11 #include <initializer_list> 24 virtual bool IsNull()
const {
return false; }
32 bool IsNull()
const override {
return true; }
47 : m_Function(activation)
96 : m_Operation(operation)
116 : m_Operation(operation)
136 : m_DimMappings(dimMappings)
190 Status SetViewOriginCoord(uint32_t view, uint32_t coord, uint32_t value);
192 uint32_t GetNumViews()
const;
194 uint32_t GetNumDimensions()
const;
196 const uint32_t* GetViewOrigin(uint32_t idx)
const;
199 void ReorderOrigins(
unsigned int* newOrdering,
unsigned int numNewOrdering);
203 void SetConcatAxis(
unsigned int concatAxis);
205 unsigned int GetConcatAxis()
const;
208 unsigned int m_ConcatAxis;
210 uint32_t m_NumDimensions;
211 uint32_t** m_ViewOrigins;
233 Status SetViewOriginCoord(uint32_t view, uint32_t coord, uint32_t value);
237 Status SetViewSize(uint32_t view, uint32_t coord, uint32_t value);
240 uint32_t GetNumViews()
const;
242 uint32_t GetNumDimensions()
const;
244 const uint32_t* GetViewOrigin(uint32_t idx)
const;
246 const uint32_t* GetViewSizes(uint32_t idx)
const;
254 uint32_t** m_ViewSizes;
260 template <
typename TensorShapeIt>
263 unsigned int concatenationDimension)
265 auto numInputs = std::distance(first, last);
272 const auto& firstInputShape = *first;
274 const unsigned int numDimensions = firstInputShape.GetNumDimensions();
275 for (
auto it = first + 1; it != last; ++it)
277 if (it->GetNumDimensions() != numDimensions)
283 if (concatenationDimension >= numDimensions)
288 for (
auto it = first; it != last; ++it)
290 for (
unsigned int d = 0; d < numDimensions; ++d)
292 const bool dimSizeOk = (d == concatenationDimension) || (firstInputShape[d] == (*it)[d]);
296 " except the concatenation dimension");
301 OriginsDescriptor viewsDescriptor(static_cast<uint32_t>(numInputs), numDimensions);
304 uint32_t viewIndex = 0u;
305 uint32_t coordAlongConcatDim = 0u;
306 for (
auto it = first; it != last; ++it)
308 const auto& inputShape = *it;
310 for (
unsigned int i = 0; i < concatenationDimension; ++i)
315 viewsDescriptor.
SetViewOriginCoord(viewIndex, concatenationDimension, coordAlongConcatDim);
316 unsigned int dimSize = inputShape[concatenationDimension];
317 coordAlongConcatDim += dimSize;
320 for (
unsigned int i = concatenationDimension + 1; i < numDimensions; ++i)
328 return viewsDescriptor;
471 : m_BiasEnabled(false)
472 , m_TransposeWeightMatrix(false)
473 , m_ConstantWeights(true)
485 uint32_t GetNumViews()
const;
488 uint32_t GetNumInputs()
const;
510 , m_BiasEnabled(false)
566 , m_BiasEnabled(false)
589 uint32_t GetNumInputs()
const;
633 , m_BiasEnabled(false)
677 , m_MaxClassesPerDetection(1)
678 , m_DetectionsPerClass(1)
679 , m_NmsScoreThreshold(0)
680 , m_NmsIouThreshold(0)
682 , m_UseRegularNms(false)
818 return m_Gamma == rhs.
m_Gamma &&
820 m_Eps == rhs.
m_Eps &&
838 : m_BlockShape({1, 1})
839 , m_Crops({{0, 0}, {0, 0}})
844 std::vector<std::pair<unsigned int, unsigned int>> crops)
845 : m_BlockShape(blockShape)
860 std::vector<std::pair<unsigned int, unsigned int>>
m_Crops;
875 return m_Min == rhs.
m_Min && m_Max == rhs.
m_Max;
916 return m_Axis == rhs.
