diff --git a/src/backends/backendsCommon/test/layerTests/ChannelShuffleTestImpl.cpp b/src/backends/backendsCommon/test/layerTests/ChannelShuffleTestImpl.cpp
new file mode 100644
index 0000000..46ee7d9
--- /dev/null
+++ b/src/backends/backendsCommon/test/layerTests/ChannelShuffleTestImpl.cpp
@@ -0,0 +1,269 @@
+//
+// Copyright © 2021 Arm Ltd and Contributors. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+
+#include "ChannelShuffleTestImpl.hpp"
+
+#include <backendsCommon/test/DataTypeUtils.hpp>
+#include <backendsCommon/test/TensorCopyUtils.hpp>
+#include <backendsCommon/test/WorkloadTestUtils.hpp>
+
+namespace
+{
+
+template<typename T, size_t NumDims>
+LayerTestResult<T, NumDims> ChannelShuffleTestImpl(
+        armnn::IWorkloadFactory& workloadFactory,
+        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
+        const armnn::ITensorHandleFactory& tensorHandleFactory,
+        armnn::ChannelShuffleDescriptor descriptor,
+        armnn::TensorInfo inputTensorInfo,
+        armnn::TensorInfo outputTensorInfo,
+        const std::vector<T>& inputData,
+        const std::vector<T>& outputExpectedData)
+{
+    IgnoreUnused(memoryManager);
+    std::vector<T> actualOutput(outputTensorInfo.GetNumElements());
+
+    std::unique_ptr<armnn::ITensorHandle> inputHandle = tensorHandleFactory.CreateTensorHandle(inputTensorInfo);
+    std::unique_ptr<armnn::ITensorHandle> outputHandle = tensorHandleFactory.CreateTensorHandle(outputTensorInfo);
+
+    armnn::ChannelShuffleQueueDescriptor data;
+    data.m_Parameters = descriptor;
+    armnn::WorkloadInfo info;
+    AddInputToWorkload(data, info, inputTensorInfo, inputHandle.get());
+    AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get());
+
+    std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateChannelShuffle(data, info);
+
+    inputHandle->Allocate();
+    outputHandle->Allocate();
+
+    CopyDataToITensorHandle(inputHandle.get(), inputData.data());
+
+    workload->Execute();
+
+    CopyDataFromITensorHandle(actualOutput.data(), outputHandle.get());
+
+    return LayerTestResult<T, NumDims>(actualOutput,
+                                       outputExpectedData,
+                                       outputHandle->GetShape(),
+                                       outputTensorInfo.GetShape());
+}
+} // anonymous namespace
+
+template<armnn::DataType ArmnnType, typename T>
+LayerTestResult<T, 4> SimpleChannelShuffleTest(
+        armnn::IWorkloadFactory& workloadFactory,
+        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
+        const armnn::ITensorHandleFactory& tensorHandleFactory)
+{
+    armnn::TensorInfo inputTensorInfo;
+    armnn::TensorInfo outputTensorInfo;
+
+    unsigned int inputShape[] = { 1,9,1,1 };
+    unsigned int outputShape[] = { 1,9,1,1 };
+
+    armnn::ChannelShuffleDescriptor descriptor;
+    descriptor.m_Axis = 1;
+    descriptor.m_NumGroups = 3;
+
+    inputTensorInfo = armnn::TensorInfo(4, inputShape, ArmnnType);
+    inputTensorInfo.SetQuantizationScale(1.0f);
+    outputTensorInfo = armnn::TensorInfo(4, outputShape, ArmnnType);
+    outputTensorInfo.SetQuantizationScale(1.0f);
+
+    auto input = ConvertToDataType<ArmnnType>(
+            {
+                0.0f, 1.0f, 2.0f,   3.0f, 4.0f, 5.0f,   6.0f, 7.0f, 8.0f
+            },
+            inputTensorInfo);
+    auto outputExpected = ConvertToDataType<ArmnnType>(
+            {
+                0.0f, 3.0f, 6.0f, 1.0f, 4.0f, 7.0f, 2.0f, 5.0f, 8.0f
+            },
+            outputTensorInfo);
+
+    return ChannelShuffleTestImpl<T, 4>(
+                workloadFactory,
+                memoryManager,
+                tensorHandleFactory,
+                descriptor,
+                inputTensorInfo,
+                outputTensorInfo,
+                input,
+                outputExpected);
+}
+
+template<armnn::DataType ArmnnType, typename T>
+LayerTestResult<T, 2> ChannelShuffle2DTest(
+        armnn::IWorkloadFactory& workloadFactory,
+        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
+        const armnn::ITensorHandleFactory& tensorHandleFactory)
+{
+    armnn::TensorInfo inputTensorInfo;
+    armnn::TensorInfo outputTensorInfo;
+
+    unsigned int inputShape[] = { 3, 12 };
+    unsigned int outputShape[] = { 3, 12 };
+
+    armnn::ChannelShuffleDescriptor descriptor;
+    descriptor.m_Axis = 1;
+    descriptor.m_NumGroups = 3;
+
+    inputTensorInfo = armnn::TensorInfo(2, inputShape, ArmnnType);
+    inputTensorInfo.SetQuantizationScale(1.0f);
+    outputTensorInfo = armnn::TensorInfo(2, outputShape, ArmnnType);
+    outputTensorInfo.SetQuantizationScale(1.0f);
+
+    auto input = ConvertToDataType<ArmnnType>(
+            {
+                0, 1, 2, 3,       4, 5, 6, 7,       8, 9, 10, 11,
+               12, 13, 14, 15,   16, 17, 18, 19,   20, 21, 22, 23,
+               24, 25, 26, 27,   28, 29, 30, 31,   32, 33, 34, 35
+            },
+            inputTensorInfo);
+
+    auto outputExpected = ConvertToDataType<ArmnnType>(
