public class MPSMatrixBatchNormalization extends MPSMatrixUnaryKernel
[@dependency] This depends on Metal.framework.
Applies a batch normalization to a matrix.
A MPSMatrixBatchNormalization object computes the batch normalization of a collection of feature vectors stored in an MPSMatrix.
Feature vectors are stored in a row of the supplied input matrix and the normalization is performed along columns:
y[i,j] = gamma[j] * (x[i,j] - mean(x[:,j])) / (variance(x[:,j]) + epsilon) + beta[j]
where gamma and beta are supplied weight and bias factors and epsilon is a small value added to the variance.
Optionally a neuron activation function may be applied to the result.
NSObject.Function_instanceMethodForSelector_ret, NSObject.Function_methodForSelector_ret| Modifier | Constructor and Description |
|---|---|
protected |
MPSMatrixBatchNormalization(org.moe.natj.general.Pointer peer) |
| Modifier and Type | Method and Description |
|---|---|
boolean |
_supportsSecureCoding()
This property must return YES on all classes that allow secure coding.
|
static boolean |
accessInstanceVariablesDirectly() |
static MPSMatrixBatchNormalization |
alloc() |
static MPSMatrixBatchNormalization |
allocWithZone(org.moe.natj.general.ptr.VoidPtr zone) |
static boolean |
automaticallyNotifiesObserversForKey(java.lang.String key) |
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() |
boolean |
computeStatistics()
[@property] computeStatistics
|
MPSMatrixBatchNormalization |
copyWithZoneDevice(org.moe.natj.general.ptr.VoidPtr zone,
MTLDevice device)
Make a copy of this kernel for a new device - @see MPSKernel
|
static java.lang.String |
debugDescription_static() |
static java.lang.String |
description_static() |
void |
encodeToCommandBufferInputMatrixMeanVectorVarianceVectorGammaVectorBetaVectorResultMatrix(MTLCommandBuffer commandBuffer,
MPSMatrix inputMatrix,
MPSVector meanVector,
MPSVector varianceVector,
MPSVector gammaVector,
MPSVector betaVector,
MPSMatrix resultMatrix)
Encode a MPSMatrixBatchNormalization object to a command buffer.
|
float |
epsilon()
[@property] epsilon
|
static long |
hash_static() |
MPSMatrixBatchNormalization |
init() |
MPSMatrixBatchNormalization |
initWithCoder(NSCoder aDecoder)
NS_DESIGNATED_INITIALIZER
|
MPSMatrixBatchNormalization |
initWithCoderDevice(NSCoder aDecoder,
java.lang.Object device)
NSSecureCoding compatability
|
MPSMatrixBatchNormalization |
initWithDevice(java.lang.Object device)
Standard init with default properties per filter type
|
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) |
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
|
int |
neuronType()
Getter funtion for neuronType set using setNeuronType:parameterA:parameterB:parameterC method
|
static MPSMatrixBatchNormalization |
new_objc() |
static boolean |
resolveClassMethod(org.moe.natj.objc.SEL sel) |
static boolean |
resolveInstanceMethod(org.moe.natj.objc.SEL sel) |
void |
setComputeStatistics(boolean value)
[@property] computeStatistics
|
void |
setEpsilon(float value)
[@property] epsilon
|
void |
setNeuronTypeParameterAParameterBParameterC(int neuronType,
float parameterA,
float parameterB,
float parameterC)
Specifies a neuron activation function to be used.
|
void |
setSourceInputFeatureChannels(long value)
[@property] sourceInputFeatureChannels
|
void |
setSourceNumberOfFeatureVectors(long value)
[@property] sourceNumberOfFeatureVectors
|
static void |
setVersion_static(long aVersion) |
long |
sourceInputFeatureChannels()
[@property] sourceInputFeatureChannels
|
long |
sourceNumberOfFeatureVectors()
[@property] sourceNumberOfFeatureVectors
|
static org.moe.natj.objc.Class |
superclass_static() |
static boolean |
supportsSecureCoding() |
static long |
version_static() |
batchSize, batchStart, resultMatrixOrigin, setBatchSize, setBatchStart, setResultMatrixOrigin, setSourceMatrixOrigin, sourceMatrixOrigincopyWithZone, device, encodeWithCoder, label, options, setLabel, setOptionsaccessibilityActivate, 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, willChangeValuesAtIndexesForKeyprotected MPSMatrixBatchNormalization(org.moe.natj.general.Pointer peer)
public static boolean accessInstanceVariablesDirectly()
public static MPSMatrixBatchNormalization alloc()
public static MPSMatrixBatchNormalization allocWithZone(org.moe.natj.general.ptr.VoidPtr zone)
public static boolean automaticallyNotifiesObserversForKey(java.lang.String key)
public static void cancelPreviousPerformRequestsWithTarget(java.lang.Object aTarget)
public static void cancelPreviousPerformRequestsWithTargetSelectorObject(java.lang.Object aTarget,
org.moe.natj.objc.SEL aSelector,
java.lang.Object anArgument)
public static NSArray<java.lang.String> classFallbacksForKeyedArchiver()
public static org.moe.natj.objc.Class classForKeyedUnarchiver()
public boolean computeStatistics()
If YES the batch statistics will be computed prior to performing the normalization. Otherwise the provided statistics will be used. Defaults to NO at initialization time.
public MPSMatrixBatchNormalization copyWithZoneDevice(org.moe.natj.general.ptr.VoidPtr zone, MTLDevice device)
copyWithZoneDevice in class MPSKernelzone - The NSZone in which to allocate the objectdevice - The device for the new MPSKernel. If nil, then use
self.device.public static java.lang.String debugDescription_static()
public static java.lang.String description_static()
public void encodeToCommandBufferInputMatrixMeanVectorVarianceVectorGammaVectorBetaVectorResultMatrix(MTLCommandBuffer commandBuffer, MPSMatrix inputMatrix, MPSVector meanVector, MPSVector varianceVector, MPSVector gammaVector, MPSVector betaVector, MPSMatrix resultMatrix)
Encodes the operation to the specified command buffer. resultMatrix must be large enough to hold a MIN(sourceNumberOfFeatureVectors, inputMatrix.rows - sourceMatrixOrigin.x) x MIN(inputMatrix.columns - sourceMatrixOrigin.y, sourceInputFeatureChannels) array.