m_Axis;
929 ResizeBilinearDescriptor()
933 , m_AlignCorners(
false)
934 , m_HalfPixelCenters(
false)
938 bool operator ==(
const ResizeBilinearDescriptor& rhs)
const 940 return m_TargetWidth == rhs.m_TargetWidth &&
941 m_TargetHeight == rhs.m_TargetHeight &&
942 m_DataLayout == rhs.m_DataLayout &&
943 m_AlignCorners == rhs.m_AlignCorners &&
944 m_HalfPixelCenters == rhs.m_HalfPixelCenters;
949 uint32_t m_TargetWidth;
951 uint32_t m_TargetHeight;
957 bool m_HalfPixelCenters;
968 , m_AlignCorners(false)
969 , m_HalfPixelCenters(false)
1006 : m_TargetShape(shape)
1022 : m_BlockShape({1, 1})
1023 , m_PadList({{0, 0}, {0, 0}})
1028 const std::vector<std::pair<unsigned int, unsigned int>>& padList)
1029 : m_BlockShape(blockShape)
1030 , m_PadList(padList)
1045 std::vector<std::pair<unsigned int, unsigned int>>
m_PadList;
1058 : m_BlockSize(blockSize)
1059 , m_DataLayout(dataLayout)
1081 : m_ActivationFunc(1)
1082 , m_ClippingThresCell(0.0)
1083 , m_ClippingThresProj(0.0)
1084 , m_CifgEnabled(true)
1085 , m_PeepholeEnabled(false)
1086 , m_ProjectionEnabled(false)
1087 , m_LayerNormEnabled(false)
1088 , m_TimeMajor(false)
1133 , m_KeepDims(keepDims)
1153 PadDescriptor(
const std::vector<std::pair<unsigned int, unsigned int>>& padList,
1154 const float& padValue = 0,
1156 : m_PadList(padList)
1157 , m_PadValue(padValue)
1158 , m_PaddingMode(paddingMode)
1170 std::vector<std::pair<unsigned int, unsigned int>>
m_PadList;
1182 SliceDescriptor(
const std::vector<unsigned int>& begin,
const std::vector<unsigned int>& size)
1213 , m_NumInputs(numInputs)
1214 , m_InputShape(inputShape)
1219 return m_Axis == rhs.
m_Axis &&
1238 : m_NumInputs(numInputs)
1239 , m_NumOutputs(numOutputs)
1249 uint32_t m_NumInputs = 0;
1251 uint32_t m_NumOutputs = 0;
1258 const std::vector<int>& end,
1259 const std::vector<int>& stride)
1265 , m_ShrinkAxisMask(0)
1277 return m_Begin == rhs.
m_Begin &&
1278 m_End == rhs.
m_End &&
1288 int GetStartForAxis(
const TensorShape& inputShape,
unsigned int axis)
const;
1291 int startForAxis)
const;
1322 : m_NumInputSlots(numInputSlots), m_NumOutputSlots(numOutputSlots)
1336 , m_ProjectionClip(0.0)
1337 , m_CifgEnabled(true)
1338 , m_PeepholeEnabled(false)
1339 , m_ProjectionEnabled(false)
1340 , m_LayerNormEnabled(false)
1341 , m_InputIntermediateScale(0.0)
1342 , m_ForgetIntermediateScale(0.0)
1343 , m_CellIntermediateScale(0.0)
1344 , m_OutputIntermediateScale(0.0)
1345 , m_HiddenStateZeroPoint(0)
1346 , m_HiddenStateScale(0.0)
1401 m_BiasEnabled(false),
1403 m_OutputShapeEnabled(false)
1449 : m_DimMappings(dimMappings)
1470 : m_Operation(operation)
1510 : m_NumGroups(0), m_Axis(0)
1514 : m_NumGroups(numGroups), m_Axis(axis)
ElementwiseUnaryDescriptor(UnaryOperation operation)
uint32_t m_PadBottom
Padding bottom value in the height dimension.
bool m_BiasEnabled
Enable/disable bias.
