Namespaces
	assembly_utils

	cl_direct_conv

	cl_dwc

	cl_gemm

	cl_indirect_conv

	cl_matmul

	cl_tuner

	cpu

	cpuinfo

	detail

	experimental

	gpu

	graph

	graph_utils

	helpers

	io

	kernels

	logging

	misc

	mlgo

	opencl
	Interface to convert the 2D Fully Connected weights from NCHW to NHWC or vice versa.

	quantization

	scale_helpers

	scale_utils

	scheduler_utils

	softmax_helpers

	support

	test

	utility

	utils

	weights_transformations

	wrapper

Data Structures
class	AccessWindowAutoPadding
	Dummy access window. More...

class	AccessWindowHorizontal
	Implementation of a row access pattern. More...

class	AccessWindowRectangle
	Implementation of a rectangular access pattern. More...

class	AccessWindowStatic
	Implementation of a static rectangular access pattern. More...

class	AccessWindowTranspose
	Implementation of a XY-transpose access pattern. More...

class	AccessWindowVertical
	Implementation of a column access pattern. More...

class	ActivationLayerInfo
	Activation Layer Information class. More...

class	Allocator
	Default malloc allocator implementation. More...

class	AllocatorWrapper
	Default malloc allocator implementation. More...

class	Array
	Basic implementation of the IArray interface which allocates a static number of T values. More...

class	bfloat16
	Brain floating point representation class. More...

struct	BlobInfo
	Meta-data information for each blob. More...

class	BlobLifetimeManager
	Concrete class that tracks the lifetime of registered tensors and calculates the systems memory requirements in terms of blobs. More...

class	BlobMemoryPool
	Blob memory pool. More...

struct	BorderSize
	Container for 2D border size. More...

class	BoundingBoxTransformInfo
	Bounding Box Transform information class. More...

class	BoxNMSLimitInfo
	BoxWithNonMaximaSuppressionLimit Information class. More...

class	CLAbsLayer
	Basic function to get the absolute value of an input tensor. More...

class	CLActivationLayer
	Basic function to run opencl::kernels::ClActivationKernel. More...

class	CLArgMinMaxLayer
	Function to calculate the index of the minimum or maximum values in a tensor based on an axis. More...

class	CLArgMinMaxLayerKernel
	Interface for the reduction operation kernel. More...

class	CLArithmeticAddition
	Basic function to run opencl::kernels::ClSaturatedArithmeticKernel for addition. More...

class	CLArithmeticDivision
	Basic function to run opencl::kernels::ClSaturatedArithmeticKernel for division. More...

class	CLArithmeticSubtraction
	Basic function to run opencl::kernels::ClSaturatedArithmeticKernel for subtraction. More...

class	CLArray
	CLArray implementation. More...

class	CLBatchNormalizationLayer
	Basic function to run CLNormalizationLayerKernel and simulate a batch normalization layer. More...

class	CLBatchNormalizationLayerKernel
	Interface for the BatchNormalization layer kernel. More...

class	CLBatchToSpaceLayer
	Basic function to run CLBatchToSpaceLayerKernel. More...

class	CLBatchToSpaceLayerKernel
	Interface for the batch to space kernel. More...

class	CLBitwiseAnd
	Basic function to perform bitwise AND by running CLBitwiseKernel. More...

class	CLBitwiseKernel
	Interface for the bitwise operation kernel. More...

class	CLBitwiseNot
	Basic function to perform bitwise NOT by running CLBitwiseKernel. More...

class	CLBitwiseOr
	Basic function to perform bitwise OR by running CLBitwiseKernel. More...

class	CLBitwiseXor
	Basic function to perform bitwise XOR by running CLBitwiseKernel. More...

class	CLBoundingBoxTransform
	Basic function to run CLBoundingBoxTransformKernel. More...

class	CLBoundingBoxTransformKernel
	Interface for the bounding box kernel. More...

class	CLBufferAllocator
	Default OpenCL cl buffer allocator implementation. More...

class	CLBufferMemoryRegion
	OpenCL buffer memory region implementation. More...

class	CLBuildOptions
	Build options. More...

class	CLCast
	Basic function to run opencl::kernels::ClCastKernel. More...

class	CLChannelShuffleLayer
	Basic function to run CLChannelShuffleLayerKernel. More...

class	CLChannelShuffleLayerKernel
	Interface for the channel shuffle kernel. More...

class	CLCoarseSVMMemoryRegion
	OpenCL coarse-grain SVM memory region implementation. More...

class	CLComparison
	Basic function to run CLComparisonKernel. More...

class	CLComparisonKernel
	Interface for the comparison kernel. More...

class	CLComparisonStatic
	Basic function to run CLComparisonKernel. More...

class	CLCompileContext
	CLCompileContext class. More...

class	CLComplexPixelWiseMultiplication
	Basic function to run opencl::ClComplexMul. More...

class	CLComputeAllAnchorsKernel
	Interface for Compute All Anchors kernel. More...

class	CLComputeMeanVariance
	Interface for compute Mean and Variance per channel. More...

class	CLConcatenateLayer
	Basic function to execute concatenate tensors along a given axis. More...

class	CLConv3D
	Basic function to compute the convolution3d layer. More...

class	CLConvertFullyConnectedWeights
	Basic function to run an opencl::kernels::ClConvertFullyConnectedWeightsKernel. More...

class	CLConvolutionLayer
	Basic function to compute the convolution layer. More...

class	CLCopy
	Basic function to run opencl::kernels::ClCopyKernel. More...

class	CLCrop
	Basic function to run opencl::kernels::ClCropKernel. More...

class	CLCropResize
	Function to perform cropping and resizing. More...

class	CLDeconvolutionLayer
	Basic function to compute the deconvolution layer. More...

class	CLDeconvolutionLayerUpsample
	Basic function to execute deconvolution upsample on OpenCL. More...

class	CLDeconvolutionLayerUpsampleKernel
	Interface for the Deconvolution layer kernel on OpenCL. More...

class	CLDeconvolutionReshapeOutputKernel
	Interface for the OpenCL kernel to be used for reshaping the tensor before returning the result of deconvolution. More...

class	CLDepthConvertLayer
	Basic function to run opencl::kernels::ClCastKernel. More...

class	CLDepthToSpaceLayer
	Basic function to run CLDepthToSpaceLayerKernel. More...

class	CLDepthToSpaceLayerKernel
	Interface for the depth to space kernel. More...

class	CLDepthwiseConvolutionLayer
	Function to execute a depthwise convolution. More...

class	CLDepthwiseConvolutionLayerNativeKernel
	Interface for the kernel to run a MxN depthwise convolution. More...

class	CLDequantizationLayer
	Basic function to run opencl::ClDequantize that dequantizes an input tensor. More...

class	CLDevice
	OpenCL device type class. More...

struct	CLDeviceOptions
	OpenCL device options. More...

class	CLDirectConvolutionLayer
	Basic function to execute direct convolution function: More...

class	CLDirectDeconvolutionLayer
	Function to run the deconvolution layer. More...

class	CLElementwiseMax
	Basic function to run opencl::kernels::ClArithmeticKernel for max. More...

class	CLElementwiseMin
	Basic function to run opencl::kernels::ClArithmeticKernel for min. More...

class	CLElementwisePower
	Basic function to run opencl::kernels::ClArithmeticKernel for power. More...

class	CLElementwiseSquaredDiff
	Basic function to run opencl::kernels::ClArithmeticKernel for squared difference. More...

class	CLExpLayer
	Basic function to perform exponential on an input tensor. More...

class	CLFFT1D
	Basic function to execute one dimensional FFT. More...

class	CLFFT2D
	Basic function to execute two dimensional FFT. More...

class	CLFFTConvolutionLayer
	Basic function to execute FFT-based convolution on OpenCL. More...

class	CLFFTDigitReverseKernel
	Interface for the digit reverse operation kernel. More...

class	CLFFTRadixStageKernel
	Interface for the FFT radix stage kernel. More...

class	CLFFTScaleKernel
	Interface for the inverse fft scale kernel. More...

class	CLFill
	Basic function to run opencl::kernels::ClFillKernel. More...

class	CLFillBorderKernel
	Interface for filling the border of a kernel. More...

class	CLFineSVMMemoryRegion
	OpenCL fine-grain SVM memory region implementation. More...

class	CLFlattenLayer
	Basic function to execute flatten. More...

class	CLFloor
	Basic function to run opencl::kernels::ClFloorKernel. More...

class	CLFullyConnectedLayer
	Basic function to compute a Fully Connected layer on OpenCL. More...

class	CLFuseBatchNormalization
	Basic function to fuse the batch normalization node to a preceding convolution node. More...

class	CLFuseBatchNormalizationKernel
	OpenCL kernel to fuse the batch normalization node to a preceding convolution node. More...

class	CLGather
	Basic function to run CLGatherKernel. More...

class	CLGatherKernel
	Interface for the kernel to perform tensor reshaping. More...

class	CLGEMM
	Basic function to execute GEMM on OpenCL. More...

class	CLGEMMConvolutionLayer
	Basic function to compute the convolution layer. More...

class	CLGEMMDeconvolutionLayer
	Function to run the deconvolution layer through a call to GEMM. More...

class	CLGEMMHeuristicsHandle
	Handle for loading and retrieving GEMM heuristics. More...

struct	CLGEMMKernelSelectionParams
	OpenCL GEMM kernel selection parameters. More...

class	CLGEMMLowpMatrixMultiplyCore
	Basic function to execute GEMMLowpMatrixMultiplyCore on OpenCL. More...

class	CLGEMMLowpOutputStage
	Basic function to execute GEMMLowpQuantizeDown kernels on CL. More...

class	CLGenerateProposalsLayer
	Basic function to generate proposals for a RPN (Region Proposal Network) More...

class	CLIndirectConvolutionLayer
	Basic function to run the indirect convolution function. More...

class	CLInstanceNormalizationLayer
	Basic function to perform a Instance normalization. More...

class	CLInstanceNormalizationLayerKernel
	Interface for performing an instance normalization. More...

class	CLKernelLibrary
	CLKernelLibrary class. More...

class	CLL2NormalizeLayer
	Basic function to perform a L2 normalization on a given axis. More...

class	CLL2NormalizeLayerKernel
	Interface for performing a L2 normalize on a given axis given the square sum of it in this axis. More...

class	CLLogicalAnd
	Basic function to run arm_compute::opencl::kernels::ClLogicalBinaryKernel. More...

class	CLLogicalNot
	Basic function to do logical NOT operation. More...

class	CLLogicalOr
	Basic function to run arm_compute::opencl::kernels::ClLogicalBinaryKernel. More...

class	CLLogLayer
	Basic function to perform elementwise log on an input tensor. More...

class	CLLSTMLayer
	This function performs a single time step in a Long Short-Term Memory (LSTM) layer. More...

class	CLLSTMLayerQuantized
	Basic function to run CLLSTMLayerQuantized. More...

class	CLMatMul
	Basic function to execute MatMul (Matrix Multiplication) on OpenCL. More...

class	CLMaxUnpoolingLayer
	Function to perform MaxUnpooling. More...

class	CLMaxUnpoolingLayerKernel
	Interface for the pooling layer kernel. More...

class	CLMeanStdDevNormalizationKernel
	Interface for the kernel to normalize the input 2D tensor across the first dimension with respect to mean and standard deviation of the same dimension. More...

class	CLMeanStdDevNormalizationLayer
	Basic function to execute mean and standard deviation normalization by calling CLMeanStdDevNormalizationKernel. More...

class	CLMemory
	OpenCL implementation of memory object. More...

class	CLNegLayer
	Basic function to negate an input tensor. More...

class	CLNormalizationLayer
	Basic function to compute a normalization layer. More...

class	CLNormalizationLayerKernel
	Interface for the normalization layer kernel. More...

class	CLNormalizePlanarYUVLayer
	Basic function to run CLNormalizePlanarYUVLayerKernel. More...

class	CLNormalizePlanarYUVLayerKernel
	Interface for the NormalizePlanarYUV layer kernel. More...

class	CLPadLayer
	Basic function to pad a tensor. More...

class	CLPadLayerKernel
	Interface for the PadLayer function. More...

class	CLPermute
	Basic function to execute an opencl::kernels::ClPermuteKernel. More...

class	CLPixelWiseMultiplication
	Basic function to run opencl::ClMul. More...

class	CLPooling3dLayer
	Basic function to run opencl::ClPool3d. More...

class	CLPoolingLayer
	Basic function to run opencl::ClPool2d. More...

class	CLPReluLayer
	Basic function to run opencl::kernels::ClArithmeticKernel for PRELU. More...

class	CLPriorBoxLayer
	Basic function to run CLPriorBoxLayerKernel. More...

class	CLPriorBoxLayerKernel
	Interface for the PriorBox layer kernel. More...

class	CLQLSTMLayer
	Basic function to run CLQLSTMLayer. More...

class	CLQLSTMLayerNormalizationKernel
	Interface for the kernel to do layer normalization. More...

struct	CLQuantization
	OpenCL quantization data. More...

class	CLQuantizationLayer
	Basic function to simulate a quantization layer. More...

class	CLRange
	Basic function to run CLRangeKernel. More...

class	CLRangeKernel
	Kernel class for Range. More...

class	CLReduceMean
	Basic function to perform reduce operation. More...

class	CLReductionOperation
	Perform reduction operation. More...

class	CLReductionOperationKernel
	Interface for the reduction operation kernel. More...

class	CLReorgLayer

class	CLReorgLayerKernel
	OpenCL kernel to perform a reorg layer. More...

class	CLReshapeLayer
	Basic function to run opencl::kernels::ClReshapeKernel. More...

class	CLReverse
	Basic function to run CLReverseKernel. More...

class	CLReverseKernel
	Interface for the reverse kernel. More...

class	CLRNNLayer
	Basic function to run CLRNNLayer. More...

class	CLROIAlignLayer
	Basic function to run CLROIAlignLayerKernel. More...

class	CLROIAlignLayerKernel
	Interface for the RoIAlign kernel. More...

class	CLROIPoolingLayer
	Basic function to run CLROIPoolingLayerKernel. More...

class	CLROIPoolingLayerKernel
	Interface for the ROI pooling layer kernel. More...

class	CLRoundLayer
	Basic function to get the round (to the nearest even) value of an input tensor. More...

class	CLRsqrtLayer
	Basic function to perform inverse square root on an input tensor. More...

class	CLRuntimeContext
	Runtime context. More...

class	CLScale
	Basic function to run opencl::ClScale. More...

class	CLScheduler
	Provides global access to a CL context and command queue. More...

class	CLSelect
	Basic function to run CLSelect. More...

class	CLSelectKernel
	OpenCL interface for executing the select kernel. More...

class	CLSinLayer
	Basic function to calculate sine of an input tensor. More...

class	CLSlice
	Basic function to perform tensor slicing. More...

class	CLSoftmaxLayerGeneric
	Basic function to compute a SoftmaxLayer. More...

class	CLSpaceToBatchLayer
	Basic function to spatial divide a tensor. More...

class	CLSpaceToBatchLayerKernel
	Interface for the space to batch kernel. More...

class	CLSpaceToDepthLayer
	Basic function to run CLSpaceToDepthLayerKernel. More...

class	CLSpaceToDepthLayerKernel
	Interface for the space to depth kernel. More...

class	CLSplit
	Basic function to split a tensor along a given axis. More...

class	CLStackLayer
	Basic function to stack tensors along an axis. More...

class	CLStackLayerKernel
	OpenCL kernel to stacks a rank-R tensor into one with rank-(R+1) along the axis dimension. More...

class	CLStridedSlice
	Basic function to run CLStridedSliceKernel. More...

class	CLStridedSliceKernel
	Interface for the kernel to perform tensor strided slicing. More...

class	CLSubTensor
	Basic implementation of the OpenCL sub-tensor interface. More...

class	CLSymbols
	Class for loading OpenCL symbols. More...

class	CLTensor
	Basic implementation of the OpenCL tensor interface. More...

class	CLTensorAllocator
	Basic implementation of a CL memory tensor allocator. More...

class	CLTile
	Basic function to run CLTileKernel. More...

class	CLTileKernel
	OpenCL kernel to perform a Tile operation. More...

class	CLTranspose
	Basic function to execute an opencl::kernels::ClTransposeKernel. More...

class	CLTuner
	Basic implementation of the OpenCL tuner interface. More...

struct	CLTuningInfo

class	CLTuningParams
	< OpenCL tuner parameters More...

class	CLUnstack
	Basic function to unpack a rank-R tensor into rank-(R-1) tensors. More...

class	CLWinogradConvolutionLayer
	Basic function to execute Winograd-based convolution on OpenCL. More...

class	ComputeAnchorsInfo
	ComputeAnchors information class. More...

struct	Conv2dInfo
	Descriptor used by the 2d Convolution function. More...

struct	Conv3dInfo
	Descriptor used by the 3d Convolution function. More...

struct	ConvolutionInfo

class	Coordinates
	Coordinates of an item. More...

struct	Coordinates2D
	Coordinate type. More...

struct	Coordinates3D
	Coordinate type. More...

class	CPPBoxWithNonMaximaSuppressionLimit
	Basic function to run CPPBoxWithNonMaximaSuppressionLimitKernel. More...

class	CPPBoxWithNonMaximaSuppressionLimitKernel
	CPP kernel to perform computation of BoxWithNonMaximaSuppressionLimit. More...

class	CPPDetectionOutputLayer
	CPP Function to generate the detection output based on location and confidence predictions by doing non maximum suppression. More...

class	CPPDetectionPostProcessLayer
	CPP Function to generate the detection output based on center size encoded boxes, class prediction and anchors by doing non maximum suppression. More...

class	CPPNonMaximumSuppression
	CPP Function to perform non maximum suppression on the bounding boxes and scores. More...

class	CPPNonMaximumSuppressionKernel
	CPP Function to perform non maximum suppression on the bounding boxes and scores. More...

class	CPPPermute
	Basic function to run CPPPermuteKernel. More...

class	CPPPermuteKernel
	CPP kernel to perform tensor permutation. More...

class	CPPScheduler
	C++11 implementation of a pool of threads to automatically split a kernel's execution among several threads. More...

class	CPPSplit
	Basic function to split a tensor along a given axis. More...

class	CPPTopKV
	Basic function to run CPPTopKVKernel. More...

class	CPPTopKVKernel
	CPP kernel to perform tensor TopKV operation. More...

class	CPPUpsample
	Basic function to run CPPUpsample. More...

class	CPPUpsampleKernel
	CPP kernel to perform tensor upsample. More...

class	CPUInfo

class	CpuMatMulSettings
	Settings for MatMul Cpu implementation. More...

class	DetectionOutputLayerInfo
	Detection Output layer info. More...

class	DetectionPostProcessLayerInfo
	Detection Output layer info. More...

struct	DetectionWindow
	Detection window used for the object detection. More...

class	Dimensions
	Dimensions with dimensionality. More...

struct	DirectConvComputeKernelInfo
	Compute descriptor used by the direct convolution kernel. More...

struct	DirectConvolutionLayerOutputStageKernelInfo
	Descriptor used by the direct convolution layer output stage kernels. More...

struct	DWCComputeKernelInfo
	Compute descriptor used by the depthwise convolution native kernel. More...

struct	enable_bitwise_ops
	Disable bitwise operations by default. More...

struct	enable_bitwise_ops< arm_compute::GPUTarget >
	Enable bitwise operations on GPUTarget enumerations. More...

struct	FFT1DInfo
	Descriptor used by the FFT1D function. More...

struct	FFT2DInfo
	Descriptor used by the FFT2D function. More...

struct	FFTDigitReverseKernelInfo
	Descriptor for FFT digit reverse kernels. More...

struct	FFTRadixStageKernelInfo
	Descriptor used by the FFT core kernels. More...

struct	FFTScaleKernelInfo
	Descriptor for FFT scale kernels. More...

struct	FullyConnectedLayerInfo
	Fully connected layer info. More...

class	GEMMInfo
	GEMM information class. More...

struct	GEMMKernelInfo
	Descriptor used by the GEMM kernels. More...

struct	GEMMLHSMatrixInfo
	GEMM LHS (Left Hand Side) matrix information. More...

struct	GEMMLowpOutputStageInfo
	GEMMLowp output stage info. More...

struct	GEMMLowpReductionKernelInfo

class	GEMMReshapeInfo
	GEMM reshape information class. More...

struct	GEMMRHSMatrixInfo
	GEMM RHS (Right Hand Side) matrix information. More...

class	GenerateProposalsInfo
	Generate Proposals Information class. More...

class	GpuMatMulSettings
	Settings for MatMul OpenCL implementation. More...

class	IAccessWindow
	Interface describing methods to update access window and padding based on kernel parameters. More...

class	IAllocator
	Allocator interface. More...

class	IArray
	Array of type T. More...

class	IAssetManager
	Asset manager interface. More...

class	ICLArray
	Interface for OpenCL Array. More...

class	ICLKernel
	Common interface for all the OpenCL kernels. More...

class	ICLMemoryRegion
	OpenCL memory region interface. More...

class	ICLSimple2DKernel
	Interface for simple OpenCL kernels having 1 tensor input and 1 tensor output. More...

class	ICLSimple3DKernel
	Interface for simple OpenCL kernels having 1 tensor input and 1 tensor output. More...

