69 template <LayerType Type>
72 template <LayerType Type>
78 #define DECLARE_LAYER_IMPL(_, LayerName) \ 79 class LayerName##Layer; \ 81 struct LayerTypeOfImpl<LayerType::_##LayerName> \ 83 using Type = LayerName##Layer; \ 86 constexpr LayerType LayerEnumOf(const LayerName##Layer*) \ 88 return LayerType::_##LayerName; \ 91 #define DECLARE_LAYER(LayerName) DECLARE_LAYER_IMPL(, LayerName) void BatchToSpaceNd(const DataLayoutIndexed &dataLayout, const TensorInfo &inputTensorInfo, const TensorInfo &outputTensorInfo, const std::vector< unsigned int > &blockShape, const std::vector< std::pair< unsigned int, unsigned int >> &cropsData, Decoder< float > &inputDecoder, Encoder< float > &outputEncoder)
void Pooling2d(Decoder< float > &rInputDecoder, Encoder< float > &rOutputEncoder, const TensorInfo &inputInfo, const TensorInfo &outputInfo, const Pooling2dDescriptor ¶ms)
Computes the Pooling2d operation.
void Permute(const armnn::TensorShape &dstShape, const armnn::PermutationVector &mappings, const void *src, void *dst, size_t dataTypeSize)
void FakeQuantization(const float *inputData, float *outputData, uint32_t numElements, float min, float max)
#define DECLARE_LAYER(LayerName)
void Debug(const TensorInfo &inputInfo, const T *inputData, LayerGuid guid, const std::string &layerName, unsigned int slotIndex)
void DetectionPostProcess(const TensorInfo &boxEncodingsInfo, const TensorInfo &scoresInfo, const TensorInfo &anchorsInfo, const TensorInfo &detectionBoxesInfo, const TensorInfo &detectionClassesInfo, const TensorInfo &detectionScoresInfo, const TensorInfo &numDetectionsInfo, const DetectionPostProcessDescriptor &desc, Decoder< float > &boxEncodings, Decoder< float > &scores, Decoder< float > &anchors, float *detectionBoxes, float *detectionClasses, float *detectionScores, float *numDetections)
QuantizedType Quantize(float value, float scale, int32_t offset)
Explicit specialization of Quantize for int8_t.
void SpaceToBatchNd(const TensorInfo &inputInfo, const TensorInfo &outputInfo, const SpaceToBatchNdDescriptor ¶ms, Decoder< float > &inputData, Encoder< float > &outputData)
void Gather(const TensorInfo ¶msInfo, const TensorInfo &indicesInfo, const TensorInfo &outputInfo, Decoder< float > ¶ms, const int32_t *indices, Encoder< float > &output)
typename LayerTypeOfImpl< Type >::Type LayerTypeOf
float Dequantize(QuantizedType value, float scale, int32_t offset)
void Softmax(Decoder< float > &in, Encoder< float > &out, const TensorInfo &inputTensorInfo, float beta, int axis)
Computes the softmax function on some inputs, into outputs, with a shape given by tensorInfo...
void Pad(const TensorInfo &inputInfo, const TensorInfo &outputInfo, std::vector< std::pair< unsigned int, unsigned int >> m_padList, const T *inputData, T *outData, const float padValue)
void ArgMinMax(Decoder< float > &in, int32_t *out, const TensorInfo &inputTensorInfo, const TensorInfo &outputTensorInfo, ArgMinMaxFunction function, int axis)
void Mean(const armnn::TensorInfo &inputInfo, const armnn::TensorInfo &outputInfo, const std::vector< unsigned int > &axis, Decoder< float > &input, Encoder< float > &output)
void FullyConnected(const TensorShape &rInputShape, Decoder< float > &rInputDecoder, const TensorShape &rOutputShape, Encoder< float > &rOutputEncoder, Decoder< float > &rWeightDecoder, Decoder< float > &rBiasDecoder, const bool biasEnabled, const unsigned int K, const bool transposeWeights)
Performs a matrix multiplication and optionally adds a bias.
void StridedSlice(const TensorInfo &inputInfo, const StridedSliceDescriptor ¶ms, const void *inputData, void *outputData, unsigned int dataTypeSize)
void Slice(const TensorInfo &inputInfo, const SliceDescriptor &descriptor, const void *inputData, void *outputData, unsigned int dataTypeSize)
void SpaceToDepth(const TensorInfo &inputInfo, const TensorInfo &outputInfo, const SpaceToDepthDescriptor ¶ms, Decoder< float > &inputData, Encoder< float > &outputData)
void Splitter(const SplitterQueueDescriptor &data)
void Resize(Decoder< float > &in, const TensorInfo &inputInfo, Encoder< float > &out, const TensorInfo &outputInfo, DataLayoutIndexed dataLayout, armnn::ResizeMethod resizeMethod, bool alignCorners)
float Activation(float in, ActivationFunction function, float a, float b)
void Stack(const StackQueueDescriptor &data, std::vector< std::unique_ptr< Decoder< float >>> &inputs, Encoder< float > &output)
void DepthToSpace(const TensorInfo &inputInfo, const DepthToSpaceDescriptor &descriptor, const void *inputData, void *outputData, unsigned int dataTypeSize)
constexpr LayerType LayerEnumOf(const T *=nullptr)
void LogSoftmax(Decoder< float > &input, Encoder< float > &output, const TensorInfo &inputInfo, const LogSoftmaxDescriptor &descriptor)