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>
diff --git a/src/backends/reference/workloads/RefFullyConnectedWorkload.cpp b/src/backends/reference/workloads/RefFullyConnectedWorkload.cpp
new file mode 100644
index 0000000..dc7030e
--- /dev/null
+++ b/src/backends/reference/workloads/RefFullyConnectedWorkload.cpp
@@ -0,0 +1,65 @@
+//
+// Copyright © 2017 Arm Ltd. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+
+#include "RefFullyConnectedWorkload.hpp"
+
+#include "FullyConnected.hpp"
+#include "RefWorkloadUtils.hpp"
+
+#include "Profiling.hpp"
+
+namespace armnn
+{
+RefFullyConnectedWorkload::RefFullyConnectedWorkload(
+ const FullyConnectedQueueDescriptor& descriptor, const WorkloadInfo& info)
+ : BaseWorkload<FullyConnectedQueueDescriptor>(descriptor, info),
+ m_Weight(std::make_unique<ScopedCpuTensorHandle>(*(descriptor.m_Weight)))
+{
+ const TensorInfo& rWeightInfo = GetTensorInfo(m_Weight.get());
+ m_WeightShape = rWeightInfo.GetShape();
+ m_WeightDecoder = MakeDecoder<float>(rWeightInfo, m_Weight->Map(true));
+
+ if (descriptor.m_Parameters.m_BiasEnabled)
+ {
+ m_Bias = std::make_unique<ScopedCpuTensorHandle>(*(descriptor.m_Bias));
+ const TensorInfo& biasInfo = GetTensorInfo(m_Bias.get());
+ m_BiasDecoder = MakeDecoder<float>(biasInfo, m_Bias->Map(true));
+ }
+}
+
+void RefFullyConnectedWorkload::PostAllocationConfigure()
+{
+ const TensorInfo& inputInfo = GetTensorInfo(m_Data.m_Inputs[0]);
+ BOOST_ASSERT(inputInfo.GetNumDimensions() > 1);
+ m_InputShape = inputInfo.GetShape();
+ m_InputDecoder = MakeDecoder<float>(inputInfo, m_Data.m_Inputs[0]->Map());
+
+ const TensorInfo& outputInfo = GetTensorInfo(m_Data.m_Outputs[0]);
+ m_OutputShape = outputInfo.GetShape();
+ m_OutputEncoder = MakeEncoder<float>(outputInfo, m_Data.m_Outputs[0]->Map());
+
+ m_NumActivations = 1; // Total number of activations in the input.
+ for (unsigned int i = 1; i < inputInfo.GetNumDimensions(); i++)
+ {
+ m_NumActivations *= inputInfo.GetShape()[i];
+ }
+}
+
+void RefFullyConnectedWorkload::Execute() const
+{
+ ARMNN_SCOPED_PROFILING_EVENT(Compute::CpuRef, "RefFullyConnectedWorkload_Execute");
+
+ FullyConnected(m_InputShape,
+ *m_InputDecoder,
+ m_OutputShape,
+ *m_OutputEncoder,
+ *m_WeightDecoder,
+ *m_BiasDecoder,
+ m_Data.m_Parameters.m_BiasEnabled,
+ m_NumActivations,
+ m_Data.m_Parameters.m_TransposeWeightMatrix);
+}
+
+} //namespace armnn