IVGCVSW-3025: Refactor reference Convolution2d workload

 * Refactored RefConvolution2dWorkload to support all DataTypes through Encoders and Decoders.
 * Added Convolute function to ConvImpl that uses Encoders and Decoders to support all DataTypes.
 * Deleted RefConvolution2dFloat32Workload and RefConvolution2dUint8Workload.

Signed-off-by: Mike Kelly <mike.kelly@arm.com>
Signed-off-by: Teresa Charlin <teresa.charlinreyes@arm.com>
Change-Id: Ic5ef0f499d08b948fa65fdee54b5f681fd0b1c05

1 files changed, 53 insertions, 0 deletions

diff --git a/src/backends/reference/workloads/RefConvolution2dWorkload.cpp b/src/backends/reference/workloads/RefConvolution2dWorkload.cpp
new file mode 100644
index 0000000000..0824d5cf1c
--- /dev/null
+++ b/src/backends/reference/workloads/RefConvolution2dWorkload.cpp
@@ -0,0 +1,53 @@
+//
+// Copyright © 2017 Arm Ltd. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+
+#include "RefConvolution2dWorkload.hpp"
+
+#include "ConvImpl.hpp"
+#include "RefWorkloadUtils.hpp"
+
+#include "Profiling.hpp"
+
+namespace armnn
+{
+RefConvolution2dWorkload::RefConvolution2dWorkload(
+        const Convolution2dQueueDescriptor& descriptor, const WorkloadInfo& info)
+        : BaseWorkload<Convolution2dQueueDescriptor>(descriptor, info)
+{
+    m_Weight = std::make_unique<ScopedCpuTensorHandle>(*(descriptor.m_Weight));
+    const TensorInfo& rFilterInfo = GetTensorInfo(m_Weight.get());
+    m_FilterShape = rFilterInfo.GetShape();
+    m_FilterDecoder = MakeDecoder<float>(rFilterInfo, m_Weight.get()->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.get()->Map(true));
+    }
+}
+
+void RefConvolution2dWorkload::PostAllocationConfigure()
+{
+    const TensorInfo& inputInfo = GetTensorInfo(m_Data.m_Inputs[0]);
+    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());
+}
+
+void RefConvolution2dWorkload::Execute() const {
+    ARMNN_SCOPED_PROFILING_EVENT(Compute::CpuRef, "RefConvolution2dWorkload_Execute");
+
+    Convolve(m_InputShape, *m_InputDecoder, m_OutputShape, *m_OutputEncoder, m_FilterShape,
+             *m_FilterDecoder, m_Data.m_Parameters.m_BiasEnabled, m_BiasDecoder.get(),
+             m_Data.m_Parameters.m_DataLayout, m_Data.m_Parameters.m_PadTop, m_Data.m_Parameters.m_PadLeft,
+             m_Data.m_Parameters.m_StrideX, m_Data.m_Parameters.m_StrideY,
+             m_Data.m_Parameters.m_DilationX, m_Data.m_Parameters.m_DilationY);
+}
+
+} //namespace armnn