diff options
Diffstat (limited to 'src/backends/cl/ClLayerSupport.cpp')
| -rw-r--r-- | src/backends/cl/ClLayerSupport.cpp | 304 |
1 files changed, 299 insertions, 5 deletions
diff --git a/src/backends/cl/ClLayerSupport.cpp b/src/backends/cl/ClLayerSupport.cpp index 494b339952..68563944b4 100644 --- a/src/backends/cl/ClLayerSupport.cpp +++ b/src/backends/cl/ClLayerSupport.cpp @@ -3,13 +3,10 @@ // SPDX-License-Identifier: MIT // -#include "LayerSupportCommon.hpp" - #include "ClLayerSupport.hpp" + #include "InternalTypes.hpp" -#include <armnn/Descriptors.hpp> -#include <armnn/Types.hpp> -#include <armnn/Tensor.hpp> +#include "LayerSupportCommon.hpp" #include <boost/core/ignore_unused.hpp> @@ -38,6 +35,303 @@ using namespace boost; namespace armnn { + +bool ClLayerSupport::IsActivationSupported(const TensorInfo& input, + const TensorInfo& output, + const ActivationDescriptor& descriptor, + Optional<std::string&> reasonIfUnsupported) const +{ + return armnn::IsActivationSupportedCl(input, output, descriptor, reasonIfUnsupported); +} + +bool ClLayerSupport::IsAdditionSupported(const TensorInfo& input0, + const TensorInfo& input1, + const TensorInfo& output, + Optional<std::string&> reasonIfUnsupported) const +{ + return armnn::IsAdditionSupportedCl(input0, input1, output, reasonIfUnsupported); +} + +bool ClLayerSupport::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::IsBatchNormalizationSupportedCl(input, + output, + mean, + var, + beta, + gamma, + descriptor, + reasonIfUnsupported); +} + +bool ClLayerSupport::IsConstantSupported(const TensorInfo& output, + Optional<std::string&> reasonIfUnsupported) const +{ + return armnn::IsConstantSupportedCl(output, reasonIfUnsupported); +} + +bool ClLayerSupport::IsConvertFp16ToFp32Supported(const TensorInfo& input, + const TensorInfo& output, + Optional<std::string&> reasonIfUnsupported) const +{ + return armnn::IsConvertFp16ToFp32SupportedCl(input, output, reasonIfUnsupported); +} + +bool ClLayerSupport::IsConvertFp32ToFp16Supported(const TensorInfo& input, + const TensorInfo& output, + Optional<std::string&> reasonIfUnsupported) const +{ + return armnn::IsConvertFp32ToFp16SupportedCl(input, output, reasonIfUnsupported); +} + +bool ClLayerSupport::IsConvolution2dSupported(const TensorInfo& input, + const TensorInfo& output, + const Convolution2dDescriptor& descriptor, + const TensorInfo& weights, + const Optional<TensorInfo>& biases, + Optional<std::string&> reasonIfUnsupported) const +{ + return armnn::IsConvolution2dSupportedCl(input, + output, + descriptor, + weights, + biases, + reasonIfUnsupported); +} + +bool ClLayerSupport::IsDepthwiseConvolutionSupported(const TensorInfo& input, + const TensorInfo& output, + const DepthwiseConvolution2dDescriptor& descriptor, + const TensorInfo& weights, + const Optional<TensorInfo>& biases, + Optional<std::string&> reasonIfUnsupported) const +{ + return armnn::IsDepthwiseConvolutionSupportedCl(input, + output, + descriptor, + weights, + biases, + reasonIfUnsupported); +} + +bool ClLayerSupport::IsDivisionSupported(const TensorInfo& input0, + const TensorInfo& input1, + const TensorInfo& output, + Optional<std::string&> reasonIfUnsupported) const +{ + return armnn::IsDivisionSupportedCl(input0, input1, output, reasonIfUnsupported); +} + +bool ClLayerSupport::IsFakeQuantizationSupported(const TensorInfo& input, + const FakeQuantizationDescriptor& descriptor, + Optional<std::string&> reasonIfUnsupported) const +{ + return armnn::IsFakeQuantizationSupportedCl(input, descriptor, reasonIfUnsupported); +} + +bool ClLayerSupport::IsFloorSupported(const TensorInfo& input, + const TensorInfo& output, + Optional<std::string&> reasonIfUnsupported) const +{ + return armnn::IsFloorSupportedCl(input, output, reasonIfUnsupported); +} + +bool ClLayerSupport::IsFullyConnectedSupported(const TensorInfo& input, + const TensorInfo& output, + const TensorInfo& weights, + const TensorInfo& biases, + const FullyConnectedDescriptor& descriptor, + Optional<std::string&> reasonIfUnsupported) const +{ + return armnn::IsFullyConnectedSupportedCl(input, + output, + weights, + biases, + descriptor, + reasonIfUnsupported); +} + +bool