apple.metalperformanceshaders

Class MPSRNNMatrixTrainingLayer

java.lang.Object

org.moe.natj.general.NativeObject

org.moe.natj.objc.ObjCObject

apple.NSObject

apple.metalperformanceshaders.MPSKernel

apple.metalperformanceshaders.MPSRNNMatrixTrainingLayer

All Implemented Interfaces:

NSCoding, NSCopying, NSSecureCoding, NSObject

public class MPSRNNMatrixTrainingLayer
extends MPSKernel

MPSRNNMatrixTrainingLayer [@dependency] This depends on Metal.framework

The MPSRNNMatrixTrainingLayer specifies a recurrent neural network layer for training on MPSMatrices.

A MPSRNNMatrixTrainingLayer is initialized using a @ref MPSRNNLayerDescriptor, which further specifies the recurrent network layer. The input and output vectors in encode calls are stored as rows of the input and output matrices and MPSRNNMatrixTrainingLayer supports matrices with decreasing number of rows: The row-indices identify the different sequences that may be of different lengths - for example if we have three sequences: ( x1, x2, x3 ), ( y1, y2, y3, y4 ) and ( z1, z2 ) of vectors xi, yi and zi, then these can be inserted together as a batch to the sequence encoding kernel by using the matrices: [@code] ( y1 ) ( y2 ) ( y3 ) ( y4 ) m1 = ( x1 ), m2 = ( x2 ), m3 = ( x3 ), m4 = ( z1 ) ( z2 ) [@endcode] The gradient computation pass is then achieved by passing the corresponding gradient sequence from the previous layer ( dx1, dx2, dx3 ), ( dy1, dy2, dy3, dy4 ) and ( dz1, dz2 ) as matrices [@code] ( dy1 ) ( dy2 ) ( dy3 ) ( dy4 ) dm1 = ( dx1 ), dm2 = ( dx2 ), dm3 = ( dx3 ), dm4 = ( dz1 ) ( dz2 ) [@endcode]

The mathematical operation described in the linear transformations of @ref MPSRNNSingleGateDescriptor [@ref] MPSLSTMDescriptor and @ref MPSGRUDescriptor are y^T = W x^T <=> y = x W^T, where x is the matrix containing the input vectors as rows, y is the matrix containing the output vectors as rows and W is the weight matrix.

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	MPSRNNMatrixTrainingLayer(org.moe.natj.general.Pointer peer)

