCTensor gamma, float varianceEpsilon, float momentum) Create a batch normalization layer
MLCTensor	mean() [@property] mean
float	momentum() [@property] momentum
static MLCBatchNormalizationLayer	new_objc()
static boolean	resolveClassMethod(org.moe.natj.objc.SEL sel)
static boolean	resolveInstanceMethod(org.moe.natj.objc.SEL sel)
static void	setVersion_static(long aVersion)
static org.moe.natj.objc.Class	superclass_static()
static boolean	supportsDataTypeOnDevice(int dataType, MLCDevice device)
MLCTensor	variance() [@property] variance
float	varianceEpsilon() [@property] varianceEpsilon
static long	version_static()

Methods inherited from class apple.mlcompute.MLCLayer

deviceType, isDebuggingEnabled, label, layerID, setIsDebuggingEnabled, setLabel

Methods inherited from class apple.NSObject

accessibilityActivate, accessibilityActivationPoint, accessibilityAssistiveTechnologyFocusedIdentifiers, accessibilityAttributedHint, accessibilityAttributedLabel, accessibilityAttributedUserInputLabels, accessibilityAttributedValue, accessibilityContainerType, accessibilityCustomActions, accessibilityCustomRotors, accessibilityDecrement, accessibilityDragSourceDescriptors, accessibilityDropPointDescriptors, accessibilityElementAtIndex, accessibilityElementCount, accessibilityElementDidBecomeFocused, accessibilityElementDidLoseFocus, accessibilityElementIsFocused, accessibilityElements, accessibilityElementsHidden, accessibilityFrame, accessibilityHint, accessibilityIncrement, accessibilityLabel, accessibilityLanguage, accessibilityNavigationStyle, accessibilityPath, accessibilityPerformEscape, accessibilityPerformMagicTap, accessibilityRespondsToUserInteraction, accessibilityScroll, accessibilityTextualContext, accessibilityTraits, accessibilityUserInputLabels, accessibilityValue, accessibilityViewIsModal, addObserverForKeyPathOptionsContext, attemptRecoveryFromErrorOptionIndex, attemptRecoveryFromErrorOptionIndexDelegateDidRecoverSelectorContextInfo, autoContentAccessingProxy, awakeAfterUsingCoder, awakeFromNib, class_objc, classForCoder, classForKeyedArchiver, copy, dealloc, debugDescription, description, dictionaryWithValuesForKeys, didChangeValueForKey, didChangeValueForKeyWithSetMutationUsingObjects, didChangeValuesAtIndexesForKey, doesNotRecognizeSelector, fileManagerShouldProceedAfterError, fileManagerWillProcessPath, finalize_objc, forwardingTargetForSelector, forwardInvocation, hash, indexOfAccessibilityElement, isAccessibilityElement, isEqual, isKindOfClass, isMemberOfClass, isProxy, methodForSelector, methodSignatureForSelector, mutableArrayValueForKey, mutableArrayValueForKeyPath, mutableCopy, mutableOrderedSetValueForKey, mutableOrderedSetValueForKeyPath, mutableSetValueForKey, mutableSetValueForKeyPath, observationInfo, observeValueForKeyPathOfObjectChangeContext, performSelector, performSelectorInBackgroundWithObject, performSelectorOnMainThreadWithObjectWaitUntilDone, performSelectorOnMainThreadWithObjectWaitUntilDoneModes, performSelectorOnThreadWithObjectWaitUntilDone, performSelectorOnThreadWithObjectWaitUntilDoneModes, performSelectorWithObject, performSelectorWithObjectAfterDelay, performSelectorWithObjectAfterDelayInModes, performSelectorWithObjectWithObject, prepareForInterfaceBuilder, provideImageDataBytesPerRowOrigin_Size_UserInfo, removeObserverForKeyPath, removeObserverForKeyPathContext, replacementObjectForCoder, replacementObjectForKeyedArchiver, respondsToSelector, self, setAccessibilityActivationPoint, setAccessibilityAttributedHint, setAccessibilityAttributedLabel, setAccessibilityAttributedUserInputLabels, setAccessibilityAttributedValue, setAccessibilityContainerType, setAccessibilityCustomActions, setAccessibilityCustomRotors, setAccessibilityDragSourceDescriptors, setAccessibilityDropPointDescriptors, setAccessibilityElements, setAccessibilityElementsHidden, setAccessibilityFrame, setAccessibilityHint, setAccessibilityLabel, setAccessibilityLanguage, setAccessibilityNavigationStyle, setAccessibilityPath, setAccessibilityRespondsToUserInteraction, setAccessibilityTextualContext, setAccessibilityTraits, setAccessibilityUserInputLabels, setAccessibilityValue, setAccessibilityViewIsModal, setIsAccessibilityElement, setNilValueForKey, setObservationInfo, setShouldGroupAccessibilityChildren, setValueForKey, setValueForKeyPath, setValueForUndefinedKey, setValuesForKeysWithDictionary, shouldGroupAccessibilityChildren, superclass, validateValueForKeyError, validateValueForKeyPathError, valueForKey, valueForKeyPath, valueForUndefinedKey, willChangeValueForKey, willChangeValueForKeyWithSetMutationUsingObjects, willChangeValuesAtIndexesForKey

