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

1 files changed, 33 insertions, 0 deletions

diff --git a/src/backends/reference/RefLayerSupport.cpp b/src/backends/reference/RefLayerSupport.cpp
index 5eba3e5919..aaf9aa0e7c 100644
--- a/src/backends/reference/RefLayerSupport.cpp
+++ b/src/backends/reference/RefLayerSupport.cpp
@@ -333,6 +333,39 @@ bool RefLayerSupport::IsCastSupported(const TensorInfo& input,
     return supported;
 }
 
+bool RefLayerSupport::IsChannelShuffleSupported(const TensorInfo& input,
+                                                const TensorInfo& output,
+                                                const ChannelShuffleDescriptor& descriptor,
+                                                Optional<std::string&> reasonIfUnsupported) const
+{
+    IgnoreUnused(descriptor);
+    bool supported = true;
+
+    // Define supported output and inputs types.
+    std::array<DataType, 7> supportedTypes =
+    {
+        DataType::BFloat16,
+        DataType::Float32,
+        DataType::Float16,
+        DataType::QAsymmS8,
+        DataType::QAsymmU8,
+        DataType::QSymmS8,
+        DataType::QSymmS16
+    };
+
+    supported &= CheckSupportRule(TypeAnyOf(input, supportedTypes), reasonIfUnsupported,
+                                  "Reference ChannelShuffle: input is not a supported type.");
+
+    supported &= CheckSupportRule(TypeAnyOf(output, supportedTypes), reasonIfUnsupported,
+                                  "Reference ChannelShuffle: output is not a supported type.");
+
+    supported &= CheckSupportRule(TypesAreEqual(input, output), reasonIfUnsupported,
+                                  "Reference ChannelShuffle: input and output types are mismatched.");
+
+    return supported;
+}
+
+
 bool RefLayerSupport::IsComparisonSupported(const TensorInfo& input0,
                                             const TensorInfo& input1,
                                             const TensorInfo& output,