IVGCVSW-2946 RefElementwiseWorkload configures prior to first execute

+ Added PostAllocationConfigure() method to workload interface
+ Elementwise function now deduces types based on Functor
- Replaced RefComparisonWorkload with RefElementwiseWorkload specialization
+ Fixed up unit tests and minor formatting

Change-Id: I33d08797767bba01cf4efb2904920ce0f950a4fe
Signed-off-by: Derek Lamberti <derek.lamberti@arm.com>

1 files changed, 15 insertions, 16 deletions

diff --git a/src/backends/reference/workloads/ElementwiseFunction.cpp b/src/backends/reference/workloads/ElementwiseFunction.cpp
index 934a86217a..7a5c071f70 100644
--- a/src/backends/reference/workloads/ElementwiseFunction.cpp
+++ b/src/backends/reference/workloads/ElementwiseFunction.cpp
@@ -13,26 +13,25 @@
 namespace armnn
 {
 
-template <typename Functor, typename DecoderOp, typename EncoderOp>
-ElementwiseFunction<Functor, DecoderOp, EncoderOp>::ElementwiseFunction(const TensorShape& inShape0,
-                                                                        const TensorShape& inShape1,
-                                                                        const TensorShape& outShape,
-                                                                        DecoderOp& inData0,
-                                                                        DecoderOp& inData1,
-                                                                        EncoderOp& outData)
+template <typename Functor>
+ElementwiseFunction<Functor>::ElementwiseFunction(const TensorShape& inShape0,
+                                                   const TensorShape& inShape1,
+                                                   const TensorShape& outShape,
+                                                   armnn::Decoder<InType>& inData0,
+                                                   armnn::Decoder<InType>& inData1,
+                                                   armnn::Encoder<OutType>& outData)
 {
     BroadcastLoop(inShape0, inShape1, outShape).Unroll(Functor(), 0, inData0, inData1, outData);
 }
 
 } //namespace armnn
 
-template struct armnn::ElementwiseFunction<std::plus<float>, armnn::Decoder, armnn::Encoder>;
-template struct armnn::ElementwiseFunction<std::minus<float>, armnn::Decoder, armnn::Encoder>;
-template struct armnn::ElementwiseFunction<std::multiplies<float>, armnn::Decoder, armnn::Encoder>;
-template struct armnn::ElementwiseFunction<std::divides<float>, armnn::Decoder, armnn::Encoder>;
-template struct armnn::ElementwiseFunction<armnn::maximum<float>, armnn::Decoder, armnn::Encoder>;
-template struct armnn::ElementwiseFunction<armnn::minimum<float>, armnn::Decoder, armnn::Encoder>;
-
-template struct armnn::ElementwiseFunction<std::equal_to<float>, armnn::Decoder, armnn::ComparisonEncoder>;
-template struct armnn::ElementwiseFunction<std::greater<float>, armnn::Decoder, armnn::ComparisonEncoder>;
+template struct armnn::ElementwiseFunction<std::plus<float>>;
+template struct armnn::ElementwiseFunction<std::minus<float>>;
+template struct armnn::ElementwiseFunction<std::multiplies<float>>;
+template struct armnn::ElementwiseFunction<std::divides<float>>;
+template struct armnn::ElementwiseFunction<armnn::maximum<float>>;
+template struct armnn::ElementwiseFunction<armnn::minimum<float>>;
+template struct armnn::ElementwiseFunction<std::equal_to<float>>;
+template struct armnn::ElementwiseFunction<std::greater<float>>;