+            {
+                0, 4, 8, 1, 5, 9, 2, 6, 10, 3, 7, 11,
+                12, 16, 20, 13, 17, 21, 14, 18, 22, 15, 19, 23,
+                24, 28, 32, 25, 29, 33, 26, 30, 34, 27, 31, 35
+            },
+            outputTensorInfo);
+
+    return ChannelShuffleTestImpl<T, 2>(
+            workloadFactory,
+            memoryManager,
+            tensorHandleFactory,
+            descriptor,
+            inputTensorInfo,
+            outputTensorInfo,
+            input,
+            outputExpected);
+}
+
+template<armnn::DataType ArmnnType, typename T>
+LayerTestResult<T, 4> ChannelShuffle4DTest(
+        armnn::IWorkloadFactory& workloadFactory,
+        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
+        const armnn::ITensorHandleFactory& tensorHandleFactory)
+{
+    armnn::TensorInfo inputTensorInfo;
+    armnn::TensorInfo outputTensorInfo;
+
+    unsigned int inputShape[] = { 2, 9, 1, 2 };
+    unsigned int outputShape[] = { 2, 9, 1, 2 };
+
+    armnn::ChannelShuffleDescriptor descriptor;
+    descriptor.m_Axis = 1;
+    descriptor.m_NumGroups = 3;
+
+    inputTensorInfo = armnn::TensorInfo(4, inputShape, ArmnnType);
+    inputTensorInfo.SetQuantizationScale(1.0f);
+    outputTensorInfo = armnn::TensorInfo(4, outputShape, ArmnnType);
+    outputTensorInfo.SetQuantizationScale(1.0f);
+
+    auto input = ConvertToDataType<ArmnnType>(
+            {
+                    0.0f, 1.0f,
+                    2.0f, 3.0f,
+                    4.0f, 5.0f,
+
+                    6.0f, 7.0f,
+                    8.0f, 9.0f,
+                    10.0f, 11.0f,
+
+                    12.0f, 13.0f,
+                    14.0f, 15.0f,
+                    16.0f, 17.0f,
+
+                    18.0f, 19.0f,
+                    20.0f, 21.0f,
+                    22.0f, 23.0f,
+
+                    24.0f, 25.0f,
+                    26.0f, 27.0f,
+                    28.0f, 29.0f,
+
+                    30.0f, 31.0f,
+                    32.0f, 33.0f,
+                    34.0f, 35.0f
+            },
+            inputTensorInfo);
+
+    auto outputExpected = ConvertToDataType<ArmnnType>(
+            {
+                    0.0f, 1.0f,
+                    6.0f, 7.0f,
+                    12.0f, 13.0f,
+                    2.0f, 3.0f,
+                    8.0f, 9.0f,
+                    14.0f, 15.0f,
+                    4.0f, 5.0f,
+                    10.0f, 11.0f,
+                    16.0f, 17.0f,
+
+                    18.0f, 19.0f,
+                    24.0f, 25.0f,
+                    30.0f, 31.0f,
+                    20.0f, 21.0f,
+                    26.0f, 27.0f,
+                    32.0f, 33.0f,
+                    22.0f, 23.0f,
+                    28.0f, 29.0f,
+                    34.0f, 35.0f
+            },
+            outputTensorInfo);
+
+    return ChannelShuffleTestImpl<T, 4>(
+            workloadFactory,
+            memoryManager,
+            tensorHandleFactory,
+            descriptor,
+            inputTensorInfo,
+            outputTensorInfo,
+            input,
+            outputExpected);
+}
+
+//
+// Explicit template specializations
+//
+
+template LayerTestResult<armnn::ResolveType<armnn::DataType::Float32>, 4>
+SimpleChannelShuffleTest<armnn::DataType::Float32>(
+        armnn::IWorkloadFactory& workloadFactory,
+        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
+        const armnn::ITensorHandleFactory& tensorHandleFactory);
+
+template LayerTestResult<armnn::ResolveType<armnn::DataType::QAsymmU8>, 4>
+SimpleChannelShuffleTest<armnn::DataType::QAsymmU8>(
+        armnn::IWorkloadFactory& workloadFactory,
+        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
+        const armnn::ITensorHandleFactory& tensorHandleFactory);
+
+template LayerTestResult<armnn::ResolveType<armnn::DataType::Float32>, 2>
+ChannelShuffle2DTest<armnn::DataType::Float32>(
+    armnn::IWorkloadFactory& workloadFactory,
+    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
+    const armnn::ITensorHandleFactory& tensorHandleFactory);
+
+template LayerTestResult<armnn::ResolveType<armnn::DataType::QAsymmU8>, 2>
+ChannelShuffle2DTest<armnn::DataType::QAsymmU8>(
+    armnn::IWorkloadFactory& workloadFactory,
+    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
+    const armnn::ITensorHandleFactory& tensorHandleFactory);
+
+template LayerTestResult<armnn::ResolveType<armnn::DataType::Float32>, 4>
+ChannelShuffle4DTest<armnn::DataType::Float32>(
+        armnn::IWorkloadFactory& workloadFactory,
+        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
+        const armnn::ITensorHandleFactory& tensorHandleFactory);
+
+template LayerTestResult<armnn::ResolveType<armnn::DataType::QAsymmU8>, 4>
+ChannelShuffle4DTest<armnn::DataType::QAsymmU8>(
+        armnn::IWorkloadFactory& workloadFactory,
+        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
+        const armnn::ITensorHandleFactory& tensorHandleFactory);
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