IVGCVSW-3738 Add end-to-end layer test for DepthToSpace

* Added end-to-end layer test implementation for DepthToSpace
* Added test to reference, CL and NEON backends for all supported
  data types and data layouts
* Extracted common data permutation code into new utility file and
  refactored some existing tests to reduce code duplication
* Fixed EndToEndLayerTestImpl template to work with Float16 data

Signed-off-by: Aron Virginas-Tar <Aron.Virginas-Tar@arm.com>
Change-Id: Iaf7a0012c520451052b20c37e36dc05fa8314ff6

2 files changed, 22 insertions, 44 deletions

diff --git a/src/backends/backendsCommon/test/layerTests/DepthToSpaceTestImpl.cpp b/src/backends/backendsCommon/test/layerTests/DepthToSpaceTestImpl.cpp
index 9588f560ef..e21a4b64f8 100644
--- a/src/backends/backendsCommon/test/layerTests/DepthToSpaceTestImpl.cpp
+++ b/src/backends/backendsCommon/test/layerTests/DepthToSpaceTestImpl.cpp
@@ -9,6 +9,7 @@
 
 #include <armnn/ArmNN.hpp>
 
+#include <backendsCommon/test/DataLayoutUtils.hpp>
 #include <backendsCommon/test/TensorCopyUtils.hpp>
 #include <backendsCommon/test/WorkloadTestUtils.hpp>
 
@@ -29,22 +30,10 @@ LayerTestResult<T, 4> DepthToSpaceTestImpl(
     const float qScale = 1.0f,
     const int32_t qOffset = 0)
 {
-    const armnn::PermutationVector permVector{0, 2, 3, 1};
-
     if (descriptor.m_Parameters.m_DataLayout == armnn::DataLayout::NCHW)
     {
-        inputInfo  = armnnUtils::Permuted(inputInfo, permVector);
-        outputInfo = armnnUtils::Permuted(outputInfo, permVector);
-
-        constexpr size_t typeSize = sizeof(float);
-
-        std::vector<float> inputTmp(inputData.size());
-        armnnUtils::Permute(inputInfo.GetShape(), permVector, inputData.data(), inputTmp.data(), typeSize);
-        inputData = inputTmp;
-
-        std::vector<float> outputTmp(expectedOutputData.size());
-        armnnUtils::Permute(outputInfo.GetShape(), permVector, expectedOutputData.data(), outputTmp.data(), typeSize);
-        expectedOutputData = outputTmp;
+        PermuteTensorNhwcToNchw<float>(inputInfo, inputData);
+        PermuteTensorNhwcToNchw<float>(outputInfo, expectedOutputData);
     }
 
     if(armnn::IsQuantizedType<T>())
diff --git a/src/backends/backendsCommon/test/layerTests/TransposeConvolution2dTestImpl.hpp b/src/backends/backendsCommon/test/layerTests/TransposeConvolution2dTestImpl.hpp
index 6191adf61f..7391f9c198 100644
--- a/src/backends/backendsCommon/test/layerTests/TransposeConvolution2dTestImpl.hpp
+++ b/src/backends/backendsCommon/test/layerTests/TransposeConvolution2dTestImpl.hpp
@@ -12,7 +12,7 @@
 
 #include <backendsCommon/CpuTensorHandle.hpp>
 
-#include <backendsCommon/test/CommonTestUtils.hpp>
+#include <backendsCommon/test/DataLayoutUtils.hpp>
 #include <backendsCommon/test/QuantizeHelper.hpp>
 #include <backendsCommon/test/TensorCopyUtils.hpp>
 #include <backendsCommon/test/WorkloadTestUtils.hpp>
@@ -194,27 +194,16 @@ LayerTestResult<T, 4> TransposeConvolution2dTest(
 }
 
