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, 29 insertions, 12 deletions

diff --git a/src/backends/reference/workloads/RefFullyConnectedWorkload.cpp b/src/backends/reference/workloads/RefFullyConnectedWorkload.cpp
index 49e105f206..deb56d4c6b 100644
--- a/src/backends/reference/workloads/RefFullyConnectedWorkload.cpp
+++ b/src/backends/reference/workloads/RefFullyConnectedWorkload.cpp
@@ -34,28 +34,32 @@ RefFullyConnectedWorkload::RefFullyConnectedWorkload(
 
 void RefFullyConnectedWorkload::PostAllocationConfigure()
 {
-    const TensorInfo& inputInfo = GetTensorInfo(m_Data.m_Inputs[0]);
+    PostAllocationConfigure(m_Data.m_Inputs, m_Data.m_Outputs);
+}
+
+void RefFullyConnectedWorkload::PostAllocationConfigure(std::vector<ITensorHandle*> inputs,
+                                                        std::vector<ITensorHandle*> outputs)
+{
+    const TensorInfo& inputInfo = GetTensorInfo(inputs[0]);
     ARMNN_ASSERT(inputInfo.GetNumDimensions() > 1);
     m_InputShape = inputInfo.GetShape();
-    m_InputDecoder = MakeDecoder<float>(inputInfo);
 
     if (!m_Data.m_Parameters.m_ConstantWeights)
     {
-        const TensorInfo& rWeightInfo = GetTensorInfo(m_Data.m_Inputs[1]);
+        const TensorInfo& rWeightInfo = GetTensorInfo(inputs[1]);
         ARMNN_ASSERT(inputInfo.GetNumDimensions() > 1);
         m_WeightShape = rWeightInfo.GetShape();
         m_WeightDecoder = MakeDecoder<float>(rWeightInfo);
 
         if (m_Data.m_Parameters.m_BiasEnabled)
         {
-            const TensorInfo& biasInfo = GetTensorInfo(m_Data.m_Inputs[2]);
+            const TensorInfo& biasInfo = GetTensorInfo(inputs[2]);
             m_BiasDecoder = MakeDecoder<float>(biasInfo);
         }
     }
 
-    const TensorInfo& outputInfo = GetTensorInfo(m_Data.m_Outputs[0]);
+    const TensorInfo& outputInfo = GetTensorInfo(outputs[0]);
     m_OutputShape = outputInfo.GetShape();
-    m_OutputEncoder = MakeEncoder<float>(outputInfo);
 
     m_NumActivations = 1; // Total number of activations in the input.
     for (unsigned int i = 1; i < inputInfo.GetNumDimensions(); i++)
@@ -66,23 +70,36 @@ void RefFullyConnectedWorkload::PostAllocationConfigure()
 
 void RefFullyConnectedWorkload::Execute() const
 {
+    Execute(m_Data.m_Inputs, m_Data.m_Outputs);
+}
+
+void RefFullyConnectedWorkload::ExecuteAsync(WorkingMemDescriptor &workingMemDescriptor)
+{
+    PostAllocationConfigure(workingMemDescriptor.m_Inputs, workingMemDescriptor.m_Outputs);
+
+    Execute(workingMemDescriptor.m_Inputs, workingMemDescriptor.m_Outputs);
+}
+
+void RefFullyConnectedWorkload::Execute(std::vector<ITensorHandle*> inputs, std::vector<ITensorHandle*> outputs) const
+{
     ARMNN_SCOPED_PROFILING_EVENT(Compute::CpuRef, "RefFullyConnectedWorkload_Execute");
 
-    m_InputDecoder->Reset(m_Data.m_Inputs[0]->Map());
+    std::unique_ptr<Decoder<float>> inputDecoder = MakeDecoder<float>(GetTensorInfo(inputs[0]), inputs[0]->Map());
+    std::unique_ptr<Encoder<float>> OutputEncoder = MakeEncoder<float>(GetTensorInfo(outputs[0]), outputs[0]->Map());
+
     if (!m_Data.m_Parameters.m_ConstantWeights)
     {
-        m_WeightDecoder->Reset(m_Data.m_Inputs[1]->Map());
+        m_WeightDecoder->Reset(inputs[1]->Map());
         if (m_Data.m_Parameters.m_BiasEnabled)
         {
-            m_BiasDecoder->Reset(m_Data.m_Inputs[2]->Map());
+            m_BiasDecoder->Reset(inputs[2]->Map());
         }
     }
-    m_OutputEncoder->Reset(m_Data.m_Outputs[0]->Map());
 
     FullyConnected(m_InputShape,
-                   *m_InputDecoder,
+                   *inputDecoder,
                    m_OutputShape,
-                   *m_OutputEncoder,
+                   *OutputEncoder,
                    m_WeightShape,
                    *m_WeightDecoder,
                    *m_BiasDecoder,