class	ICLSimpleFunction
	Basic interface for functions which have a single OpenCL kernel. More...

class	ICLSimpleKernel
	Interface for simple OpenCL kernels having 1 tensor input and 1 tensor output. More...

class	ICLSVMMemoryRegion
	OpenCL SVM memory region interface. More...

class	ICLTensor
	Interface for OpenCL tensor. More...

class	ICLTuner
	Basic interface for tuning the OpenCL kernels. More...

class	IContext
	Context interface. More...

class	ICPPKernel
	Common interface for all kernels implemented in C++. More...

class	ICPPSimpleFunction
	Basic interface for functions which have a single CPP kernel. More...

class	IDevice
	Interface for device object. More...

class	IFunction
	Base class for all functions. More...

class	IKernel
	Common information for all the kernels. More...

class	ILifetimeManager
	Interface for managing the lifetime of objects. More...

class	IMemory
	Memory interface. More...

class	IMemoryGroup
	Memory group interface. More...

class	IMemoryManageable
	Interface of an object than can be memory managed. More...

class	IMemoryManager
	Memory manager interface to handle allocations of backing memory. More...

class	IMemoryPool
	Memory Pool Inteface. More...

class	IMemoryRegion
	Memory region interface. More...

class	INESimpleFunction
	Basic interface for functions which have a single CPU kernel. More...

class	INESimpleFunctionNoBorder
	Basic interface for functions which have a single CPU kernel and no border. More...

struct	InstanceNormalizationLayerKernelInfo

struct	IOFormatInfo
	IO formatting information class. More...

class	IOperator
	Base class specifying the operator interface. More...

class	IPoolManager
	Memory pool manager interface. More...

class	IQueue
	Base class specifying the queue interface. More...

class	IRuntimeContext
	Context interface. More...

class	IScheduler
	Scheduler interface to run kernels. More...

class	ISimpleLifetimeManager
	Abstract class of the simple lifetime manager interface. More...

class	ITensor
	Interface for CPU tensor. More...

class	ITensorAllocator
	Interface to allocate tensors. More...

class	ITensorInfo
	Store the tensor's metadata. More...

class	ITensorPack
	Tensor packing service. More...

class	ITensorV2
	Base class specifying the tensor interface. More...

class	Iterator
	Iterator updated by execute_window_loop for each window element. More...

class	ITransformWeights
	Weights tensor transform interface In order to identify the different reshape functions, each reshape function has to generate a unique id. More...

class	IWeightsManager
	Weights manager interface to handle weights transformations. More...

class	Kernel
	Kernel class. More...

class	LSTMParams

class	MatMulInfo
	Class for holding information related to matrix multiplication function. More...

struct	MatMulKernelInfo

class	Memory
	CPU implementation of memory object. More...

class	MemoryGroup
	Memory group. More...

class	MemoryGroupResourceScope
	Memory group resources scope handling class. More...

class	MemoryManagerOnDemand
	On-demand memory manager. More...

class	MemoryRegion
	Memory region CPU implementation. More...

struct	MinMaxLocationValues
	Min and max values and locations. More...

class	NEActivationLayer
	Basic function to run cpu::kernels::CpuActivationKernel. More...

class	NEAddMulAdd
	Function to compute Add+Mul+Add fused operation. More...

class	NEArgMinMaxLayer
	Function to calculate the index of the minimum or maximum values in a tensor based on an axis. More...

class	NEArithmeticAddition
	Basic function to run cpu::kernels::CpuAddKernel. More...

class	NEArithmeticSubtraction
	Basic function to run cpu::kernels::CpuSubKernel. More...

class	NEBatchNormalizationLayer
	Basic function to run NENormalizationLayerKernel and simulate a batch normalization layer. More...

class	NEBatchNormalizationLayerKernel
	Interface for the batch normalization layer kernel. More...

class	NEBatchToSpaceLayer
	Basic function to run NEBatchToSpaceLayerKernel. More...

class	NEBatchToSpaceLayerKernel
	Interface for the batch to space kernel. More...

class	NEBitwiseAnd
	Basic function to run NEBitwiseAndKernel. More...

class	NEBitwiseAndKernel
	Interface for the kernel to perform bitwise AND between XY-planes of two tensors. More...

class	NEBitwiseNot
	Basic function to run NEBitwiseNotKernel. More...

class	NEBitwiseNotKernel
	Interface for the kernel to perform bitwise NOT operation. More...

class	NEBitwiseOr
	Basic function to run NEBitwiseOrKernel. More...

class	NEBitwiseOrKernel
	Interface for the kernel to perform bitwise inclusive OR between two tensors. More...

class	NEBitwiseXor
	Basic function to run NEBitwiseXorKernel. More...

class	NEBitwiseXorKernel
	Interface for the kernel to perform bitwise exclusive OR (XOR) between two tensors. More...

class	NEBoundingBoxTransform
	Basic function to run NEBoundingBoxTransformKernel. More...

class	NEBoundingBoxTransformKernel
	Interface for the bounding box kernel. More...

class	NECast
	Basic function to run cpu::kernels::CpuCastKernel. More...

class	NEChannelShuffleLayer
	Basic function to run NEChannelShuffleLayerKernel. More...

class	NEChannelShuffleLayerKernel
	Interface for the channel shuffle kernel. More...

class	NECol2ImKernel
	Kernel to perform col2im reshaping. More...

class	NEComplexPixelWiseMultiplication
	Basic function to run cpu::CpuComplexMul. More...

class	NEComputeAllAnchorsKernel
	Interface for Compute All Anchors kernel. More...

class	NEConcatenateLayer
	Basic function to execute concatenate tensors along a given axis. More...

class	NEConv3D
	Basic function to simulate a 3d convolution. More...

class	NEConvertFullyConnectedWeights
	Basic function to run cpu::kernels::CpuConvertFullyConnectedWeightsKernel. More...

class	NEConvolutionLayer
	Basic function to simulate a convolution layer. More...

class	NECopy
	Basic function to run cpu::kernels::CpuCopyKernel. More...

class	NECropKernel
	Interface for the kernel to perform tensor cropping. More...

class	NECropResize
	Function to perform cropping and resizing. More...

class	NEDeconvolutionLayer
	Function to run the deconvolution layer. More...

class	NEDepthConvertLayer
	Basic function to run cpu::kernels::CpuCastKernel. More...

class	NEDepthToSpaceLayer
	Basic function to run NEDepthToSpaceLayerKernel. More...

class	NEDepthToSpaceLayerKernel
	Interface for the depth to space kernel. More...

class	NEDepthwiseConvolutionLayer
	Function to execute a depthwise convolution. More...

class	NEDequantizationLayer
	Basic function to run cpu::CpuDequantize that dequantizes an input tensor. More...

class	NEDetectionPostProcessLayer
	NE Function to generate the detection output based on center size encoded boxes, class prediction and anchors by doing non maximum suppression. More...

class	NEDirectConvolutionLayer
	Function to run the direct convolution. More...

class	NEElementwiseComparison
	Basic function to run cpu::kernels::CpuComparisonKernel. More...

class	NEElementwiseComparisonStatic
	Basic function to run cpu::kernels::CpuComparisonKernel. More...

class	NEElementwiseDivision
	Basic function to run cpu::kernels::CpuArithmeticKernel for division. More...

class	NEElementwiseMax
	Basic function to run cpu::kernels::CpuArithmeticKernel for max. More...

class	NEElementwiseMin
	Basic function to run cpu::kernels::CpuArithmeticKernel for min. More...

class	NEElementwisePower
	Basic function to run cpu::kernels::CpuArithmeticKernel for power. More...

class	NEElementwiseSquaredDiff
	Basic function to run cpu::kernels::CpuArithmeticKernel for squared difference. More...

class	NEElementwiseUnaryLayer
	Basic function to perform unary elementwise operations. More...

class	NEFFT1D
	Basic function to execute one dimensional FFT. More...

class	NEFFT2D
	Basic function to execute two dimensional FFT. More...

class	NEFFTConvolutionLayer
	Basic function to execute FFT-based convolution on CPU. More...

class	NEFFTDigitReverseKernel
	Interface for the digit reverse operation kernel. More...

class	NEFFTRadixStageKernel
	Interface for the FFT kernel. More...

class	NEFFTScaleKernel
	Interface for the inverse fft scale kernel. More...

class	NEFill
	Basic function to run cpu::kernels::CpuFillKernel. More...

class	NEFillBorder
	Basic function to run NEFillBorderKernel. More...

class	NEFillBorderKernel
	Interface for the kernel to fill borders. More...

class	NEFlattenLayer
	Basic function to execute flatten layer kernel. More...

class	NEFloor
	Basic function to run cpu::kernels::CpuFloorKernel. More...

class	NEFullyConnectedLayer
	Basic function to compute a Fully Connected layer. More...

class	NEFuseBatchNormalization
	Basic function to fuse the batch normalization node to a preceding convolution node. More...

class	NEFuseBatchNormalizationKernel
	OpenNE kernel to fuse the batch normalization node to a preceding convolution node. More...

class	NEGather
	Basic function to run NEGatherKernel. More...

class	NEGatherKernel
	Kernel to perform gather operation. More...

class	NEGEMM
	Basic function to execute GEMM. More...

class	NEGEMMConv2d
	Basic function to compute the convolution layer. More...

class	NEGEMMConvolutionLayer
	Basic function to compute the convolution layer. More...

class	NEGEMMLowpMatrixMultiplyCore
	Function to run Gemm on quantized types. More...

class	NEGEMMLowpOutputStage
	Basic function to execute GEMMLowpQuantizeDown kernels. More...

class	NEGenerateProposalsLayer
	Basic function to generate proposals for a RPN (Region Proposal Network) More...

class	NEInstanceNormalizationLayer
	Basic function to perform a Instance normalization. More...

class	NEInstanceNormalizationLayerKernel
	Interface for performing an instance normalization. More...

class	NEL2NormalizeLayer
	Basic function to perform a L2 normalization on a given axis. More...

class	NEL2NormalizeLayerKernel
	Interface for performing a L2 normalize on a given axis given the square sum of it in this axis. More...

class	NELogicalAnd
	Basic function to perform logical AND. More...

class	NELogicalNot
	Basic function to perform logical NOT. More...

class	NELogicalOr
	Basic function to perform logical OR. More...

class	NELSTMLayer
	Basic function to run NELSTMLayer. More...

class	NELSTMLayerQuantized
	Basic function to run NELSTMLayerQuantized. More...

class	NEMatMul
	Basic function to run the following operators: More...

class	NEMaxUnpoolingLayer
	Function to perform MaxUnpooling. More...

class	NEMeanStdDevNormalizationKernel
	Interface for the kernel to normalize the input 2D tensor across the first dimension with respect to mean and standard deviation of the same dimension. More...

class	NEMeanStdDevNormalizationLayer
	Basic function to execute mean and standard deviation normalization by calling NEMeanStdDevNormalizationKernel. More...

class	NENormalizationLayer
	Basic function to compute a normalization layer. More...

class	NENormalizationLayerKernel
	Interface for the normalization layer kernel. More...

class	NEPadLayer
	Basic function to pad a tensor. More...

class	NEPadLayerKernel
	Basic kernel to pad the input tensor given padding information. More...

class	NEPermute
	Basic function to run cpu::kernels::CpuPermuteKernel. More...

class	NEPixelWiseMultiplication
	Basic function to run cpu::CpuMul. More...

class	NEPooling3dLayer
	Basic function to simulate a pooling 3d layer with the specified pooling operation. More...

class	NEPoolingLayer
	Basic function to simulate a pooling layer with the specified pooling operation. More...

class	NEPReluLayer
	Basic function to run cpu::kernels::CpuArithmeticKernel for PRELU. More...

class	NEPriorBoxLayer
	Basic function to run NEPriorBoxLayerKernel. More...

class	NEPriorBoxLayerKernel
	Interface for the kernel to calculate prior boxes. More...

class	NEQLSTMLayer
	Basic function to run NEQLSTMLayer. More...

class	NEQLSTMLayerNormalizationKernel
	Kernel to perform layer normalization for QLSTM. More...

class	NEQuantizationLayer
	Basic function to run a quantization layer using cpu::CpuQuantize. More...

class	NERange
	Basic function to run NERangeKernel. More...

class	NERangeKernel
	Kernel class for Range. More...

class	NEReduceMean
	Basic function to perform reduce operation. More...

class	NEReductionOperation
	Basic function to simulate a reduction operation. More...

class	NEReductionOperationKernel
	Kernel to perform a reduction operation. More...

class	NEReorgLayer
	Basic function to run NEReorgLayerKernel. More...

class	NEReorgLayerKernel
	Interface for the kernel to perform tensor re-organization. More...

class	NEReshapeLayer
	Basic function to run cpu::kernels::CpuReshapeKernel. More...

class	NEReverse
	Basic function to run NEReverseKernel. More...

class	NEReverseKernel
	Interface for the reverse layer kernel. More...

class	NERNNLayer
	Basic function to run NERNNLayer. More...

class	NEROIAlignLayer
	Basic function to run NEROIAlignLayerKernel. More...

class	NEROIAlignLayerKernel
	Interface for the RoIAlign kernel. More...

class	NEROIPoolingLayer
	Basic function to run NEROIPoolingLayerKernel. More...

class	NEROIPoolingLayerKernel
	Interface for the ROI pooling layer kernel. More...

class	NEScale
	Basic function to compute Scale. More...

class	NESelect
	Basic function to run NESelect. More...

class	NESelectKernel
	Interface for the select kernel. More...

class	NESlice
	Basic function to perform tensor slicing. More...

class	NESoftmaxLayerGeneric
	Basic function to compute a SoftmaxLayer and a Log SoftmaxLayer. More...

class	NESpaceToBatchLayer
	Basic function to spatial divide a tensor. More...

class	NESpaceToBatchLayerKernel
	Interface for the space to batch kernel. More...

class	NESpaceToDepthLayer
	Basic function to run NESpaceToDepthLayerKernel. More...

class	NESpaceToDepthLayerKernel
	Interface for the space to depth kernel. More...

class	NESplit
	Basic function to split a tensor along a given axis. More...

class	NEStackLayer
	Basic function to stack tensors along an axis. More...

class	NEStackLayerKernel
	Basic kernel to stack a rank-R tensor into one with rank-(R+1) along the axis dimension. More...

class	NEStridedSlice
	Basic function to run NEStridedSliceKernel. More...

class	NEStridedSliceKernel
	Interface for the kernel to perform tensor strided slicing. More...

class	NETile
	Basic function to run NETileKernel. More...

class	NETileKernel
	Basic kernel to perform a tile operation. More...

class	NETranspose
	Basic function to run cpu::kernels::CpuTransposeKernel. More...

class	NEUnstack
	Basic function to unpack a rank-R tensor into rank-(R-1) tensors. More...

class	NEWinogradConvolutionLayer
	Basic function to simulate a convolution layer. More...

class	NormalizationLayerInfo
	Normalization Layer Information class. More...

class	OffsetLifetimeManager
	Concrete class that tracks the lifetime of registered tensors and calculates the systems memory requirements in terms of a single blob and a list of offsets. More...

class	OffsetMemoryPool
	Offset based memory pool. More...

class	OMPScheduler
	Pool of threads to automatically split a kernel's execution among several threads. More...

struct	Padding2D
	Padding information for 2D operations like Conv2d. More...

struct	Padding3D
	Padding information for 3D operations like Conv3d. More...

class	PadStrideInfo
	Padding and stride information class. More...

class	PixelValue
	Class describing the value of a pixel for any image format. More...

struct	Pooling3dLayerInfo
	Pooling Layer Information struct. More...

struct	PoolingLayerInfo
	Pooling Layer Information struct. More...

class	PoolManager
	Memory pool manager. More...

class	PriorBoxLayerInfo
	PriorBox layer info. More...

class	Program
	Program class. More...

struct	Qasymm8QuantizationHelper

class	QuantizationInfo
	Quantization information. More...

struct	Rectangle
	Rectangle type. More...

class	ROIPoolingLayerInfo
	ROI Pooling Layer Information class. More...

class	RuntimeContext
	Runtime context. More...

struct	ScaleKernelInfo

class	Scheduler
	Configurable scheduler which supports multiple multithreading APIs and choosing between different schedulers at runtime. More...

class	SchedulerFactory
	Scheduler Factory. More...

class	Semaphore
	Semamphore class. More...

class	SingleThreadScheduler
	Pool of threads to automatically split a kernel's execution among several threads. More...

class	Size2D
	Class for specifying the size of an image or rectangle. More...

class	Size3D
	Class for specifying the size of a 3D shape or object. More...

struct	SoftmaxKernelInfo
	Descriptor used by the softmax kernels. More...

class	Status
	Status class. More...

class	Steps
	Class to describe a number of elements in each dimension. More...

class	StridedSliceLayerInfo

class	Strides
	Strides of an item in bytes. More...

class	SubTensor
	Basic implementation of the sub-tensor interface. More...

class	SubTensorInfo
	Store the sub tensor's metadata. More...

class	Tensor
	Basic implementation of the tensor interface. More...

class	TensorAccessor
	Tensor accessors to make it easier to interface with arm_gemm. More...

class	TensorAllocator
	Basic implementation of a CPU memory tensor allocator. More...

class	TensorInfo
	Store the tensor's metadata. More...

class	TensorPack
	Tensor packing service. More...

class	TensorShape
	Shape of a tensor. More...

struct	ThreadInfo
	Information about executing thread and CPU. More...

struct	UniformQuantizationInfo
	Quantization info when assuming per layer quantization. More...

struct	ValidRegion
	Container for valid region of a window. More...

class	WeightsInfo
	Convolution Layer Weights Information class. More...

class	Window
	Describe a multidimensional execution window. More...

class	WindowIterator
	Iterate over a portion of a Window. More...

struct	WinogradInfo
	Winograd information. More...

struct	WorkspaceDataElement

Typedefs
using	ICLUInt8Array = ICLArray< cl_uchar >
	Interface for OpenCL Array of uint8s. More...

using	ICLUInt16Array = ICLArray< cl_ushort >
	Interface for OpenCL Array of uint16s. More...

using	ICLUInt32Array = ICLArray< cl_uint >
	Interface for OpenCL Array of uint32s. More...

using	ICLInt16Array = ICLArray< cl_short >
	Interface for OpenCL Array of int16s. More...

using	ICLInt32Array = ICLArray< cl_int >
	Interface for OpenCL Array of int32s. More...

using	ICLFloatArray = ICLArray< cl_float >
	Interface for OpenCL Array of floats. More...

using	ICLImage = ICLTensor

using	IUInt8Array = IArray< uint8_t >
	Interface for Array of uint8s. More...

using	IUInt16Array = IArray< uint16_t >
	Interface for Array of uint16s. More...

using	IUInt32Array = IArray< uint32_t >
	Interface for Array of uint32s. More...

using	IInt16Array = IArray< int16_t >
	Interface for Array of int16s. More...

using	IInt32Array = IArray< int32_t >
	Interface for Array of int32s. More...

using	IFloatArray = IArray< float >
	Interface for Array of floats. More...

using	IImage = ITensor

using	qasymm8_signed_t = int8_t
	8 bit signed quantized asymmetric scalar value More...

using	qasymm8_t = uint8_t
	8 bit quantized asymmetric scalar value More...

using	qsymm16_t = int16_t
	16 bit quantized symmetric scalar value More...

using	qasymm16_t = uint16_t
	16 bit quantized asymmetric scalar value More...

using	half = half_float::half
	16-bit floating point type More...

using	PermutationVector = Strides
	Permutation vector. More...

using	BiStrides = Coordinates
	Bidirectional strides. More...

using	PaddingSize = BorderSize
	Container for 2D padding size. More...

using	PaddingInfo = std::pair< uint32_t, uint32_t >
	Padding information as a pair of unsigned int start/end. More...

using	PaddingList = std::vector< PaddingInfo >
	List of padding information. More...

using	Multiples = std::vector< uint32_t >
	Information to produce a tiled version of a Tensor. More...

using	BBox = std::array< float, 4 >

using	LabelBBox = std::map< int, std::vector< BBox > >

using	CropInfo = Padding2D
	Class for holding information related to cropping. More...

using	UInt8Array = Array< uint8_t >
	Array of uint8s. More...

using	UInt16Array = Array< uint16_t >
	Array of uint16s. More...

using	UInt32Array = Array< uint32_t >
	Array of uint32s. More...

using	Int16Array = Array< int16_t >
	Array of int16s. More...

using	Int32Array = Array< int32_t >
	Array of int32s. More...

using	FloatArray = Array< float >
	Array of floats. More...

using	CLUInt8Array = CLArray< cl_uchar >
	OpenCL Array of uint8s. More...

using	CLUInt16Array = CLArray< cl_ushort >
	OpenCL Array of uint16s. More...

using	CLUInt32Array = CLArray< cl_uint >
	OpenCL Array of uint32s. More...

using	CLInt16Array = CLArray< cl_short >
	OpenCL Array of int16s. More...

using	CLInt32Array = CLArray< cl_int >
	OpenCL Array of int32s. More...

using	CLFloatArray = CLArray< cl_float >
	OpenCL Array of floats. More...

using	CLImage = CLTensor
	OpenCL Image. More...

