| // |
| // Copyright © 2017 Arm Ltd. All rights reserved. |
| // SPDX-License-Identifier: MIT |
| // |
| |
| #include "RefLayerSupport.hpp" |
| |
| #include <LayerSupportCommon.hpp> |
| |
| #include <armnn/Descriptors.hpp> |
| #include <armnn/Types.hpp> |
| #include <armnn/Tensor.hpp> |
| |
| #include <boost/core/ignore_unused.hpp> |
| #include "InternalTypes.hpp" |
| |
| using namespace boost; |
| |
| namespace armnn |
| { |
| |
| bool RefLayerSupport::IsActivationSupported(const TensorInfo& input, |
| const TensorInfo& output, |
| const ActivationDescriptor& descriptor, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| return armnn::IsActivationSupportedRef(input, output, descriptor, reasonIfUnsupported); |
| } |
| |
| bool RefLayerSupport::IsAdditionSupported(const TensorInfo& input0, |
| const TensorInfo& input1, |
| const TensorInfo& output, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| return armnn::IsAdditionSupportedRef(input0, input1, output, reasonIfUnsupported); |
| } |
| |
| bool RefLayerSupport::IsBatchNormalizationSupported(const TensorInfo& input, |
| const TensorInfo& output, |
| const TensorInfo& mean, |
| const TensorInfo& var, |
| const TensorInfo& beta, |
| const TensorInfo& gamma, |
| const BatchNormalizationDescriptor& descriptor, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| return armnn::IsBatchNormalizationSupportedRef(input, |
| output, |
| mean, |
| var, |
| beta, |
| gamma, |
| descriptor, |
| reasonIfUnsupported); |
| } |
| |
| bool RefLayerSupport::IsConstantSupported(const TensorInfo& output, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| return armnn::IsConstantSupportedRef(output, reasonIfUnsupported); |
| } |
| |
| bool RefLayerSupport::IsConvertFp16ToFp32Supported(const TensorInfo& input, |
| const TensorInfo& output, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| return armnn::IsConvertFp16ToFp32SupportedRef(input, output, reasonIfUnsupported); |
| } |
| |
| bool RefLayerSupport::IsConvertFp32ToFp16Supported(const TensorInfo& input, |
| const TensorInfo& output, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| return armnn::IsConvertFp32ToFp16SupportedRef(input, output, reasonIfUnsupported); |
| } |
| |
| bool RefLayerSupport::IsConvolution2dSupported(const TensorInfo& input, |
| const TensorInfo& output, |
| const Convolution2dDescriptor& descriptor, |
| const TensorInfo& weights, |
| const Optional<TensorInfo>& biases, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| return armnn::IsConvolution2dSupportedRef(input, |
| output, |
| descriptor, |
| weights, |
| biases, |
| reasonIfUnsupported); |
| } |
| |
| bool RefLayerSupport::IsDepthwiseConvolutionSupported(const TensorInfo& input, |
| const TensorInfo& output, |
| const DepthwiseConvolution2dDescriptor& descriptor, |
| const TensorInfo& weights, |
| const Optional<TensorInfo>& biases, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| return armnn::IsDepthwiseConvolutionSupportedRef(input, |
| output, |
| descriptor, |
| weights, |
| biases, |
| reasonIfUnsupported); |
| } |
| |
| bool RefLayerSupport::IsDivisionSupported(const TensorInfo& input0, |
| const TensorInfo& input1, |
| const TensorInfo& output, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| return armnn::IsDivisionSupportedRef(input0, input1, output, reasonIfUnsupported); |
| } |
| |
| bool RefLayerSupport::IsFakeQuantizationSupported(const TensorInfo& input, |
| const FakeQuantizationDescriptor& descriptor, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| return armnn::IsFakeQuantizationSupportedRef(input, descriptor, reasonIfUnsupported); |
| } |
| |
| bool RefLayerSupport::IsFloorSupported(const TensorInfo& input, |