Method Summary

Modifier and Type	Method and Description
boolean	_supportsSecureCoding() This property must return YES on all classes that allow secure coding.
static boolean	accessInstanceVariablesDirectly()
boolean	accumulateWeightGradients() [@property] accumulateWeightGradients
static MPSRNNMatrixTrainingLayer	alloc()
static MPSRNNMatrixTrainingLayer	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()
MPSRNNMatrixTrainingLayer	copyWithZoneDevice(org.moe.natj.general.ptr.VoidPtr zone, MTLDevice device) Make a copy of this kernel for a new device - @see MPSKernel
void	createTemporaryWeightGradientMatricesDataTypeCommandBuffer(NSMutableArray<MPSMatrix> matricesOut, int dataType, MTLCommandBuffer commandBuffer) As @ref createWeightGradientMatrices, but the matrices will be temporary with readCount = 1, which means that they become invalid after the first encode call that reads them.
void	createWeightGradientMatricesDataType(NSMutableArray<MPSMatrix> matricesOut, int dataType) Initializes a set of matrices that can be used in training for weight and bias gradient outputs in
void	createWeightMatrices(NSMutableArray<MPSMatrix> matricesOut) Initializes a set of matrices that can be used in training for weight and bias matrices in the forward and backward passes.
static java.lang.String	debugDescription_static()
static java.lang.String	description_static()
void	encodeCopyWeightsToCommandBufferWeightsMatrixIdMatrixCopyFromWeightsToMatrixMatrixOffset(MTLCommandBuffer commandBuffer, NSArray<? extends MPSMatrix> weights, long matrixId, MPSMatrix matrix, boolean copyFromWeightsToMatrix, MTLOrigin matrixOffset) Encode a copy kernel that copies one matrix from the trainable weight set to a matrix with standard layout, where the column index is the input feature channel index (in forward direction) and row index is the output feature channel index.
void	encodeForwardSequenceToCommandBufferSourceMatricesDestinationMatricesTrainingStatesWeights(MTLCommandBuffer commandBuffer, NSArray<? extends MPSMatrix> sourceMatrices, NSArray<? extends MPSMatrix> destinationMatrices, NSMutableArray<MPSRNNMatrixTrainingState> trainingStates, NSArray<? extends MPSMatrix> weights) Encode an MPSRNNMatrixTrainingLayer forward pass kernel for a sequence of inputs into a command buffer.
void	encodeForwardSequenceToCommandBufferSourceMatricesSourceOffsetsDestinationMatricesDestinationOffsetsTrainingStatesRecurrentInputStateRecurrentOutputStatesWeights(MTLCommandBuffer commandBuffer, NSArray<? extends MPSMatrix> sourceMatrices, org.moe.natj.general.ptr.NUIntPtr sourceOffsets, NSArray<? extends MPSMatrix> destinationMatrices, org.moe.natj.general.ptr.NUIntPtr destinationOffsets, NSMutableArray<MPSRNNMatrixTrainingState> trainingStates, MPSRNNRecurrentMatrixState recurrentInputState, NSMutableArray<MPSRNNRecurrentMatrixState> recurrentOutputStates, NSArray<? extends MPSMatrix> weights) Encode an MPSRNNMatrixTrainingLayer forward pass kernel for a sequence of inputs into a command buffer.
void	encodeGradientSequenceToCommandBufferForwardSourcesForwardSourceOffsetsSourceGradientsSourceGradientOffsetsDestinationGradientsDestinationOffsetsWeightGradientsTrainingStatesRecurrentInputStateRecurrentOutputStatesWeights(MTLCommandBuffer commandBuffer, NSArray<? extends MPSMatrix> forwardSources, org.moe.natj.general.ptr.NUIntPtr forwardSourceOffsets, NSArray<? extends MPSMatrix> sourceGradients, org.moe.natj.general.ptr.NUIntPtr sourceGradientOffsets, NSArray<? extends MPSMatrix> destinationGradients, org.moe.natj.general.ptr.NUIntPtr destinationOffsets, NSArray<? extends MPSMatrix> weightGradients, NSArray<? extends MPSRNNMatrixTrainingState> trainingStates, MPSRNNRecurrentMatrixState recurrentInputState, NSMutableArray<MPSRNNRecurrentMatrixState> recurrentOutputStates, NSArray<? extends MPSMatrix> weights) Encode an MPSRNNMatrixTrainingLayer gradient pass kernel for a sequence of input gradients into a command buffer.
void	encodeGradientSequenceToCommandBufferForwardSourcesSourceGradientsDestinationGradientsWeightGradientsTrainingStatesWeights(MTLCommandBuffer commandBuffer, NSArray<? extends MPSMatrix> forwardSources, NSArray<? extends MPSMatrix> sourceGradients, NSArray<? extends MPSMatrix> destinationGradients, NSArray<? extends MPSMatrix> weightGradients, NSArray<? extends MPSRNNMatrixTrainingState> trainingStates, NSArray<? extends MPSMatrix> weights) Encode an MPSRNNMatrixTrainingLayer gradient pass kernel for a sequence of input gradients into a command buffer.
static long	hash_static()
MPSRNNMatrixTrainingLayer	init()
MPSRNNMatrixTrainingLayer	initWithCoder(NSCoder aDecoder) NS_DESIGNATED_INITIALIZER
MPSRNNMatrixTrainingLayer	initWithCoderDevice(NSCoder aDecoder, java.lang.Object device) NSSecureCoding compatability
MPSRNNMatrixTrainingLayer	initWithDevice(java.lang.Object device) Standard init with default properties per filter type
MPSRNNMatrixTrainingLayer	initWithDeviceRnnDescriptorTrainableWeights(MTLDevice device, MPSRNNDescriptor rnnDescriptor, NSMutableArray<MPSMatrix> trainableWeights) Initializes a linear (fully connected) RNN kernel for training
long	inputFeatureChannels() [@property] 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 MPSRNNMatrixTrainingLayer	new_objc()
long	outputFeatureChannels() [@property] outputFeatureChannels
boolean	recurrentOutputIsTemporary() [@property] recurrentOutputIsTemporary
static boolean	resolveClassMethod(org.moe.natj.objc.SEL sel)
static boolean	resolveInstanceMethod(org.moe.natj.objc.SEL sel)
void	setAccumulateWeightGradients(boolean value) [@property] accumulateWeightGradients
void	setRecurrentOutputIsTemporary(boolean value) [@property] recurrentOutputIsTemporary
void	setStoreAllIntermediateStates(boolean value) [@property] storeAllIntermediateStates
void	setTrainingStateIsTemporary(boolean value) [@property] trainingStateIsTemporary
static void	setVersion_static(long aVersion)
boolean	storeAllIntermediateStates() [@property] storeAllIntermediateStates
static org.moe.natj.objc.Class	superclass_static()
static boolean	supportsSecureCoding()
boolean	trainingStateIsTemporary() [@property] trainingStateIsTemporary
static long	version_static()