using	CLEqual = CLComparisonStatic< ComparisonOperation::Equal >
	Basic function to run equal comparison. More...

using	CLNotEqual = CLComparisonStatic< ComparisonOperation::NotEqual >
	Basic function to run not equal comparison. More...

using	CLGreater = CLComparisonStatic< ComparisonOperation::Greater >
	Basic function to run greater comparison. More...

using	CLGreaterEqual = CLComparisonStatic< ComparisonOperation::GreaterEqual >
	Basic function to run greater-equal comparison. More...

using	CLLess = CLComparisonStatic< ComparisonOperation::Less >
	Basic function to run less comparison. More...

using	CLLessEqual = CLComparisonStatic< ComparisonOperation::LessEqual >
	Basic function to run less-equal comparison. More...

using	CLSoftmaxLayer = CLSoftmaxLayerGeneric< false >

using	CLLogSoftmaxLayer = CLSoftmaxLayerGeneric< true >

using	NEEqual = NEElementwiseComparisonStatic< ComparisonOperation::Equal >
	Basic function to run equal comparison. More...

using	NENotEqual = NEElementwiseComparisonStatic< ComparisonOperation::NotEqual >
	Basic function to run not equal comparison. More...

using	NEGreater = NEElementwiseComparisonStatic< ComparisonOperation::Greater >
	Basic function to run greater comparison. More...

using	NEGreaterEqual = NEElementwiseComparisonStatic< ComparisonOperation::GreaterEqual >
	Basic function to run greater-equal comparison. More...

using	NELess = NEElementwiseComparisonStatic< ComparisonOperation::Less >
	Basic function to run less comparison. More...

using	NELessEqual = NEElementwiseComparisonStatic< ComparisonOperation::LessEqual >
	Basic function to run less-equal comparison. More...

using	NERsqrtLayer = NEElementwiseUnaryLayer< ElementWiseUnary::RSQRT >

using	NEExpLayer = NEElementwiseUnaryLayer< ElementWiseUnary::EXP >

using	NENegLayer = NEElementwiseUnaryLayer< ElementWiseUnary::NEG >

using	NELogLayer = NEElementwiseUnaryLayer< ElementWiseUnary::LOG >

using	NEAbsLayer = NEElementwiseUnaryLayer< ElementWiseUnary::ABS >

using	NERoundLayer = NEElementwiseUnaryLayer< ElementWiseUnary::ROUND >

using	NESinLayer = NEElementwiseUnaryLayer< ElementWiseUnary::SIN >

using	NESoftmaxLayer = NESoftmaxLayerGeneric< false >

using	NELogSoftmaxLayer = NESoftmaxLayerGeneric< true >

using	INEKernel = ICPPKernel
	Common interface for all kernels implemented in Neon. More...

using	NEScheduler = Scheduler
	CPU Scheduler. More...

using	Image = Tensor
	Image. More...

using	MemoryMappings = std::map< IMemory *, size_t >
	A map of (handle, index/offset), where handle is the memory handle of the object to provide the memory for and index/offset is the buffer/offset from the pool that should be used. More...

using	GroupMappings = std::map< size_t, MemoryMappings >
	A map of the groups and memory mappings. More...

using	MemoryRequirements = experimental::MemoryRequirements

template<typename TensorType >
using	WorkspaceData = std::vector< WorkspaceDataElement< TensorType > >

using	qasymm8x8_t = uint8x8_t
	8 bit quantized asymmetric vector with 8 elements More...

using	qasymm8x8x2_t = uint8x8x2_t
	8 bit quantized asymmetric vector with 16 elements More...

using	qasymm8x8x3_t = uint8x8x3_t
	8 bit quantized asymmetric vector with 24 elements More...

using	qasymm8x8x4_t = uint8x8x4_t
	8 bit quantized asymmetric vector with 32 elements More...

using	qasymm8x16_t = uint8x16_t
	8 bit quantized asymmetric vector with 16 elements More...

using	qasymm8x8_signed_t = int8x8_t
	8 bit quantized signed asymmetric vector with 8 elements More...

using	qasymm8x8x2_signed_t = int8x8x2_t
	8 bit quantized signed asymmetric vector with 16 elements More...

using	qasymm8x8x3_signed_t = int8x8x3_t
	8 bit quantized signed asymmetric vector with 24 elements More...

using	qasymm8x8x4_signed_t = int8x8x4_t
	8 bit quantized signed asymmetric vector with 32 elements More...

using	qasymm8x16_signed_t = int8x16_t
	8 bit quantized signed asymmetric vector with 16 elements More...

using	qsymm8_t = int8_t
	8 bit quantized symmetric scalar value More...

using	qsymm16x8_t = int16x8_t
	16 bit quantized symmetric vector with 8 elements More...

using	qsymm16x8x2_t = int16x8x2_t
	16 bit quantized symmetric vector with 16 elements More...

using	OperatorType = opencl::ClGemm

using	Mutex = std::mutex
	Wrapper of Mutex data-object. More...

template<typename Mutex >
using	lock_guard = std::lock_guard< Mutex >
	Wrapper of lock_guard data-object. More...

template<typename Mutex >
using	unique_lock = std::unique_lock< Mutex >
	Wrapper of lock_guard data-object. More...

Enumerations
enum	CLVersion { CL10, CL11, CL12, CL20, CL30, UNKNOWN }
	Available OpenCL Version. More...

enum	CLKernelType { UNKNOWN, UNKNOWN, DEPTHWISE, DIRECT, ELEMENTWISE, GEMM, POOL, WINOGRAD }

enum	CPUModel { X, GENERIC, GENERIC_FP16, GENERIC_FP16_DOT, A53, A55r0, A55r1, A35, A73, A76, A510, X1, V1, A64FX, N1 }
	CPU models types. More...

enum	ErrorCode { OK, RUNTIME_ERROR, UNSUPPORTED_EXTENSION_USE }
	Available error codes. More...

enum	TensorType : int32_t { ACL_UNKNOWN = -1, ACL_SRC_DST = 0, ACL_SRC = 0, ACL_SRC_0 = 0, ACL_SRC_1 = 1, ACL_SRC_2 = 2, ACL_SRC_3 = 3, ACL_SRC_4 = 4, ACL_SRC_5 = 5, ACL_SRC_6 = 6, ACL_SRC_END = 6, ACL_DST = 30, ACL_DST_0 = 30, ACL_DST_1 = 31, ACL_DST_2 = 32, ACL_DST_END = 32, ACL_INT = 50, ACL_INT_0 = 50, ACL_INT_1 = 51, ACL_INT_2 = 52, ACL_INT_3 = 53, ACL_INT_4 = 54, ACL_SRC_VEC = 256, ACL_DST_VEC = 512, ACL_INT_VEC = 1024, ACL_BIAS = ACL_SRC_2, ACL_VEC_ROW_SUM = ACL_SRC_3, ACL_VEC_COL_SUM = ACL_SRC_4, ACL_SHIFTS = ACL_SRC_5, ACL_MULTIPLIERS = ACL_SRC_6, EXPERIMENTAL_ACL_POST_OP_ARG = 2048, EXPERIMENTAL_ACL_POST_OP_ARG_FIRST = EXPERIMENTAL_ACL_POST_OP_ARG, EXPERIMENTAL_ACL_POST_OP_ARG_LAST = EXPERIMENTAL_ACL_POST_OP_ARG_FIRST + 1024 }
	Memory type. More...

enum	GPUTarget { UNKNOWN = 0x101, GPU_ARCH_MASK = 0xF00, GPU_GENERATION_MASK = 0x0F0, MIDGARD = 0x100, BIFROST = 0x200, VALHALL = 0x300, T600 = 0x110, T700 = 0x120, T800 = 0x130, G71 = 0x210, G72 = 0x220, G51 = 0x221, G51BIG = 0x222, G51LIT = 0x223, G31 = 0x224, G76 = 0x230, G52 = 0x231, G52LIT = 0x232, G77 = 0x310, G57 = 0x311, G78 = 0x320, G68 = 0x321, G78AE = 0x330, G710 = 0x340, G610 = 0x341, G510 = 0x342, G310 = 0x343, G715 = 0x350, G615 = 0x351 }
	Available GPU Targets. More...

enum	DeviceType { NEON, CL }
	Device types. More...

enum	RoundingPolicy { TO_ZERO, TO_NEAREST_UP, TO_NEAREST_EVEN }
	Rounding method. More...

enum	Format { UNKNOWN, U8, S16, U16, S32, U32, BFLOAT16, F16, F32, UV88, RGB888, RGBA8888, YUV444, YUYV422, NV12, NV21, IYUV, UYVY422 }
	Image colour formats. More...

enum	DataType { UNKNOWN, U8, S8, QSYMM8, QASYMM8, QASYMM8_SIGNED, QSYMM8_PER_CHANNEL, U16, S16, QSYMM16, QASYMM16, U32, S32, U64, S64, BFLOAT16, F16, F32, F64, SIZET }
	Available data types. More...

enum	SamplingPolicy { CENTER, TOP_LEFT }
	Available Sampling Policies. More...

enum	DataLayout { UNKNOWN, NCHW, NHWC, NCDHW, NDHWC }
	[DataLayout enum definition] More...

enum	DataLayoutDimension { CHANNEL, HEIGHT, WIDTH, DEPTH, BATCHES }
	[DataLayout enum definition] More...

enum	ConvolutionMethod { GEMM, GEMM_CONV2D, DIRECT, INDIRECT, WINOGRAD, FFT }
	Available ConvolutionMethod. More...

enum	DepthwiseConvolutionFunction { OPTIMIZED, GENERIC }
	Available DepthwiseConvolutionFunction. More...

enum	DeconvolutionMethod { GEMM, DIRECT, UPSCALE_CONV2D }
	Available DeconvolutionMethod. More...

enum	FuseBatchNormalizationType { CONVOLUTION, DEPTHWISECONVOLUTION }
	Available FuseBatchNormalizationType. More...

enum	PaddingMode { CONSTANT, REFLECT, SYMMETRIC }
	Padding mode to use for PadLayer. More...

enum	ComparisonOperation { Equal, NotEqual, Greater, GreaterEqual, Less, LessEqual }
	Supported comparison operations. More...

enum	BorderMode { UNDEFINED, CONSTANT, REPLICATE }
	Methods available to handle borders. More...

enum	ConvertPolicy { WRAP, SATURATE }
	Policy to handle integer overflow. More...

enum	InterpolationPolicy { NEAREST_NEIGHBOR, BILINEAR, AREA }
	Interpolation method. More...

enum	BilinearInterpolation { BILINEAR_OLD_NEW, BILINEAR_SCHARR }
	Bilinear Interpolation method used by LKTracker. More...

enum	Channel { UNKNOWN, C0, C1, C2, C3, R, G, B, A, Y, U, V }
	Available channels. More...

enum	ReductionOperation { ARG_IDX_MAX, ARG_IDX_MIN, MEAN_SUM, PROD, SUM_SQUARE, SUM, MIN, MAX }
	Available reduction operations. More...

enum	ArithmeticOperation { ADD, SUB, DIV, MIN, MAX, SQUARED_DIFF, POWER, PRELU }
	Available element-wise operations. More...

enum	ElementWiseUnary { RSQRT, EXP, NEG, LOG, ABS, SIN, ROUND, LOGICAL_NOT }
	Available element wise unary operations. More...

enum	BitwiseOperation { AND, NOT, OR, XOR }
	Available bitwise operations. More...

enum	NormType { IN_MAP_1D, IN_MAP_2D, CROSS_MAP }
	The normalization type used for the normalization layer. More...

enum	DimensionRoundingType { FLOOR, CEIL }
	Dimension rounding type when down-scaling on CNNs. More...

enum	PoolingType { MAX, AVG, L2 }
	Available pooling types. More...

enum	NMSType { LINEAR, GAUSSIAN, ORIGINAL }
	Available non maxima suppression types. More...

enum	DetectionOutputLayerCodeType { CORNER, CENTER_SIZE, CORNER_SIZE, TF_CENTER }
	Available Detection Output code types. More...

enum	WeightFormat { UNSPECIFIED = 0x1, ANY = 0x2, OHWI = 0x100100, OHWIo2 = 0x100200, OHWIo4 = 0x100400, OHWIo8 = 0x100800, OHWIo16 = 0x101000, OHWIo32 = 0x102000, OHWIo64 = 0x104000, OHWIo128 = 0x108000, OHWIo4i2 = 0x200400, OHWIo4i2_bf16 = 0x200410, OHWIo8i2 = 0x200800, OHWIo8i2_bf16 = 0x200810, OHWIo16i2 = 0x201000, OHWIo16i2_bf16 = 0x201010, OHWIo32i2 = 0x202000, OHWIo32i2_bf16 = 0x202010, OHWIo64i2 = 0x204000, OHWIo64i2_bf16 = 0x204010, OHWIo4i4 = 0x400400, OHWIo4i4_bf16 = 0x400410, OHWIo8i4 = 0x400800, OHWIo8i4_bf16 = 0x400810, OHWIo16i4 = 0x401000, OHWIo16i4_bf16 = 0x401010, OHWIo32i4 = 0x402000, OHWIo32i4_bf16 = 0x402010, OHWIo64i4 = 0x404000, OHWIo64i4_bf16 = 0x404010, OHWIo2i8 = 0x800200, OHWIo4i8 = 0x800400, OHWIo8i8 = 0x800800, OHWIo16i8 = 0x801000, OHWIo32i8 = 0x802000, OHWIo64i8 = 0x804000 }
	Memory layouts for the weights tensor. More...

enum	GEMMLowpOutputStageType { NONE, QUANTIZE_DOWN, QUANTIZE_DOWN_FIXEDPOINT, QUANTIZE_DOWN_FLOAT }
	GEMMLowp output stage type. More...

enum	CLTunerMode { EXHAUSTIVE, NORMAL, RAPID }
	< OpenCL tuner modes More...

enum	CLGEMMKernelType { NATIVE, RESHAPED, RESHAPED_ONLY_RHS, RESHAPED_ONLY_RHS_MMUL }
	OpenCL GEMM kernel types. More...

enum	CLBackendType { Native, Clvk }
	List the possible OpenCL backends. More...

enum	FFTDirection { Forward, Inverse }
	FFT direction to use. More...

enum	MappingType { BLOBS, OFFSETS }
	Mapping type. More...

enum	StatusCode { Success = AclSuccess, RuntimeError = AclRuntimeError, OutOfMemory = AclOutOfMemory, Unimplemented = AclUnimplemented, UnsupportedTarget = AclUnsupportedTarget, InvalidTarget = AclInvalidTarget, InvalidArgument = AclInvalidArgument, UnsupportedConfig = AclUnsupportedConfig, InvalidObjectState = AclInvalidObjectState }

enum	Target { Cpu = AclTarget::AclCpu, GpuOcl = AclTarget::AclGpuOcl }

enum	ExecutionMode { FastRerun = AclPreferFastRerun, FastStart = AclPreferFastStart }

enum	ImportMemoryType { HostPtr = AclImportMemoryType::AclHostPtr }

enum	CLImage2DType { ReadOnly, WriteOnly }
	OpenCL Image2D types. More...

enum	LogicalOperation { Unknown, And, Or, Not }
	List of supported logical operations. More...

Functions
std::string	get_cl_type_from_data_type (const DataType &dt)
	Translates a tensor data type to the appropriate OpenCL type. More...

std::string	get_cl_promoted_type_from_data_type (const DataType &dt)
	Translates a tensor data type to the appropriate OpenCL promoted type. More...

std::string	get_cl_unsigned_type_from_element_size (size_t element_size)
	Translates the element size to an unsigned integer data type. More...

std::string	get_cl_signed_type_from_element_size (size_t element_size)
	Translates the element size to an signed integer data type. More...

std::string	get_cl_select_type_from_data_type (const DataType &dt)
	Translates a tensor data type to the appropriate OpenCL select type. More...

std::string	get_cl_dot8_acc_type_from_data_type (const DataType &dt)
	Translates a tensor data type to the appropriate OpenCL dot8 accumulator type. More...

std::string	get_data_size_from_data_type (const DataType &dt)
	Get the size of a data type in number of bits. More...

GPUTarget	get_target_from_device (const cl::Device &device)
	Helper function to get the GPU target from CL device. More...

CLVersion	get_cl_version (const cl::Device &device)
	Helper function to get the highest OpenCL version supported. More...

size_t	get_cl_image_pitch_alignment (const cl::Device &device)
	Helper function to get the cl_image pitch alignment in pixels. More...

bool	get_cl_non_uniform_work_group_supported (const cl::Device &device)
	Helper function to check whether non-uniform work group is supported. More...

bool	device_supports_extension (const cl::Device &device, const char *extension_name)
	Helper function to check whether a given extension is supported. More...

bool	fp16_supported (const cl::Device &device)
	Helper function to check whether the cl_khr_fp16 extension is supported. More...

bool	arm_non_uniform_workgroup_supported (const cl::Device &device)
	Helper function to check whether the arm_non_uniform_work_group_size extension is supported. More...

bool	dot8_supported (const cl::Device &device)
	Helper function to check whether the cl_arm_integer_dot_product_int8 extension is supported. More...

bool	dot8_acc_supported (const cl::Device &device)
	Helper function to check whether the cl_arm_integer_dot_product_accumulate_int8 extension is supported. More...

bool	cl_winograd_convolution_layer_supported (const Size2D &output_tile, const Size2D &kernel_size, DataLayout data_layout)
	This function checks if the Winograd configuration (defined through the output tile, kernel size and the data layout) is supported on OpenCL. More...

size_t	preferred_vector_width (const cl::Device &device, DataType dt)
	Helper function to get the preferred native vector width size for built-in scalar types that can be put into vectors. More...

bool	preferred_dummy_work_items_support (const cl::Device &device)
	Helper function to check if "dummy work-items" are preferred to have a power of two NDRange In case dummy work-items is enabled, it is OpenCL kernel responsibility to check if the work-item is out-of range or not. More...

bool	image2d_from_buffer_supported (const cl::Device &device)
	Helper function to check whether the cl_khr_image2d_from_buffer extension is supported. More...

cl::Kernel	create_kernel (const CLCompileContext &ctx, const std::string &kernel_name, const std::set< std::string > &build_opts=std::set< std::string >())
	Creates an opencl kernel using a compile context. More...

cl::NDRange	create_lws_hint_parallel_implementations (unsigned int input_dimension, unsigned int vector_size)
	Creates a suitable LWS hint object for parallel implementations. More...

bool	get_wbsm_support_info (const cl::Device &device)

void	set_wbsm (cl::Kernel &kernel, cl_int wbsm_hint)

bool	export_to_cl_image (const ITensorInfo *tensor)

void	set_unroll_with_pragma (CLBuildOptions &built_opts, std::initializer_list< int > values)

bool	arm_matrix_multiply_supported (const cl::Device &device)
	Helper function to check whether the cl_arm_matrix_multiply extension is supported. More...

bool	opencl_is_available ()
	Check if OpenCL is available. More...

template<typename T >
bool	operator== (const Dimensions< T > &lhs, const Dimensions< T > &rhs)
	Check that given dimensions are equal. More...

template<typename T >
bool	operator!= (const Dimensions< T > &lhs, const Dimensions< T > &rhs)
	Check that given dimensions are not equal. More...

template<typename... T>
void	ignore_unused (T &&...)
	Ignores unused arguments. More...

Status	create_error (ErrorCode error_code, std::string msg)
	Creates an error containing the error message. More...

Status	create_error_msg (ErrorCode error_code, const char func, const char file, int line, const char *msg)
	Creates an error and the error message. More...

void	throw_error (Status err)
	Throw an std::runtime_error. More...

const std::string &	string_from_target (GPUTarget target)
	Translates a given gpu device target to string. More...

GPUTarget	get_target_from_name (const std::string &device_name)
	Helper function to get the GPU target from a device name. More...

GPUTarget	get_arch_from_target (GPUTarget target)
	Helper function to get the GPU arch. More...

template<typename... Args>
bool	gpu_target_is_in (GPUTarget target_to_check, GPUTarget target, Args... targets)
	Helper function to check whether a gpu target is equal to the provided targets. More...

bool	gpu_target_is_in (GPUTarget target_to_check, GPUTarget target)
	Variant of gpu_target_is_in for comparing two targets. More...

template<typename L , typename... Ts>
void	execute_window_loop (const Window &w, L &&lambda_function, Ts &&... iterators)
	Iterate through the passed window, automatically adjusting the iterators and calling the lambda_functino for each element. More...

template<typename T >
void	permute (Dimensions< T > &dimensions, const PermutationVector &perm)
	Permutes given Dimensions according to a permutation vector. More...

void	permute (TensorShape &shape, const PermutationVector &perm)
	Permutes given TensorShape according to a permutation vector. More...

ValidRegion	calculate_valid_region_scale (const ITensorInfo &src_info, const TensorShape &dst_shape, InterpolationPolicy interpolate_policy, SamplingPolicy sampling_policy, bool border_undefined)
	Helper function to calculate the Valid Region for Scale. More...

Coordinates	index2coords (const TensorShape &shape, int index)
	Convert a linear index into n-dimensional coordinates. More...

int	coords2index (const TensorShape &shape, const Coordinates &coord)
	Convert n-dimensional coordinates into a linear index. More...

const std::map< DataLayout, std::vector< DataLayoutDimension > > &	get_layout_map ()
	Returns a static map used to find an index or dimension based on a data layout. More...

size_t	get_data_layout_dimension_index (const DataLayout &data_layout, const DataLayoutDimension &data_layout_dimension)
	Get the index of the given dimension. More...