| const TensorInfo& output, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| return armnn::IsFloorSupportedRef(input, output, reasonIfUnsupported); |
| } |
| |
| bool RefLayerSupport::IsFullyConnectedSupported(const TensorInfo& input, |
| const TensorInfo& output, |
| const TensorInfo& weights, |
| const TensorInfo& biases, |
| const FullyConnectedDescriptor& descriptor, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| return armnn::IsFullyConnectedSupportedRef(input, |
| output, |
| weights, |
| biases, |
| descriptor, |
| reasonIfUnsupported); |
| } |
| |
| bool RefLayerSupport::IsInputSupported(const TensorInfo& input, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| return armnn::IsInputSupportedRef(input, reasonIfUnsupported); |
| } |
| |
| bool RefLayerSupport::IsL2NormalizationSupported(const TensorInfo& input, |
| const TensorInfo& output, |
| const L2NormalizationDescriptor& descriptor, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| return armnn::IsL2NormalizationSupportedRef(input, output, descriptor, reasonIfUnsupported); |
| } |
| |
| bool RefLayerSupport::IsLstmSupported(const TensorInfo& input, |
| const TensorInfo& outputStateIn, |
| const TensorInfo& cellStateIn, |
| const TensorInfo& scratchBuffer, |
| const TensorInfo& outputStateOut, |
| const TensorInfo& cellStateOut, |
| const TensorInfo& output, |
| const LstmDescriptor& descriptor, |
| const TensorInfo& inputToForgetWeights, |
| const TensorInfo& inputToCellWeights, |
| const TensorInfo& inputToOutputWeights, |
| const TensorInfo& recurrentToForgetWeights, |
| const TensorInfo& recurrentToCellWeights, |
| const TensorInfo& recurrentToOutputWeights, |
| const TensorInfo& forgetGateBias, |
| const TensorInfo& cellBias, |
| const TensorInfo& outputGateBias, |
| const TensorInfo* inputToInputWeights, |
| const TensorInfo* recurrentToInputWeights, |
| const TensorInfo* cellToInputWeights, |
| const TensorInfo* inputGateBias, |
| const TensorInfo* projectionWeights, |
| const TensorInfo* projectionBias, |
| const TensorInfo* cellToForgetWeights, |
| const TensorInfo* cellToOutputWeights, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| return armnn::IsLstmSupportedRef(input, |
| outputStateIn, |
| cellStateIn, |
| scratchBuffer, |
| outputStateOut, |
| cellStateOut, |
| output, |
| descriptor, |
| inputToForgetWeights, |
| inputToCellWeights, |
| inputToOutputWeights, |
| recurrentToForgetWeights, |
| recurrentToCellWeights, |
| recurrentToOutputWeights, |
| forgetGateBias, |
| cellBias, |
| outputGateBias, |
| inputToInputWeights, |
| recurrentToInputWeights, |
| cellToInputWeights, |
| inputGateBias, |
| projectionWeights, |
| projectionBias, |
| cellToForgetWeights, |
| cellToOutputWeights, |
| reasonIfUnsupported); |
| } |
| |
| bool RefLayerSupport::IsMeanSupported(const TensorInfo& input, |
| const TensorInfo& output, |
| const MeanDescriptor& descriptor, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| return armnn::IsMeanSupportedRef(input, output, descriptor,reasonIfUnsupported); |
| } |
| |
| bool RefLayerSupport::IsMergerSupported(const std::vector<const TensorInfo*> inputs, |
| const OriginsDescriptor& descriptor, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| return armnn::IsMergerSupportedRef(inputs, descriptor, reasonIfUnsupported); |
| } |
| |
| bool RefLayerSupport::IsMultiplicationSupported(const TensorInfo& input0, |
| const TensorInfo& input1, |
| const TensorInfo& output, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| return armnn::IsMultiplicationSupportedRef(input0, input1, output, reasonIfUnsupported); |
| } |
| |
| bool RefLayerSupport::IsNormalizationSupported(const TensorInfo& input, |
| const TensorInfo& output, |
