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author | josh minor <josh.minor@arm.com> | 2020-01-06 16:40:46 -0600 |
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committer | Derek Lamberti <derek.lamberti@arm.com> | 2020-01-23 14:29:14 +0000 |
commit | 4a3c61091037e7e86e8b03bb060d8c1ab82731a9 (patch) | |
tree | 928644023400ad5ac0c26b33dfff2f975567d6e8 /src/armnn/layers/ElementwiseUnaryLayer.cpp | |
parent | 190a39a4a9598e42b636ae4ab843761884148160 (diff) | |
download | armnn-4a3c61091037e7e86e8b03bb060d8c1ab82731a9.tar.gz |
IVGCVSW-4259 Add frontend and reference workload for UnaryOperationLayer
* Added new layer named ElementwiseUnary
* Deprecated existing Abs/Rsqrt layer functions
* Updated existing Abs/Rsqrt test infrastructure to use new layer
* Added boilerplate for new Exp,Neg,Sqrt elemwise op layers
* AbsQuantize test removed pending future commit
* Serialization support added
!android-nn-driver:2550
Change-Id: Ic595c645925e17b45db568187fd05646daf2e87f
Signed-off-by: josh minor <josh.minor@arm.com>
Diffstat (limited to 'src/armnn/layers/ElementwiseUnaryLayer.cpp')
-rw-r--r-- | src/armnn/layers/ElementwiseUnaryLayer.cpp | 62 |
1 files changed, 62 insertions, 0 deletions
diff --git a/src/armnn/layers/ElementwiseUnaryLayer.cpp b/src/armnn/layers/ElementwiseUnaryLayer.cpp new file mode 100644 index 0000000000..d3843da060 --- /dev/null +++ b/src/armnn/layers/ElementwiseUnaryLayer.cpp @@ -0,0 +1,62 @@ +// +// Copyright © 2019 Arm Ltd. All rights reserved. +// SPDX-License-Identifier: MIT +// + +#include "ElementwiseUnaryLayer.hpp" + +#include "LayerCloneBase.hpp" + +#include <backendsCommon/WorkloadData.hpp> +#include <backendsCommon/WorkloadFactory.hpp> + +#include <algorithm> + +namespace armnn +{ + +ElementwiseUnaryLayer::ElementwiseUnaryLayer(const ElementwiseUnaryDescriptor& param, const char* name) + : LayerWithParameters(1, 1, LayerType::ElementwiseUnary, param, name) +{ +} + +std::unique_ptr<IWorkload> ElementwiseUnaryLayer::CreateWorkload(const IWorkloadFactory& factory) const +{ + ElementwiseUnaryQueueDescriptor descriptor; + return factory.CreateElementwiseUnary(descriptor, PrepInfoAndDesc(descriptor)); +} + +ElementwiseUnaryLayer* ElementwiseUnaryLayer::Clone(Graph& graph) const +{ + return CloneBase<ElementwiseUnaryLayer>(graph, m_Param, GetName()); +} + +std::vector<TensorShape> ElementwiseUnaryLayer::InferOutputShapes(const std::vector<TensorShape>& inputShapes) const +{ + // Should return the shape of the input tensor + BOOST_ASSERT(inputShapes.size() == 1); + const TensorShape& input = inputShapes[0]; + + return std::vector<TensorShape>({ input }); +} + +void ElementwiseUnaryLayer::ValidateTensorShapesFromInputs() +{ + VerifyLayerConnections(1, CHECK_LOCATION()); + + std::vector<TensorShape> inferredShapes = InferOutputShapes({ + GetInputSlot(0).GetConnection()->GetTensorInfo().GetShape()}); + BOOST_ASSERT(inferredShapes.size() == 1); + + ConditionalThrowIfNotEqual<LayerValidationException>( + "ElementwiseUnaryLayer: TensorShape set on OutputSlot[0] does not match the inferred shape.", + GetOutputSlot(0).GetTensorInfo().GetShape(), + inferredShapes[0]); +} + +void ElementwiseUnaryLayer::Accept(ILayerVisitor& visitor) const +{ + visitor.VisitElementwiseUnaryLayer(this, GetParameters(), GetName()); +} + +} // namespace armnn |