DataLayoutDimension	get_index_data_layout_dimension (const DataLayout &data_layout, const size_t index)
	Get the DataLayoutDimension of a given index and layout. More...

Size2D	compute_winograd_convolution_tiles (const Size2D &in_dims, const Size2D &kernel_size, const Size2D &output_tile_size, const PadStrideInfo &conv_info)
	Calculate the number of output tiles required by Winograd Convolution layer. More...

template<typename T >
T	wrap_around (T x, T m)
	Wrap-around a number within the range 0 <= x < m. More...

Coordinates &	convert_negative_axis (Coordinates &coords, int max_value)
	Convert negative coordinates to positive in the range [0, num_dims_input]. More...

int	adjust_down (int required, int available, int step)
	Decrease `required` in steps of `step` until it's less than `available`. More...

int	adjust_up (int required, int available, int step)
	Increase `required` in steps of `step` until it's greater than `available`. More...

bool	operator== (const QuantizationInfo &lhs, const QuantizationInfo &rhs)
	Check whether two quantization info are equal. More...

bool	operator!= (const QuantizationInfo &lhs, const QuantizationInfo &rhs)
	Check whether two quantization info are not equal. More...

bool	operator== (const UniformQuantizationInfo &lhs, const UniformQuantizationInfo &rhs)
	Check whether two quantization info are equal. More...

bool	operator!= (const UniformQuantizationInfo &lhs, const UniformQuantizationInfo &rhs)
	Check whether two quantization info are not equal. More...

template<typename INFO_TYPE >
uint8_t	quantize_qasymm8 (float value, const INFO_TYPE &qinfo, RoundingPolicy rounding_policy=RoundingPolicy::TO_NEAREST_UP)
	Quantize a value given an unsigned 8-bit asymmetric quantization scheme. More...

template<typename INFO_TYPE >
int8_t	quantize_qasymm8_signed (float value, const INFO_TYPE &qinfo, RoundingPolicy rounding_policy=RoundingPolicy::TO_NEAREST_UP)
	Quantize a value given a signed 8-bit asymmetric quantization scheme. More...

int8_t	quantize_qsymm8 (float value, const QuantizationInfo &qinfo)
	Quantize a value given a 8-bit symmetric quantization scheme. More...

int8_t	quantize_qsymm8_per_channel (float value, const QuantizationInfo &qinfo, size_t channel_id=0)
	Quantize a value given a 8-bit symmetric per channel quantization scheme. More...

template<typename INFO_TYPE >
float	dequantize_qasymm8 (uint8_t value, const INFO_TYPE &qinfo)
	Dequantize a value given an unsigned 8-bit asymmetric quantization scheme. More...

template<typename INFO_TYPE >
float	dequantize_qasymm8_signed (int8_t value, const INFO_TYPE &qinfo)
	Dequantize a value given a signed 8-bit asymmetric quantization scheme. More...

float	dequantize (uint8_t value, float scale, int32_t offset)
	Dequantize a value given an 8-bit asymmetric quantization scheme. More...

float	dequantize_qsymm8 (int8_t value, const UniformQuantizationInfo &qinfo)
	Dequantize a value given a 8-bit symmetric quantization scheme. More...

qasymm8_t	qasymm8_hard_swish (qasymm8_t in, const UniformQuantizationInfo &qi_in, const UniformQuantizationInfo &qi_out)

qasymm8_signed_t	qasymm8_signed_hard_swish (qasymm8_signed_t in, const UniformQuantizationInfo &qi_in, const UniformQuantizationInfo &qi_out)

qasymm8_t	qasymm8_leaky_relu (qasymm8_t in, const UniformQuantizationInfo &qi_in, const UniformQuantizationInfo &qi_out, float alpha)

qasymm8_t	qasymm8_logistic (qasymm8_t in, const UniformQuantizationInfo &qi_in, const UniformQuantizationInfo &qi_out)

qasymm8_signed_t	qasymm8_signed_logistic (qasymm8_signed_t in, const UniformQuantizationInfo &qi_in, const UniformQuantizationInfo &qi_out)

float	dequantize (int8_t value, float scale)
	Dequantize a value given a 8-bit symmetric quantization scheme. More...

float	dequantize (int16_t value, float scale)
	Dequantize a value given a 16-bit symmetric quantization scheme. More...

float	dequantize (uint16_t value, float scale, int32_t offset)
	Dequantize a value given a 16-bit asymmetric quantization scheme. More...

int16_t	quantize_qsymm16 (float value, const UniformQuantizationInfo &qinfo, RoundingPolicy rounding_policy=RoundingPolicy::TO_NEAREST_UP)
	Quantize a value given a 16-bit symmetric quantization scheme. More...

float	dequantize_qsymm16 (int16_t value, const UniformQuantizationInfo &qinfo)
	Dequantize a value given a 16-bit symmetric quantization scheme. More...

int16_t	quantize_qsymm16 (float value, const QuantizationInfo &qinfo)
	Quantize a value given a 16-bit symmetric quantization scheme. More...

float	dequantize_qsymm16 (int16_t value, const QuantizationInfo &qinfo)
	Dequantize a value given a 16-bit symmetric quantization scheme. More...

uint16_t	quantize_qasymm16 (float value, const UniformQuantizationInfo &qinfo, RoundingPolicy rounding_policy=RoundingPolicy::TO_NEAREST_UP)
	Quantize a value given a 16-bit asymmetric quantization scheme. More...

float	dequantize_qasymm16 (uint16_t value, const UniformQuantizationInfo &qinfo)
	Dequantize a value given a 16-bit asymmetric quantization scheme. More...

uint16_t	quantize_qasymm16 (float value, const QuantizationInfo &qinfo)
	Quantize a value given a 16-bit asymmetric quantization scheme. More...

float	dequantize_qasymm16 (uint16_t value, const QuantizationInfo &qinfo)
	Dequantize a value given a 16-bit asymmetric quantization scheme. More...

UniformQuantizationInfo	compute_requantization_scale_offset (const UniformQuantizationInfo &uqinfo_in, const UniformQuantizationInfo &uqinfo_out)

int	round (float x, RoundingPolicy rounding_policy)
	Return a rounded value of x. More...

bool	operator== (const TensorInfo &lhs, const TensorInfo &rhs)
	Check whether two tensor info are equal. More...

bool	operator== (const ValidRegion &lhs, const ValidRegion &rhs)

int	interleave_by (const WeightFormat wf)

int	block_by (const WeightFormat wf)

bool	is_fixed_format (const WeightFormat &wf)

bool	is_fixed_format_fast_math (const WeightFormat &wf)

template<typename S , typename T >
constexpr auto	DIV_CEIL (S val, T m) -> decltype((val+m - 1)/m)
	Calculate the rounded up quotient of val / m. More...

template<typename S , typename T >
auto	ceil_to_multiple (S value, T divisor) -> decltype(((value+divisor - 1)/divisor) *divisor)
	Computes the smallest number larger or equal to value that is a multiple of divisor. More...

template<typename S , typename T >
auto	floor_to_multiple (S value, T divisor) -> decltype((value/divisor) *divisor)
	Computes the largest number smaller or equal to value that is a multiple of divisor. More...

std::string	read_file (const std::string &filename, bool binary)
	Load an entire file in memory. More...

size_t	data_size_from_type (DataType data_type)
	The size in bytes of the data type. More...

size_t	pixel_size_from_format (Format format)
	The size in bytes of the pixel format. More...

size_t	element_size_from_data_type (DataType dt)
	The size in bytes of the data type. More...

DataType	data_type_from_format (Format format)
	Return the data type used by a given single-planar pixel format. More...

int	plane_idx_from_channel (Format format, Channel channel)
	Return the plane index of a given channel given an input format. More...

int	channel_idx_from_format (Format format, Channel channel)
	Return the channel index of a given channel given an input format. More...

size_t	num_planes_from_format (Format format)
	Return the number of planes for a given format. More...

size_t	num_channels_from_format (Format format)
	Return the number of channels for a given single-planar pixel format. More...

DataType	get_promoted_data_type (DataType dt)
	Return the promoted data type of a given data type. More...

std::tuple< PixelValue, PixelValue >	get_min_max (DataType dt)
	Compute the mininum and maximum values a data type can take. More...

bool	has_format_horizontal_subsampling (Format format)
	Return true if the given format has horizontal subsampling. More...

bool	has_format_vertical_subsampling (Format format)
	Return true if the given format has vertical subsampling. More...

TensorShape	adjust_odd_shape (const TensorShape &shape, Format format)
	Adjust tensor shape size if width or height are odd for a given multi-planar format. More...

TensorShape	calculate_subsampled_shape (const TensorShape &shape, Format format, Channel channel=Channel::UNKNOWN)
	Calculate subsampled shape for a given format and channel. More...

template<typename T >
void	permute_strides (Dimensions< T > &dimensions, const PermutationVector &perm)
	Permutes the given dimensions according the permutation vector. More...

PadStrideInfo	calculate_same_pad (TensorShape input_shape, TensorShape weights_shape, PadStrideInfo conv_info, DataLayout data_layout=DataLayout::NCHW, const Size2D &dilation=Size2D(1u, 1u), const DimensionRoundingType &rounding_type=DimensionRoundingType::FLOOR)
	Calculate padding requirements in case of SAME padding. More...

std::pair< unsigned int, unsigned int >	deconvolution_output_dimensions (unsigned int in_width, unsigned int in_height, unsigned int kernel_width, unsigned int kernel_height, const PadStrideInfo &pad_stride_info)
	Returns expected width and height of the deconvolution's output tensor. More...

std::pair< unsigned int, unsigned int >	scaled_dimensions (int width, int height, int kernel_width, int kernel_height, const PadStrideInfo &pad_stride_info, const Size2D &dilation=Size2D(1U, 1U))
	Returns expected width and height of output scaled tensor depending on dimensions rounding mode. More...

std::pair< int, int >	scaled_dimensions_signed (int width, int height, int kernel_width, int kernel_height, const PadStrideInfo &pad_stride_info)
	Returns calculated width and height of output scaled tensor depending on dimensions rounding mode. More...

std::tuple< int, int, int >	scaled_3d_dimensions_signed (int width, int height, int depth, int kernel_width, int kernel_height, int kernel_depth, const Pooling3dLayerInfo &pool3d_info)
	Returns calculated width, height and depth of output scaled tensor depending on dimensions rounding mode. More...

bool	needs_serialized_reduction (ReductionOperation op, DataType dt, unsigned int axis)
	Check if the given reduction operation should be handled in a serial way. More...

QuantizationInfo	get_softmax_output_quantization_info (DataType input_type, bool is_log)
	Returns output quantization information for softmax layer. More...

std::pair< int32_t, int32_t >	get_quantized_activation_min_max (ActivationLayerInfo act_info, DataType data_type, UniformQuantizationInfo oq_info)
	Returns a pair of minimum and maximum values for a quantized activation. More...

const std::string &	string_from_format (Format format)
	Convert a tensor format into a string. More...

const std::string &	string_from_channel (Channel channel)
	Convert a channel identity into a string. More...

const std::string &	string_from_data_layout (DataLayout dl)
	Convert a data layout identity into a string. More...

const std::string &	string_from_data_type (DataType dt)
	Convert a data type identity into a string. More...

const std::string &	string_from_activation_func (ActivationLayerInfo::ActivationFunction act)
	Translates a given activation function to a string. More...

const std::string &	string_from_interpolation_policy (InterpolationPolicy policy)
	Translates a given interpolation policy to a string. More...

const std::string &	string_from_border_mode (BorderMode border_mode)
	Translates a given border mode policy to a string. More...

const std::string &	string_from_norm_type (NormType type)
	Translates a given normalization type to a string. More...

const std::string &	string_from_pooling_type (PoolingType type)
	Translates a given pooling type to a string. More...

bool	is_pool_region_entirely_outside_input (const PoolingLayerInfo &info)
	Check if the pool region is entirely outside the input tensor. More...

bool	is_pool_3d_region_entirely_outside_input (const Pooling3dLayerInfo &info)
	Check if the 3d pool region is entirely outside the input tensor. More...

bool	is_symmetric (const Padding3D &info)
	Check if the 3D padding is symmetric i.e. More...

const std::string &	string_from_gemmlowp_output_stage (GEMMLowpOutputStageType output_stage)
	Translates a given GEMMLowp output stage to a string. More...

std::string	string_from_pixel_value (const PixelValue &value, const DataType data_type)
	Convert a PixelValue to a string, represented through the specific data type. More...

DataType	data_type_from_name (const std::string &name)
	Convert a string to DataType. More...

std::unordered_map< const ITensorInfo *, PaddingSize >	get_padding_info (std::initializer_list< const ITensorInfo *> infos)
	Stores padding information before configuring a kernel. More...

std::unordered_map< const ITensorInfo *, PaddingSize >	get_padding_info (std::initializer_list< const ITensor *> tensors)
	Stores padding information before configuring a kernel. More...

bool	has_padding_changed (const std::unordered_map< const ITensorInfo *, PaddingSize > &padding_map)
	Check if the previously stored padding info has changed after configuring a kernel. More...

inline ::std::istream &	operator>> (::std::istream &stream, DataType &data_type)
	Input Stream operator for DataType. More...

std::string	lower_string (const std::string &val)
	Lower a given string. More...

std::string	upper_string (const std::string &val)
	Raise a given string to upper case. More...

bool	is_data_type_float (DataType dt)
	Check if a given data type is of floating point type. More...

bool	is_data_type_quantized (DataType dt)
	Check if a given data type is of quantized type. More...

bool	is_data_type_quantized_asymmetric (DataType dt)
	Check if a given data type is of asymmetric quantized type. More...

bool	is_data_type_quantized_asymmetric_signed (DataType dt)
	Check if a given data type is of asymmetric quantized signed type. More...

bool	is_data_type_quantized_symmetric (DataType dt)
	Check if a given data type is of symmetric quantized type. More...

bool	is_data_type_quantized_per_channel (DataType dt)
	Check if a given data type is of per channel type. More...

std::string	float_to_string_with_full_precision (float val)
	Create a string with the float in full precision. More...

size_t	num_of_elements_in_range (const float start, const float end, const float step)
	Returns the number of elements required to go from start to end with the wanted step. More...

template<typename T >
bool	check_value_range (T val, DataType dt, QuantizationInfo qinfo=QuantizationInfo())
	Returns true if the value can be represented by the given data type. More...

unsigned int	adjust_vec_size (unsigned int vec_size, size_t dim0)
	Returns the adjusted vector size in case it is less than the input's first dimension, getting rounded down to its closest valid vector size. More...

std::string	cpu_impl_dt (const DataType &data_type)
	Returns the suffix string of CPU kernel implementation names based on the given data type. More...

template<typename... Ts>
arm_compute::Status	error_on_nullptr (const char function, const char file, const int line, Ts &&... pointers)
	Create an error if one of the pointers is a nullptr. More...

arm_compute::Status	error_on_mismatching_windows (const char function, const char file, const int line, const Window &full, const Window &win)
	Return an error if the passed window is invalid. More...

arm_compute::Status	error_on_invalid_subwindow (const char function, const char file, const int line, const Window &full, const Window &sub)
	Return an error if the passed subwindow is invalid. More...

arm_compute::Status	error_on_window_not_collapsable_at_dimension (const char function, const char file, const int line, const Window &full, const Window &window, const int dim)
	Return an error if the window can't be collapsed at the given dimension. More...

arm_compute::Status	error_on_coordinates_dimensions_gte (const char function, const char file, const int line, const Coordinates &pos, unsigned int max_dim)
	Return an error if the passed coordinates have too many dimensions. More...

arm_compute::Status	error_on_window_dimensions_gte (const char function, const char file, const int line, const Window &win, unsigned int max_dim)
	Return an error if the passed window has too many dimensions. More...

template<typename T , typename... Ts>
arm_compute::Status	error_on_mismatching_dimensions (const char function, const char file, int line, const Dimensions< T > &dim1, const Dimensions< T > &dim2, Ts &&... dims)
	Return an error if the passed dimension objects differ. More...

template<typename... Ts>
arm_compute::Status	error_on_tensors_not_even (const char function, const char file, int line, const Format &format, const ITensor *tensor1, Ts... tensors)
	Return an error if the passed tensor objects are not even. More...

template<typename... Ts>
arm_compute::Status	error_on_tensors_not_subsampled (const char function, const char file, int line, const Format &format, const TensorShape &shape, const ITensor *tensor1, Ts... tensors)
	Return an error if the passed tensor objects are not sub-sampled. More...

template<typename... Ts>
arm_compute::Status	error_on_mismatching_shapes (const char function, const char file, const int line, const ITensorInfo tensor_info_1, const ITensorInfo tensor_info_2, Ts... tensor_infos)
	Return an error if the passed two tensor infos have different shapes from the given dimension. More...

template<typename... Ts>
arm_compute::Status	error_on_mismatching_shapes (const char function, const char file, const int line, const ITensor tensor_1, const ITensor tensor_2, Ts... tensors)
	Return an error if the passed two tensors have different shapes from the given dimension. More...

template<typename... Ts>
arm_compute::Status	error_on_mismatching_shapes (const char function, const char file, const int line, unsigned int upper_dim, const ITensorInfo tensor_info_1, const ITensorInfo tensor_info_2, Ts... tensor_infos)
	Return an error if the passed two tensors have different shapes from the given dimension. More...

template<typename... Ts>
arm_compute::Status	error_on_mismatching_shapes (const char function, const char file, const int line, unsigned int upper_dim, const ITensor tensor_1, const ITensor tensor_2, Ts... tensors)
	Return an error if the passed two tensors have different shapes from the given dimension. More...

template<typename... Ts>
arm_compute::Status	error_on_mismatching_data_layouts (const char function, const char file, const int line, const ITensorInfo *tensor_info, Ts... tensor_infos)
	Return an error if the passed tensor infos have different data layouts. More...

template<typename... Ts>
arm_compute::Status	error_on_mismatching_data_layouts (const char function, const char file, const int line, const ITensor *tensor, Ts... tensors)
	Return an error if the passed tensors have different data layouts. More...

template<typename... Ts>
arm_compute::Status	error_on_mismatching_data_types (const char function, const char file, const int line, const ITensorInfo *tensor_info, Ts... tensor_infos)
	Return an error if the passed two tensor infos have different data types. More...

template<typename... Ts>
arm_compute::Status	error_on_mismatching_data_types (const char function, const char file, const int line, const ITensor *tensor, Ts... tensors)
	Return an error if the passed two tensors have different data types. More...

template<typename... Ts>
arm_compute::Status	error_on_mismatching_quantization_info (const char function, const char file, const int line, const ITensorInfo tensor_info_1, const ITensorInfo tensor_info_2, Ts... tensor_infos)
	Return an error if the passed tensor infos have different asymmetric quantized data types or different quantization info. More...

template<typename... Ts>
arm_compute::Status	error_on_mismatching_quantization_info (const char function, const char file, const int line, const ITensor tensor_1, const ITensor tensor_2, Ts... tensors)
	Return an error if the passed tensor have different asymmetric quantized data types or different quantization info. More...

template<typename T , typename F , typename... Fs>
void	error_on_format_not_in (const char function, const char file, const int line, const T *object, F &&format, Fs &&... formats)
	Throw an error if the format of the passed tensor/multi-image does not match any of the formats provided. More...

template<typename T , typename... Ts>
arm_compute::Status	error_on_data_type_not_in (const char function, const char file, const int line, const ITensorInfo *tensor_info, T &&dt, Ts &&... dts)
	Return an error if the data type of the passed tensor info does not match any of the data types provided. More...

template<typename T , typename... Ts>
arm_compute::Status	error_on_data_type_not_in (const char function, const char file, const int line, const ITensor *tensor, T &&dt, Ts &&... dts)
	Return an error if the data type of the passed tensor does not match any of the data types provided. More...

template<typename T , typename... Ts>
arm_compute::Status	error_on_data_layout_not_in (const char function, const char file, const int line, const ITensorInfo *tensor_info, T &&dl, Ts &&... dls)
	Return an error if the data layout of the passed tensor info does not match any of the data layouts provided. More...

template<typename T , typename... Ts>
arm_compute::Status	error_on_data_layout_not_in (const char function, const char file, const int line, const ITensor *tensor, T &&dl, Ts &&... dls)
	Return an error if the data layout of the passed tensor does not match any of the data layout provided. More...

template<typename T , typename... Ts>
arm_compute::Status	error_on_data_type_channel_not_in (const char function, const char file, const int line, const ITensorInfo *tensor_info, size_t num_channels, T &&dt, Ts &&... dts)
	Return an error if the data type or the number of channels of the passed tensor info does not match any of the data types and number of channels provided. More...

template<typename T , typename... Ts>
arm_compute::Status	error_on_data_type_channel_not_in (const char function, const char file, const int line, const ITensor *tensor, size_t num_channels, T &&dt, Ts &&... dts)
	Return an error if the data type or the number of channels of the passed tensor does not match any of the data types and number of channels provided. More...

arm_compute::Status	error_on_unsupported_fp16 (const char function, const char file, const int line, const ITensorInfo *tensor_info, bool is_fp16_supported)
	Return an error if the data type of the passed tensor info is FP16 and FP16 extension is not supported by the device. More...

arm_compute::Status	error_on_unsupported_fp16 (const char function, const char file, const int line, const ITensor *tensor, bool is_fp16_supported)
	Return an error if the data type of the passed tensor is FP16 and FP16 extension is not supported by the device. More...

arm_compute::Status	error_on_tensor_not_2d (const char function, const char file, const int line, const ITensor *tensor)
	Return an error if the tensor is not 2D. More...

arm_compute::Status	error_on_tensor_not_2d (const char function, const char file, const int line, const ITensorInfo *tensor)
	Return an error if the tensor info is not 2D. More...

template<typename T , typename... Ts>
arm_compute::Status	error_on_channel_not_in (const char function, const char file, const int line, T cn, T &&channel, Ts &&... channels)
	Return an error if the channel is not in channels. More...

arm_compute::Status	error_on_channel_not_in_known_format (const char function, const char file, const int line, Format fmt, Channel cn)
	Return an error if the channel is not in format. More...

arm_compute::Status	error_on_unconfigured_kernel (const char function, const char file, const int line, const IKernel *kernel)
	Return an error if the kernel is not configured. More...

arm_compute::Status	error_on_invalid_subtensor (const char function, const char file, const int line, const TensorShape &parent_shape, const Coordinates &coords, const TensorShape &shape)
	Return an error if if the coordinates and shape of the subtensor are within the parent tensor. More...

arm_compute::Status	error_on_invalid_subtensor_valid_region (const char function, const char file, const int line, const ValidRegion &parent_valid_region, const ValidRegion &valid_region)
	Return an error if the valid region of a subtensor is not inside the valid region of the parent tensor. More...

std::string	build_information ()
	Returns the arm_compute library build information. More...

void	swap (Window &lhs, Window &rhs)

bool	operator== (const Window &lhs, const Window &rhs)

Coordinates	convert_window_coord_to_position (const Window &w, const Coordinates &offset)
	Convert an offset in window steps into absolute coordinates. More...

template<typename L >
WindowIterator< L >	create_window_iterator (const Window &w, const Coordinates &start, const Coordinates &end, L &&lambda_function)
	Create a WindowIterator object. More...

arm_compute::DataLayout	data_layout_from_name (const std::string &name)
	Converts a string to a strong types enumeration DataLayout. More...

inline ::std::istream &	operator>> (::std::istream &stream, arm_compute::DataLayout &data_layout)
	Input Stream operator for DataLayout. More...

std::tuple< cl::Context, cl::Device, cl_int >	create_opencl_context_and_device (CLBackendType cl_backend_type)
	This function creates an OpenCL context and a device. More...

void	schedule_kernel_on_ctx (CLRuntimeContext ctx, ICLKernel kernel, bool flush=true)
	Schedules a kernel using the context if not nullptr else uses the legacy scheduling flow. More...

cl::Platform	select_preferable_platform (CLBackendType cl_backend_type)
	This function selects the OpenCL platform based on the backend type. More...

