IVGCVSW-5091 Add Logical ops frontend and ref impl

* Add frontend and reference implementation for logical
  ops NOT, AND, OR.
* Unary NOT uses existing ElementwiseUnary layer and
  ElementwiseUnary descriptor.
* Binary AND/OR uses new layer LogicalBinary and new
  LogicalBinary descriptor.
* Add serialization/deserializion support and add missing
  ElementwiseUnary deserializer code.
* Add additional Boolean decoder in BaseIterator.hpp.

Signed-off-by: James Conroy <james.conroy@arm.com>
Change-Id: Id343b01174053a166de1b98b6175e04a5065f720

1 files changed, 64 insertions, 0 deletions

diff --git a/src/backends/reference/workloads/RefLogicalUnaryWorkload.cpp b/src/backends/reference/workloads/RefLogicalUnaryWorkload.cpp
new file mode 100644
index 0000000000..76eb5ac39f
--- /dev/null
+++ b/src/backends/reference/workloads/RefLogicalUnaryWorkload.cpp
@@ -0,0 +1,64 @@
+//
+// Copyright © 2020 Arm Ltd and Contributors. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+
+#include "RefLogicalUnaryWorkload.hpp"
+
+#include "Decoders.hpp"
+#include "ElementwiseFunction.hpp"
+#include "Encoders.hpp"
+#include "RefWorkloadUtils.hpp"
+
+#include <Profiling.hpp>
+
+#include <armnn/TypesUtils.hpp>
+
+namespace armnn
+{
+
+RefLogicalUnaryWorkload::RefLogicalUnaryWorkload(const ElementwiseUnaryQueueDescriptor& desc,
+                                                 const WorkloadInfo& info)
+    : BaseWorkload<ElementwiseUnaryQueueDescriptor>(desc, info)
+{}
+
+void RefLogicalUnaryWorkload::PostAllocationConfigure()
+{
+    const TensorInfo& inputInfo = GetTensorInfo(m_Data.m_Inputs[0]);
+    const TensorInfo& outputInfo = GetTensorInfo(m_Data.m_Outputs[0]);
+
+    m_Input = MakeDecoder<InType>(inputInfo);
+    m_Output = MakeEncoder<OutType>(outputInfo);
+}
+
+void RefLogicalUnaryWorkload::Execute() const
+{
+    ARMNN_SCOPED_PROFILING_EVENT(Compute::CpuRef, "RefLogicalUnaryWorkload_Execute");
+
+    const TensorInfo& inputInfo = GetTensorInfo(m_Data.m_Inputs[0]);
+    const TensorInfo& outputInfo = GetTensorInfo(m_Data.m_Outputs[0]);
+
+    const TensorShape& inShape = inputInfo.GetShape();
+    const TensorShape& outShape = outputInfo.GetShape();
+
+    m_Input->Reset(m_Data.m_Inputs[0]->Map());
+    m_Output->Reset(m_Data.m_Outputs[0]->Map());
+
+    using NotFunction = LogicalUnaryFunction<std::logical_not<bool>>;
+
+    switch (m_Data.m_Parameters.m_Operation)
+    {
+        case UnaryOperation::LogicalNot:
+        {
+            NotFunction(inShape, outShape, *m_Input, *m_Output);
+            break;
+        }
+        default:
+        {
+            throw InvalidArgumentException(std::string("Unsupported Logical Unary operation") +
+                GetUnaryOperationAsCString(m_Data.m_Parameters.m_Operation), CHECK_LOCATION());
+        }
+    }
+}
+
+} // namespace armnn