IVGCVSW-3705 Add Channel Shuffle Front end and Ref Implementation

* Add front end
* Add reference workload
* Add unit tests
* Add Serializer and Deserializer
* Update ArmNN Versioning

Signed-off-by: Simon Obute <simon.obute@arm.com>
Change-Id: I9ac1f953af3974382eac8e8d62d794d2344e8f47

2 files changed, 91 insertions, 0 deletions

diff --git a/src/armnn/layers/ChannelShuffleLayer.cpp b/src/armnn/layers/ChannelShuffleLayer.cpp
new file mode 100644
index 0000000000..a3b85f1ba7
--- /dev/null
+++ b/src/armnn/layers/ChannelShuffleLayer.cpp
@@ -0,0 +1,54 @@
+//
+// Copyright © 2021 Arm Ltd and Contributors. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+
+#include "ChannelShuffleLayer.hpp"
+
+#include "LayerCloneBase.hpp"
+
+#include  <armnn/TypesUtils.hpp>
+
+#include <backendsCommon/Workload.hpp>
+#include <backendsCommon/WorkloadFactory.hpp>
+
+namespace armnn
+{
+ChannelShuffleLayer::ChannelShuffleLayer(const ChannelShuffleDescriptor& param, const char* name)
+: LayerWithParameters(1, 1, LayerType::ChannelShuffle, param, name)
+{
+}
+
+std::unique_ptr<IWorkload> ChannelShuffleLayer::CreateWorkload(const IWorkloadFactory &factory) const
+{
+    ChannelShuffleQueueDescriptor descriptor;
+    SetAdditionalInfo(descriptor);
+
+    return factory.CreateChannelShuffle(descriptor, PrepInfoAndDesc(descriptor));
+}
+
+ChannelShuffleLayer* ChannelShuffleLayer::Clone(Graph& graph) const
+{
+    return CloneBase<ChannelShuffleLayer>(graph, m_Param, GetName());
+}
+
+void ChannelShuffleLayer::ValidateTensorShapesFromInputs()
+{
+    VerifyLayerConnections(1, CHECK_LOCATION());
+
+    const TensorShape& outputShape = GetOutputSlot(0).GetTensorInfo().GetShape();
+
+    VerifyShapeInferenceType(outputShape, m_ShapeInferenceMethod);
+
+    auto inferredShapes = Layer::InferOutputShapes({GetInputSlot(0).GetConnection()->GetTensorInfo().GetShape() });
+
+    ARMNN_ASSERT(inferredShapes.size() == 1);
+
+    ValidateAndCopyShape(outputShape, inferredShapes[0], m_ShapeInferenceMethod, "ChannelShuffleLayer");
+}
+void ChannelShuffleLayer::Accept(ILayerVisitor& visitor) const
+{
+    IgnoreUnused(visitor);
+    throw armnn::Exception("ChannelShuffleLayer: VisitChannelShuffleLayer is not implemented");
+}
+}
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diff --git a/src/armnn/layers/ChannelShuffleLayer.hpp b/src/armnn/layers/ChannelShuffleLayer.hpp
new file mode 100644
index 0000000000..399b651f5e
--- /dev/null
+++ b/src/armnn/layers/ChannelShuffleLayer.hpp
@@ -0,0 +1,37 @@
+//
+// Copyright © 2021 Arm Ltd and Contributors. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+#pragma once
+
+#include "LayerWithParameters.hpp"
+
+namespace armnn
+{
+class ChannelShuffleLayer : public LayerWithParameters<ChannelShuffleDescriptor>
+{
+public:
+    void Accept(ILayerVisitor& visitor) const override;
+
+    /// Creates a dynamically-allocated copy of this layer.
+    /// @param graph The graph into which this layer is being cloned
+    ChannelShuffleLayer* Clone(Graph& graph) const override;
+
+    /// Makes a workload for the ChannelShuffle type.
+    /// @param factory The workload factory which will create the workload
+    /// @return A pointer to the created workload, or nullptr if not created.
+    virtual std::unique_ptr<IWorkload> CreateWorkload(const IWorkloadFactory& factory) const override;
+
+    /// Check if the input tensor shape(s)
+    /// will lead to a valid configuration of @ref ChannelShuffleLayer.
+    /// @param [in] shapeInferenceMethod Indicates if output shape shall be overwritten or just validated.
+    void ValidateTensorShapesFromInputs() override;
+
+    // TODO Do you need to create an InferOutputShapes function for ChannelShuffle?
+protected:
+    ChannelShuffleLayer(const ChannelShuffleDescriptor& param, const char* name);
+
+    ~ChannelShuffleLayer() = default;
+};
+
+} // namespace
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