Methods inherited from class apple.metalperformanceshaders.MPSKernel

copyWithZone, device, encodeWithCoder, label, options, setLabel, setOptions

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

MPSRNNMatrixTrainingLayer

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

Method Detail

accessInstanceVariablesDirectly

public static boolean accessInstanceVariablesDirectly()

accumulateWeightGradients

public boolean accumulateWeightGradients()

[@property] accumulateWeightGradients

If yes then the computed weight gradients are accumulated on top of existing values in calls to the gradient computation functions: encodeGradientSequenceToCommandBuffer. Defaults to NO.

alloc

public static MPSRNNMatrixTrainingLayer alloc()

allocWithZone

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

automaticallyNotifiesObserversForKey

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

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()

copyWithZoneDevice

public MPSRNNMatrixTrainingLayer copyWithZoneDevice(org.moe.natj.general.ptr.VoidPtr zone,
                                                    MTLDevice device)

Make a copy of this kernel for a new device - @see MPSKernel

Overrides:

copyWithZoneDevice in class MPSKernel

Parameters:

zone - The NSZone in which to allocate the object

device - The device for the new MPSKernel. If nil, then use self.device.

Returns:

a pointer to a copy of this MPSKernel. This will fail, returning nil if the device is not supported. Devices must be MTLFeatureSet_iOS_GPUFamily2_v1 or later.

createTemporaryWeightGradientMatricesDataTypeCommandBuffer

public void createTemporaryWeightGradientMatricesDataTypeCommandBuffer(NSMutableArray<MPSMatrix> matricesOut,
                                                                       int dataType,
                                                                       MTLCommandBuffer commandBuffer)

As @ref createWeightGradientMatrices, but the matrices will be temporary with readCount = 1, which means that they become invalid after the first encode call that reads them. Note also that as the matrices are temporary, their storage mode will be private which means that you can only access the data using a kernel on the GPU.

Parameters:

matricesOut - An array where the newly created matrices will be stored, will be initialized to zero.

dataType - Datatype for the entries - currently MPSDataTypeFloat32 and MPSDataTypeFloat16 are supported.

commandBuffer - The command buffer that the temporary matrices will live on.

createWeightGradientMatricesDataType

public void createWeightGradientMatricesDataType(NSMutableArray<MPSMatrix> matricesOut,
                                                 int dataType)

Initializes a set of matrices that can be used in training for weight and bias gradient outputs in

Parameters:

matricesOut - An array where the newly created matrices will be stored, will be initialized to zero.

dataType - Datatype for the entries - currently MPSDataTypeFloat32 and MPSDataTypeFloat16 are supported.

See Also:

Can be also used to easily create auxiliary matrices for example for ADAM and other advanced optimization schemes. The layout and number of matrices is the same as for the outputs of, initWithDevice, but the data type may differ. NOTE: These matrices cannot be used as weight matrices in the forward and backward encode calls, but matrices from initWithDevice() or createWeightMatrices() should be used instead.

createWeightMatrices

public void createWeightMatrices(NSMutableArray<MPSMatrix> matricesOut)

Initializes a set of matrices that can be used in training for weight and bias matrices in the forward and backward passes. The layout, datatype and number of matrices is the same as for the outputs of

Parameters:

matricesOut - An array where the newly created matrices will be stored, will be initialized to zero.