Let numChannels = MIN(inputMatrix.columns - sourceMatrixOrigin.y, sourceInputFeatureChannels)
The gamma, beta, mean, and variance vectors must contain at least numChannels elements.
commandBuffer - A valid MTLCommandBuffer to receive the encoded kernel.inputMatrix - A valid MPSMatrix object which specifies the input array.meanVector - A valid MPSVector object containing batch mean values to be used
to normalize the inputs if computeStatistics is NO. If
computeStatistics is YES the resulting batch mean values
will be returned in this array.varianceVector - A valid MPSVector object containing batch variance values to be used
to normalize the inputs if computeStatistics is NO. If
computeStatistics is YES the resulting batch variance values
will be returned in this array.gammaVector - A valid MPSVector object which specifies the gamma terms, or
a null object to indicate that no scaling is to be applied.betaVector - A valid MPSVector object which specifies the beta terms, or
a null object to indicate that no values are to be added.resultMatrix - A valid MPSMatrix object which specifies the output array.public float epsilon()
A small value to add to the variance when normalizing the inputs. Defaults to FLT_MIN upon initialization.
public static long hash_static()
public MPSMatrixBatchNormalization init()
init in class MPSMatrixUnaryKernelpublic MPSMatrixBatchNormalization initWithCoder(NSCoder aDecoder)
NSCodinginitWithCoder in interface NSCodinginitWithCoder in class MPSMatrixUnaryKernelpublic MPSMatrixBatchNormalization initWithCoderDevice(NSCoder aDecoder, java.lang.Object device)
See @ref MPSKernel#initWithCoder.
initWithCoderDevice in class MPSMatrixUnaryKernelaDecoder - The NSCoder subclass with your serialized MPSMatrixBatchNormalization object.device - The MTLDevice on which to make the MPSMatrixBatchNormalization object.public MPSMatrixBatchNormalization initWithDevice(java.lang.Object device)
MPSKernelinitWithDevice in class MPSMatrixUnaryKerneldevice - The device that the filter will be used on. May not be NULL.public static NSObject.Function_instanceMethodForSelector_ret instanceMethodForSelector(org.moe.natj.objc.SEL aSelector)
public static NSMethodSignature instanceMethodSignatureForSelector(org.moe.natj.objc.SEL aSelector)
public static boolean instancesRespondToSelector(org.moe.natj.objc.SEL aSelector)
public static boolean isSubclassOfClass(org.moe.natj.objc.Class aClass)
public static NSSet<java.lang.String> keyPathsForValuesAffectingValueForKey(java.lang.String key)
public float neuronParameterA()
public float neuronParameterB()
public float neuronParameterC()
public int neuronType()
public static MPSMatrixBatchNormalization new_objc()
public static boolean resolveClassMethod(org.moe.natj.objc.SEL sel)
public static boolean resolveInstanceMethod(org.moe.natj.objc.SEL sel)
public void setComputeStatistics(boolean value)
If YES the batch statistics will be computed prior to performing the normalization. Otherwise the provided statistics will be used. Defaults to NO at initialization time.
public void setEpsilon(float value)
A small value to add to the variance when normalizing the inputs. Defaults to FLT_MIN upon initialization.
public void setNeuronTypeParameterAParameterBParameterC(int neuronType,
float parameterA,
float parameterB,
float parameterC)
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. An MPSMatrixNeuron kernel is initialized with a default neuron function of MPSCNNNeuronTypeNone.
neuronType - Type of neuron activation function. For full list see MPSCNNNeuronType.hparameterA - 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.public void setSourceInputFeatureChannels(long value)
The input size to to use in the operation. This is equivalent to the number of columns in the primary (input array) source matrix to consider and the number of channels to produce for the output matrix. 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 sourceMatrixOrigin.y) should be considered. Defines also the number of output feature channels. Note: The value used in the operation will be MIN(inputMatrix.columns - sourceMatrixOrigin.y, sourceInputFeatureChannels)
public void setSourceNumberOfFeatureVectors(long value)
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 sourceMatrixOrigin.x) should be considered.
public static void setVersion_static(long aVersion)
public long sourceInputFeatureChannels()
The input size to to use in the operation. This is equivalent to the number of columns in the primary (input array) source matrix to consider and the number of channels to produce for the output matrix. 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 sourceMatrixOrigin.y) should be considered. Defines also the number of output feature channels. Note: The value used in the operation will be MIN(inputMatrix.columns - sourceMatrixOrigin.y, sourceInputFeatureChannels)
public long sourceNumberOfFeatureVectors()
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 sourceMatrixOrigin.x) should be considered.
public static org.moe.natj.objc.Class superclass_static()
public static boolean supportsSecureCoding()
public boolean _supportsSecureCoding()
NSSecureCoding_supportsSecureCoding in interface NSSecureCoding_supportsSecureCoding in class MPSMatrixUnaryKernelpublic static long version_static()