IVGCVSW-5787 Add/Update Execute() implementations in RefActivationWorkload

 * Added multithreaded StridedSliceEndToEndTest

Signed-off-by: Finn Williams <Finn.Williams@arm.com>
Change-Id: I4579db7b5959e0a22256f1bda00238c22e611dec

1 files changed, 19 insertions, 17 deletions

diff --git a/src/backends/reference/workloads/RefElementwiseWorkload.cpp b/src/backends/reference/workloads/RefElementwiseWorkload.cpp
index 60acbd6252..dd7d325ca5 100644
--- a/src/backends/reference/workloads/RefElementwiseWorkload.cpp
+++ b/src/backends/reference/workloads/RefElementwiseWorkload.cpp
@@ -26,39 +26,41 @@ RefElementwiseWorkload<Functor, ParentDescriptor, DebugString>::RefElementwiseWo
 }
 
 template <typename Functor, typename ParentDescriptor, typename armnn::StringMapping::Id DebugString>
-void RefElementwiseWorkload<Functor, ParentDescriptor, DebugString>::PostAllocationConfigure()
+void RefElementwiseWorkload<Functor, ParentDescriptor, DebugString>::Execute() const
 {
-    const TensorInfo& inputInfo0 = GetTensorInfo(m_Data.m_Inputs[0]);
-    const TensorInfo& inputInfo1 = GetTensorInfo(m_Data.m_Inputs[1]);
-    const TensorInfo& outputInfo = GetTensorInfo(m_Data.m_Outputs[0]);
+    Execute(m_Data.m_Inputs, m_Data.m_Outputs);
+}
 
-    m_Input0 = MakeDecoder<InType>(inputInfo0);
-    m_Input1 = MakeDecoder<InType>(inputInfo1);
-    m_Output = MakeEncoder<OutType>(outputInfo);
+template <typename Functor, typename ParentDescriptor, typename armnn::StringMapping::Id DebugString>
+void RefElementwiseWorkload<Functor, ParentDescriptor, DebugString>::ExecuteAsync(
+        WorkingMemDescriptor &workingMemDescriptor)
+{
+    Execute(workingMemDescriptor.m_Inputs, workingMemDescriptor.m_Outputs);
 }
 
 template <typename Functor, typename ParentDescriptor, typename armnn::StringMapping::Id DebugString>
-void RefElementwiseWorkload<Functor, ParentDescriptor, DebugString>::Execute() const
+void RefElementwiseWorkload<Functor, ParentDescriptor, DebugString>::Execute(
+        std::vector<ITensorHandle*> inputs, std::vector<ITensorHandle*> outputs) const
 {
     ARMNN_SCOPED_PROFILING_EVENT(Compute::CpuRef, StringMapping::Instance().Get(DebugString));
-    const TensorInfo& inputInfo0 = GetTensorInfo(m_Data.m_Inputs[0]);
-    const TensorInfo& inputInfo1 = GetTensorInfo(m_Data.m_Inputs[1]);
-    const TensorInfo& outputInfo = GetTensorInfo(m_Data.m_Outputs[0]);
+    const TensorInfo& inputInfo0 = GetTensorInfo(inputs[0]);
+    const TensorInfo& inputInfo1 = GetTensorInfo(inputs[1]);
+    const TensorInfo& outputInfo = GetTensorInfo(outputs[0]);
 
     const TensorShape& inShape0 = inputInfo0.GetShape();
     const TensorShape& inShape1 = inputInfo1.GetShape();
     const TensorShape& outShape = outputInfo.GetShape();
 
-    m_Input0->Reset(m_Data.m_Inputs[0]->Map());
-    m_Input1->Reset(m_Data.m_Inputs[1]->Map());
-    m_Output->Reset(m_Data.m_Outputs[0]->Map());
+    std::unique_ptr<Decoder<InType>> input0 = MakeDecoder<InType>(inputInfo0, inputs[0]->Map());
+    std::unique_ptr<Decoder<InType>> input1 = MakeDecoder<InType>(inputInfo1, inputs[1]->Map());
+    std::unique_ptr<Encoder<OutType>> output= MakeEncoder<OutType>(outputInfo, outputs[0]->Map());
 
     ElementwiseBinaryFunction<Functor>(inShape0,
                                        inShape1,
                                        outShape,
-                                       *m_Input0,
-                                       *m_Input1,
-                                       *m_Output);
+                                       *input0,
+                                       *input1,
+                                       *output);
 }
 
 } //namespace armnn