1 files changed, 20 insertions, 37 deletions

diff --git a/src/backends/reference/workloads/RefFullyConnectedWorkload.cpp b/src/backends/reference/workloads/RefFullyConnectedWorkload.cpp
index c6ea147043..087fc9da68 100644
--- a/src/backends/reference/workloads/RefFullyConnectedWorkload.cpp
+++ b/src/backends/reference/workloads/RefFullyConnectedWorkload.cpp
@@ -12,43 +12,26 @@
 
 namespace armnn
 {
-RefFullyConnectedWorkload::RefFullyConnectedWorkload(
-    const FullyConnectedQueueDescriptor& descriptor, const WorkloadInfo& info)
-        : RefBaseWorkload<FullyConnectedQueueDescriptor>(descriptor, info)
-{
-}
 
-void RefFullyConnectedWorkload::PostAllocationConfigure()
+unsigned int GetNumActivations(const TensorInfo& inputInfo)
 {
-    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();
-
-    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)
+    unsigned int numActivations = 1; // Total number of activations in the input.
+    for (unsigned int i = 1; i < inputInfo.GetNumDimensions(); i++)
     {
-        const TensorInfo& biasInfo = GetTensorInfo(inputs[2]);
-        m_BiasDecoder = MakeDecoder<float>(biasInfo);
+        numActivations *= inputInfo.GetShape()[i];
     }
+    return numActivations;
+}
 
-    const TensorInfo& outputInfo = GetTensorInfo(outputs[0]);
-    m_OutputShape = outputInfo.GetShape();
 
-    m_NumActivations = 1; // Total number of activations in the input.
-    for (unsigned int i = 1; i < inputInfo.GetNumDimensions(); i++)
-    {
-        m_NumActivations *= inputInfo.GetShape()[i];
-    }
+RefFullyConnectedWorkload::RefFullyConnectedWorkload(
+    const FullyConnectedQueueDescriptor& descriptor, const WorkloadInfo& info)
+        : RefBaseWorkload<FullyConnectedQueueDescriptor>(descriptor, info)
+        , m_InputShape(info.m_InputTensorInfos[0].GetShape())
+        , m_WeightShape(info.m_InputTensorInfos[1].GetShape())
+        , m_OutputShape(info.m_OutputTensorInfos[0].GetShape())
+        , m_NumActivations(GetNumActivations(info.m_InputTensorInfos[0]))
+{
 }
 
 void RefFullyConnectedWorkload::Execute() const
@@ -58,8 +41,6 @@ void RefFullyConnectedWorkload::Execute() const
 
 void RefFullyConnectedWorkload::ExecuteAsync(WorkingMemDescriptor &workingMemDescriptor)
 {
-    PostAllocationConfigure(workingMemDescriptor.m_Inputs, workingMemDescriptor.m_Outputs);
-
     Execute(workingMemDescriptor.m_Inputs, workingMemDescriptor.m_Outputs);
 }
 
@@ -70,10 +51,12 @@ void RefFullyConnectedWorkload::Execute(std::vector<ITensorHandle*> inputs, std:
     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());
 
-    m_WeightDecoder->Reset(inputs[1]->Map());
+    std::unique_ptr<Decoder<float>> weightsDecoder = MakeDecoder<float>(GetTensorInfo(inputs[1]), inputs[1]->Map());
+    std::unique_ptr<Decoder<float>> biasDecoder;
+
     if (m_Data.m_Parameters.m_BiasEnabled)
     {
-        m_BiasDecoder->Reset(inputs[2]->Map());
+        biasDecoder = MakeDecoder<float>(GetTensorInfo(inputs[2]), inputs[2]->Map());
     }
 
     FullyConnected(m_InputShape,
@@ -81,8 +64,8 @@ void RefFullyConnectedWorkload::Execute(std::vector<ITensorHandle*> inputs, std:
                    m_OutputShape,
                    *OutputEncoder,
                    m_WeightShape,
-                   *m_WeightDecoder,
-                   m_BiasDecoder.get(),
+                   *weightsDecoder,
+                   biasDecoder.get(),
                    m_Data.m_Parameters.m_BiasEnabled,
                    m_NumActivations,
                    m_Data.m_Parameters.m_TransposeWeightMatrix);