| const NormalizationDescriptor& descriptor, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| return armnn::IsNormalizationSupportedRef(input, |
| output, |
| descriptor, |
| reasonIfUnsupported); |
| } |
| |
| bool RefLayerSupport::IsOutputSupported(const TensorInfo& output, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| return armnn::IsOutputSupportedRef(output, reasonIfUnsupported); |
| } |
| |
| bool RefLayerSupport::IsPadSupported(const TensorInfo& input, |
| const TensorInfo& output, |
| const PadDescriptor& descriptor, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| return armnn::IsPadSupportedRef(input, output, descriptor, reasonIfUnsupported); |
| } |
| |
| bool RefLayerSupport::IsPermuteSupported(const TensorInfo& input, |
| const TensorInfo& output, |
| const PermuteDescriptor& descriptor, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| return armnn::IsPermuteSupportedRef(input, output, descriptor, reasonIfUnsupported); |
| } |
| |
| bool RefLayerSupport::IsPooling2dSupported(const TensorInfo& input, |
| const TensorInfo& output, |
| const Pooling2dDescriptor& descriptor, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| return armnn::IsPooling2dSupportedRef(input, output, descriptor, reasonIfUnsupported); |
| } |
| |
| bool RefLayerSupport::IsReshapeSupported(const TensorInfo& input, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| return armnn::IsReshapeSupportedRef(input, reasonIfUnsupported); |
| } |
| |
| bool RefLayerSupport::IsResizeBilinearSupported(const TensorInfo& input, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| return armnn::IsResizeBilinearSupportedRef(input, reasonIfUnsupported); |
| } |
| |
| bool RefLayerSupport::IsSoftmaxSupported(const TensorInfo& input, |
| const TensorInfo& output, |
| const SoftmaxDescriptor& descriptor, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| return armnn::IsSoftmaxSupportedRef(input, output, descriptor, reasonIfUnsupported); |
| } |
| |
| bool RefLayerSupport::IsSplitterSupported(const TensorInfo& input, |
| const ViewsDescriptor& descriptor, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| return armnn::IsSplitterSupportedRef(input, descriptor, reasonIfUnsupported); |
| } |
| |
| bool RefLayerSupport::IsSubtractionSupported(const TensorInfo& input0, |
| const TensorInfo& input1, |
| const TensorInfo& output, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| return armnn::IsSubtractionSupportedRef(input0, input1, output, reasonIfUnsupported); |
| } |
| |
| // |
| // Implementation functions |
| // |
| // TODO: Functions kept for backward compatibility. Remove once transition to plugable backends is complete! |
| |
| template<typename Float32Func, typename Uint8Func, typename ... Params> |
| bool IsSupportedForDataTypeRef(Optional<std::string&> reasonIfUnsupported, |
| DataType dataType, |
| Float32Func floatFuncPtr, |
| Uint8Func uint8FuncPtr, |
| Params&&... params) |
| { |
| return IsSupportedForDataTypeGeneric(reasonIfUnsupported, |
| dataType, |
| &FalseFunc<Params...>, |
| floatFuncPtr, |
| uint8FuncPtr, |
| std::forward<Params>(params)...); |
| } |
| |
| bool IsActivationSupportedRef(const TensorInfo& input, |
| const TensorInfo& output, |
| const ActivationDescriptor& descriptor, |
| Optional<std::string&> reasonIfUnsupported) |
| { |
| ignore_unused(output); |
| ignore_unused(descriptor); |
| return IsSupportedForDataTypeRef(reasonIfUnsupported, |
| input.GetDataType(), |
| &TrueFunc<>, |
| &TrueFunc<>); |
| } |
| |
| bool IsAdditionSupportedRef(const TensorInfo& input0, |
| const TensorInfo& input1, |
| const TensorInfo& output, |
| Optional<std::string&> reasonIfUnsupported) |
| { |
| ignore_unused(input1); |