 template<typename T>
-void SwizzleData(const armnn::TensorInfo& inputInfo,
+void SwizzleData(armnn::TensorInfo& inputInfo,
                  std::vector<T>& inputData,
-                 const armnn::TensorInfo& outputInfo,
+                 armnn::TensorInfo& outputInfo,
                  std::vector<T>& outputData,
-                 const armnn::TensorInfo& weightsInfo,
+                 armnn::TensorInfo& weightsInfo,
                  std::vector<T>& weightsData)
 {
-    constexpr size_t dataTypeSize = sizeof(float);
-    const armnn::PermutationVector nchwToNhwc = { 0, 3, 1, 2 };
-
-    std::vector<T> tmp(inputData.size());
-    armnnUtils::Permute(inputInfo.GetShape(), nchwToNhwc, inputData.data(), tmp.data(), dataTypeSize);
-    inputData = tmp;
-
-    tmp.resize(weightsData.size());
-    armnnUtils::Permute(weightsInfo.GetShape(), nchwToNhwc, weightsData.data(), tmp.data(), dataTypeSize);
-    weightsData = tmp;
-
-    tmp.resize(outputData.size());
-    armnnUtils::Permute(outputInfo.GetShape(), nchwToNhwc, outputData.data(), tmp.data(), dataTypeSize);
-    outputData = tmp;
+    PermuteTensorNchwToNhwc<T>(inputInfo, inputData);
+    PermuteTensorNchwToNhwc<T>(outputInfo, outputData);
+    PermuteTensorNchwToNhwc<T>(weightsInfo, weightsData);
 }
 
 } // anonymous namespace
@@ -240,9 +229,9 @@ LayerTestResult<T, 4> SimpleTransposeConvolution2dTest(
     constexpr unsigned int wWeights = 3u;
     constexpr unsigned int hWeights = wWeights;
 
-    TensorShape inputShape   = MakeTensorShape(batches, channels, hInput, wInput, layout);
-    TensorShape outputShape  = MakeTensorShape(batches, channels, hOutput, wOutput, layout);
-    TensorShape weightsShape = MakeTensorShape(batches, channels, hWeights, wWeights, layout);
+    TensorShape inputShape   = { batches, channels, hInput,   wInput   };
+    TensorShape outputShape  = { batches, channels, hOutput,  wOutput  };
+    TensorShape weightsShape = { batches, channels, hWeights, wWeights };
 
     TensorInfo inputInfo(inputShape, ArmnnType);
     TensorInfo outputInfo(outputShape, ArmnnType);
@@ -327,9 +316,9 @@ LayerTestResult<T, 4> PaddedTransposeConvolution2dTest(
     constexpr unsigned int wWeights = 3u;
     constexpr unsigned int hWeights = wWeights;
 
-    TensorShape inputShape   = MakeTensorShape(batches, channels, hInput, wInput, layout);
-    TensorShape outputShape  = MakeTensorShape(batches, channels, hOutput, wOutput, layout);
-    TensorShape weightsShape = MakeTensorShape(batches, channels, hWeights, wWeights, layout);
+    TensorShape inputShape   = { batches, channels, hInput,   wInput   };
+    TensorShape outputShape  = { batches, channels, hOutput,  wOutput  };
+    TensorShape weightsShape = { batches, channels, hWeights, wWeights };
 
     TensorInfo inputInfo(inputShape, ArmnnType);
     TensorInfo outputInfo(outputShape, ArmnnType);
@@ -416,9 +405,9 @@ LayerTestResult<T, 4> StridedTransposeConvolution2dTest(
     constexpr unsigned int wWeights = 3u;
     constexpr unsigned int hWeights = wWeights;
 
-    TensorShape inputShape   = MakeTensorShape(batches, channels, hInput, wInput, layout);
-    TensorShape outputShape  = MakeTensorShape(batches, channels, hOutput, wOutput, layout);
-    TensorShape weightsShape = MakeTensorShape(batches, channels, hWeights, wWeights, layout);
+    TensorShape inputShape   = { batches, channels, hInput,   wInput   };
+    TensorShape outputShape  = { batches, channels, hOutput,  wOutput  };
+    TensorShape weightsShape = { batches, channels, hWeights, wWeights };
 
     TensorInfo inputInfo(inputShape, ArmnnType);
     TensorInfo outputInfo(outputShape, ArmnnType);
@@ -492,11 +481,11 @@ LayerTestResult<T, 4> MultiChannelTransposeConvolution2dTest(
 {
     using namespace armnn;
 
-    TensorShape inputShape   = MakeTensorShape(1, 1, 2, 2, layout);
-    TensorShape outputShape  = MakeTensorShape(1, 2, 5, 5, layout);
+    TensorShape inputShape   = { 1, 1, 2, 2 };
+    TensorShape outputShape  = { 1, 2, 5, 5 };
 
     // OIHW for NCHW; OHWI for NHWC
-    TensorShape weightsShape = MakeTensorShape(2, 1, 3, 3, layout);
+    TensorShape weightsShape = { 2, 1, 3, 3 };
     TensorShape biasesShape  = { 2 };
 
     TensorInfo inputInfo(inputShape, ArmnnType);