Class MPSRNNDescriptor

    • Constructor Detail

      • MPSRNNDescriptor

        protected MPSRNNDescriptor​(org.moe.natj.general.Pointer peer)
    • Method Detail

      • accessInstanceVariablesDirectly

        public static boolean accessInstanceVariablesDirectly()
      • allocWithZone

        public static java.lang.Object 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()
      • debugDescription_static

        public static java.lang.String debugDescription_static()
      • description_static

        public static java.lang.String description_static()
      • hash_static

        public static long hash_static()
      • inputFeatureChannels

        public long inputFeatureChannels()
        [@property] inputFeatureChannels The number of feature channels per pixel in the input image or number of rows in the input matrix.
      • 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)
      • layerSequenceDirection

        public long layerSequenceDirection()
        [@property] layerSequenceDirection When the layer specified with this descriptor is used to process a sequence of inputs by calling @see encodeBidirectionalSequenceToCommandBuffer then this parameter defines in which direction the sequence is processed. The operation of the layer is: (yt, ht, ct) = f(xt,ht-1,ct-1) for MPSRNNSequenceDirectionForward and (yt, ht, ct) = f(xt,ht+1,ct+1) for MPSRNNSequenceDirectionBackward, where xt is the output of the previous layer that encodes in the same direction as this layer, (or the input image or matrix if this is the first layer in stack with this direction).
        See Also:
        and @see MPSRNNMatrixInferenceLayer.
      • new_objc

        public static java.lang.Object new_objc()
      • outputFeatureChannels

        public long outputFeatureChannels()
        [@property] outputFeatureChannels The number of feature channels per pixel in the destination image or number of rows in the destination matrix.
      • resolveClassMethod

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

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

        public void setInputFeatureChannels​(long value)
        [@property] inputFeatureChannels The number of feature channels per pixel in the input image or number of rows in the input matrix.
      • setLayerSequenceDirection

        public void setLayerSequenceDirection​(long value)
        [@property] layerSequenceDirection When the layer specified with this descriptor is used to process a sequence of inputs by calling @see encodeBidirectionalSequenceToCommandBuffer then this parameter defines in which direction the sequence is processed. The operation of the layer is: (yt, ht, ct) = f(xt,ht-1,ct-1) for MPSRNNSequenceDirectionForward and (yt, ht, ct) = f(xt,ht+1,ct+1) for MPSRNNSequenceDirectionBackward, where xt is the output of the previous layer that encodes in the same direction as this layer, (or the input image or matrix if this is the first layer in stack with this direction).
        See Also:
        and @see MPSRNNMatrixInferenceLayer.
      • setOutputFeatureChannels

        public void setOutputFeatureChannels​(long value)
        [@property] outputFeatureChannels The number of feature channels per pixel in the destination image or number of rows in the destination matrix.
      • setUseFloat32Weights

        public void setUseFloat32Weights​(boolean value)
        [@property] useFloat32Weights If YES, then @ref MPSRNNMatrixInferenceLayer uses 32-bit floating point numbers internally for weights when computing matrix transformations. If NO, then 16-bit, half precision floating point numbers are used. Currently @ref MPSRNNImageInferenceLayer ignores this property and the convolution operations always convert FP32 weights into FP16 for better performance. Defaults to NO.
      • setUseLayerInputUnitTransformMode

        public void setUseLayerInputUnitTransformMode​(boolean value)
        [@property] useLayerInputUnitTransformMode if YES then use identity transformation for all weights (W, Wr, Wi, Wf, Wo, Wc) affecting input x_j in this layer, even if said weights are specified as nil. For example 'W_ij * x_j' is replaced by 'x_j' in formulae defined in @ref MPSRNNSingleGateDescriptor. Defaults to NO.
      • setVersion_static

        public static void setVersion_static​(long aVersion)
      • superclass_static

        public static org.moe.natj.objc.Class superclass_static()
      • useFloat32Weights

        public boolean useFloat32Weights()
        [@property] useFloat32Weights If YES, then @ref MPSRNNMatrixInferenceLayer uses 32-bit floating point numbers internally for weights when computing matrix transformations. If NO, then 16-bit, half precision floating point numbers are used. Currently @ref MPSRNNImageInferenceLayer ignores this property and the convolution operations always convert FP32 weights into FP16 for better performance. Defaults to NO.
      • useLayerInputUnitTransformMode

        public boolean useLayerInputUnitTransformMode()
        [@property] useLayerInputUnitTransformMode if YES then use identity transformation for all weights (W, Wr, Wi, Wf, Wo, Wc) affecting input x_j in this layer, even if said weights are specified as nil. For example 'W_ij * x_j' is replaced by 'x_j' in formulae defined in @ref MPSRNNSingleGateDescriptor. Defaults to NO.
      • version_static

        public static long version_static()