| ignore_unused(output); |
| return IsSupportedForDataTypeRef(reasonIfUnsupported, |
| input0.GetDataType(), |
| &TrueFunc<>, |
| &TrueFunc<>); |
| } |
| |
| bool IsBatchNormalizationSupportedRef(const TensorInfo& input, |
| const TensorInfo& output, |
| const TensorInfo& mean, |
| const TensorInfo& var, |
| const TensorInfo& beta, |
| const TensorInfo& gamma, |
| const BatchNormalizationDescriptor& descriptor, |
| Optional<std::string&> reasonIfUnsupported) |
| { |
| ignore_unused(descriptor); |
| return IsSupportedForDataTypeRef(reasonIfUnsupported, |
| input.GetDataType(), |
| &TrueFunc<>, |
| &TrueFunc<>); |
| } |
| |
| bool IsConstantSupportedRef(const TensorInfo& output, |
| Optional<std::string&> reasonIfUnsupported) |
| { |
| return IsSupportedForDataTypeRef(reasonIfUnsupported, |
| output.GetDataType(), |
| &TrueFunc<>, |
| &TrueFunc<>); |
| } |
| |
| bool IsConvolution2dSupportedRef(const TensorInfo& input, |
| const TensorInfo& output, |
| const Convolution2dDescriptor& descriptor, |
| const TensorInfo& weights, |
| const Optional<TensorInfo>& biases, |
| Optional<std::string&> reasonIfUnsupported) |
| { |
| ignore_unused(descriptor); |
| ignore_unused(output); |
| ignore_unused(weights); |
| ignore_unused(biases); |
| return IsSupportedForDataTypeRef(reasonIfUnsupported, |
| input.GetDataType(), |
| &TrueFunc<>, |
| &TrueFunc<>); |
| } |
| |
| bool IsDepthwiseConvolutionSupportedRef(const TensorInfo& input, |
| const TensorInfo& output, |
| const DepthwiseConvolution2dDescriptor& descriptor, |
| const TensorInfo& weights, |
| const Optional<TensorInfo>& biases, |
| Optional<std::string&> reasonIfUnsupported) |
| { |
| ignore_unused(output); |
| ignore_unused(descriptor); |
| ignore_unused(weights); |
| ignore_unused(biases); |
| return IsSupportedForDataTypeRef(reasonIfUnsupported, |
| input.GetDataType(), |
| &TrueFunc<>, |
| &TrueFunc<>); |
| } |
| |
| bool IsDivisionSupportedRef(const TensorInfo& input0, |
| const TensorInfo& input1, |
| const TensorInfo& output, |
| Optional<std::string&> reasonIfUnsupported) |
| { |
| ignore_unused(input1); |
| ignore_unused(output); |
| return IsSupportedForDataTypeRef(reasonIfUnsupported, |
| input0.GetDataType(), |
| &TrueFunc<>, |
| &TrueFunc<>); |
| } |
| |
| bool IsSubtractionSupportedRef(const TensorInfo& input0, |
| const TensorInfo& input1, |
| const TensorInfo& output, |
| Optional<std::string&> reasonIfUnsupported) |
| { |
| ignore_unused(input1); |
| ignore_unused(output); |
| return IsSupportedForDataTypeRef(reasonIfUnsupported, |
| input0.GetDataType(), |
| &TrueFunc<>, |
| &TrueFunc<>); |
| } |
| |
| bool IsFullyConnectedSupportedRef(const TensorInfo& input, |
| const TensorInfo& output, |
| const TensorInfo& weights, |
| const TensorInfo& biases, |
| const FullyConnectedDescriptor& descriptor, |
| Optional<std::string&> reasonIfUnsupported) |
| { |
| ignore_unused(output); |
| ignore_unused(descriptor); |
| ignore_unused(weights); |
| ignore_unused(biases); |
| return IsSupportedForDataTypeRef(reasonIfUnsupported, |
| input.GetDataType(), |
| &TrueFunc<>, |
| &TrueFunc<>); |
| } |
| |
| bool IsInputSupportedRef(const TensorInfo& input, |
| Optional<std::string&> reasonIfUnsupported) |
| { |
| return IsSupportedForDataTypeRef(reasonIfUnsupported, |
| input.GetDataType(), |
| &TrueFunc<>, |
| &TrueFunc<>); |
| } |
| |
| bool IsL2NormalizationSupportedRef(const TensorInfo& input, |
| const TensorInfo& output, |
| const L2NormalizationDescriptor& descriptor, |
| Optional<std::string&> reasonIfUnsupported) |
| { |
| ignore_unused(output); |
| ignore_unused(descriptor); |
| return IsSupportedForDataTypeRef(reasonIfUnsupported, |
| input.GetDataType(), |
| &TrueFunc<>, |