PoolingAlgorithm m_PoolType
The pooling algorithm to use (Max. Average, L2).
float m_Eps
Used to avoid dividing by zero.
MeanDescriptor(const std::vector< unsigned int > &axis, bool keepDims)
bool m_ProjectionEnabled
Enable/disable the projection layer.
DataLayout m_DataLayout
The data layout to be used (NCHW, NHWC).
PreCompiledDescriptor(unsigned int numInputSlots=1u, unsigned int numOutputSlots=1u)
TransposeConvolution2dDescriptor()
SliceDescriptor(const std::vector< unsigned int > &begin, const std::vector< unsigned int > &size)
UnaryOperation m_Operation
Specifies the elementwiseUnary operation to execute.
uint32_t m_Axis
0-based axis along which to stack the input tensors.
A ViewsDescriptor for the SplitterLayer.
float m_ScaleW
Center size encoding scale weight.
uint32_t m_PadBottom
Padding bottom value in the height dimension.
bool m_BiasEnabled
Enable/disable bias.
float m_K
Kappa value used for the across channel normalization equation.
int m_Axis
Scalar, defaulted to the last index (-1), specifying the dimension the activation will be performed o...
A TransposeConvolution2dDescriptor for the TransposeConvolution2dLayer.
uint32_t m_StrideY
Stride value when proceeding through input for the height dimension.
uint32_t m_PoolWidth
Pooling width value.
uint32_t m_PadBottom
Padding bottom value in the height dimension.
uint32_t m_PadLeft
Padding left value in the width dimension.
float m_ClippingThresProj
Clipping threshold value for the projection.
uint32_t m_PoolDepth
Pooling depth value.
void swap(OriginsDescriptor &first, OriginsDescriptor &second)
int32_t m_ShrinkAxisMask
Shrink axis mask value. If set, the nth specification shrinks the dimensionality by 1...
A ReshapeDescriptor for the ReshapeLayer.
NormalizationDescriptor()
std::vector< int > m_Begin
Begin values for the input that will be sliced.
bool IsNull() const override
uint32_t m_PadBack
Padding back value in the depth dimension.
#define ARMNN_NO_DEPRECATE_WARN_BEGIN
float m_PadValue
Optional value to use for padding, defaults to 0.
DataLayout m_DataLayout
The data layout to be used (NCHW, NHWC).
DataLayout m_DataLayout
The data layout to be used (NCHW, NHWC).
A ComparisonDescriptor for the ComparisonLayer.
float m_ScaleX
Center size encoding scale x.
TensorShape m_InputShape
Required shape of all input tensors.
bool m_TransposeWeightMatrix
Enable/disable transpose weight matrix.
float m_Min
Minimum value.
PermuteDescriptor(const PermutationVector &dimMappings)
uint32_t m_PoolWidth
Pooling width value.
bool m_PeepholeEnabled
Enable/disable peephole.
uint32_t m_StrideX
Stride value when proceeding through input for the width dimension.
A Convolution2dDescriptor for the Convolution2dLayer.
float m_Alpha
Alpha value for the normalization equation.
PadDescriptor(const std::vector< std::pair< unsigned int, unsigned int >> &padList, const float &padValue=0, const PaddingMode &paddingMode=PaddingMode::Constant)
uint32_t m_PadLeft
Padding left value in the width dimension.
bool m_KeepDims
if true then output shape has no change.
float m_HiddenStateScale
Hidden State quantization scale.
bool m_BiasEnabled
Enable/disable bias.
std::vector< unsigned int > m_OutputShape
float m_OutputIntermediateScale
Output intermediate quantization scale.
ResizeMethod m_Method
The Interpolation method to use (Bilinear, NearestNeighbor).
float m_Gamma
Gamma, the scale scalar value applied for the normalized tensor. Defaults to 1.0. ...
float m_Beta
Exponentiation value.
std::vector< unsigned int > m_Size
Size of the slice in each dimension.