CLTunerMode	tuner_mode_from_name (const std::string &name)
	Converts a string to a strong types enumeration CLTunerMode. More...

inline ::std::istream &	operator>> (::std::istream &stream, CLTunerMode &tuner_mode)
	Input Stream operator for CLTunerMode. More...

void	save_program_cache_to_file (const std::string &filename="cache.bin")
	This function saves opencl kernels library to a file. More...

void	restore_program_cache_from_file (const std::string &filename="cache.bin")
	This function loads prebuilt opencl kernels from a file. More...

IContext *	get_internal (AclContext ctx)
	Extract internal representation of a Context. More...

IOperator *	get_internal (AclOperator op)
	Extract internal representation of an Operator. More...

IQueue *	get_internal (AclQueue queue)
	Extract internal representation of a Queue. More...

ITensorV2 *	get_internal (AclTensor tensor)
	Extract internal representation of a Tensor. More...

TensorPack *	get_internal (AclTensorPack pack)
	Extract internal representation of a TensoPack. More...

cl::Image2D	create_image2d_from_buffer (const cl::Context &ctx, const cl::Buffer &buffer, const TensorShape &shape2d, DataType data_type, size_t image_row_pitch, CLImage2DType image_type)
	Create a cl::Image2D object from an OpenCL buffer. More...

arm_compute::Status	error_on_unsupported_int64_base_atomics (const char function, const char file, const int line)
	Return an error if int64_base_atomics extension is not supported by the device. More...

cl::NDRange	get_default_lws_for_type (CLKernelType kernel_type, cl::NDRange gws)

void	enqueue (cl::CommandQueue &queue, ICLKernel &kernel, const Window &window, const cl::NDRange &lws_hint=CLKernelLibrary::get().default_ndrange(), bool use_dummy_work_items=false)
	Add the kernel to the command queue with the given window. More...

Status	error_on_unsupported_cpu_fp16 (const char function, const char file, const int line, const ITensorInfo *tensor_info)
	Return an error if the data type of the passed tensor info is FP16 and FP16 support is not compiled in. More...

Status	error_on_unsupported_cpu_bf16 (const char function, const char file, const int line, const ITensorInfo *tensor_info)
	Return an error if the data type of the passed tensor info is BFLOAT16 and BFLOAT16 support is not compiled in. More...

Status	error_on_unsupported_cpu_fp16 (const char function, const char file, const int line, const ITensor *tensor)
	Return an error if the data type of the passed tensor is FP16 and FP16 support is not compiled in. More...

Status	error_on_unsupported_cpu_bf16 (const char function, const char file, const int line, const ITensor *tensor)
	Return an error if the data type of the passed tensor is BFLOAT16 and BFLOAT16 support is not compiled in. More...

bool	auto_init_if_empty (ITensorInfo &info, const TensorShape &shape, int num_channels, DataType data_type, QuantizationInfo quantization_info=QuantizationInfo())
	Auto initialize the tensor info (shape, number of channels and data type) if the current assignment is empty. More...

bool	auto_init_if_empty (ITensorInfo &info_sink, const ITensorInfo &info_source)
	Auto initialize the tensor info using another tensor info. More...

bool	set_shape_if_empty (ITensorInfo &info, const TensorShape &shape)
	Set the shape to the specified value if the current assignment is empty. More...

bool	set_format_if_unknown (ITensorInfo &info, Format format)
	Set the format, data type and number of channels to the specified value if the current data type is unknown. More...

bool	set_data_type_if_unknown (ITensorInfo &info, DataType data_type)
	Set the data type and number of channels to the specified value if the current data type is unknown. More...

bool	set_data_layout_if_unknown (ITensorInfo &info, DataLayout data_layout)
	Set the data layout to the specified value if the current data layout is unknown. More...

bool	set_quantization_info_if_empty (ITensorInfo &info, QuantizationInfo quantization_info)
	Set the quantization info to the specified value if the current quantization info is empty and the data type of asymmetric quantized type. More...

int	offset_int_vec (int offset)

template<typename TensorType >
WorkspaceData< TensorType >	manage_workspace (const experimental::MemoryRequirements &mem_reqs, MemoryGroup &mgroup, ITensorPack &run_pack)

template<typename TensorType >
WorkspaceData< TensorType >	manage_workspace (const experimental::MemoryRequirements &mem_reqs, MemoryGroup &mgroup, ITensorPack &run_pack, ITensorPack &prep_pack)

template<typename TensorType >
void	release_prepare_tensors (WorkspaceData< TensorType > &workspace, ITensorPack &prep_pack)

template<typename TensorType >
void	release_temporaries (const experimental::MemoryRequirements &mem_reqs, WorkspaceData< TensorType > &workspace)
	Utility function to release tensors with lifetime marked as Prepare. More...

unsigned int	get_normalization_dimension_index (DataLayout layout, const NormalizationLayerInfo &info)
	Calculate the normalization dimension index for a given normalization type. More...

template<typename T , typename... Ts>
Strides	compute_strides (const ITensorInfo &info, T stride_x, Ts &&... fixed_strides)
	Create a strides object based on the provided strides and the tensor dimensions. More...

template<typename... Ts>
Strides	compute_strides (const ITensorInfo &info)
	Create a strides object based on the tensor dimensions. More...

unsigned int	get_next_power_two (unsigned int x)
	Given an integer value, this function returns the next power of two. More...

Window	calculate_max_window (const ValidRegion &valid_region, const Steps &steps, bool skip_border, BorderSize border_size)

Window	calculate_max_window (const TensorShape &shape, const Steps &steps, bool skip_border, BorderSize border_size)

Window	calculate_max_enlarged_window (const ValidRegion &valid_region, const Steps &steps, BorderSize border_size)

Window	calculate_max_window_horizontal (const ValidRegion &valid_region, const Steps &steps, bool skip_border, BorderSize border_size)

std::pair< Window, size_t >	calculate_squashed_or_max_window (const ITensorInfo &src0, const ITensorInfo &src1)

std::pair< Window, size_t >	calculate_squashed_or_max_window (const ITensorInfo &src)

template<typename... Ts>
bool	update_window_and_padding (Window &win, Ts &&... patterns)
	Update window and padding size for each of the access patterns. More...

template<typename... Ts>
ValidRegion	intersect_valid_regions (const Ts &... regions)
	Intersect multiple valid regions. More...

void	colorconvert_rgb_to_rgbx (const void __restrict input, void __restrict output, const Window &win)
	Convert RGB to RGBX. More...

void	colorconvert_rgb_to_u8 (const void __restrict input, void __restrict output, const Window &win)
	Convert RGB to U8. More...

void	colorconvert_rgbx_to_rgb (const void input, void output, const Window &win)
	Convert RGBX to RGB. More...

template<bool yuyv, bool alpha>
void	colorconvert_yuyv_to_rgb (const void __restrict input, void __restrict output, const Window &win)
	Convert YUYV to RGB. More...

template<bool uv, bool alpha>
void	colorconvert_nv12_to_rgb (const void __restrict input, void __restrict output, const Window &win)
	Convert NV12 to RGB. More...

template<bool alpha>
void	colorconvert_iyuv_to_rgb (const void __restrict input, void __restrict output, const Window &win)
	Convert IYUV to RGB. More...

template<bool yuyv>
void	colorconvert_yuyv_to_nv12 (const void __restrict input, void __restrict output, const Window &win)
	Convert YUYV to NV12. More...

void	colorconvert_iyuv_to_nv12 (const void __restrict input, void __restrict output, const Window &win)
	Convert IYUV to NV12. More...

template<bool uv>
void	colorconvert_nv12_to_iyuv (const void __restrict input, void __restrict output, const Window &win)
	Convert NV12 to IYUV. More...

template<bool yuyv>
void	colorconvert_yuyv_to_iyuv (const void __restrict input, void __restrict output, const Window &win)
	Convert YUYV to IYUV. More...

template<bool uv>
void	colorconvert_nv12_to_yuv4 (const void __restrict input, void __restrict output, const Window &win)
	Convert NV12 to YUV4. More...

void	colorconvert_iyuv_to_yuv4 (const void __restrict input, void __restrict output, const Window &win)
	Convert IYUV to YUV4. More...

template<bool alpha>
void	colorconvert_rgb_to_nv12 (const void __restrict input, void __restrict output, const Window &win)
	Convert RGB to NV12. More...

template<bool alpha>
void	colorconvert_rgb_to_iyuv (const void __restrict input, void __restrict output, const Window &win)
	Convert RGB to IYUV. More...

template<bool alpha>
void	colorconvert_rgb_to_yuv4 (const void __restrict input, void __restrict output, const Window &win)
	Convert RGB to YUV4. More...

template<typename T >
void	run_reverse (const Window &window, const ITensor input, const ITensor axis, ITensor *output)

uint8x16_t	vmlaq_qasymm8 (qasymm8x16_t vd, float32x4_t vs, float32x4_t vo)
	Perform a multiply-accumulate on all 16 components of a QASYMM8 vector. More...

int8x16_t	vmlaq_qasymm8_signed (qasymm8x16_signed_t vd, float32x4_t vs, float32x4_t vo)
	Perform a multiply-accumulate on all 16 components of a QASYMM8_SIGNED vector. More...

uint8x16_t	finalize_quantization (int32x4x4_t &in_s32, int result_fixedpoint_multiplier, int32_t result_shift, int32x4_t result_offset_after_shift_s32, uint8x16_t min_u8, uint8x16_t max_u8, bool is_bounded_relu)
	Performs final quantization step on 16 elements. More...

int8x16_t	finalize_quantization (int32x4x4_t &in_s32, int result_fixedpoint_multiplier, int32_t result_shift, int32x4_t result_offset_after_shift_s32, int8x16_t min_s8, int8x16_t max_s8, bool is_bounded_relu)
	Performs final quantization step on 16 elements. More...

int8x16_t	finalize_quantization_symm (int32x4x4_t &in_s32, const int32x4x4_t &result_fixedpoint_multiplier, const int32x4x4_t &result_shift, const int32x4_t &result_offset_after_shift_s32, const int8x16_t &min_s8, const int8x16_t &max_s8, const bool is_bounded_relu)
	Performs final quantization step on 16 elements for symmetric quantization. More...

uint8_t	finalize_quantization (int32_t in_value, int result_fixedpoint_multiplier, int32_t result_shift, int32_t result_offset_after_shift_s32, uint8_t min_u8, uint8_t max_u8, bool is_bounded_relu)
	Performs final quantization step on single element. More...

int8_t	finalize_quantization (int32_t in_value, int result_fixedpoint_multiplier, int32_t result_shift, int32_t result_offset_after_shift_s32, int8_t min_s8, int8_t max_s8, bool is_bounded_relu)
	Performs final quantization step on single element. More...

float32x4x2_t	vdequantize (const uint8x8_t &qv, const UniformQuantizationInfo &qi)
	Dequantize a neon vector holding 8 quantized values. More...

float32x4x2_t	vdequantize (const int8x8_t &qv, const UniformQuantizationInfo &qi)
	Dequantize a neon vector holding 8 singed quantized values. More...

float32x4x4_t	vdequantize (const uint8x16_t &qv, const UniformQuantizationInfo &qi)
	Dequantize a neon vector holding 16 quantized values. More...

float32x4x4_t	vdequantize (const int8x16_t &qv, const UniformQuantizationInfo &qi)
	Dequantize a neon vector holding 16 signed quantized values. More...

float32x4x4_t	vdequantize (const uint8x16_t &qv, float scale, int32_t offset)
	Dequantize following an asymmetric quantization scheme a neon vector holding 16 quantized values. More...

float32x4x4_t	vdequantize (const int8x16_t &qv, float scale, int32_t offset)
	Dequantize a vector of 16 values stored as signed asymmetric. More...

float32x4x4_t	vdequantize (const int8x16_t &qv, const float32x4x4_t vscale)
	Dequantize following symmetric quantization scheme a neon vector holding 16 quantized values. More...

float32x4x4_t	vdequantize (const int8x16_t &qv, float scale)
	Dequantize following a symmetric quantization scheme a neon vector holding 16 quantized values. More...

uint8x8_t	vquantize (const float32x4x2_t &qv, const UniformQuantizationInfo &qi)
	Quantize a neon vector holding 8 floating point values. More...

int8x8_t	vquantize_signed (const float32x4x2_t &qv, const UniformQuantizationInfo &qi)
	Quantize a neon vector holding 8 floating point values. More...

int32x4x4_t	vquantize_internal (const float32x4x4_t &qv, float scale, int32_t offset)

uint8x16_t	vquantize (const float32x4x4_t &qv, const UniformQuantizationInfo &qi)
	Quantize a neon vector holding 16 floating point values. More...

int8x16_t	vquantize_signed (const float32x4x4_t &qv, const UniformQuantizationInfo &qi)
	Signed quantize a neon vector holding 16 floating point values. More...

uint16x8x2_t	vquantize_qasymm16 (const float32x4x4_t &qv, const UniformQuantizationInfo &qi)
	Quantize to QASYMM16 a neon vector holding 16 floating point values. More...

template<RoundingPolicy round_policy = RoundingPolicy::TO_ZERO>
qasymm8x16_signed_t	vmlaq_qasymm8 (qasymm8x16_signed_t vd, float32x4_t vs, float32x4_t vo)

float32x4x2_t	vmax2q_f32 (float32x4x2_t a, float32x4x2_t b)
	Compute lane-by-lane maximum between elements of a float vector with 4x2 elements. More...

float32x4_t	vfloorq_f32 (float32x4_t val)
	Calculate floor of a vector. More...

float32x4_t	vroundq_rte_f32 (float32x4_t val)
	Calculate round value of a vector to nearest with ties to even. More...

float32x2_t	vinvsqrt_f32 (float32x2_t x)
	Calculate inverse square root. More...

float32x4_t	vinvsqrtq_f32 (float32x4_t x)
	Calculate inverse square root. More...

float32x2_t	vinv_f32 (float32x2_t x)
	Calculate reciprocal. More...

float32x4_t	vinvq_f32 (float32x4_t x)
	Calculate reciprocal. More...

float32x4_t	vtaylor_polyq_f32 (float32x4_t x, const std::array< float32x4_t, 8 > &coeffs)
	Perform a 7th degree polynomial approximation using Estrin's method. More...

float32x4_t	vexpq_f32 (float32x4_t x)
	Calculate exponential. More...

float32x4_t	verfq_f32 (float32x4_t x)
	Calculate error function. More...

float32x4_t	vlogq_f32 (float32x4_t x)
	Calculate logarithm. More...

float32x4_t	vtanhq_f32 (float32x4_t val)
	Calculate hyperbolic tangent. More...

float32x4_t	vpowq_f32 (float32x4_t val, float32x4_t n)
	Calculate n power of a number. More...

int32x4_t	rounding_divide_by_pow2 (int32x4_t x, int32x4_t exponent)
	Round to the nearest division by a power-of-two using exponent. More...

int32x4_t	rounding_divide_by_pow2 (int32x4_t x, int exponent)
	Round to the nearest division by a power-of-two using exponent. More...

int32_t	rounding_divide_by_pow2 (int32_t x, int exponent)
	Round to the nearest division by a power-of-two using exponent. More...

float32x4x4_t	convert_uint8x16_to_float32x4x4 (const uint8x16_t &in)
	Converts from uint8x16 to float32x4x4_t. More...

float32x4x4_t	convert_int8x16_to_float32x4x4 (const int8x16_t &in)
	Converts from int8x16 to float32x4x4_t. More...

template<typename T >
float32x4x4_t	convert_to_float32x4x4 (const T &in)
	Converts to float32x4x4_t from the specified templated 16 elements vectors. More...

void	convert_float32x4x3_to_uint8x8x3 (const float32x4x3_t &in1, const float32x4x3_t &in2, uint8x8x3_t &out)
	Converts from two float32x4x3_t to just one uint8x8x3_t. More...

void	convert_float32x4x4_to_uint8x16 (const float32x4x4_t &in, uint8x16_t &out)
	Converts from two float32x4x4_t to just one uint8x16_t. More...

void	convert_float32x4x4_to_int8x16 (const float32x4x4_t &in, int8x16_t &out)
	Converts from float32x4x4_t to just one int8x16_t. More...

template<typename float_vec_type , typename int_vec_type >
int_vec_type	convert_float_to_int (const float_vec_type &in)
	Converts from float vector to integer vector. More...

template<typename float_vec_type , typename int_vec_type >
float_vec_type	convert_int_to_float (const int_vec_type &in)
	Converts from integer vector to float vector. More...

float32x4_t	vsinq_f32 (float32x4_t val)
	Calculate sine. More...

float32x2_t	vsin_f32 (float32x2_t val)
	Calculate sine. More...

float	vreduce (const float32x4_t &v)
	Reduce a vector to be a scalar by accumulating all lanes in the vector. More...

template<>
float32x4x4_t	convert_to_float32x4x4 (const uint8x16_t &in)

template<>
float32x4x4_t	convert_to_float32x4x4 (const int8x16_t &in)

template<>
uint8x16_t	convert_float_to_int< float32x4x4_t, uint8x16_t > (const float32x4x4_t &in)

template<>
float32x4x4_t	convert_int_to_float< float32x4x4_t, uint8x16_t > (const uint8x16_t &in)

template<>
int8x16_t	convert_float_to_int< float32x4x4_t, int8x16_t > (const float32x4x4_t &in)

template<>
float32x4x4_t	convert_int_to_float< float32x4x4_t, int8x16_t > (const int8x16_t &in)

template<bool is_bounded_relu>
int16x8_t	finalize_quantization_int16 (int32x4x2_t &in_s32, int result_fixedpoint_multiplier, int32_t result_shift, int16x8_t min_s16, int16x8_t max_s16)
	Performs final quantization step on 8 signed 16-bit elements. More...

template<bool is_bounded_relu>
int16_t	finalize_quantization_int16 (int32_t in_value, int result_fixedpoint_multiplier, int32_t result_shift, int16_t min_s16, int16_t max_s16)
	Performs final quantization step on single signed 16-bit element. More...

float32x4x2_t	vdequantize_int16 (const int16x8_t &qv, float scale)
	Dequantize a neon vector holding 8 16-bit quantized values. More...

int16x8_t	vquantize_int16 (const float32x4x2_t &qv, float scale)
	Quantize a neon vector holding 8 floating point values. More...

float32x4x4_t	vdequantize (const int16x8x2_t &qv, const UniformQuantizationInfo &qi)
	Dequantize a neon vector holding 16 16-bit quantized values. More...

qsymm16x8x2_t	vquantize_qsymm16 (const float32x4x4_t &qv, const UniformQuantizationInfo &qi)
	Quantize a neon vector holding 16 floating point values. More...

int32x4x2_t	multiply_by_quantized_multiplier_2row (int32x4x2_t input, int32_t qmul, int32_t shift)
	Multiply a neon vector using quantized multiplier and shift. More...