ClLayerSupport::IsInputSupported(const TensorInfo& input, + Optional<std::string&> reasonIfUnsupported) const +{ + return armnn::IsInputSupportedCl(input, reasonIfUnsupported); +} + +bool ClLayerSupport::IsL2NormalizationSupported(const TensorInfo& input, + const TensorInfo& output, + const L2NormalizationDescriptor& descriptor, + Optional<std::string&> reasonIfUnsupported) const +{ + return armnn::IsL2NormalizationSupportedCl(input, output, descriptor, reasonIfUnsupported); +} + +bool ClLayerSupport::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::IsLstmSupportedCl(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 ClLayerSupport::IsMeanSupported(const TensorInfo& input, + const TensorInfo& output, + const MeanDescriptor& descriptor, + Optional<std::string&> reasonIfUnsupported) const +{ + return armnn::IsMeanSupportedCl(input, output, descriptor,reasonIfUnsupported); +} + +bool ClLayerSupport::IsMergerSupported(const std::vector<const TensorInfo*> inputs, + const OriginsDescriptor& descriptor, + Optional<std::string&> reasonIfUnsupported) const +{ + return armnn::IsMergerSupportedCl(inputs, descriptor, reasonIfUnsupported); +} + +bool ClLayerSupport::IsMultiplicationSupported(const TensorInfo& input0, + const TensorInfo& input1, + const TensorInfo& output, + Optional<std::string&> reasonIfUnsupported) const +{ + return armnn::IsMultiplicationSupportedCl(input0, input1, output, reasonIfUnsupported); +} + +bool ClLayerSupport::IsNormalizationSupported(const TensorInfo& input, + const TensorInfo& output, + const NormalizationDescriptor& descriptor, + Optional<std::string&> reasonIfUnsupported) const +{ + return armnn::IsNormalizationSupportedCl(input, + output, + descriptor, + reasonIfUnsupported); +} + +bool ClLayerSupport::IsOutputSupported(const TensorInfo& output, + Optional<std::string&> reasonIfUnsupported) const +{ + return armnn::IsOutputSupportedCl(output, reasonIfUnsupported); +} + +bool ClLayerSupport::IsPadSupported(const TensorInfo& input, + const TensorInfo& output, + const PadDescriptor& descriptor, + Optional<std::string&> reasonIfUnsupported) const +{ + return armnn::IsPadSupportedCl(input, output, descriptor, reasonIfUnsupported); +} + +bool ClLayerSupport::IsPermuteSupported(const TensorInfo& input, + const TensorInfo& output, + const PermuteDescriptor& descriptor, + Optional<std::string&> reasonIfUnsupported) const +{ + return armnn::IsPermuteSupportedCl(input, output, descriptor, reasonIfUnsupported); +} + +bool ClLayerSupport::IsPooling2dSupported(const TensorInfo& input, + const TensorInfo& output, + const Pooling2dDescriptor& descriptor, + Optional<std::string&> reasonIfUnsupported) const +{ + return armnn::IsPooling2dSupportedCl(input, output, descriptor, reasonIfUnsupported); +} + +bool ClLayerSupport::IsReshapeSupported(const TensorInfo& input, + Optional<std::string&> reasonIfUnsupported) const +{ + return armnn::IsReshapeSupportedCl(input, reasonIfUnsupported); +} + +bool ClLayerSupport::IsResizeBilinearSupported(const TensorInfo& input, + Optional<std::string&> reasonIfUnsupported) const +{ + return armnn::IsResizeBilinearSupportedCl(input, reasonIfUnsupported); +} + +bool ClLayerSupport::IsSoftmaxSupported(const TensorInfo& input, + const TensorInfo& output, + const SoftmaxDescriptor& descriptor, + Optional<std::string&> reasonIfUnsupported) const +{ + return armnn::IsSoftmaxSupportedCl(input, output, descriptor, reasonIfUnsupported); +} + +bool ClLayerSupport::IsSplitterSupported(const TensorInfo& input, + const ViewsDescriptor& descriptor, + Optional<std::string&> reasonIfUnsupported) const +{ + return armnn::IsSplitterSupportedCl(input, descriptor, reasonIfUnsupported); +} + +bool ClLayerSupport::IsSubtractionSupported(const TensorInfo& input0, + const TensorInfo& input1, + const TensorInfo& output, + Optional<std::string&> reasonIfUnsupported) const +{ + return armnn::IsSubtractionSupportedCl(input0, input1, output, reasonIfUnsupported); +} + +// +// Implementation functions +// +// TODO: Functions kept for backward compatibility. Remove redundant functions +// once transition to plugable backends is complete. + namespace { template<unsigned int FilterSize> |