public class MPSCNNBinaryConvolution extends MPSCNNKernel
The MPSCNNBinaryConvolution specifies a convolution with binary weights and an input image using binary approximations. The MPSCNNBinaryConvolution optionally first binarizes the input image and then convolves the result with a set of binary-valued filters, each producing one feature map in the output image (which is a normal image)
The output is computed as follows:
out[i, x, y, c] = ( sum_{dx,dy,f} in[i,x+dx, y+dy, f] x B[c,dx,dy,f] ) * scale[c] * beta[i,x,y] + bias[c], where
the sum over dx,dy is over the spatial filter kernel window defined by 'kernelWidth' and 'KernelHeight', sum over 'f' is over the input feature channel indices within group, 'B' contains the binary weights, interpreted as {-1,1} or { 0, 1 } and scale[c] is the 'outputScaleTerms' array and bias is the 'outputBiasTerms' array. Above 'i' is the image index in batch the sum over input channels 'f' runs through the group indices.
The convolution operator 'x' is defined by MPSCNNBinaryConvolutionType passed in at initialization time of the filter (@see initWithDevice). In case 'type' = MPSCNNBinaryConvolutionTypeBinaryWeights, the input image is not binarized at all and the convolution is computed interpreting the weights as [ 0, 1 ] -> { -1, 1 } with the given scaling terms. In case 'type' = MPSCNNBinaryConvolutionTypeXNOR the convolution is computed by first binarizing the input image using the sign function 'bin(x) = x < 0 ? -1 : 1' and the convolution multiplication is done with the XNOR-operator !(x ^ y) = delta_xy = { (x==y) ? 1 : 0 }, and scaled according to the optional scaling operations. Note that we output the values of the bitwise convolutions to interval { -1, 1 }, which means that the output of the XNOR-operator is scaled implicitly as follows: r = 2 * ( !(x ^ y) ) - 1 = { -1, 1 }. This means that for a dot-product of two 32-bit words the result is: r = 2 * popcount(!(x ^ y) ) - 32 = 32 - 2 * popcount( x ^ y ) = { -32, -30, ..., 30, 32 }. In case 'type' = MPSCNNBinaryConvolutionTypeAND the convolution is computed by first binarizing the input image using the sign function 'bin(x) = x < 0 ? -1 : 1' and the convolution multiplication is done with the AND-operator (x & y) = delta_xy * delta_x1 = { (x==y==1) ? 1 : 0 }. and scaled according to the optional scaling operations. Note that we output the values of the AND-operation is assumed to lie in { 0, 1 } interval and hence no more implicit scaling takes place. This means that for a dot-product of two 32-bit words the result is: r = popcount(x & y) = { 0, ..., 31, 32 }.
The input data can be pre-offset and scaled by providing the 'inputBiasTerms' and 'inputScaleTerms' parameters for the initialization functions and this can be used for example to accomplish batch normalization of the data. The scaling of input values happens before possible beta-image computation.
The parameter 'beta' above is an optional image which is used to compute scaling factors for each spatial position and image index. For the XNOR-Net based networks this is computed as follows: beta[i,x,y] = sum_{dx,dy} A[i, x+dx, y+dy] / (kx * ky), where (dx,dy) are summed over the convolution filter window [ -kx/2, (kx-1)/2], [ -ky/2, (ky-1)/2 ] and A[i,x,y] = sum_{c} abs( in[i,x,y,c] ) / Nc, where 'in' is the original input image (in full precision) and Nc is the number of input channels in the input image. Parameter 'beta' is not passed as input and to enable beta-scaling the user can provide 'MPSCNNBinaryConvolutionFlagsUseBetaScaling' in the flags parameter in the initialization functions.
Finally the normal activation neuron is applied and the result is written to the output image.
NOTE: MPSCNNBinaryConvolution does not currently support groups > 1.