ActivationDescriptor(armnn::ActivationFunction activation, float a=0, float b=0)
The padding fields don't count and are ignored.
float m_Eps
Value to add to the variance. Used to avoid dividing by zero.
PaddingMethod m_PaddingMethod
The padding method to be used. (Exclude, IgnoreValue).
ArgMinMaxFunction m_Function
Specify if the function is to find Min or Max.
uint32_t m_DetectionsPerClass
Detections per classes, used in Regular NMS.
DataLayout m_DataLayout
The data layout to be used (NCHW, NHWC).
NormalizationAlgorithmChannel
bool m_OutputShapeEnabled
Output shape if it has been specified.
DataLayout m_DataLayout
The data layout to be used (NCHW, NHWC).
BatchToSpaceNdDescriptor()
LogicalBinaryDescriptor()
uint32_t m_PadRight
Padding right value in the width dimension.
uint32_t m_PadTop
Padding top value in the height dimension.
uint32_t m_PadBottom
Padding bottom value in the height dimension.
bool m_BiasEnabled
Enable/disable bias.
A LogicalBinaryDescriptor for the LogicalBinaryLayer.
uint32_t m_PadRight
Padding right value in the width dimension.
DataLayout m_DataLayout
The data layout to be used (NCHW, NHWC).
std::vector< std::pair< unsigned int, unsigned int > > m_PadList
Specifies the padding for input dimension.
ReduceOperation m_ReduceOperation
Specifies the reduction operation to execute.
bool m_TimeMajor
Enable/disable time major.
ChannelShuffleDescriptor(const uint32_t &numGroups, const uint32_t &axis)
Copyright (c) 2021 ARM Limited and Contributors.
DataLayout m_DataLayout
The data layout to be used (NCDHW, NDHWC).
uint32_t m_PadBottom
Padding bottom value in the height dimension.
int32_t m_BeginMask
Begin mask value.
uint32_t m_PadFront
Padding front value in the depth dimension.
uint32_t m_DilationY
Dilation along y axis.
int32_t m_EndMask
End mask value.
A SpaceToDepthDescriptor for the SpaceToDepthLayer.
virtual ~BaseDescriptor()=default
std::vector< std::pair< unsigned int, unsigned int > > m_PadList
Specifies the padding values for the input dimension: heightPad{top, bottom} widthPad{left, right}.
uint32_t m_PoolHeight
Pooling height value.
uint32_t m_DilationX
Dilation along x axis.
uint32_t m_DilationY
Dilation factor value for height dimension.
StridedSliceDescriptor(const std::vector< int > &begin, const std::vector< int > &end, const std::vector< int > &stride)
LogicalBinaryOperation m_Operation
Specifies the logical operation to execute.
A BatchToSpaceNdDescriptor for the BatchToSpaceNdLayer.
uint32_t m_StrideX
Stride value when proceeding through input for the width dimension.
PermutationVector m_DimMappings
Indicates how to translate tensor elements from a given source into the target destination, when source and target potentially have different memory layouts e.g.
uint32_t m_StrideY
Stride value when proceeding through input for the height dimension.
uint32_t m_NumOutputs
Number of output tensors.
NormalizationAlgorithmMethod m_NormMethodType
Normalization method algorithm to use (LocalBrightness, LocalContrast).
A ResizeBilinearDescriptor for the ResizeBilinearLayer.
PaddingMethod
The padding method modifies the output of pooling layers.
DataLayout m_DataLayout
The data layout to be used (NCHW, NHWC).
uint32_t m_MaxClassesPerDetection
Maximum numbers of classes per detection, used in Fast NMS.
Base class for all descriptors.
std::vector< unsigned int > m_Axis
Values for the dimensions to reduce.
A StackDescriptor for the StackLayer.
DataLayout m_DataLayout
The data layout to be used (NCHW, NHWC).