| &FalseFuncU8<>); |
| } |
| |
| bool IsMergerSupportedRef(const std::vector<const TensorInfo*> inputs, |
| const OriginsDescriptor& descriptor, |
| Optional<std::string&> reasonIfUnsupported) |
| { |
| ignore_unused(descriptor); |
| return IsSupportedForDataTypeRef(reasonIfUnsupported, |
| inputs[0]->GetDataType(), |
| &TrueFunc<>, |
| &TrueFunc<>); |
| } |
| |
| bool IsMultiplicationSupportedRef(const TensorInfo& input0, |
| const TensorInfo& input1, |
| const TensorInfo& output, |
| Optional<std::string&> reasonIfUnsupported) |
| { |
| ignore_unused(input1); |
| ignore_unused(output); |
| return IsSupportedForDataTypeRef(reasonIfUnsupported, |
| input0.GetDataType(), |
| &TrueFunc<>, |
| &TrueFunc<>); |
| } |
| |
| bool IsNormalizationSupportedRef(const TensorInfo& input, |
| const TensorInfo& output, |
| const NormalizationDescriptor& descriptor, |
| Optional<std::string&> reasonIfUnsupported) |
| { |
| ignore_unused(descriptor); |
| return IsSupportedForDataTypeRef(reasonIfUnsupported, |
| input.GetDataType(), |
| &TrueFunc<>, |
| &FalseFuncU8<>); |
| } |
| |
| bool IsOutputSupportedRef(const TensorInfo& output, |
| Optional<std::string&> reasonIfUnsupported) |
| { |
| return IsSupportedForDataTypeRef(reasonIfUnsupported, |
| output.GetDataType(), |
| &TrueFunc<>, |
| &TrueFunc<>); |
| } |
| |
| bool IsPermuteSupportedRef(const TensorInfo& input, |
| const TensorInfo& output, |
| const PermuteDescriptor& descriptor, |
| Optional<std::string&> reasonIfUnsupported) |
| { |
| ignore_unused(descriptor); |
| return IsSupportedForDataTypeRef(reasonIfUnsupported, |
| input.GetDataType(), |
| &TrueFunc<>, |
| &TrueFunc<>); |
| } |
| |
| bool IsPooling2dSupportedRef(const TensorInfo& input, |
| const TensorInfo& output, |
| const Pooling2dDescriptor& descriptor, |
| Optional<std::string&> reasonIfUnsupported) |
| { |
| ignore_unused(descriptor); |
| return IsSupportedForDataTypeRef(reasonIfUnsupported, |
| input.GetDataType(), |
| &TrueFunc<>, |
| &TrueFunc<>); |
| } |
| |
| bool IsResizeBilinearSupportedRef(const TensorInfo& input, |
| Optional<std::string&> reasonIfUnsupported) |
| { |
| return IsSupportedForDataTypeRef(reasonIfUnsupported, |
| input.GetDataType(), |
| &TrueFunc<>, |
| &TrueFunc<>); |
| } |
| |
| bool IsSoftmaxSupportedRef(const TensorInfo& input, |
| const TensorInfo& output, |
| const SoftmaxDescriptor& descriptor, |
| Optional<std::string&> reasonIfUnsupported) |
| { |
| ignore_unused(output); |
| ignore_unused(descriptor); |
| return IsSupportedForDataTypeRef(reasonIfUnsupported, |
| input.GetDataType(), |
| &TrueFunc<>, |
| &TrueFunc<>); |
| } |
| |
| bool IsSplitterSupportedRef(const TensorInfo& input, |
| const ViewsDescriptor& descriptor, |
| Optional<std::string&> reasonIfUnsupported) |
| { |
| ignore_unused(descriptor); |
| return IsSupportedForDataTypeRef(reasonIfUnsupported, |
| input.GetDataType(), |
| &TrueFunc<>, |
| &TrueFunc<>); |
| } |
| |
| bool IsFakeQuantizationSupportedRef(const TensorInfo& input, |
| const FakeQuantizationDescriptor& descriptor, |
| Optional<std::string&> reasonIfUnsupported) |
| { |
| ignore_unused(descriptor); |
| return IsSupportedForDataTypeRef(reasonIfUnsupported, |
| input.GetDataType(), |
| &TrueFunc<>, |
| &FalseFuncU8<>); |
| } |
| |
| bool IsReshapeSupportedRef(const TensorInfo& input, |
| Optional<std::string&> reasonIfUnsupported) |
| { |
| return IsSupportedForDataTypeRef(reasonIfUnsupported, |
| input.GetDataType(), |
| &TrueFunc<>, |
| &TrueFunc<>); |
| } |
| |
| bool IsFloorSupportedRef(const TensorInfo& input, |
| const TensorInfo& output, |
| Optional<std::string&> reasonIfUnsupported) |
| { |
| ignore_unused(output); |
| return IsSupportedForDataTypeRef(reasonIfUnsupported, |