Status	validate (const ITensorInfo scores_in, const ITensorInfo boxes_in, const ITensorInfo batch_splits_in, const ITensorInfo scores_out, const ITensorInfo boxes_out, const ITensorInfo classes, const ITensorInfo batch_splits_out, const ITensorInfo keeps, const ITensorInfo *keeps_size, const BoxNMSLimitInfo info)

inline ::std::istream &	operator>> (::std::istream &is, BorderMode &mode)
	Formatted input of the BorderMode type. More...

template<typename T >
std::string	to_string_if_not_null (T *arg)
	Formatted output if arg is not null. More...

template<typename T >
std::string	to_string (const T &val)
	Fallback method: try to use std::to_string: More...

template<typename T >
::std::ostream &	operator<< (::std::ostream &os, const std::vector< T > &args)
	Formatted output of a vector of objects. More...

template<typename T >
std::string	to_string (const std::vector< T > &args)
	Formatted output of a vector of objects. More...

template<typename T >
inline ::std::ostream &	operator<< (::std::ostream &os, const Dimensions< T > &dimensions)
	Formatted output of the Dimensions type. More...

inline ::std::ostream &	operator<< (::std::ostream &os, const RoundingPolicy &rounding_policy)
	Formatted output of the RoundingPolicy type. More...

inline ::std::ostream &	operator<< (::std::ostream &os, const WeightsInfo &weights_info)
	Formatted output of the WeightsInfo type. More...

inline ::std::ostream &	operator<< (::std::ostream &os, const ROIPoolingLayerInfo &pool_info)
	Formatted output of the ROIPoolingInfo type. More...

std::string	to_string (const ROIPoolingLayerInfo &pool_info)
	Formatted output of the ROIPoolingInfo type. More...

inline ::std::ostream &	operator<< (::std::ostream &os, const GEMMKernelInfo &gemm_info)
	Formatted output of the GEMMKernelInfo type. More...

inline ::std::ostream &	operator<< (::std::ostream &os, const GEMMLHSMatrixInfo &gemm_info)
	Formatted output of the GEMMLHSMatrixInfo type. More...

inline ::std::ostream &	operator<< (::std::ostream &os, const GEMMRHSMatrixInfo &gemm_info)
	Formatted output of the GEMMRHSMatrixInfo type. More...

std::string	to_string (const GEMMRHSMatrixInfo &gemm_info)
	Formatted output of the GEMMRHSMatrixInfo type. More...

std::string	to_string (const GEMMLHSMatrixInfo &gemm_info)
	Formatted output of the GEMMLHSMatrixInfo type. More...

std::string	to_string (const GEMMKernelInfo &gemm_info)
	Formatted output of the GEMMKernelInfo type. More...

inline ::std::ostream &	operator<< (::std::ostream &os, const BoundingBoxTransformInfo &bbox_info)
	Formatted output of the BoundingBoxTransformInfo type. More...

std::string	to_string (const BoundingBoxTransformInfo &bbox_info)
	Formatted output of the BoundingBoxTransformInfo type. More...

inline ::std::ostream &	operator<< (::std::ostream &os, const ComputeAnchorsInfo &anchors_info)
	Formatted output of the ComputeAnchorsInfo type. More...

std::string	to_string (const ComputeAnchorsInfo &anchors_info)
	Formatted output of the ComputeAnchorsInfo type. More...

inline ::std::ostream &	operator<< (::std::ostream &os, const GenerateProposalsInfo &proposals_info)
	Formatted output of the GenerateProposalsInfo type. More...

std::string	to_string (const GenerateProposalsInfo &proposals_info)
	Formatted output of the GenerateProposalsInfo type. More...

inline ::std::ostream &	operator<< (::std::ostream &os, const QuantizationInfo &qinfo)
	Formatted output of the QuantizationInfo type. More...

std::string	to_string (const QuantizationInfo &quantization_info)
	Formatted output of the QuantizationInfo type. More...

inline ::std::ostream &	operator<< (::std::ostream &os, const ActivationLayerInfo::ActivationFunction &act_function)
	Formatted output of the activation function type. More...

std::string	to_string (const arm_compute::ActivationLayerInfo &info)
	Formatted output of the activation function info type. More...

inline ::std::ostream &	operator<< (::std::ostream &os, const ActivationLayerInfo *info)
	Formatted output of the activation function info. More...

std::string	to_string (const arm_compute::ActivationLayerInfo::ActivationFunction &function)
	Formatted output of the activation function type. More...

inline ::std::ostream &	operator<< (::std::ostream &os, const NormType &norm_type)
	Formatted output of the NormType type. More...

std::string	to_string (const arm_compute::NormalizationLayerInfo &info)
	Formatted output of NormalizationLayerInfo. More...

inline ::std::ostream &	operator<< (::std::ostream &os, const NormalizationLayerInfo &info)
	Formatted output of NormalizationLayerInfo. More...

inline ::std::ostream &	operator<< (::std::ostream &os, const PoolingType &pool_type)
	Formatted output of the PoolingType type. More...

inline ::std::ostream &	operator<< (::std::ostream &os, const PoolingLayerInfo &info)
	Formatted output of PoolingLayerInfo. More...

std::string	to_string (const RoundingPolicy &rounding_policy)
	Formatted output of RoundingPolicy. More...

inline ::std::ostream &	operator<< (::std::ostream &os, const DataLayout &data_layout)
	[Print DataLayout type] More...

std::string	to_string (const arm_compute::DataLayout &data_layout)
	Formatted output of the DataLayout type. More...

inline ::std::ostream &	operator<< (::std::ostream &os, const DataLayoutDimension &data_layout_dim)
	[Print DataLayout type] More...

inline ::std::ostream &	operator<< (::std::ostream &os, const DataType &data_type)
	Formatted output of the DataType type. More...

std::string	to_string (const arm_compute::DataType &data_type)
	Formatted output of the DataType type. More...

inline ::std::ostream &	operator<< (::std::ostream &os, const Format &format)
	Formatted output of the Format type. More...

std::string	to_string (const Format &format)
	Formatted output of the Format type. More...

inline ::std::ostream &	operator<< (::std::ostream &os, const Channel &channel)
	Formatted output of the Channel type. More...

std::string	to_string (const Channel &channel)
	Formatted output of the Channel type. More...

inline ::std::ostream &	operator<< (::std::ostream &os, const BorderMode &mode)
	Formatted output of the BorderMode type. More...

inline ::std::ostream &	operator<< (::std::ostream &os, const BorderSize &border)
	Formatted output of the BorderSize type. More...

inline ::std::ostream &	operator<< (::std::ostream &os, const PaddingList &padding)
	Formatted output of the PaddingList type. More...

inline ::std::ostream &	operator<< (::std::ostream &os, const Multiples &multiples)
	Formatted output of the Multiples type. More...

inline ::std::ostream &	operator<< (::std::ostream &os, const InterpolationPolicy &policy)
	Formatted output of the InterpolationPolicy type. More...

inline ::std::ostream &	operator<< (::std::ostream &os, const SamplingPolicy &policy)
	Formatted output of the SamplingPolicy type. More...

inline ::std::ostream &	operator<< (std::ostream &os, const ITensorInfo *info)
	Formatted output of the ITensorInfo type. More...

inline ::std::ostream &	operator<< (::std::ostream &os, const TensorInfo &info)
	Formatted output of the const TensorInfo& type. More...

std::string	to_string (const TensorInfo &info)
	Formatted output of the const TensorInfo& type. More...

std::string	to_string (const ITensorInfo &info)
	Formatted output of the const ITensorInfo& type. More...

std::string	to_string (const ITensorInfo *info)
	Formatted output of the const ITensorInfo* type. More...

std::string	to_string (ITensorInfo *info)
	Formatted output of the ITensorInfo* type. More...

std::string	to_string (const ITensor *tensor)
	Formatted output of the ITensorInfo type obtained from const ITensor* type. More...

std::string	to_string (ITensor *tensor)
	Formatted output of the ITensorInfo type obtained from the ITensor* type. More...

std::string	to_string (ITensor &tensor)
	Formatted output of the ITensorInfo type obtained from the ITensor& type. More...

template<typename T >
std::string	to_string (const Dimensions< T > &dimensions)
	Formatted output of the Dimensions type. More...

std::string	to_string (const Strides &stride)
	Formatted output of the Strides type. More...

std::string	to_string (const TensorShape &shape)
	Formatted output of the TensorShape type. More...

std::string	to_string (const Coordinates &coord)
	Formatted output of the Coordinates type. More...

inline ::std::ostream &	operator<< (::std::ostream &os, const GEMMReshapeInfo &info)
	Formatted output of the GEMMReshapeInfo type. More...

inline ::std::ostream &	operator<< (::std::ostream &os, const GEMMInfo &info)
	Formatted output of the GEMMInfo type. More...

inline ::std::ostream &	operator<< (::std::ostream &os, const Window::Dimension &dim)
	Formatted output of the Window::Dimension type. More...

inline ::std::ostream &	operator<< (::std::ostream &os, const Window &win)
	Formatted output of the Window type. More...

std::string	to_string (const WeightsInfo &info)
	Formatted output of the WeightsInfo type. More...

std::string	to_string (const GEMMReshapeInfo &info)
	Formatted output of the GEMMReshapeInfo type. More...

std::string	to_string (const GEMMInfo &info)
	Formatted output of the GEMMInfo type. More...

std::string	to_string (const Window::Dimension &dim)
	Formatted output of the Window::Dimension type. More...

std::string	to_string (const Window &win)
	Formatted output of the Window& type. More...

std::string	to_string (Window *win)
	Formatted output of the Window* type. More...

inline ::std::ostream &	operator<< (::std::ostream &os, const Rectangle &rect)
	Formatted output of the Rectangle type. More...

inline ::std::ostream &	operator<< (::std::ostream &os, const PaddingMode &mode)
	Formatted output of the PaddingMode type. More...

std::string	to_string (const PaddingMode &mode)
	Formatted output of the PaddingMode type. More...

inline ::std::ostream &	operator<< (::std::ostream &os, const PadStrideInfo &pad_stride_info)
	Formatted output of the PadStrideInfo type. More...

std::string	to_string (const PadStrideInfo &pad_stride_info)
	Formatted output of the PadStrideInfo type. More...

std::string	to_string (const BorderMode &mode)
	Formatted output of the BorderMode type. More...

std::string	to_string (const BorderSize &border)
	Formatted output of the BorderSize type. More...

std::string	to_string (const PaddingList &padding)
	Formatted output of the PaddingList type. More...

std::string	to_string (const Multiples &multiples)
	Formatted output of the Multiples type. More...

std::string	to_string (const InterpolationPolicy &policy)
	Formatted output of the InterpolationPolicy type. More...

std::string	to_string (const SamplingPolicy &policy)
	Formatted output of the SamplingPolicy type. More...

inline ::std::ostream &	operator<< (::std::ostream &os, const ConvertPolicy &policy)
	Formatted output of the ConvertPolicy type. More...

std::string	to_string (const ConvertPolicy &policy)

inline ::std::ostream &	operator<< (::std::ostream &os, const ArithmeticOperation &op)
	Formatted output of the ArithmeticOperation type. More...

std::string	to_string (const ArithmeticOperation &op)
	Formatted output of the Arithmetic Operation. More...

inline ::std::ostream &	operator<< (::std::ostream &os, const ReductionOperation &op)
	Formatted output of the Reduction Operations. More...

std::string	to_string (const ReductionOperation &op)
	Formatted output of the Reduction Operations. More...

inline ::std::ostream &	operator<< (::std::ostream &os, const ComparisonOperation &op)
	Formatted output of the Comparison Operations. More...

inline ::std::ostream &	operator<< (::std::ostream &os, const ElementWiseUnary &op)
	Formatted output of the Elementwise unary Operations. More...

std::string	to_string (const ComparisonOperation &op)
	Formatted output of the Comparison Operations. More...

std::string	to_string (const ElementWiseUnary &op)
	Formatted output of the Elementwise unary Operations. More...

std::string	to_string (const NormType &type)
	Formatted output of the Norm Type. More...

std::string	to_string (const PoolingType &type)
	Formatted output of the Pooling Type. More...

std::string	to_string (const PoolingLayerInfo &info)
	Formatted output of the Pooling Layer Info. More...

inline ::std::ostream &	operator<< (::std::ostream &os, const Size3D &size)
	Formatted output of the Size3D type. More...

std::string	to_string (const Size3D &type)
	Formatted output of the Size3D type. More...

inline ::std::ostream &	operator<< (::std::ostream &os, const Padding3D &padding3d)
	Formatted output of the Padding3D type. More...

std::string	to_string (const Padding3D &padding3d)
	Converts a Padding3D to string. More...

inline ::std::ostream &	operator<< (::std::ostream &os, const DimensionRoundingType &rounding_type)
	Formatted output of the DimensionRoundingType type. More...

inline ::std::ostream &	operator<< (::std::ostream &os, const Pooling3dLayerInfo &info)
	Formatted output of the Pooling 3d Layer Info. More...

std::string	to_string (const Pooling3dLayerInfo &info)
	Formatted output of the Pooling 3d Layer Info. More...

std::string	to_string (const PriorBoxLayerInfo &info)
	Formatted output of the PriorBoxLayerInfo. More...

inline ::std::ostream &	operator<< (::std::ostream &os, const Size2D &size)
	Formatted output of the Size2D type. More...

std::string	to_string (const Size2D &type)
	Formatted output of the Size2D type. More...

inline ::std::ostream &	operator<< (::std::ostream &os, const ConvolutionMethod &conv_method)
	Formatted output of the ConvolutionMethod type. More...

std::string	to_string (const ConvolutionMethod &conv_method)
	Formatted output of the ConvolutionMethod type. More...

inline ::std::ostream &	operator<< (::std::ostream &os, const GPUTarget &gpu_target)
	Formatted output of the GPUTarget type. More...

std::string	to_string (const GPUTarget &gpu_target)
	Formatted output of the GPUTarget type. More...

inline ::std::ostream &	operator<< (::std::ostream &os, const DetectionWindow &detection_window)
	Formatted output of the DetectionWindow type. More...

inline ::std::ostream &	operator<< (::std::ostream &os, const DetectionOutputLayerCodeType &detection_code)
	Formatted output of the DetectionOutputLayerCodeType type. More...

std::string	to_string (const DetectionOutputLayerCodeType &detection_code)
	Formatted output of the DetectionOutputLayerCodeType type. More...

inline ::std::ostream &	operator<< (::std::ostream &os, const DetectionOutputLayerInfo &detection_info)
	Formatted output of the DetectionOutputLayerInfo type. More...

std::string	to_string (const DetectionOutputLayerInfo &detection_info)
	Formatted output of the DetectionOutputLayerInfo type. More...

inline ::std::ostream &	operator<< (::std::ostream &os, const DetectionPostProcessLayerInfo &detection_info)
	Formatted output of the DetectionPostProcessLayerInfo type. More...

std::string	to_string (const DetectionPostProcessLayerInfo &detection_info)
	Formatted output of the DetectionPostProcessLayerInfo type. More...

std::string	to_string (const DetectionWindow &detection_window)
	Formatted output of the DetectionWindow type. More...

inline ::std::ostream &	operator<< (::std::ostream &os, const PriorBoxLayerInfo &info)
	Formatted output of PriorBoxLayerInfo. More...

inline ::std::ostream &	operator<< (::std::ostream &os, const WinogradInfo &info)
	Formatted output of the WinogradInfo type. More...

std::string	to_string (const WinogradInfo &type)

std::string	to_string (const CLTunerMode val)
	Convert a CLTunerMode value to a string. More...

std::string	to_string (CLGEMMKernelType val)
	Converts a CLGEMMKernelType to string. More...

inline ::std::ostream &	operator<< (::std::ostream &os, const CLTunerMode &val)
	[Print CLTunerMode type] More...

inline ::std::ostream &	operator<< (::std::ostream &os, const ConvolutionInfo &conv_info)
	Formatted output of the ConvolutionInfo type. More...

std::string	to_string (const ConvolutionInfo &info)
	Converts a ConvolutionInfo to string. More...

inline ::std::ostream &	operator<< (::std::ostream &os, const FullyConnectedLayerInfo &layer_info)
	Formatted output of the FullyConnectedLayerInfo type. More...

std::string	to_string (const FullyConnectedLayerInfo &info)
	Converts a FullyConnectedLayerInfo to string. More...

inline ::std::ostream &	operator<< (::std::ostream &os, const GEMMLowpOutputStageType &gemm_type)
	Formatted output of the GEMMLowpOutputStageType type. More...

std::string	to_string (const GEMMLowpOutputStageType &gemm_type)
	Converts a GEMMLowpOutputStageType to string. More...

inline ::std::ostream &	operator<< (::std::ostream &os, const GEMMLowpOutputStageInfo &gemm_info)
	Formatted output of the GEMMLowpOutputStageInfo type. More...

std::string	to_string (const GEMMLowpOutputStageInfo &gemm_info)
	Converts a GEMMLowpOutputStageInfo to string. More...

inline ::std::ostream &	operator<< (::std::ostream &os, const Conv2dInfo &conv_info)
	Formatted output of the Conv2dInfo type. More...

std::string	to_string (const Conv2dInfo &conv_info)
	Converts a Conv2dInfo to string. More...

inline ::std::ostream &	operator<< (::std::ostream &os, const PixelValue &pixel_value)
	Formatted output of the PixelValue type. More...

std::string	to_string (const PixelValue &pixel_value)
	Converts a PixelValue to string. More...

inline ::std::ostream &	operator<< (::std::ostream &os, const ScaleKernelInfo &scale_info)
	Formatted output of the ScaleKernelInfo type. More...

std::string	to_string (const ScaleKernelInfo &scale_info)
	Converts a ScaleKernelInfo to string. More...

inline ::std::ostream &	operator<< (::std::ostream &os, const FFTDirection &fft_dir)
	Formatted output of the FFTDirection type. More...

std::string	to_string (const FFTDirection &fft_dir)
	Converts a FFT1DInfo to string. More...

inline ::std::ostream &	operator<< (::std::ostream &os, const FFT1DInfo &fft1d_info)
	Formatted output of the FFT1DInfo type. More...

std::string	to_string (const FFT1DInfo &fft1d_info)
	Converts a FFT1DInfo to string. More...

inline ::std::ostream &	operator<< (::std::ostream &os, const FFT2DInfo &fft2d_info)
	Formatted output of the FFT2DInfo type. More...

std::string	to_string (const FFT2DInfo &fft2d_info)
	Converts a FFT2DInfo to string. More...

inline ::std::ostream &	operator<< (::std::ostream &os, const Coordinates2D &coord_2d)
	Formatted output of the Coordinates2D type. More...

std::string	to_string (const Coordinates2D &coord_2d)
	Converts a Coordinates2D to string. More...

inline ::std::ostream &	operator<< (::std::ostream &os, const FuseBatchNormalizationType &fuse_type)
	Formatted output of the FuseBatchNormalizationType type. More...

std::string	to_string (const FuseBatchNormalizationType &fuse_type)
	Converts a FuseBatchNormalizationType to string. More...

inline ::std::ostream &	operator<< (::std::ostream &os, const SoftmaxKernelInfo &info)
	Formatted output of the SoftmaxKernelInfo type. More...

std::string	to_string (const SoftmaxKernelInfo &info)
	Converts a SoftmaxKernelInfo to string. More...

template<typename T >
::std::ostream &	operator<< (::std::ostream &os, const LSTMParams< T > &lstm_params)
	Formatted output of the ScaleKernelInfo type. More...

template<typename T >
std::string	to_string (const LSTMParams< T > &lstm_params)
	Converts a LSTMParams to string. More...

std::string	to_string (const uint8_t num)
	Converts a LSTMParams to string. More...

inline ::std::ostream &	operator<< (::std::ostream &os, const NMSType &nms_type)
	Available non maxima suppression types. More...

std::string	to_string (const NMSType nms_type)
	Converts a NMSType to string. More...

inline ::std::ostream &	operator<< (::std::ostream &os, const BoxNMSLimitInfo &info)
	Formatted output of the BoxNMSLimitInfo type. More...

std::string	to_string (const BoxNMSLimitInfo &info)
	Converts a BoxNMSLimitInfo to string. More...

std::string	to_string (const DimensionRoundingType &rounding_type)
	Converts a DimensionRoundingType to string. More...

inline ::std::ostream &	operator<< (::std::ostream &os, const Conv3dInfo &conv3d_info)
	Formatted output of the Conv3dInfo type. More...

std::string	to_string (const Conv3dInfo &conv3d_info)
	Formatted output of the Conv3dInfo type. More...