See Also:

initWithDevice.

debugDescription_static

public static java.lang.String debugDescription_static()

description_static

public static java.lang.String description_static()

encodeCopyWeightsToCommandBufferWeightsMatrixIdMatrixCopyFromWeightsToMatrixMatrixOffset

public void encodeCopyWeightsToCommandBufferWeightsMatrixIdMatrixCopyFromWeightsToMatrixMatrixOffset(MTLCommandBuffer commandBuffer,
                                                                                                     NSArray<? extends MPSMatrix> weights,
                                                                                                     long matrixId,
                                                                                                     MPSMatrix matrix,
                                                                                                     boolean copyFromWeightsToMatrix,
                                                                                                     MTLOrigin matrixOffset)

Encode a copy kernel that copies one matrix from the trainable weight set to a matrix with standard layout, where the column index is the input feature channel index (in forward direction) and row index is the output feature channel index.

Parameters:

commandBuffer - A valid MTLCommandBuffer to receive the encoded filter

weights - An array weights from @see initWithDevice or @see createWeightMatrices.

matrixId - Which matrix to copy - has to be a valid Id based on inputs defined in the rnnDescriptor of @see initWithDevice.

matrix - The destination or source matrix that is used in the copy.

copyFromWeightsToMatrix - If YES then the copy direction is from the set of trainable 'weights' to 'matrix', otherwise the copy is done from 'matrix' to 'weights'.

matrixOffset - A (valid) offset into matrix to be applied to the copy operation.

encodeForwardSequenceToCommandBufferSourceMatricesDestinationMatricesTrainingStatesWeights

public void encodeForwardSequenceToCommandBufferSourceMatricesDestinationMatricesTrainingStatesWeights(MTLCommandBuffer commandBuffer,
                                                                                                       NSArray<? extends MPSMatrix> sourceMatrices,
                                                                                                       NSArray<? extends MPSMatrix> destinationMatrices,
                                                                                                       NSMutableArray<MPSRNNMatrixTrainingState> trainingStates,
                                                                                                       NSArray<? extends MPSMatrix> weights)

Encode an MPSRNNMatrixTrainingLayer forward pass kernel for a sequence of inputs into a command buffer.

Parameters:

commandBuffer - A valid MTLCommandBuffer to receive the encoded filter

sourceMatrices - An array of valid MPSMatrix objects containing the sequence of source matrices.

destinationMatrices - An array valid MPSMatrices to be overwritten by result matrix sequence. destinationMatrices may not alias sourceMatrices.

trainingStates - An array containing the training states to be passed to the gradient computation encode function.

weights - An array of valid MPSMatrix objects containing the weights, should be the array that was produced either by @see initWithDevice or @see createWeightMatrices.

encodeForwardSequenceToCommandBufferSourceMatricesSourceOffsetsDestinationMatricesDestinationOffsetsTrainingStatesRecurrentInputStateRecurrentOutputStatesWeights

public void encodeForwardSequenceToCommandBufferSourceMatricesSourceOffsetsDestinationMatricesDestinationOffsetsTrainingStatesRecurrentInputStateRecurrentOutputStatesWeights(MTLCommandBuffer commandBuffer,
                                                                                                                                                                              NSArray<? extends MPSMatrix> sourceMatrices,
                                                                                                                                                                              org.moe.natj.general.ptr.NUIntPtr sourceOffsets,
                                                                                                                                                                              NSArray<? extends MPSMatrix> destinationMatrices,
                                                                                                                                                                              org.moe.natj.general.ptr.NUIntPtr destinationOffsets,
                                                                                                                                                                              NSMutableArray<MPSRNNMatrixTrainingState> trainingStates,
                                                                                                                                                                              MPSRNNRecurrentMatrixState recurrentInputState,
                                                                                                                                                                              NSMutableArray<MPSRNNRecurrentMatrixState> recurrentOutputStates,
                                                                                                                                                                              NSArray<? extends MPSMatrix> weights)

Encode an MPSRNNMatrixTrainingLayer forward pass kernel for a sequence of inputs into a command buffer.

