IVGCVSW-1964: Cl implementation for the ILayerSupport interface
Change-Id: I04bd5e069b220712adbeaebdaede2061ba8c0eb4
diff --git a/src/backends/cl/ClLayerSupport.cpp b/src/backends/cl/ClLayerSupport.cpp
index 494b339..6856394 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 @@
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>