NSObject.Function_instanceMethodForSelector_ret, NSObject.Function_methodForSelector_ret| Modifier | Constructor and Description |
|---|---|
protected |
MPSCNNBinaryConvolution(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 MPSCNNBinaryConvolution |
alloc() |
static MPSCNNBinaryConvolution |
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() |
static java.lang.String |
debugDescription_static() |
static java.lang.String |
description_static() |
static long |
hash_static() |
MPSCNNBinaryConvolution |
init() |
MPSCNNBinaryConvolution |
initWithCoder(NSCoder aDecoder)
NS_DESIGNATED_INITIALIZER
|
MPSCNNBinaryConvolution |
initWithCoderDevice(NSCoder aDecoder,
java.lang.Object device)
NSSecureCoding compatability
|
MPSCNNBinaryConvolution |
initWithDevice(java.lang.Object device)
Standard init with default properties per filter type
|
MPSCNNBinaryConvolution |
initWithDeviceConvolutionDataOutputBiasTermsOutputScaleTermsInputBiasTermsInputScaleTermsTypeFlags(MTLDevice device,
MPSCNNConvolutionDataSource convolutionData,
org.moe.natj.general.ptr.ConstFloatPtr outputBiasTerms,
org.moe.natj.general.ptr.ConstFloatPtr outputScaleTerms,
org.moe.natj.general.ptr.ConstFloatPtr inputBiasTerms,
org.moe.natj.general.ptr.ConstFloatPtr inputScaleTerms,
long type,
long flags)
Initializes a binary convolution kernel with binary weights as well as both pre and post scaling terms.
|
MPSCNNBinaryConvolution |
initWithDeviceConvolutionDataScaleValueTypeFlags(MTLDevice device,
MPSCNNConvolutionDataSource convolutionData,
float scaleValue,
long type,
long flags)
Initializes a binary convolution kernel with binary weights and a single scaling term.
|
long |
inputFeatureChannels() |
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 MPSCNNBinaryConvolution |
new_objc() |
long |
outputFeatureChannels()
[@property] outputFeatureChannels
|
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 |
supportsSecureCoding() |
static long |
version_static() |
appendBatchBarrier, clipRect, destinationFeatureChannelOffset, destinationImageAllocator, destinationImageDescriptorForSourceImagesSourceStates, dilationRateX, dilationRateY, edgeMode, encodeToCommandBufferSourceImage, encodeToCommandBufferSourceImageDestinationImage, encodeToCommandBufferSourceImageDestinationStateDestinationImage, encodeToCommandBufferSourceImageDestinationStateDestinationStateIsTemporary, encodingStorageSizeForSourceImageSourceStatesDestinationImage, isBackwards, isResultStateReusedAcrossBatch, isStateModified, kernelHeight, kernelWidth, offset, padding, resultStateForSourceImageSourceStatesDestinationImage, setClipRect, setDestinationFeatureChannelOffset, setDestinationImageAllocator, setEdgeMode, setOffset, setPadding, setSourceFeatureChannelMaxCount, setSourceFeatureChannelOffset, sourceFeatureChannelMaxCount, sourceFeatureChannelOffset, strideInPixelsX, strideInPixelsY, temporaryResultStateForCommandBufferSourceImageSourceStatesDestinationImagecopyWithZone, copyWithZoneDevice, 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 MPSCNNBinaryConvolution(org.moe.natj.general.Pointer peer)
public static boolean accessInstanceVariablesDirectly()
public static MPSCNNBinaryConvolution alloc()
public static MPSCNNBinaryConvolution 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 static java.lang.String debugDescription_static()
public static java.lang.String description_static()
public static long hash_static()
public MPSCNNBinaryConvolution init()
init in class MPSCNNKernelpublic MPSCNNBinaryConvolution initWithCoder(NSCoder aDecoder)
NSCodinginitWithCoder in interface NSCodinginitWithCoder in class MPSCNNKernelpublic MPSCNNBinaryConvolution initWithCoderDevice(NSCoder aDecoder, java.lang.Object device)
While the standard NSSecureCoding/NSCoding method -initWithCoder: should work, since the file can't know which device your data is allocated on, we have to guess and may guess incorrectly. To avoid that problem, use initWithCoder:device instead.
initWithCoderDevice in class MPSCNNKernelaDecoder - The NSCoder subclass with your serialized MPSKerneldevice - The MTLDevice on which to make the MPSKernelpublic MPSCNNBinaryConvolution initWithDevice(java.lang.Object device)
MPSCNNKernelinitWithDevice in class MPSCNNKerneldevice - The device that the filter will be used on. May not be NULL.public MPSCNNBinaryConvolution initWithDeviceConvolutionDataOutputBiasTermsOutputScaleTermsInputBiasTermsInputScaleTermsTypeFlags(MTLDevice device, MPSCNNConvolutionDataSource convolutionData, org.moe.natj.general.ptr.ConstFloatPtr outputBiasTerms, org.moe.natj.general.ptr.ConstFloatPtr outputScaleTerms, org.moe.natj.general.ptr.ConstFloatPtr inputBiasTerms, org.moe.natj.general.ptr.ConstFloatPtr inputScaleTerms, long type, long flags)
device - The MTLDevice on which this MPSCNNBinaryConvolution filter will be usedconvolutionData - A pointer to a object that conforms to the MPSCNNConvolutionDataSource protocol.
