From 033626d1ee9256032309bbc6685c3a69a919cd64 Mon Sep 17 00:00:00 2001
From: Les Bell <les.bell@arm.com>
Date: Mon, 3 Sep 2018 16:24:52 +0100
Subject: IVGCVSW-1783 refactor add/mul/div layers

Change-Id: Ic043030455b3cf8ad7f92fd0a75175c1827a95f4
---
 src/armnn/layers/AdditionLayer.cpp | 53 +++-----------------------------------
 1 file changed, 4 insertions(+), 49 deletions(-)

(limited to 'src/armnn/layers/AdditionLayer.cpp')

diff --git a/src/armnn/layers/AdditionLayer.cpp b/src/armnn/layers/AdditionLayer.cpp
index ab73a918db..c1413102b8 100644
--- a/src/armnn/layers/AdditionLayer.cpp
+++ b/src/armnn/layers/AdditionLayer.cpp
@@ -3,6 +3,7 @@
 // See LICENSE file in the project root for full license information.
 //
 #include "AdditionLayer.hpp"
+
 #include "LayerCloneBase.hpp"
 
 #include <armnn/TypesUtils.hpp>
@@ -13,11 +14,12 @@ namespace armnn
 {
 
 AdditionLayer::AdditionLayer(const char* name)
-    : Layer(2, 1, LayerType::Addition, name)
+    : ArithmeticBaseLayer(2, 1, LayerType::Addition, name)
 {
 }
 
-std::unique_ptr<IWorkload> AdditionLayer::CreateWorkload(const Graph& graph, const IWorkloadFactory& factory) const
+std::unique_ptr<IWorkload> AdditionLayer::CreateWorkload(const Graph& graph,
+                                                         const IWorkloadFactory& factory) const
 {
     AdditionQueueDescriptor descriptor;
     return factory.CreateAddition(descriptor, PrepInfoAndDesc(descriptor, graph));
@@ -28,51 +30,4 @@ AdditionLayer* AdditionLayer::Clone(Graph& graph) const
     return CloneBase<AdditionLayer>(graph, GetName());
 }
 
-std::vector<TensorShape> AdditionLayer::InferOutputShapes(const std::vector<TensorShape>& inputShapes) const
-{
-    BOOST_ASSERT(inputShapes.size() == 2);
-    auto& input0 = inputShapes[0];
-    auto& input1 = inputShapes[1];
-
-    // Get the max of the inputs.
-    BOOST_ASSERT(input0.GetNumDimensions() == input1.GetNumDimensions());
-    unsigned int numDims = input0.GetNumDimensions();
-    std::vector<unsigned int> dims(numDims);
-
-    for (unsigned int i = 0; i < numDims; i++)
-    {
-        unsigned int dim0 = input0[i];
-        unsigned int dim1 = input1[i];
-
-    // Validates inputs are broadcast compatible.
-#if !NDEBUG
-        if (dim0 != dim1)
-        {
-            BOOST_ASSERT_MSG(dim0 == 1 || dim1 == 1, "Dimensions should either match or one should be of size 1.");
-        }
-#endif
-
-        dims[i] = std::max(dim0, dim1);
-    }
-
-    return std::vector<TensorShape>({ TensorShape(numDims, dims.data()) });
-}
-
-void AdditionLayer::ValidateTensorShapesFromInputs()
-{
-    VerifyLayerConnections(2, CHECK_LOCATION());
-
-    auto inferredShapes = InferOutputShapes({
-        GetInputSlot(0).GetConnection()->GetTensorInfo().GetShape(),
-        GetInputSlot(1).GetConnection()->GetTensorInfo().GetShape()
-    });
-
-    BOOST_ASSERT(inferredShapes.size() == 1);
-
-    ConditionalThrowIfNotEqual<LayerValidationException>(
-        "AdditionLayer: TensorShape set on OutputSlot[0] does not match the inferred shape.",
-        GetOutputSlot(0).GetTensorInfo().GetShape(),
-        inferredShapes[0]);
-}
-
 } // namespace armnn
-- 
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