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authorjosh minor <josh.minor@arm.com>2020-01-06 16:40:46 -0600
committerDerek Lamberti <derek.lamberti@arm.com>2020-01-23 14:29:14 +0000
commit4a3c61091037e7e86e8b03bb060d8c1ab82731a9 (patch)
tree928644023400ad5ac0c26b33dfff2f975567d6e8 /src/armnn/layers/ElementwiseUnaryLayer.hpp
parent190a39a4a9598e42b636ae4ab843761884148160 (diff)
downloadarmnn-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>
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+//
+// Copyright © 2019 Arm Ltd. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+
+#pragma once
+
+#include "LayerWithParameters.hpp"
+
+namespace armnn
+{
+
+/// This layer represents a elementwiseUnary operation.
+class ElementwiseUnaryLayer : public LayerWithParameters<ElementwiseUnaryDescriptor>
+{
+public:
+ /// Makes a workload for the elementwiseUnary type
+ /// @param [in] graph The graph where this layer can be found
+ /// @param [in] factory The workload factory which will create the workload
+ /// @return A pointer to the created workload, or nullptr if not created
+ virtual std::unique_ptr<IWorkload> CreateWorkload(const IWorkloadFactory& factory) const override;
+
+ /// Creates a dynamically-allocated copy of this layer
+ /// @param [in] graph The graph into which this layer is being cloned
+ ElementwiseUnaryLayer* Clone(Graph& graph) const override;
+
+ /// Returns inputShapes by default.
+ /// @param [in] inputShapes The input shapes layer has.
+ /// @return A vector to the inferred output shape.
+ std::vector<TensorShape> InferOutputShapes(const std::vector<TensorShape>& inputShapes) const override;
+
+ /// Check if the input tensor shape(s) will lead to a valid configuration
+ /// of @ref ElementwiseUnaryLayer
+ void ValidateTensorShapesFromInputs() override;
+
+ void Accept(ILayerVisitor& visitor) const override;
+
+protected:
+ /// Constructor to create a ElementwiseUnaryLayer
+ /// @param [in] param ElementwiseUnaryDescriptor to configure the ElementwiseUnaryLayer
+ /// @param [in] name Optional name for the layer
+ ElementwiseUnaryLayer(const ElementwiseUnaryDescriptor& param, const char* name);
+
+ /// Default destructor
+ ~ElementwiseUnaryLayer() = default;
+};
+
+} // namespace armnn