Parameters:

commandBuffer - A valid MTLCommandBuffer to receive the encoded filter

sourceMatrices - An array of valid MPSMatrix objects containing the sequence of source matrices.

sourceOffsets - An array of byte-offsets into the sourceMatrices, if nil zeros are assumed and if not nil must contain offset for every matrix in sourceMatrices.

destinationMatrices - An array valid MPSMatrices to be overwritten by result matrix sequence. destinationMatrices may not alias sourceMatrices.

destinationOffsets - An array of byte-offsets into the destinationMatrices, if nil zeros are assumed and if not nil must contain offset for every matrix in destinationMatrices.

trainingStates - An array containing the training states to be passed to the gradient computation encode function.

recurrentInputState - An optional state containing the output matrices and memory cells (for LSTMs) of the layer obtained from the previous input matrices in a sequence of inputs. Has to be the output of a previous call to this function or nil (assumed zero).

recurrentOutputStates - An array that will be appended with the recurrent output states. May not be nil. If recurrentOutputIsTemporary is YES and then all returned recurrent states will be temporary. @see MPSState:isTemporary.

weights - An array of valid MPSMatrix objects containing the weights, should be the array that was produced either by @see initWithDevice or @see createWeightMatrices.

encodeGradientSequenceToCommandBufferForwardSourcesForwardSourceOffsetsSourceGradientsSourceGradientOffsetsDestinationGradientsDestinationOffsetsWeightGradientsTrainingStatesRecurrentInputStateRecurrentOutputStatesWeights

public void encodeGradientSequenceToCommandBufferForwardSourcesForwardSourceOffsetsSourceGradientsSourceGradientOffsetsDestinationGradientsDestinationOffsetsWeightGradientsTrainingStatesRecurrentInputStateRecurrentOutputStatesWeights(MTLCommandBuffer commandBuffer,
                                                                                                                                                                                                                                          NSArray<? extends MPSMatrix> forwardSources,
                                                                                                                                                                                                                                          org.moe.natj.general.ptr.NUIntPtr forwardSourceOffsets,
                                                                                                                                                                                                                                          NSArray<? extends MPSMatrix> sourceGradients,
                                                                                                                                                                                                                                          org.moe.natj.general.ptr.NUIntPtr sourceGradientOffsets,
                                                                                                                                                                                                                                          NSArray<? extends MPSMatrix> destinationGradients,
                                                                                                                                                                                                                                          org.moe.natj.general.ptr.NUIntPtr destinationOffsets,
                                                                                                                                                                                                                                          NSArray<? extends MPSMatrix> weightGradients,
                                                                                                                                                                                                                                          NSArray<? extends MPSRNNMatrixTrainingState> trainingStates,
                                                                                                                                                                                                                                          MPSRNNRecurrentMatrixState recurrentInputState,
                                                                                                                                                                                                                                          NSMutableArray<MPSRNNRecurrentMatrixState> recurrentOutputStates,
                                                                                                                                                                                                                                          NSArray<? extends MPSMatrix> weights)

Encode an MPSRNNMatrixTrainingLayer gradient pass kernel for a sequence of input gradients into a command buffer. NOTE: The time sequence indexing follows the array indexing in the inputs: sourceGradients[0] has to contain the gradients corresponding to the first matrix in the forward pass corresponding to the current subsequence, which is typically sourceMatrices[0].

Parameters:

commandBuffer - A valid MTLCommandBuffer to receive the encoded filter

forwardSources - An array of MPSMatrix objects containing the sequence of source matrices of the forward pass.

forwardSourceOffsets - An array of byte-offsets into the forwardSources, if nil zeros are assumed and if not nil must contain offset for every matrix in forwardSources.

sourceGradients - An array of valid MPSMatrix objects containing the sequence of source gradient matrices.

sourceGradientOffsets - An array of byte-offsets into the sourceGradients, if nil zeros are assumed and if not nil must contain offset for every matrix in sourceGradients.

destinationGradients - An array valid MPSMatrix objects that will receive the backpropagated gradients, may be nil if not needed (for example first layer in graph).

destinationOffsets - An array of byte-offsets into the destinationGradients, if nil zeros are assumed and if not nil must contain offset for every matrix in destinationGradients.

weightGradients - An array of valid MPSMatrix objects that will receive the gradient wrt. weights and biases of the layer - should be the array that was produced either by @see initWithDevice or @see createWeightMatrices. May be nil in which case the gradients for the weights are not computed.