Methods inherited from class org.moe.natj.objc.ObjCObject

equals, toString

Methods inherited from class org.moe.natj.general.NativeObject

finalize, getPeer, getPeerPointer

Methods inherited from class java.lang.Object

clone, getClass, hashCode, notify, notifyAll, wait, wait, wait

Constructor Detail

MLCBatchNormalizationLayer

protected MLCBatchNormalizationLayer(org.moe.natj.general.Pointer peer)

Method Detail

accessInstanceVariablesDirectly

public static boolean accessInstanceVariablesDirectly()

alloc

public static MLCBatchNormalizationLayer alloc()

allocWithZone

public static MLCBatchNormalizationLayer allocWithZone(org.moe.natj.general.ptr.VoidPtr zone)

automaticallyNotifiesObserversForKey

public static boolean automaticallyNotifiesObserversForKey(java.lang.String key)

beta

public MLCTensor beta()

[@property] beta

The beta tensor

betaParameter

public MLCTensorParameter betaParameter()

[@property] betaParameter

The beta tensor parameter used for optimizer update

cancelPreviousPerformRequestsWithTarget

public static void cancelPreviousPerformRequestsWithTarget(java.lang.Object aTarget)

cancelPreviousPerformRequestsWithTargetSelectorObject

public static void cancelPreviousPerformRequestsWithTargetSelectorObject(java.lang.Object aTarget,
                                                                         org.moe.natj.objc.SEL aSelector,
                                                                         java.lang.Object anArgument)

classFallbacksForKeyedArchiver

public static NSArray<java.lang.String> classFallbacksForKeyedArchiver()

classForKeyedUnarchiver

public static org.moe.natj.objc.Class classForKeyedUnarchiver()

debugDescription_static

public static java.lang.String debugDescription_static()

description_static

public static java.lang.String description_static()

featureChannelCount

public long featureChannelCount()

[@property] featureChannelCount

The number of feature channels

gamma

public MLCTensor gamma()

[@property] gamma

The gamma tensor

gammaParameter

public MLCTensorParameter gammaParameter()

[@property] gammaParameter

The gamma tensor parameter used for optimizer update

hash_static

public static long hash_static()

init

public MLCBatchNormalizationLayer init()

Overrides:

init in class MLCLayer

instanceMethodForSelector

public static NSObject.Function_instanceMethodForSelector_ret instanceMethodForSelector(org.moe.natj.objc.SEL aSelector)

instanceMethodSignatureForSelector

public static NSMethodSignature instanceMethodSignatureForSelector(org.moe.natj.objc.SEL aSelector)

instancesRespondToSelector

public static boolean instancesRespondToSelector(org.moe.natj.objc.SEL aSelector)

isSubclassOfClass

public static boolean isSubclassOfClass(org.moe.natj.objc.Class aClass)

keyPathsForValuesAffectingValueForKey

public static NSSet<java.lang.String> keyPathsForValuesAffectingValueForKey(java.lang.String key)

layerWithFeatureChannelCountMeanVarianceBetaGammaVarianceEpsilon

public static MLCBatchNormalizationLayer layerWithFeatureChannelCountMeanVarianceBetaGammaVarianceEpsilon(long featureChannelCount,
                                                                                                          MLCTensor mean,
                                                                                                          MLCTensor variance,
                                                                                                          MLCTensor beta,
                                                                                                          MLCTensor gamma,
                                                                                                          float varianceEpsilon)

Create a batch normalization layer

Parameters:

featureChannelCount - The number of feature channels

mean - The mean tensor

variance - The variance tensor

beta - The beta tensor

gamma - The gamma tensor

varianceEpsilon - The epslion value

Returns:

A new batch normalization layer.

layerWithFeatureChannelCountMeanVarianceBetaGammaVarianceEpsilonMomentum

public static MLCBatchNormalizationLayer layerWithFeatureChannelCountMeanVarianceBetaGammaVarianceEpsilonMomentum(long featureChannelCount,
                                                                                                                  MLCTensor mean,
                                                                                                                  MLCTensor variance,
                                                                                                                  MLCTensor beta,
                                                                                                                  MLCTensor gamma,
                                                                                                                  float varianceEpsilon,
                                                                                                                  float momentum)

Create a batch normalization layer

Parameters:

featureChannelCount - The number of feature channels

mean - The mean tensor

variance - The variance tensor

beta - The beta tensor

gamma - The gamma tensor

varianceEpsilon - The epslion value

momentum - The momentum value for the running mean and variance computation

Returns:

A new batch normalization layer.

mean

public MLCTensor mean()

[@property] mean

The mean tensor

momentum

public float momentum()

[@property] momentum

The value used for the running mean and variance computation

The default is 0.99f.

new_objc

public static MLCBatchNormalizationLayer new_objc()

resolveClassMethod

public static boolean resolveClassMethod(org.moe.natj.objc.SEL sel)

resolveInstanceMethod

public static boolean resolveInstanceMethod(org.moe.natj.objc.SEL sel)

setVersion_static

public static void setVersion_static(long aVersion)

superclass_static

public static org.moe.natj.objc.Class superclass_static()

supportsDataTypeOnDevice

public static boolean supportsDataTypeOnDevice(int dataType,
                                               MLCDevice device)

variance

public MLCTensor variance()

[@property] variance

The variance tensor

varianceEpsilon

public float varianceEpsilon()

[@property] varianceEpsilon

A value used for numerical stability

version_static

public static long version_static()