L2NormalizationDescriptor()
TensorShape m_TargetShape
Target shape value.
ComparisonDescriptor(ComparisonOperation operation)
uint32_t m_PoolHeight
Pooling height value.
Convolution2dDescriptor()
uint32_t m_PadTop
Padding top value in the height dimension.
uint32_t m_MaxDetections
Maximum numbers of detections.
A PadDescriptor for the PadLayer.
FullyConnectedDescriptor()
uint32_t m_StrideX
Stride value when proceeding through input for the width dimension.
uint32_t m_PadBack
Padding back value in the depth dimension.
uint32_t m_StrideX
Stride value when proceeding through input for the width dimension.
bool operator==(const armnn::DataLayout &dataLayout, const DataLayoutIndexed &indexed)
Equality methods.
Null Descriptor used as a return value from the IConnectableLayer GetParameters method by layers whic...
bool m_LayerNormEnabled
Enable/disable layer normalization.
float m_NmsIouThreshold
Intersection over union threshold.
TransposeDescriptor(const PermutationVector &dimMappings)
An LstmDescriptor for the LstmLayer.
uint32_t m_PadRight
Padding right value in the width dimension.
#define ARMNN_NO_DEPRECATE_WARN_END
uint32_t m_DilationX
Dilation factor value for width dimension.
uint32_t m_PadTop
Padding top value in the height dimension.
std::vector< unsigned int > m_Begin
Beginning indices of the slice in each dimension.
int32_t m_NewAxisMask
New axis mask value.
bool m_KeepDims
Enable/disable keep dimensions. If true, then the reduced dimensions that are of length 1 are kept...
std::vector< unsigned int > m_BlockShape
Block shape values.
float m_Eps
Epsilon, small scalar value added to variance to avoid dividing by zero. Defaults to 1e-12f...
A L2NormalizationDescriptor for the L2NormalizationLayer.
An ArgMinMaxDescriptor for ArgMinMaxLayer.
An OriginsDescriptor for the ConcatLayer.
A ReduceDescriptor for the REDUCE operators.
float m_ProjectionClip
Clipping threshold value for the projection.
A FullyConnectedDescriptor for the FullyConnectedLayer.
ChannelShuffleDescriptor()
int32_t m_EllipsisMask
Ellipsis mask value.
bool m_BiasEnabled
Enable/disable bias.
float m_InputIntermediateScale
Input intermediate quantization scale.
OutputShapeRounding m_OutputShapeRounding
The rounding method for the output shape. (Floor, Ceiling).
A FakeQuantizationDescriptor for the FakeQuantizationLayer.
DepthwiseConvolution2dDescriptor()
SpaceToBatchNdDescriptor()
uint32_t m_TargetWidth
Target width value.
A GatherDescriptor for the GatherLayer.
uint32_t m_PadBottom
Padding bottom value in the height dimension.
bool m_PeepholeEnabled
Enable/disable peephole.
uint32_t m_NumClasses
Number of classes.
bool m_HalfPixelCenters
Half Pixel Centers.
ARMNN_NO_DEPRECATE_WARN_BEGIN struct ARMNN_DEPRECATED_MSG_REMOVAL_DATE("ResizeBilinearQueueDescriptor is deprecated use ResizeQueueDescriptor instead", "22.08") ResizeBilinearQueueDescriptor
uint32_t m_PadTop
Padding top value in the height dimension.
A StandInDescriptor for the StandIn layer.
A QLstmDescriptor for the QLstmLayer.
unsigned int m_NumInputSlots
bool m_UseRegularNms
Use Regular NMS.
uint32_t m_PadFront
Padding front value in the depth dimension.
DataLayout m_DataLayout
The data layout to be used (NCHW, NHWC).
std::vector< unsigned int > m_BlockShape
Block shape value.
std::vector< int > m_Stride
Stride values for the input that will be sliced.
PaddingMode
The padding mode controls whether the padding should be filled with constant values (Constant)...