trainingStates - An array containing the training states from the forward pass - the array must contain the states corresponding to the input gradients is sourceGradients.

recurrentInputState - An optional state containing the output matrices and memory cells (for LSTMs) of the layer obtained from the previous input gradients in a sequence of inputs. Has to be the output of a previous call to this function or nil (assumed zero).

recurrentOutputStates - An array that will be appended with the recurrent output states. Can be nil. If recurrentOutputIsTemporary is YES and then all returned recurrent states will be temporary. @see MPSState:isTemporary.

weights - An array of valid MPSMatrix objects containing the weights, should be the array that was produced either by @see initWithDevice or @see createWeightMatrices.

encodeGradientSequenceToCommandBufferForwardSourcesSourceGradientsDestinationGradientsWeightGradientsTrainingStatesWeights

public void encodeGradientSequenceToCommandBufferForwardSourcesSourceGradientsDestinationGradientsWeightGradientsTrainingStatesWeights(MTLCommandBuffer commandBuffer,
                                                                                                                                       NSArray<? extends MPSMatrix> forwardSources,
                                                                                                                                       NSArray<? extends MPSMatrix> sourceGradients,
                                                                                                                                       NSArray<? extends MPSMatrix> destinationGradients,
                                                                                                                                       NSArray<? extends MPSMatrix> weightGradients,
                                                                                                                                       NSArray<? extends MPSRNNMatrixTrainingState> trainingStates,
                                                                                                                                       NSArray<? extends MPSMatrix> weights)

Encode an MPSRNNMatrixTrainingLayer gradient pass kernel for a sequence of input gradients into a command buffer. NOTE: The time sequence indexing follows the array indexing in the inputs: sourceGradients[0] has to contain the gradients corresponding to the first matrix in the forward pass corresponding to the current subsequence, which is typically sourceMatrices[0].

Parameters:

commandBuffer - A valid MTLCommandBuffer to receive the encoded filter

forwardSources - An array of MPSMatrix objects containing the sequence of source matrices of the forward pass.

sourceGradients - An array of MPSMatrix objects containing the sequence of source gradient matrices.

destinationGradients - An array valid MPSMatrix objects that will receive the backpropagated gradients, may be nil if not needed (for example first layer in graph).

weightGradients - An array valid MPSMatrix objects that will receive the gradient wrt. weights and biases of the layer - should be the array that was produced either by @see initWithDevice or @see createWeightMatrices. May be nil in which case the gradients for the weights are not computed. NOTE: The weight gradients are accumulated on top of existing values so

trainingStates - An array containing the training states from the forward pass - the array must contain the states corresponding to the input gradients is sourceGradients.

weights - An array of valid MPSMatrix objects containing the weights, should be the array that was produced either by @see initWithDevice or @see createWeightMatrices.

hash_static

public static long hash_static()

init

public MPSRNNMatrixTrainingLayer init()

Overrides:

init in class MPSKernel

initWithCoder

public MPSRNNMatrixTrainingLayer initWithCoder(NSCoder aDecoder)

Description copied from interface: NSCoding

NS_DESIGNATED_INITIALIZER

Specified by:

initWithCoder in interface NSCoding

Overrides:

initWithCoder in class MPSKernel

initWithCoderDevice

public MPSRNNMatrixTrainingLayer initWithCoderDevice(NSCoder aDecoder,
                                                     java.lang.Object device)

NSSecureCoding compatability

See @ref MPSKernel#initWithCoder.

Overrides:

initWithCoderDevice in class MPSKernel

Parameters:

aDecoder - The NSCoder subclass with your serialized MPSRNNMatrixTrainingLayer

device - The MTLDevice on which to make the MPSRNNMatrixTrainingLayer

Returns:

A new MPSRNNMatrixTrainingLayer object, or nil if failure.

initWithDevice

public MPSRNNMatrixTrainingLayer initWithDevice(java.lang.Object device)

Description copied from class: MPSKernel

Standard init with default properties per filter type

Overrides:

initWithDevice in class MPSKernel

Parameters:

device - The device that the filter will be used on. May not be NULL.