| input.GetDataType(), |
| &TrueFunc<>, |
| &FalseFuncU8<>); |
| } |
| |
| bool IsLstmSupportedRef(const TensorInfo& input, |
| const TensorInfo& outputStateIn, |
| const TensorInfo& cellStateIn, |
| const TensorInfo& scratchBuffer, |
| const TensorInfo& outputStateOut, |
| const TensorInfo& cellStateOut, |
| const TensorInfo& output, |
| const LstmDescriptor& descriptor, |
| const TensorInfo& inputToForgetWeights, |
| const TensorInfo& inputToCellWeights, |
| const TensorInfo& inputToOutputWeights, |
| const TensorInfo& recurrentToForgetWeights, |
| const TensorInfo& recurrentToCellWeights, |
| const TensorInfo& recurrentToOutputWeights, |
| const TensorInfo& forgetGateBias, |
| const TensorInfo& cellBias, |
| const TensorInfo& outputGateBias, |
| const TensorInfo* inputToInputWeights, |
| const TensorInfo* recurrentToInputWeights, |
| const TensorInfo* cellToInputWeights, |
| const TensorInfo* inputGateBias, |
| const TensorInfo* projectionWeights, |
| const TensorInfo* projectionBias, |
| const TensorInfo* cellToForgetWeights, |
| const TensorInfo* cellToOutputWeights, |
| Optional<std::string&> reasonIfUnsupported) |
| { |
| ignore_unused(input); |
| ignore_unused(outputStateIn); |
| ignore_unused(cellStateIn); |
| ignore_unused(scratchBuffer); |
| ignore_unused(outputStateOut); |
| ignore_unused(cellStateOut); |
| ignore_unused(output); |
| ignore_unused(descriptor); |
| ignore_unused(inputToForgetWeights); |
| ignore_unused(inputToCellWeights); |
| ignore_unused(inputToOutputWeights); |
| ignore_unused(recurrentToForgetWeights); |
| ignore_unused(recurrentToCellWeights); |
| ignore_unused(recurrentToOutputWeights); |
| ignore_unused(forgetGateBias); |
| ignore_unused(cellBias); |
| ignore_unused(outputGateBias); |
| ignore_unused(inputToInputWeights); |
| ignore_unused(recurrentToInputWeights); |
| ignore_unused(cellToInputWeights); |
| ignore_unused(inputGateBias); |
| ignore_unused(projectionWeights); |
| ignore_unused(projectionBias); |
| ignore_unused(cellToForgetWeights); |
| ignore_unused(cellToOutputWeights); |
| ignore_unused(reasonIfUnsupported); |
| return false; |
| } |
| |
| bool IsConvertFp16ToFp32SupportedRef(const TensorInfo& input, |
| const TensorInfo& output, |
| Optional<std::string&> reasonIfUnsupported) |
| { |
| return (IsSupportedForDataTypeGeneric(reasonIfUnsupported, |
| input.GetDataType(), |
| &TrueFunc<>, |
| &FalseInputFuncF32<>, |
| &FalseFuncU8<>) && |
| IsSupportedForDataTypeGeneric(reasonIfUnsupported, |
| output.GetDataType(), |
| &FalseOutputFuncF16<>, |
| &TrueFunc<>, |
| &FalseFuncU8<>)); |
| } |
| |
| bool IsConvertFp32ToFp16SupportedRef(const TensorInfo& input, |
| const TensorInfo& output, |
| Optional<std::string&> reasonIfUnsupported) |
| { |
| return (IsSupportedForDataTypeGeneric(reasonIfUnsupported, |
| input.GetDataType(), |
| &FalseInputFuncF16<>, |
| &TrueFunc<>, |
| &FalseFuncU8<>) && |
| IsSupportedForDataTypeGeneric(reasonIfUnsupported, |
| output.GetDataType(), |
| &TrueFunc<>, |
| &FalseOutputFuncF32<>, |
| &FalseFuncU8<>)); |
| } |
| |
| bool IsMeanSupportedRef(const TensorInfo& input, |
| const TensorInfo& output, |
| const MeanDescriptor& descriptor, |
| Optional<std::string&> reasonIfUnsupported) |
| { |
| ignore_unused(output); |
| ignore_unused(descriptor); |
| return IsSupportedForDataTypeRef(reasonIfUnsupported, |
| input.GetDataType(), |
| &TrueFunc<>, |
| &TrueFunc<>); |
| } |
| |
| bool IsPadSupportedRef(const TensorInfo& input, |
| const TensorInfo& output, |
| const PadDescriptor& descriptor, |
| Optional<std::string&> reasonIfUnsupported) |
| { |
| ignore_unused(output); |
| ignore_unused(descriptor); |
| return false; |
| } |
| |
| } // namespace armnn |