The MPSCNNConvolutionDataSource protocol declares the methods that an
instance of MPSCNNBinaryConvolution uses to obtain the weights and the convolution descriptor.
Each entry in the convolutionData:weights array is a 32-bit unsigned integer value
and each bit represents one filter weight (given in machine byte order).
The featurechannel indices increase from the least significant bit within the 32-bits.
The number of entries is =
ceil( inputFeatureChannels/32.0 ) * outputFeatureChannels * kernelHeight * kernelWidth
The layout of filter weight is so that it can be reinterpreted as a 4D tensor (array)
weight[ outputChannels ][ kernelHeight ][ kernelWidth ][ ceil( inputChannels / 32.0 ) ]
(The ordering of the reduction from 4D tensor to 1D is per C convention. The index based on
inputchannels varies most rapidly, followed by kernelWidth, then kernelHeight and finally
outputChannels varies least rapidly.)outputBiasTerms - A pointer to bias terms to be applied to the convolution output. Each entry is a float value.
The number of entries is = numberOfOutputFeatureMaps. If nil then 0.0 is used for bias.
The values stored in the pointer are copied in and the array can be freed after this function returns.outputScaleTerms - A pointer to scale terms to be applied to binary convolution results per output feature channel.
Each entry is a float value. The number of entries is = numberOfOutputFeatureMaps. If nil then 1.0 is used.
The values stored in the pointer are copied in and the array can be freed after this function returns.inputBiasTerms - A pointer to offset terms to be applied to the input before convolution and before input scaling.
Each entry is a float value. The number of entries is 'inputFeatureChannels'. If NULL then 0.0 is used for bias.
The values stored in the pointer are copied in and the array can be freed after this function returns.inputScaleTerms - A pointer to scale terms to be applied to the input before convolution, but after input biasing.
Each entry is a float value. The number of entries is 'inputFeatureChannels'. If nil then 1.0 is used.
The values stored in the pointer are copied in and the array can be freed after this function returns.type - What kind of binarization strategy is to be used.flags - See documentation above and documentation of MPSCNNBinaryConvolutionFlags.public MPSCNNBinaryConvolution initWithDeviceConvolutionDataScaleValueTypeFlags(MTLDevice device, MPSCNNConvolutionDataSource convolutionData, float scaleValue, long type, long flags)
device - The MTLDevice on which this MPSCNNBinaryConvolution filter will be usedconvolutionData - A pointer to a object that conforms to the MPSCNNConvolutionDataSource protocol.
The MPSCNNConvolutionDataSource protocol declares the methods that an
instance of MPSCNNBinaryConvolution uses to obtain the weights and bias terms as
well as the convolution descriptor.
Each entry in the convolutionData:weights array is a 32-bit unsigned integer value
and each bit represents one filter weight (given in machine byte order).
The featurechannel indices increase from the least significant bit within the 32-bits.
The number of entries is =
ceil( inputFeatureChannels/32.0 ) * outputFeatureChannels * kernelHeight * kernelWidth
The layout of filter weight is so that it can be reinterpreted as a 4D tensor (array)
weight[ outputChannels ][ kernelHeight ][ kernelWidth ][ ceil( inputChannels / 32.0 ) ]
(The ordering of the reduction from 4D tensor to 1D is per C convention. The index based on
inputchannels varies most rapidly, followed by kernelWidth, then kernelHeight and finally
outputChannels varies least rapidly.)scaleValue - A floating point value used to scale the entire convolution.type - What kind of binarization strategy is to be used.flags - See documentation above and documentation of MPSCNNBinaryConvolutionFlags.public long inputFeatureChannels()
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 static MPSCNNBinaryConvolution new_objc()
public long outputFeatureChannels()
The number of feature channels per pixel in the output image.
public static boolean resolveClassMethod(org.moe.natj.objc.SEL sel)
public static boolean resolveInstanceMethod(org.moe.natj.objc.SEL sel)
public static void setVersion_static(long aVersion)
public static org.moe.natj.objc.Class superclass_static()
public static boolean supportsSecureCoding()
public boolean _supportsSecureCoding()
NSSecureCoding_supportsSecureCoding in interface NSSecureCoding_supportsSecureCoding in class MPSCNNKernelpublic static long version_static()