1 files changed, 147 insertions, 0 deletions
diff --git a/src/backends/backendsCommon/test/SpaceToDepthTestImpl.hpp b/src/backends/backendsCommon/test/SpaceToDepthTestImpl.hpp
new file mode 100644
index 0000000000..99926cd026
--- /dev/null
+++ b/src/backends/backendsCommon/test/SpaceToDepthTestImpl.hpp
@@ -0,0 +1,147 @@
+//
+// Copyright © 2017 Arm Ltd. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+#pragma once
+
+#include "WorkloadTestUtils.hpp"
+
+#include <armnn/ArmNN.hpp>
+#include <armnn/Tensor.hpp>
+#include <armnn/TypesUtils.hpp>
+
+#include <backendsCommon/CpuTensorHandle.hpp>
+#include <backendsCommon/IBackendInternal.hpp>
+#include <backendsCommon/WorkloadFactory.hpp>
+
+#include <test/TensorHelpers.hpp>
+
+template<typename T>
+LayerTestResult<T, 4> SpaceToDepthTestImpl(
+    armnn::IWorkloadFactory& workloadFactory,
+    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
+    armnn::TensorInfo& inputTensorInfo,
+    armnn::TensorInfo& outputTensorInfo,
+    std::vector<float>& inputData,
+    std::vector<float>& outputExpectedData,
+    armnn::SpaceToDepthQueueDescriptor descriptor,
+    const float qScale = 1.0f,
+    const int32_t qOffset = 0)
+{
+    const armnn::PermutationVector NHWCToNCHW = {0, 2, 3, 1};
+
+    if (descriptor.m_Parameters.m_DataLayout == armnn::DataLayout::NCHW)
+    {
+        inputTensorInfo = armnnUtils::Permuted(inputTensorInfo, NHWCToNCHW);
+        outputTensorInfo = armnnUtils::Permuted(outputTensorInfo, NHWCToNCHW);
+
+        std::vector<float> inputTmp(inputData.size());
+        armnnUtils::Permute(inputTensorInfo.GetShape(), NHWCToNCHW,
+            inputData.data(), inputTmp.data(), sizeof(float));
+        inputData = inputTmp;
+
+        std::vector<float> outputTmp(outputExpectedData.size());
+        armnnUtils::Permute(outputTensorInfo.GetShape(), NHWCToNCHW,
+            outputExpectedData.data(), outputTmp.data(), sizeof(float));
+        outputExpectedData = outputTmp;
+    }
+
+    if(armnn::IsQuantizedType<T>())
+    {
+        inputTensorInfo.SetQuantizationScale(qScale);
+        inputTensorInfo.SetQuantizationOffset(qOffset);
+        outputTensorInfo.SetQuantizationScale(qScale);
+        outputTensorInfo.SetQuantizationOffset(qOffset);
+    }
+
+    boost::multi_array<T, 4> input = MakeTensor<T, 4>(inputTensorInfo, QuantizedVector<T>(qScale, qOffset, inputData));
+
+    LayerTestResult<T, 4> ret(outputTensorInfo);
+    ret.outputExpected = MakeTensor<T, 4>(outputTensorInfo, QuantizedVector<T>(qScale, qOffset, outputExpectedData));
+
+    std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo);
+    std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo);
+
+    armnn::WorkloadInfo info;
+    AddInputToWorkload(descriptor, info, inputTensorInfo, inputHandle.get());
+    AddOutputToWorkload(descriptor, info, outputTensorInfo, outputHandle.get());
+
+    std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateSpaceToDepth(descriptor, info);
+
+    inputHandle->Allocate();
+    outputHandle->Allocate();
+
+    CopyDataToITensorHandle(inputHandle.get(), &input[0][0][0][0]);
+
+    workload->Execute();
+
+    CopyDataFromITensorHandle(&ret.output[0][0][0][0], outputHandle.get());
+
+    return ret;
+}
+
+template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
+LayerTestResult<T, 4> SpaceToDepthSimpleTest(
+    armnn::IWorkloadFactory& workloadFactory,
+    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
+    armnn::DataLayout dataLayout = armnn::DataLayout::NHWC)
+{
+    unsigned int inputShape[] = {1, 2, 2, 1};
+    unsigned int outputShape[] = {1, 1, 1, 4};
+
+    std::vector<float> input = std::vector<float>(
+    {
+        1.0f, 2.0f, 3.0f, 4.0f
+    });
+
+    std::vector<float> outputExpected = std::vector<float>(
+    {
+        1.0f, 2.0f, 3.0f, 4.0f
+    });
+
+    armnn::TensorInfo inputTensorInfo;
+    armnn::TensorInfo outputTensorInfo;
+
+    armnn::SpaceToDepthQueueDescriptor desc;
+    desc.m_Parameters.m_DataLayout = dataLayout;
+    desc.m_Parameters.m_BlockSize = 2;
+
+    inputTensorInfo = armnn::TensorInfo(4, inputShape, ArmnnType);
+    outputTensorInfo = armnn::TensorInfo(4, outputShape, ArmnnType);
+
+    return SpaceToDepthTestImpl<T>(
+        workloadFactory, memoryManager, inputTensorInfo, outputTensorInfo, input, outputExpected, desc);
+}
+
+template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
+LayerTestResult<T, 4> SpaceToDepthFloatTest(
+    armnn::IWorkloadFactory& workloadFactory,
+    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
+    armnn::DataLayout dataLayout = armnn::DataLayout::NHWC)
+{
+    unsigned int inputShape[] = {1, 2, 2, 2};
+    unsigned int outputShape[] = {1, 1, 1, 8};
+
+    std::vector<float> input = std::vector<float>(
+    {
+        1.4f, 2.3f, 3.2f, 4.1f, 5.4f, 6.3f, 7.2f, 8.1f
+    });
+
+    std::vector<float> outputExpected = std::vector<float>(
+    {
+        1.4f, 2.3f, 3.2f, 4.1f, 5.4f, 6.3f, 7.2f, 8.1f
+    });
+
+    armnn::TensorInfo inputTensorInfo;
+    armnn::TensorInfo outputTensorInfo;
+
+    armnn::SpaceToDepthQueueDescriptor desc;
+    desc.m_Parameters.m_DataLayout = dataLayout;
+    desc.m_Parameters.m_BlockSize = 2;
+
+    inputTensorInfo = armnn::TensorInfo(4, inputShape, ArmnnType);
+    outputTensorInfo = armnn::TensorInfo(4, outputShape, ArmnnType);
+
+    return SpaceToDepthTestImpl<T>(
+        workloadFactory, memoryManager, inputTensorInfo, outputTensorInfo, input, outputExpected, desc);
+}