Returns:

a pointer to the newly initialized object. This will fail, returning nil if the device is not supported. Devices must be MTLFeatureSet_iOS_GPUFamily2_v1 or later.

initWithDeviceRnnDescriptorTrainableWeights

public MPSRNNMatrixTrainingLayer initWithDeviceRnnDescriptorTrainableWeights(MTLDevice device,
                                                                             MPSRNNDescriptor rnnDescriptor,
                                                                             NSMutableArray<MPSMatrix> trainableWeights)

Initializes a linear (fully connected) RNN kernel for training

Parameters:

device - The MTLDevice on which this MPSRNNMatrixLayer filter will be used

rnnDescriptor - The descriptor that defines the RNN layer

trainableWeights - An array where to store the weights of the layer as MPSMatrices. NOTE: The exact layout and number of matrices may vary between platforms and therefore you should not save out these weights directly, but instead use the function encodeCopyWeightsToCommandBuffer to identify the weights and biases for serialization. Typically you should pass here an initialized but empty NSMutableArray and when this function returns the array will have been populated with the weight matrices needed in the encode-calls, by using initial values from the datasources in rnnDescriptor.

Returns:

A valid MPSRNNMatrixTrainingLayer object or nil, if failure.

inputFeatureChannels

public long inputFeatureChannels()

[@property] inputFeatureChannels

The number of feature channels input vector/matrix.

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)

new_objc

public static MPSRNNMatrixTrainingLayer new_objc()

outputFeatureChannels

public long outputFeatureChannels()

[@property] outputFeatureChannels

The number of feature channels in the output vector/matrix.

recurrentOutputIsTemporary

public boolean recurrentOutputIsTemporary()

[@property] recurrentOutputIsTemporary

How recurrent output states from @ref encodeForwardSequenceToCommandBuffer and encodeGradientSequenceToCommandBuffer are constructed. Defaults to NO. For reference @see MPSState.

resolveClassMethod

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

resolveInstanceMethod

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

setAccumulateWeightGradients

public void setAccumulateWeightGradients(boolean value)

[@property] accumulateWeightGradients

If yes then the computed weight gradients are accumulated on top of existing values in calls to the gradient computation functions: encodeGradientSequenceToCommandBuffer. Defaults to NO.

setRecurrentOutputIsTemporary

public void setRecurrentOutputIsTemporary(boolean value)

[@property] recurrentOutputIsTemporary

How recurrent output states from @ref encodeForwardSequenceToCommandBuffer and encodeGradientSequenceToCommandBuffer are constructed. Defaults to NO. For reference @see MPSState.

setStoreAllIntermediateStates

public void setStoreAllIntermediateStates(boolean value)

[@property] storeAllIntermediateStates

If YES then calls to functions @ref encodeForwardSequenceToCommandBuffer and [@ref] encodeGradientSequenceToCommandBuffer return every recurrent state in the array: recurrentOutputStates. Defaults to NO.

setTrainingStateIsTemporary

public void setTrainingStateIsTemporary(boolean value)

[@property] trainingStateIsTemporary

How training output states from @ref encodeForwardSequenceToCommandBuffer are constructed. Defaults to NO. For reference @see MPSState.

setVersion_static

public static void setVersion_static(long aVersion)

storeAllIntermediateStates

public boolean storeAllIntermediateStates()

[@property] storeAllIntermediateStates

If YES then calls to functions @ref encodeForwardSequenceToCommandBuffer and [@ref] encodeGradientSequenceToCommandBuffer return every recurrent state in the array: recurrentOutputStates. Defaults to NO.

superclass_static

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

supportsSecureCoding

public static boolean supportsSecureCoding()

_supportsSecureCoding

public boolean _supportsSecureCoding()

Description copied from interface: NSSecureCoding

This property must return YES on all classes that allow secure coding. Subclasses of classes that adopt NSSecureCoding and override initWithCoder: must also override this method and return YES. The Secure Coding Guide should be consulted when writing methods that decode data.

Specified by:

_supportsSecureCoding in interface NSSecureCoding

Overrides:

_supportsSecureCoding in class MPSKernel

trainingStateIsTemporary

public boolean trainingStateIsTemporary()

[@property] trainingStateIsTemporary

How training output states from @ref encodeForwardSequenceToCommandBuffer are constructed. Defaults to NO. For reference @see MPSState.

version_static

public static long version_static()