An ActivationDescriptor for the ActivationLayer.
SpaceToBatchNdDescriptor(const std::vector< unsigned int > &blockShape, const std::vector< std::pair< unsigned int, unsigned int >> &padList)
uint32_t m_NumInputs
Number of input tensors.
uint32_t m_PadLeft
Padding left value in the width dimension.
uint32_t m_TargetHeight
Target height value.
uint32_t m_ActivationFunc
The activation function to use.
A SliceDescriptor for the SliceLayer.
uint32_t m_StrideY
Stride value when proceeding through input for the height dimension.
ElementwiseUnaryDescriptor()
A Convolution3dDescriptor for the Convolution3dLayer.
uint32_t m_PadRight
Padding right value in the width dimension.
float m_ClippingThresCell
Clipping threshold value for the cell state.
unsigned int m_BlockSize
Scalar specifying the input block size. It must be >= 1.
uint32_t m_NumGroups
Number of groups for the channel shuffle operation.
PaddingMode m_PaddingMode
Specifies the Padding mode (Constant, Reflect or Symmetric)
DataLayout m_DataLayout
The data layout to be used (NCHW, NHWC).
float m_ForgetIntermediateScale
Forget intermediate quantization scale.
DataLayout m_DataLayout
The data layout to be used (NCHW, NHWC).
float m_Beta
Beta, the offset scalar value applied for the normalized tensor. Defaults to 1.0. ...
InstanceNormalizationDescriptor()
A Pooling3dDescriptor for the Pooling3dLayer.
uint32_t m_StrideZ
Stride value when proceeding through input for the depth dimension.
std::vector< uint32_t > m_vAxis
The indices of the dimensions to reduce.
float m_ScaleH
Center size encoding scale height.
ComparisonOperation m_Operation
Specifies the comparison operation to execute.
std::vector< int > m_End
End values for the input that will be sliced.
A SpaceToBatchNdDescriptor for the SpaceToBatchNdLayer.
DataLayout m_DataLayout
The data layout to be used (NDHWC, NCDHW).
NormalizationAlgorithmChannel m_NormChannelType
Normalization channel algorithm to use (Across, Within).
float m_CellClip
Clipping threshold value for the cell state.
float m_A
Alpha upper bound value used by the activation functions. (BoundedReLu, Linear, TanH, Elu).
uint32_t m_DilationX
Dilation along x axis.
FillDescriptor(const float &value)
DataLayout m_DataLayout
The data layout to be used (NCHW, NHWC).
bool m_CifgEnabled
Enable/disable cifg (coupled input & forget gate).
StandInDescriptor(uint32_t numInputs, uint32_t numOutputs)
uint32_t m_PadLeft
Padding left value in the width dimension.
bool m_AlignCorners
Aligned corners.
uint32_t m_StrideX
Stride value when proceeding through input for the width dimension.
int32_t m_Axis
The axis in params to gather indices from.
A ElementwiseUnaryDescriptor for the ElementwiseUnaryLayer.
PoolingAlgorithm m_PoolType
The pooling algorithm to use (Max. Average, L2).
uint32_t m_StrideY
Stride value when proceeding through input for the height dimension.
uint32_t m_StrideY
Stride value when proceeding through input for the height dimension.
uint32_t m_PadLeft
Padding left value in the width dimension.
SpaceToDepthDescriptor(unsigned int blockSize, DataLayout dataLayout)
std::vector< std::pair< unsigned int, unsigned int > > m_Crops
The values to crop from the input dimension.
uint32_t m_PadTop
Padding top value in the height dimension.
uint32_t m_PadTop
Padding top value in the height dimension.
bool m_ProjectionEnabled
Enable/disable the projection layer.
OutputShapeRounding m_OutputShapeRounding
The rounding method for the output shape. (Floor, Ceiling).
uint32_t m_NumInputs
Number of input tensors.