std::string	to_string (const WeightFormat wf)
	Formatted output of the arm_compute::WeightFormat type. More...

inline ::std::ostream &	operator<< (::std::ostream &os, const arm_compute::WeightFormat &wf)
	Formatted output of the arm_compute::WeightFormat type. More...

std::string	to_string (const std::tuple< TensorShape, TensorShape, arm_compute::WeightFormat > values)
	Formatted output of the std::tuple<TensorShape, TensorShape, arm_compute::WeightFormat> tuple. More...

inline ::std::ostream &	operator<< (::std::ostream &os, const Padding2D &padding2d)
	Formatted output of the Padding2D type. More...

std::string	to_string (const Padding2D &padding2d)
	Converts a Padding2D to string. More...

inline ::std::ostream &	operator<< (::std::ostream &os, const experimental::dynamic_fusion::Pool2dAttributes &pool2d_attr)
	Formatted output of the arm_compute::experimental::dynamic_fusion::Pool2dAttributes type. More...

std::string	to_string (const experimental::dynamic_fusion::Pool2dAttributes &pool2d_attr)
	Formatted output of the arm_compute::experimental::dynamic_fusion::Pool2dAttributes type. More...

inline ::std::ostream &	operator<< (::std::ostream &os, const experimental::dynamic_fusion::GpuPool2dSettings &settings)
	Formatted output of the arm_compute::experimental::dynamic_fusion::GpuPool2dSettings type. More...

std::string	to_string (const experimental::dynamic_fusion::GpuPool2dSettings &settings)
	Formatted output of the arm_compute::experimental::dynamic_fusion::GpuPool2dSettings type. More...

inline ::std::ostream &	operator<< (::std::ostream &os, const experimental::dynamic_fusion::Conv2dAttributes &conv2d_attr)
	Formatted output of the arm_compute::experimental::dynamic_fusion::Conv2dAttributes type. More...

std::string	to_string (const experimental::dynamic_fusion::Conv2dAttributes &conv2d_attr)
	Formatted output of the arm_compute::experimental::dynamic_fusion::Conv2dAttributes type. More...

inline ::std::ostream &	operator<< (::std::ostream &os, const experimental::dynamic_fusion::CastAttributes &cast_attr)
	Formatted output of the arm_compute::experimental::dynamic_fusion::CastAttributes type. More...

std::string	to_string (const experimental::dynamic_fusion::CastAttributes &cast_attr)
	Formatted output of the arm_compute::experimental::dynamic_fusion::CastAttributes type. More...

inline ::std::ostream &	operator<< (::std::ostream &os, const experimental::dynamic_fusion::DepthwiseConv2dAttributes &dw_conv2d_attr)
	Formatted output of the arm_compute::experimental::dynamic_fusion::DepthwiseConv2dAttributes type. More...

std::string	to_string (const experimental::dynamic_fusion::DepthwiseConv2dAttributes &dw_conv2d_attr)
	Formatted output of the arm_compute::experimental::dynamic_fusion::DepthwiseConv2dAttributes type. More...

inline ::std::ostream &	operator<< (::std::ostream &os, const experimental::dynamic_fusion::ClampAttributes &clamp_attr)
	Formatted output of the arm_compute::experimental::dynamic_fusion::ClampAttributes type. More...

std::string	to_string (const experimental::dynamic_fusion::ClampAttributes &clamp_attr)
	Formatted output of the arm_compute::experimental::dynamic_fusion::ClampAttributes type. More...

inline ::std::ostream &	operator<< (::std::ostream &os, const experimental::dynamic_fusion::ResizeAttributes &resize_attr)
	Formatted output of the arm_compute::experimental::dynamic_fusion::ResizeAttributes type. More...

std::string	to_string (const experimental::dynamic_fusion::ResizeAttributes &resize_attr)
	Formatted output of the arm_compute::experimental::dynamic_fusion::ResizeAttributes type. More...

inline ::std::ostream &	operator<< (::std::ostream &os, const experimental::dynamic_fusion::SoftmaxAttributes &softmax_attr)
	Formatted output of the arm_compute::experimental::dynamic_fusion::SoftmaxAttributes type. More...

std::string	to_string (const experimental::dynamic_fusion::SoftmaxAttributes &softmax_attr)
	Formatted output of the arm_compute::experimental::dynamic_fusion::SoftmaxAttributes type. More...

inline ::std::ostream &	operator<< (::std::ostream &os, const arm_compute::MatMulInfo &matmul_info)
	Formatted output of the arm_compute::MatMulInfo type. More...

std::string	to_string (const arm_compute::MatMulInfo &matmul_info)
	Formatted output of the arm_compute::MatMulInfo type. More...

inline ::std::ostream &	operator<< (::std::ostream &os, const arm_compute::MatMulKernelInfo &matmul_info)
	Formatted output of the arm_compute::MatMulKernelInfo type. More...

std::string	to_string (const arm_compute::MatMulKernelInfo &matmul_info)
	Formatted output of the arm_compute::MatMulKernelInfo type. More...

inline ::std::ostream &	operator<< (::std::ostream &os, const arm_compute::CpuMatMulSettings &settings)
	Formatted output of the arm_compute::CpuMatMulSettings type. More...

std::string	to_string (const arm_compute::CpuMatMulSettings &settings)
	Formatted output of the arm_compute::CpuMatMulSettings type. More...

(EXPERIMENTAL_POST_OPS)
inline ::std::ostream &	operator<< (::std::ostream &os, experimental::PostOpType post_op_type)
	Formmated output of the experimental::PostOpType type. More...

std::string	to_string (experimental::PostOpType post_op_type)
	Converts a experimental::PostOpType to string. More...

template<typename T >
inline ::std::ostream &	operator<< (::std::ostream &os, const experimental::IPostOp< T > &post_op)
	Formatted output of the experimental::IPostOp type. More...

template<typename T >
std::string	to_string (const experimental::IPostOp< T > &post_op)
	Converts an experimental::IPostOp to string. More...

template<typename T >
inline ::std::ostream &	operator<< (::std::ostream &os, const experimental::PostOpList< T > &post_ops)
	Formatted output of the experimental::PostOpList type. More...

template<typename T >
std::string	to_string (const experimental::PostOpList< T > &post_ops)
	Converts a experimental::PostOpList to string. More...

Variables
constexpr size_t	MAX_DIMS = 6
	Constant value used to indicate maximum dimensions of a Window, TensorShape and Coordinates. More...

const std::array< float32x4_t, 8 >	log_tab
	Logarithm polynomial coefficients. More...

constexpr float	te_sin_coeff2 = 0.166666666666f
	Sin polynomial coefficients. More...

constexpr float	te_sin_coeff3 = 0.05f

constexpr float	te_sin_coeff4 = 0.023809523810f

constexpr float	te_sin_coeff5 = 0.013888888889f

Detailed Description

Synced with tests/validation/dynamic_fusion/gpu/cl/DirectConv2d.cpp Please check there for any differences in the coverage.

A DotMLGO file parser (LL(k) parser)

[CLReshapeLayer snippet]

[ClReshapeKernel Kernel]

[NEReshapeLayerKernel Kernel]

(EXPERIMENTAL_POST_OPS)

This file contains all available output stages for GEMMLowp.

This file contains all available output stages for GEMMLowp on OpenCL.

SPDX-License-Identifier: MIT

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

In gemmlowp, the "output stage" is the process that takes a final int32 accumulator value (the output of CLGEMMLowpMatrixMultiplyCore), and processes it to obtain the final QASYMM8/QASYMM8_SIGNED value.

More information about the GEMMLowp output stage can be found at https://github.com/google/gemmlowp/blob/master/doc/output.md

In gemmlowp, the "output stage" is the process that takes a final int32 accumulator value (the output of NEGEMMLowpMatrixMultiplyCore), and processes it to obtain the final ASYMM8 value.

More information about the GEMMLowp output stage can be found at https://github.com/google/gemmlowp/blob/master/doc/output.md

The grammar of DotMLGO is defined as the following ENBF:

delim = "," | "\n"; // Note that delimiters are omitted from the definition below

mlgo = header, heuristics-table, {heuristic-tree};

header = "<header>", gemm-version, ip-type, "</header>"; gemm-version = "gemm-version", "[", int, int, int, "]"; ip-type = "ip-type", ("gpu" | "cpu");

heiristics-table = "<heuristics-table>", {heuristics-table-entry}, "</heuristics-table>"; heuristics-table-entry = entry-id, ip-name, num-cores, data-type, gpu-priority, gpu-behavior, heuristic-type, free-vars; entry-id = int; ip-name = char-sequence; num-cores = int; data-type = "f32" | "f16" | "qasymm8"; gpu-priority = "best-performance" | "best-memory-usage"; gpu-behavior = "static" | "dynamic"; heuristic-type = "gemm-type" | "gemm-config-native" | "gemm-config-reshaped-only-rhs" | "gemm-config-reshaped"; free-vars = "[", {char-sequence}, "]";

heuristic-tree = "<heuristic", entry-id, ">", {tree-node}, "</heuristic>"; tree-node = branch-node | leaf-node; branch-node = "b", entry-id, lhs-type, lhs-value, conditional-op, rhs-type, rhs-value, true-node, false-node; lhs-type = comparator-type; lhs-value = comparator-value; rhs-type = comparator-type; rhs-value = comparator-value; comparator-type = "var" | "num" | "enum"; comparator-value = char-sequence | float; conditional-op = "<" | "<=" | "==" | ">=" | ">"; true-node = entry-id; false-node = entry-id; leaf-node = "l", entry-id, heuristic-type, leaf-value; leaf-value = gemm-type | gemm-config-native | gemm-config-reshaped-only-rhs | gemm-config-reshaped gemm-type = "native" | "reshaped-only-rhs" | "reshaped"; gemm-config-native = "[", int, int, int, "]"; gemm-config-reshaped-only-rhs = "[", int, int, int, int, bool, bool, bool, "]"; gemm-config-reshaped = "[", int, int, int, int, int, bool, bool, bool, bool, "]";

Typedef Documentation

◆ BBox

using BBox = std::array<float, 4>

Definition at line 950 of file Types.h.

◆ BiStrides

using BiStrides = Coordinates

Bidirectional strides.

Definition at line 53 of file Types.h.

◆ CLEqual

using CLEqual = CLComparisonStatic<ComparisonOperation::Equal>

Basic function to run equal comparison.

Definition at line 124 of file CLComparison.h.

◆ CLFloatArray

using CLFloatArray = CLArray<cl_float>

OpenCL Array of floats.

Definition at line 116 of file CLArray.h.

◆ CLGreater

using CLGreater = CLComparisonStatic<ComparisonOperation::Greater>

Basic function to run greater comparison.

Definition at line 128 of file CLComparison.h.

◆ CLGreaterEqual

using CLGreaterEqual = CLComparisonStatic<ComparisonOperation::GreaterEqual>

Basic function to run greater-equal comparison.

Definition at line 130 of file CLComparison.h.

◆ CLImage

using CLImage = CLTensor

OpenCL Image.

Definition at line 104 of file CLTensor.h.

◆ CLInt16Array

using CLInt16Array = CLArray<cl_short>

OpenCL Array of int16s.

Definition at line 112 of file CLArray.h.

◆ CLInt32Array

using CLInt32Array = CLArray<cl_int>

OpenCL Array of int32s.

Definition at line 114 of file CLArray.h.

◆ CLLess

using CLLess = CLComparisonStatic<ComparisonOperation::Less>

Basic function to run less comparison.

Definition at line 132 of file CLComparison.h.

◆ CLLessEqual

using CLLessEqual = CLComparisonStatic<ComparisonOperation::LessEqual>

Basic function to run less-equal comparison.

Definition at line 134 of file CLComparison.h.

◆ CLLogSoftmaxLayer

using CLLogSoftmaxLayer = CLSoftmaxLayerGeneric<true>

Definition at line 112 of file CLSoftmaxLayer.h.

◆ CLNotEqual

using CLNotEqual = CLComparisonStatic<ComparisonOperation::NotEqual>

Basic function to run not equal comparison.

Definition at line 126 of file CLComparison.h.

◆ CLSoftmaxLayer

using CLSoftmaxLayer = CLSoftmaxLayerGeneric<false>

Definition at line 111 of file CLSoftmaxLayer.h.

◆ CLUInt16Array

using CLUInt16Array = CLArray<cl_ushort>

OpenCL Array of uint16s.

Definition at line 108 of file CLArray.h.

◆ CLUInt32Array

using CLUInt32Array = CLArray<cl_uint>

OpenCL Array of uint32s.

Definition at line 110 of file CLArray.h.

◆ CLUInt8Array

using CLUInt8Array = CLArray<cl_uchar>

OpenCL Array of uint8s.

Definition at line 106 of file CLArray.h.

◆ CropInfo

using CropInfo = Padding2D

Class for holding information related to cropping.

Definition at line 2762 of file Types.h.

◆ FloatArray

using FloatArray = Array<float>

Array of floats.

Definition at line 74 of file Array.h.

◆ GroupMappings

using GroupMappings = std::map<size_t, MemoryMappings>

A map of the groups and memory mappings.

Definition at line 48 of file Types.h.

◆ half

using half = half_float::half

16-bit floating point type

Definition at line 48 of file Types.h.

◆ ICLFloatArray

using ICLFloatArray = ICLArray<cl_float>

Interface for OpenCL Array of floats.

Definition at line 129 of file ICLArray.h.

◆ ICLImage

using ICLImage = ICLTensor

Definition at line 117 of file ICLTensor.h.

◆ ICLInt16Array

using ICLInt16Array = ICLArray<cl_short>

Interface for OpenCL Array of int16s.

Definition at line 125 of file ICLArray.h.

◆ ICLInt32Array

using ICLInt32Array = ICLArray<cl_int>

Interface for OpenCL Array of int32s.

Definition at line 127 of file ICLArray.h.

◆ ICLUInt16Array

using ICLUInt16Array = ICLArray<cl_ushort>

Interface for OpenCL Array of uint16s.

Definition at line 121 of file ICLArray.h.

◆ ICLUInt32Array

using ICLUInt32Array = ICLArray<cl_uint>

Interface for OpenCL Array of uint32s.

Definition at line 123 of file ICLArray.h.

◆ ICLUInt8Array

using ICLUInt8Array = ICLArray<cl_uchar>

Interface for OpenCL Array of uint8s.

Definition at line 119 of file ICLArray.h.

◆ IFloatArray

using IFloatArray = IArray<float>

Interface for Array of floats.

Definition at line 144 of file IArray.h.

◆ IImage

using IImage = ITensor

Definition at line 100 of file ITensor.h.

◆ IInt16Array

using IInt16Array = IArray<int16_t>

Interface for Array of int16s.

Definition at line 140 of file IArray.h.

◆ IInt32Array

using IInt32Array = IArray<int32_t>

Interface for Array of int32s.

Definition at line 142 of file IArray.h.

◆ Image

using Image = Tensor

Image.

Definition at line 69 of file Tensor.h.

◆ INEKernel

typedef ICPPKernel INEKernel

Common interface for all kernels implemented in Neon.

Definition at line 39 of file INEOperator.h.

◆ Int16Array

using Int16Array = Array<int16_t>

Array of int16s.

Definition at line 70 of file Array.h.

◆ Int32Array

using Int32Array = Array<int32_t>

Array of int32s.

Definition at line 72 of file Array.h.

◆ IUInt16Array

using IUInt16Array = IArray<uint16_t>

Interface for Array of uint16s.

Definition at line 136 of file IArray.h.

◆ IUInt32Array

using IUInt32Array = IArray<uint32_t>

Interface for Array of uint32s.

Definition at line 138 of file IArray.h.

◆ IUInt8Array

using IUInt8Array = IArray<uint8_t>

Interface for Array of uint8s.

Definition at line 134 of file IArray.h.

◆ LabelBBox

using LabelBBox = std::map<int, std::vector<BBox> >

Definition at line 952 of file Types.h.

◆ lock_guard

using lock_guard = std::lock_guard<Mutex>

Wrapper of lock_guard data-object.

Definition at line 37 of file Mutex.h.

◆ MemoryMappings

using MemoryMappings = std::map<IMemory *, size_t>

A map of (handle, index/offset), where handle is the memory handle of the object to provide the memory for and index/offset is the buffer/offset from the pool that should be used.

Note: All objects are pre-pinned to specific buffers to avoid any relevant overheads

Definition at line 45 of file Types.h.

◆ MemoryRequirements

using MemoryRequirements = experimental::MemoryRequirements

Definition at line 55 of file IOperator.h.

◆ Multiples

using Multiples = std::vector<uint32_t>

Information to produce a tiled version of a Tensor.

Definition at line 458 of file Types.h.

◆ Mutex

using Mutex = std::mutex

Wrapper of Mutex data-object.

Definition at line 33 of file Mutex.h.

◆ NEAbsLayer

using NEAbsLayer = NEElementwiseUnaryLayer<ElementWiseUnary::ABS>

Definition at line 91 of file NEElementwiseUnaryLayer.h.

◆ NEEqual

using NEEqual = NEElementwiseComparisonStatic<ComparisonOperation::Equal>

Basic function to run equal comparison.

Definition at line 436 of file NEElementwiseOperations.h.

◆ NEExpLayer

using NEExpLayer = NEElementwiseUnaryLayer<ElementWiseUnary::EXP>

Definition at line 88 of file NEElementwiseUnaryLayer.h.

◆ NEGreater

using NEGreater = NEElementwiseComparisonStatic<ComparisonOperation::Greater>

Basic function to run greater comparison.

Definition at line 440 of file NEElementwiseOperations.h.

◆ NEGreaterEqual

using NEGreaterEqual = NEElementwiseComparisonStatic<ComparisonOperation::GreaterEqual>

Basic function to run greater-equal comparison.

Definition at line 442 of file NEElementwiseOperations.h.

◆ NELess

using NELess = NEElementwiseComparisonStatic<ComparisonOperation::Less>

Basic function to run less comparison.

Definition at line 444 of file NEElementwiseOperations.h.

◆ NELessEqual

using NELessEqual = NEElementwiseComparisonStatic<ComparisonOperation::LessEqual>

Basic function to run less-equal comparison.

Definition at line 446 of file NEElementwiseOperations.h.

◆ NELogLayer

using NELogLayer = NEElementwiseUnaryLayer<ElementWiseUnary::LOG>

Definition at line 90 of file NEElementwiseUnaryLayer.h.

◆ NELogSoftmaxLayer

using NELogSoftmaxLayer = NESoftmaxLayerGeneric<true>

Definition at line 98 of file NESoftmaxLayer.h.

◆ NENegLayer

using NENegLayer = NEElementwiseUnaryLayer<ElementWiseUnary::NEG>

Definition at line 89 of file NEElementwiseUnaryLayer.h.

◆ NENotEqual

using NENotEqual = NEElementwiseComparisonStatic<ComparisonOperation::NotEqual>

Basic function to run not equal comparison.

Definition at line 438 of file NEElementwiseOperations.h.

◆ NERoundLayer

using NERoundLayer = NEElementwiseUnaryLayer<ElementWiseUnary::ROUND>

Definition at line 92 of file NEElementwiseUnaryLayer.h.

◆ NERsqrtLayer

using NERsqrtLayer = NEElementwiseUnaryLayer<ElementWiseUnary::RSQRT>

Definition at line 87 of file NEElementwiseUnaryLayer.h.

◆ NEScheduler

using NEScheduler = Scheduler

CPU Scheduler.

Definition at line 32 of file NEScheduler.h.

◆ NESinLayer

using NESinLayer = NEElementwiseUnaryLayer<ElementWiseUnary::SIN>

Definition at line 93 of file NEElementwiseUnaryLayer.h.

◆ NESoftmaxLayer

using NESoftmaxLayer = NESoftmaxLayerGeneric<false>

Definition at line 97 of file NESoftmaxLayer.h.

◆ OperatorType

typedef cpu::CpuPRelu OperatorType

Definition at line 39 of file CLGEMM.cpp.

◆ PaddingInfo

using PaddingInfo = std::pair<uint32_t, uint32_t>

Padding information as a pair of unsigned int start/end.

Definition at line 452 of file Types.h.

◆ PaddingList

using PaddingList = std::vector<PaddingInfo>

List of padding information.

Definition at line 455 of file Types.h.

◆ PaddingSize

using PaddingSize = BorderSize

Container for 2D padding size.

Definition at line 399 of file Types.h.

◆ PermutationVector

using PermutationVector = Strides

Permutation vector.

Definition at line 51 of file Types.h.

◆ qasymm16_t

using qasymm16_t = uint16_t

16 bit quantized asymmetric scalar value

Definition at line 41 of file QuantizationInfo.h.

◆ qasymm8_signed_t

using qasymm8_signed_t = int8_t

8 bit signed quantized asymmetric scalar value

Definition at line 38 of file QuantizationInfo.h.

◆ qasymm8_t

using qasymm8_t = uint8_t

8 bit quantized asymmetric scalar value

Definition at line 39 of file QuantizationInfo.h.

◆ qasymm8x16_signed_t

using qasymm8x16_signed_t = int8x16_t

8 bit quantized signed asymmetric vector with 16 elements

Definition at line 43 of file NEAsymm.h.

◆ qasymm8x16_t

using qasymm8x16_t = uint8x16_t

8 bit quantized asymmetric vector with 16 elements

Definition at line 37 of file NEAsymm.h.

