IVGCVSW-3134 Refactor FullyConnected workloads into single workload

 * Refactor FullyConnected workloads into single workload.
 * Refactor FullyConnected ref implementation to use Encoders
   and Decoders to support all DataTypes.
 * Deleted RefFullyConnectedFloat32Workload and
   RefFullyConnected2dUint8Workload.

Change-Id: Iad30fb0287ab7491e1297997e7d61f1d00785541
Signed-off-by: Francis Murtagh <francis.murtagh@arm.com>

1 files changed, 26 insertions, 24 deletions

diff --git a/src/backends/reference/workloads/FullyConnected.cpp b/src/backends/reference/workloads/FullyConnected.cpp
index bf5814d2ad..02d9b060ef 100644
--- a/src/backends/reference/workloads/FullyConnected.cpp
+++ b/src/backends/reference/workloads/FullyConnected.cpp
@@ -5,32 +5,29 @@
 
 #include "FullyConnected.hpp"
 
+#include "RefWorkloadUtils.hpp"
+
 #include <boost/assert.hpp>
 
 namespace armnn
 {
 
-void FullyConnected(const float*      inputData,
-                    float*            outputData,
-                    const TensorInfo& inputTensorInfo,
-                    const TensorInfo& outputTensorInfo,
-                    const float*      weightData,
-                    const float*      biasData,
-                    bool              transposeWeights)
+void FullyConnected(const TensorShape& rInputShape,
+                    Decoder<float>& rInputDecoder,
+                    const TensorShape& rOutputShape,
+                    Encoder<float>& rOutputEncoder,
+                    Decoder<float>& rWeightDecoder,
+                    Decoder<float>& rBiasDecoder,
+                    const bool biasEnabled,
+                    const unsigned int K,
+                    const bool transposeWeights)
 {
-    unsigned int N = outputTensorInfo.GetShape()[1]; // Outputs Vector Size.
-
-    BOOST_ASSERT(inputTensorInfo.GetNumDimensions() > 1); // Needs some data.
-
-    unsigned int K = 1; // Total number of activations in the input.
-    for (unsigned int i = 1; i < inputTensorInfo.GetNumDimensions(); i++)
-    {
-        K *= inputTensorInfo.GetShape()[i];
-    }
+    // Perform FullyConnected implementation
+    unsigned int outputSize = rOutputShape[1];
 
-    for (unsigned int n = 0; n < inputTensorInfo.GetShape()[0]; n++)
+    for (unsigned int n = 0; n < rInputShape[0]; n++)
     {
-        for (unsigned int channelOutput = 0; channelOutput < N; channelOutput++)
+        for (unsigned int channelOutput = 0; channelOutput < outputSize; channelOutput++)
         {
             float outval = 0.f;
 
@@ -39,22 +36,27 @@ void FullyConnected(const float*      inputData,
                 float weight;
                 if (transposeWeights)
                 {
-                    weight = weightData[channelOutput * K + channelInput];
+                    rWeightDecoder[channelOutput * K + channelInput];
+                    weight = rWeightDecoder.Get();
                 }
                 else
                 {
-                    weight = weightData[channelInput * N + channelOutput];
+                    rWeightDecoder[channelInput * outputSize + channelOutput];
+                    weight = rWeightDecoder.Get();
                 }
 
-                outval += weight * inputData[n * K + channelInput];
+                rInputDecoder[n * K + channelInput];
+                outval += weight * rInputDecoder.Get();
             }
 
-            if (biasData)
+            if (biasEnabled)
             {
-                outval += biasData[channelOutput];
+                rBiasDecoder[channelOutput];
+                outval += rBiasDecoder.Get();
             }
 
-            outputData[n * N + channelOutput] = outval;
+            rOutputEncoder[n * outputSize + channelOutput];
+            rOutputEncoder.Set(outval);
         }
     }
 }