FakeQuantizationDescriptor()
void SetConcatAxis(unsigned int concatAxis)
Set the concatenation axis value.
A MeanDescriptor for the MeanLayer.
Convolution3dDescriptor()
bool m_LayerNormEnabled
Enable/disable layer normalization.
uint32_t m_PadRight
Padding right value in the width dimension.
A TransposeDescriptor for the TransposeLayer.
A StridedSliceDescriptor for the StridedSliceLayer.
uint32_t m_Axis
Axis to apply channel shuffle operation on.
int m_Axis
Axis to reduce across the input tensor.
float m_ScaleY
Center size encoding scale y.
OriginsDescriptor CreateDescriptorForConcatenation(TensorShapeIt first, TensorShapeIt last, unsigned int concatenationDimension)
Convenience template to create an OriginsDescriptor to use when creating a ConcatLayer for performing...
float m_NmsScoreThreshold
NMS score threshold.
A PreCompiledDescriptor for the PreCompiledLayer.
GatherDescriptor(int32_t axis)
Krichevsky 2012: Local Brightness Normalization.
A Pooling2dDescriptor for the Pooling2dLayer.
A NormalizationDescriptor for the NormalizationLayer.
uint32_t m_StrideX
Stride value when proceeding through input for the width dimension.
DataLayout m_DataLayout
The data layout to be used (NCHW, NHWC).
An InstanceNormalizationDescriptor for InstanceNormalizationLayer.
PaddingMethod m_PaddingMethod
The padding method to be used. (Exclude, IgnoreValue).
NormalizationAlgorithmMethod
unsigned int m_NumOutputSlots
A ChannelShuffleDescriptor for the ChannelShuffle operator.
StackDescriptor(uint32_t axis, uint32_t numInputs, const TensorShape &inputShape)
ReshapeDescriptor(const TensorShape &shape)
float m_CellIntermediateScale
Cell intermediate quantization scale.
LogicalBinaryDescriptor(LogicalBinaryOperation operation)
DetectionPostProcessDescriptor()
uint32_t m_DilationZ
Dilation along z axis.
float m_B
Beta lower bound value used by the activation functions. (BoundedReLu, Linear, TanH).
A SoftmaxDescriptor for the SoftmaxLayer.
float m_Beta
Beta value for the normalization equation.
float m_Max
Maximum value.
virtual bool IsNull() const
uint32_t m_StrideZ
Stride value when proceeding through input for the depth dimension.
BatchToSpaceNdDescriptor(std::vector< unsigned int > blockShape, std::vector< std::pair< unsigned int, unsigned int >> crops)
bool m_CifgEnabled
Enable/disable CIFG (coupled input & forget gate).
PermutationVector m_DimMappings
Indicates how to translate tensor elements from a given source into the target destination, when source and target potentially have different memory layouts e.g.
uint32_t m_NormSize
Depth radius value.
ActivationFunction m_Function
The activation function to use (Sigmoid, TanH, Linear, ReLu, BoundedReLu, SoftReLu, LeakyReLu, Abs, Sqrt, Square, Elu).
armnn::DataType m_Output_Type
Deprecated and will be removed in future release.
uint32_t m_StrideY
Stride value when proceeding through input for the height dimension.
A DepthwiseConvolution2dDescriptor for the DepthwiseConvolution2dLayer.
uint32_t m_DilationY
Dilation along y axis.
A FillDescriptor for the FillLayer.
A BatchNormalizationDescriptor for the BatchNormalizationLayer.
uint32_t m_PadLeft
Padding left value in the width dimension.
Status SetViewOriginCoord(uint32_t view, uint32_t coord, uint32_t value)
Set the view origin coordinates.
A PermuteDescriptor for the PermuteLayer.
uint32_t m_PadRight
Padding right value in the width dimension.
int32_t m_HiddenStateZeroPoint
Hidden State zero point.
bool m_ConstantWeights
Enable/disable constant weights and biases.
BatchNormalizationDescriptor()