◆ qasymm8x8_signed_t

using qasymm8x8_signed_t = int8x8_t

8 bit quantized signed asymmetric vector with 8 elements

Definition at line 39 of file NEAsymm.h.

◆ qasymm8x8_t

using qasymm8x8_t = uint8x8_t

8 bit quantized asymmetric vector with 8 elements

Definition at line 33 of file NEAsymm.h.

◆ qasymm8x8x2_signed_t

using qasymm8x8x2_signed_t = int8x8x2_t

8 bit quantized signed asymmetric vector with 16 elements

Definition at line 40 of file NEAsymm.h.

◆ qasymm8x8x2_t

using qasymm8x8x2_t = uint8x8x2_t

8 bit quantized asymmetric vector with 16 elements

Definition at line 34 of file NEAsymm.h.

◆ qasymm8x8x3_signed_t

using qasymm8x8x3_signed_t = int8x8x3_t

8 bit quantized signed asymmetric vector with 24 elements

Definition at line 41 of file NEAsymm.h.

◆ qasymm8x8x3_t

using qasymm8x8x3_t = uint8x8x3_t

8 bit quantized asymmetric vector with 24 elements

Definition at line 35 of file NEAsymm.h.

◆ qasymm8x8x4_signed_t

using qasymm8x8x4_signed_t = int8x8x4_t

8 bit quantized signed asymmetric vector with 32 elements

Definition at line 42 of file NEAsymm.h.

◆ qasymm8x8x4_t

using qasymm8x8x4_t = uint8x8x4_t

8 bit quantized asymmetric vector with 32 elements

Definition at line 36 of file NEAsymm.h.

◆ qsymm16_t

typedef int16_t qsymm16_t

16 bit quantized symmetric scalar value

Definition at line 40 of file QuantizationInfo.h.

◆ qsymm16x8_t

using qsymm16x8_t = int16x8_t

16 bit quantized symmetric vector with 8 elements

Definition at line 36 of file NESymm.h.

◆ qsymm16x8x2_t

using qsymm16x8x2_t = int16x8x2_t

16 bit quantized symmetric vector with 16 elements

Definition at line 37 of file NESymm.h.

◆ qsymm8_t

using qsymm8_t = int8_t

8 bit quantized symmetric scalar value

Definition at line 33 of file NESymm.h.

◆ UInt16Array

using UInt16Array = Array<uint16_t>

Array of uint16s.

Definition at line 66 of file Array.h.

◆ UInt32Array

using UInt32Array = Array<uint32_t>

Array of uint32s.

Definition at line 68 of file Array.h.

◆ UInt8Array

using UInt8Array = Array<uint8_t>

Array of uint8s.

Definition at line 64 of file Array.h.

◆ unique_lock

using unique_lock = std::unique_lock<Mutex>

Wrapper of lock_guard data-object.

Definition at line 41 of file Mutex.h.

◆ WorkspaceData

using WorkspaceData = std::vector<WorkspaceDataElement<TensorType> >

Definition at line 52 of file MemoryHelpers.h.

Enumeration Type Documentation

◆ ArithmeticOperation

enum ArithmeticOperation

strong

Available element-wise operations.

Enumerator
ADD	(x + y)
SUB	(x - y)
DIV	(x / y)
MIN	Min(x, y)
MAX	Max(x, y)
SQUARED_DIFF	(x - y)^2
POWER	x ^ y
PRELU	y*x if x < 0, x otherwise

Definition at line 491 of file Types.h.

 {
     ADD,          /**< (x + y) */
     SUB,          /**< (x  - y) */
     DIV,          /**< (x / y) */
     MIN,          /**< Min(x, y) */
     MAX,          /**< Max(x, y) */
     SQUARED_DIFF, /**< (x - y)^2 */
     POWER,        /**< x ^ y */
     PRELU,        /**< y*x if x < 0, x otherwise */
 };

◆ BilinearInterpolation

enum BilinearInterpolation

strong

Bilinear Interpolation method used by LKTracker.

Enumerator
BILINEAR_OLD_NEW	Old-new method.
BILINEAR_SCHARR	Scharr method.

Definition at line 421 of file Types.h.

 {
     BILINEAR_OLD_NEW, /**< Old-new method */
     BILINEAR_SCHARR   /**< Scharr method */
 };

◆ BitwiseOperation

enum BitwiseOperation

strong

Available bitwise operations.

Enumerator
AND	Bitwise AND operation.
NOT	Bitwise NOT operation.
OR	Bitwise OR operation.
XOR	Bitwise XOR operation.

Definition at line 517 of file Types.h.

 {
     AND, /**< Bitwise AND operation */
     NOT, /**< Bitwise NOT operation */
     OR,  /**< Bitwise OR operation  */
     XOR, /**< Bitwise XOR operation  */
 };

◆ BorderMode

enum BorderMode

strong

Methods available to handle borders.

Enumerator
UNDEFINED	Borders are left undefined.
CONSTANT	Pixels outside the image are assumed to have a constant value.
REPLICATE	Pixels outside the image are assumed to have the same value as the closest image pixel.

Definition at line 276 of file Types.h.

 {
     UNDEFINED, /**< Borders are left undefined */
     CONSTANT,  /**< Pixels outside the image are assumed to have a constant value */
     REPLICATE  /**< Pixels outside the image are assumed to have the same value as the closest image pixel */
 };

◆ Channel

enum Channel

strong

Available channels.

Enumerator
UNKNOWN
C0	Unknown channel format. First channel (used by formats with unknown channel types).
C1	Second channel (used by formats with unknown channel types).
C2	Third channel (used by formats with unknown channel types).
C3	Fourth channel (used by formats with unknown channel types).
R	Red channel.
G	Green channel.
B	Blue channel.
A	Alpha channel.
Y	Luma channel.
U	Cb/U channel.
V	Cr/V/Value channel.

Definition at line 461 of file Types.h.

 {
     UNKNOWN, /** Unknown channel format */
     C0,      /**< First channel (used by formats with unknown channel types). */
     C1,      /**< Second channel (used by formats with unknown channel types). */
     C2,      /**< Third channel (used by formats with unknown channel types). */
     C3,      /**< Fourth channel (used by formats with unknown channel types). */
     R,       /**< Red channel. */
     G,       /**< Green channel. */
     B,       /**< Blue channel. */
     A,       /**< Alpha channel. */
     Y,       /**< Luma channel. */
     U,       /**< Cb/U channel. */
     V        /**< Cr/V/Value channel. */
 };

◆ CLBackendType

enum CLBackendType

strong

List the possible OpenCL backends.

Enumerator
Native	OpenCL native backend.
Clvk	CLVK backend.

Definition at line 55 of file CLTypes.h.

 {
     Native, /**< OpenCL native backend */
     Clvk,   /**< CLVK backend */
 };

◆ CLGEMMKernelType

enum CLGEMMKernelType

strong

OpenCL GEMM kernel types.

Enumerator
NATIVE	Native GEMM kernel with configurable block size.
RESHAPED	Reshaped GEMM kernel where both lhs and rhs matrices are reshaped. Configurable reshape and block size
RESHAPED_ONLY_RHS	Reshaped GEMM kernel where only the rhs matrix is reshaped. Configurable reshape and block size
RESHAPED_ONLY_RHS_MMUL	Reshaped GEMM kernel where only the rhs matrix is reshaped. Using MMUL with configurable block size.

Definition at line 31 of file CLTypes.h.

 {
     /** Native GEMM kernel with configurable block size.*/
     NATIVE,
     /** Reshaped GEMM kernel where both lhs and rhs matrices are reshaped. Configurable reshape and block size */
     RESHAPED,
     /** Reshaped GEMM kernel where only the rhs matrix is reshaped. Configurable reshape and block size */
     RESHAPED_ONLY_RHS,
     /** Reshaped GEMM kernel where only the rhs matrix is reshaped. Using MMUL with configurable block size. */
     RESHAPED_ONLY_RHS_MMUL
 };

◆ CLImage2DType

enum CLImage2DType

strong

OpenCL Image2D types.

Enumerator
ReadOnly
WriteOnly

Definition at line 38 of file CLUtils.h.

 {
     ReadOnly,
     WriteOnly
 };

◆ CLKernelType

enum CLKernelType

Enumerator
UNKNOWN	Unknown CL kernel type.
UNKNOWN
DEPTHWISE	Depthwise CL kernel type.
DIRECT	Direct Convolution CL kernel type.
ELEMENTWISE	Elementwise CL kernel type.
GEMM	GEMM CL kernel type.
POOL	Pool CL kernel type.
WINOGRAD	Winograd CL kernel type.

Definition at line 80 of file CLTypes.h.

 {
     UNKNOWN,     /**< Unknown CL kernel type */
     DEPTHWISE,   /**< Depthwise CL kernel type */
     DIRECT,      /**< Direct Convolution CL kernel type */
     ELEMENTWISE, /**< Elementwise CL kernel type */
     GEMM,        /**< GEMM CL kernel type */
     POOL,        /**< Pool CL kernel type */
     WINOGRAD     /**< Winograd CL kernel type */
 };

◆ CLTunerMode

enum CLTunerMode

strong

< OpenCL tuner modes

Enumerator
EXHAUSTIVE	Searches all possible LWS configurations while tuning.
NORMAL	Searches a subset of LWS configurations while tuning.
RAPID	Searches a minimal subset of LWS configurations while tuning.

Definition at line 35 of file CLTunerTypes.h.

 {
     EXHAUSTIVE, /**< Searches all possible LWS configurations while tuning */
     NORMAL,     /**< Searches a subset of LWS configurations while tuning */
     RAPID       /**< Searches a minimal subset of LWS configurations while tuning */
 };

◆ CLVersion

enum CLVersion

strong

Available OpenCL Version.

Enumerator
CL10
CL11
CL12
CL20
CL30
UNKNOWN

Definition at line 39 of file CLTypes.h.

 {
     CL10,   /* the OpenCL 1.0 */
     CL11,   /* the OpenCL 1.1 */
     CL12,   /* the OpenCL 1.2 */
     CL20,   /* the OpenCL 2.x */
     CL30,   /* the OpenCL 3.x */
     UNKNOWN /* unkown version */
 };

◆ ComparisonOperation

enum ComparisonOperation

strong

Supported comparison operations.

Enumerator
Equal	Equal comparison ( \( x == y \) )
NotEqual	NotEqual comparison ( \( x != y \) )
Greater	Greater comparison ( \( x > y \) )
GreaterEqual	Greater equal comparison ( \( x >= y \) )
Less	Less comparison ( \( x < y \) )
LessEqual	Less equal comparison ( \( x <= y \) )

Definition at line 175 of file Types.h.

 {
     Equal,        /**< Equal comparison ( \f$ x == y \f$ ) */
     NotEqual,     /**< NotEqual comparison ( \f$ x != y \f$ ) */
     Greater,      /**< Greater comparison ( \f$ x > y \f$ ) */
     GreaterEqual, /**< Greater equal comparison ( \f$ x >= y \f$ ) */
     Less,         /**< Less comparison ( \f$ x < y \f$ ) */
     LessEqual     /**< Less equal comparison ( \f$ x <= y \f$ ) */
 };

◆ ConvertPolicy

enum ConvertPolicy

strong

Policy to handle integer overflow.

Note: : This is ignored by floating point operations where the overflow behavior adheres to the IEEE-754 standard which states that in case of overflow ±infinity is returned for the round-to-nearest modes (and follows the rounding rules for the directed rounding modes) by default.

Enumerator
WRAP	Wrap around.
SATURATE	Saturate.

Definition at line 406 of file Types.h.

 {
     WRAP,    /**< Wrap around */
     SATURATE /**< Saturate */
 };

◆ ConvolutionMethod

enum ConvolutionMethod

strong

Available ConvolutionMethod.

Enumerator
GEMM	Convolution using GEMM.
GEMM_CONV2D	Direct 2D GEMM convolution.
DIRECT	Direct convolution.
INDIRECT	Indirect convolution.
WINOGRAD	Convolution using Winograd.
FFT	Convolution using FFT.

Definition at line 134 of file Types.h.

 {
     GEMM,        /**< Convolution using GEMM */
     GEMM_CONV2D, /**< Direct 2D GEMM convolution */
     DIRECT,      /**< Direct convolution */
     INDIRECT,    /**< Indirect convolution */
     WINOGRAD,    /**< Convolution using Winograd */
     FFT          /**< Convolution using FFT */
 };

◆ CPUModel

enum CPUModel

strong

CPU models types.

Note: We only need to detect CPUs we have microarchitecture-specific code for.; Architecture features are detected via HWCAPs.

Enumerator
X
GENERIC
GENERIC_FP16
GENERIC_FP16_DOT
A53
A55r0
A55r1
A35
A73
A76
A510
X1
V1
A64FX
N1

Definition at line 59 of file CPPTypes.h.

 {
 #define X(model) model,
     ARM_COMPUTE_CPU_MODEL_LIST
 #undef X
 };

◆ DataLayout

enum DataLayout

strong

[DataLayout enum definition]

Supported tensor data layouts

Enumerator
UNKNOWN	Unknown data layout.
NCHW	Num samples, channels, height, width.
NHWC	Num samples, height, width, channels.
NCDHW	Num samples, channels, depth, height, width.
NDHWC	Num samples, depth, height, width, channels.

Definition at line 113 of file Types.h.

 {
     UNKNOWN, /**< Unknown data layout */
     NCHW,    /**< Num samples, channels, height, width */
     NHWC,    /**< Num samples, height, width, channels */
     NCDHW,   /**< Num samples, channels, depth, height, width */
     NDHWC    /**< Num samples, depth, height, width, channels */
 };

◆ DataLayoutDimension

enum DataLayoutDimension

strong

[DataLayout enum definition]

Supported tensor data layout dimensions

Enumerator
CHANNEL	channel
HEIGHT	height
WIDTH	width
DEPTH	depth
BATCHES	batches

Definition at line 124 of file Types.h.

 {
     CHANNEL, /**< channel */
     HEIGHT,  /**< height */
     WIDTH,   /**< width */
     DEPTH,   /**< depth */
     BATCHES  /**< batches */
 };

◆ DataType

enum DataType

strong

Available data types.

Enumerator
UNKNOWN	Unknown data type.
U8	unsigned 8-bit number
S8	signed 8-bit number
QSYMM8	quantized, symmetric fixed-point 8-bit number
QASYMM8	quantized, asymmetric fixed-point 8-bit number unsigned
QASYMM8_SIGNED	quantized, asymmetric fixed-point 8-bit number signed
QSYMM8_PER_CHANNEL	quantized, symmetric per channel fixed-point 8-bit number
U16	unsigned 16-bit number
S16	signed 16-bit number
QSYMM16	quantized, symmetric fixed-point 16-bit number
QASYMM16	quantized, asymmetric fixed-point 16-bit number
U32	unsigned 32-bit number
S32	signed 32-bit number
U64	unsigned 64-bit number
S64	signed 64-bit number
BFLOAT16	16-bit brain floating-point number
F16	16-bit floating-point number
F32	32-bit floating-point number
F64	64-bit floating-point number
SIZET	size_t

Definition at line 79 of file Types.h.

 {
     UNKNOWN,            /**< Unknown data type */
     U8,                 /**< unsigned 8-bit number */
     S8,                 /**< signed 8-bit number */
     QSYMM8,             /**< quantized, symmetric fixed-point 8-bit number */
     QASYMM8,            /**< quantized, asymmetric fixed-point 8-bit number unsigned */
     QASYMM8_SIGNED,     /**< quantized, asymmetric fixed-point 8-bit number signed */
     QSYMM8_PER_CHANNEL, /**< quantized, symmetric per channel fixed-point 8-bit number */
     U16,                /**< unsigned 16-bit number */
     S16,                /**< signed 16-bit number */
     QSYMM16,            /**< quantized, symmetric fixed-point 16-bit number */
     QASYMM16,           /**< quantized, asymmetric fixed-point 16-bit number */
     U32,                /**< unsigned 32-bit number */
     S32,                /**< signed 32-bit number */
     U64,                /**< unsigned 64-bit number */
     S64,                /**< signed 64-bit number */
     BFLOAT16,           /**< 16-bit brain floating-point number */
     F16,                /**< 16-bit floating-point number */
     F32,                /**< 32-bit floating-point number */
     F64,                /**< 64-bit floating-point number */
     SIZET               /**< size_t */
 };

◆ DeconvolutionMethod

enum DeconvolutionMethod

strong

Available DeconvolutionMethod.

Enumerator
GEMM	Deconvolution using GEMM.
DIRECT	Direct deconvolution.
UPSCALE_CONV2D	Deconvolution with Upscaling.

Definition at line 152 of file Types.h.

 {
     GEMM,          /**< Deconvolution using GEMM */
     DIRECT,        /**< Direct deconvolution */
     UPSCALE_CONV2D /**< Deconvolution with Upscaling */
 };

◆ DepthwiseConvolutionFunction

enum DepthwiseConvolutionFunction

strong

Available DepthwiseConvolutionFunction.

Enumerator
OPTIMIZED	Optimized Depthwise Convolution.
GENERIC	Generic Depthwise Convolution.

Definition at line 145 of file Types.h.

 {
     OPTIMIZED, /**< Optimized Depthwise Convolution */
     GENERIC,   /**< Generic Depthwise Convolution */
 };

◆ DetectionOutputLayerCodeType

enum DetectionOutputLayerCodeType

strong

Available Detection Output code types.

Enumerator
CORNER	Use box corners.
CENTER_SIZE	Use box centers and size.
CORNER_SIZE	Use box centers and size.
TF_CENTER	Use box centers and size but flip x and y co-ordinates.

Definition at line 955 of file Types.h.

 {
     CORNER,      /**< Use box corners */
     CENTER_SIZE, /**< Use box centers and size */
     CORNER_SIZE, /**< Use box centers and size */
     TF_CENTER    /**< Use box centers and size but flip x and y co-ordinates */
 };

◆ DeviceType

enum DeviceType

strong

Device types.

Enumerator
NEON
CL

Definition at line 33 of file IDevice.h.

 {
     NEON,
     CL,
 };

◆ DimensionRoundingType

enum DimensionRoundingType

strong

Dimension rounding type when down-scaling on CNNs.

Note: Used in pooling and convolution layer

Enumerator
FLOOR	Floor rounding.
CEIL	Ceil rounding.

Definition at line 552 of file Types.h.

 {
     FLOOR, /**< Floor rounding */
     CEIL   /**< Ceil rounding */
 };

◆ ElementWiseUnary

enum ElementWiseUnary

strong

Available element wise unary operations.

Enumerator
RSQRT	Reverse square root.
EXP	Exponential.
NEG	Negate.
LOG	Natural Logarithm.
ABS	Absolute value.
SIN	Sine.
ROUND	Round.
LOGICAL_NOT	Logical Not.

Definition at line 504 of file Types.h.

 {
     RSQRT,       /**< Reverse square root */
     EXP,         /**< Exponential */
     NEG,         /**< Negate */
     LOG,         /**< Natural Logarithm */
     ABS,         /**< Absolute value */
     SIN,         /**< Sine */
     ROUND,       /**< Round */
     LOGICAL_NOT, /**< Logical Not */
 };

◆ ErrorCode

enum ErrorCode

Namespaces

Data Structures

Typedefs

Enumerations

Functions

Variables

Detailed Description

Typedef Documentation

◆ BBox

◆ BiStrides

◆ CLEqual

◆ CLFloatArray

◆ CLGreater

◆ CLGreaterEqual

◆ CLImage

◆ CLInt16Array

◆ CLInt32Array

◆ CLLess

◆ CLLessEqual

◆ CLLogSoftmaxLayer

◆ CLNotEqual

◆ CLSoftmaxLayer

◆ CLUInt16Array

◆ CLUInt32Array

◆ CLUInt8Array

◆ CropInfo

◆ FloatArray

◆ GroupMappings

◆ half

◆ ICLFloatArray

◆ ICLImage

◆ ICLInt16Array

◆ ICLInt32Array

◆ ICLUInt16Array

◆ ICLUInt32Array

◆ ICLUInt8Array

◆ IFloatArray

◆ IImage

◆ IInt16Array

◆ IInt32Array

◆ Image

◆ INEKernel

◆ Int16Array

◆ Int32Array

◆ IUInt16Array

◆ IUInt32Array

◆ IUInt8Array

◆ LabelBBox

◆ lock_guard

◆ MemoryMappings

◆ MemoryRequirements

◆ Multiples

◆ Mutex

◆ NEAbsLayer

◆ NEEqual

◆ NEExpLayer

◆ NEGreater

◆ NEGreaterEqual

◆ NELess

◆ NELessEqual

◆ NELogLayer

◆ NELogSoftmaxLayer

◆ NENegLayer

◆ NENotEqual

◆ NERoundLayer

◆ NERsqrtLayer

◆ NEScheduler

◆ NESinLayer

◆ NESoftmaxLayer

◆ OperatorType

◆ PaddingInfo

◆ PaddingList

◆ PaddingSize

◆ PermutationVector

◆ qasymm16_t

◆ qasymm8_signed_t

◆ qasymm8_t

◆ qasymm8x16_signed_t

◆ qasymm8x16_t

◆ qasymm8x8_signed_t