IVGCVSW-3616 Add multi-channel unit test for TransposeConvolution2d
Signed-off-by: Aron Virginas-Tar <Aron.Virginas-Tar@arm.com>
Change-Id: Ib9271920b39fb9d730006c79a322e32008096b56
diff --git a/src/backends/backendsCommon/test/TransposeConvolution2dTestImpl.hpp b/src/backends/backendsCommon/test/TransposeConvolution2dTestImpl.hpp
index 3bbd5d6..bf424eb 100644
--- a/src/backends/backendsCommon/test/TransposeConvolution2dTestImpl.hpp
+++ b/src/backends/backendsCommon/test/TransposeConvolution2dTestImpl.hpp
@@ -106,7 +106,7 @@
}
template<armnn::DataType ArmnnType, armnn::DataType ArmnnBType, typename T = armnn::ResolveType<ArmnnType>>
-LayerTestResult<T, 4> TransposeConvolution2dTestImpl(
+LayerTestResult<T, 4> TransposeConvolution2dTest(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
const armnn::TransposeConvolution2dDescriptor& descriptor,
@@ -124,8 +124,8 @@
// set up quantization parameters
if (armnn::IsQuantizedType<T>())
{
- constexpr float qScale = 0.25f;
- constexpr int32_t qOffset = 50;
+ constexpr float qScale = 0.50f;
+ constexpr int32_t qOffset = 10;
inputInfo.SetQuantizationScale(qScale);
inputInfo.SetQuantizationOffset(qOffset);
@@ -191,10 +191,34 @@
return testResult;
}
+template<typename T>
+void SwizzleData(const armnn::TensorInfo& inputInfo,
+ std::vector<T>& inputData,
+ const armnn::TensorInfo& outputInfo,
+ std::vector<T>& outputData,
+ const 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;
+}
+
} // anonymous namespace
template<armnn::DataType ArmnnType, armnn::DataType ArmnnBType, typename T = armnn::ResolveType<ArmnnType>>
-LayerTestResult<T, 4> SimpleTransposeConvolution2dTestImpl(
+LayerTestResult<T, 4> SimpleTransposeConvolution2dTest(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
bool biasEnabled,
@@ -264,37 +288,24 @@
// swizzle data if needed
if (layout == armnn::DataLayout::NHWC)
{
- constexpr size_t dataTypeSize = sizeof(float);
- const armnn::PermutationVector nchwToNhwc = { 0, 3, 1, 2 };
-
- std::vector<float> 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(expectedOutputData.size());
- armnnUtils::Permute(outputInfo.GetShape(), nchwToNhwc, expectedOutputData.data(), tmp.data(), dataTypeSize);
- expectedOutputData = tmp;
+ SwizzleData(inputInfo, inputData, outputInfo, expectedOutputData, weightsInfo, weightsData);
}
- return TransposeConvolution2dTestImpl<ArmnnType, ArmnnBType>(workloadFactory,
- memoryManager,
- descriptor,
- inputInfo,
- inputData,
- outputInfo,
- expectedOutputData,
- weightsInfo,
- weightsData,
- biasesInfo,
- biasesData);
+ return TransposeConvolution2dTest<ArmnnType, ArmnnBType>(workloadFactory,
+ memoryManager,
+ descriptor,
+ inputInfo,
+ inputData,
+ outputInfo,
+ expectedOutputData,
+ weightsInfo,
+ weightsData,
+ biasesInfo,
+ biasesData);
}
template<armnn::DataType ArmnnType, armnn::DataType ArmnnBType, typename T = armnn::ResolveType<ArmnnType>>
-LayerTestResult<T, 4> PaddedTransposeConvolution2dTestImpl(
+LayerTestResult<T, 4> PaddedTransposeConvolution2dTest(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
bool biasEnabled,
@@ -366,41 +377,28 @@
// swizzle data if needed
if (layout == armnn::DataLayout::NHWC)
{
- constexpr size_t dataTypeSize = sizeof(float);
- const armnn::PermutationVector nchwToNhwc = { 0, 3, 1, 2 };
-
- std::vector<float> 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(expectedOutputData.size());
- armnnUtils::Permute(outputInfo.GetShape(), nchwToNhwc, expectedOutputData.data(), tmp.data(), dataTypeSize);
- expectedOutputData = tmp;
+ SwizzleData(inputInfo, inputData, outputInfo, expectedOutputData, weightsInfo, weightsData);
}
- return TransposeConvolution2dTestImpl<ArmnnType, ArmnnBType>(workloadFactory,
- memoryManager,
- descriptor,
- inputInfo,
- inputData,
- outputInfo,
- expectedOutputData,
- weightsInfo,
- weightsData,
- biasesInfo,
- biasesData);
+ return TransposeConvolution2dTest<ArmnnType, ArmnnBType>(workloadFactory,
+ memoryManager,
+ descriptor,
+ inputInfo,
+ inputData,
+ outputInfo,
+ expectedOutputData,
+ weightsInfo,
+ weightsData,
+ biasesInfo,
+ biasesData);
}
- template<armnn::DataType ArmnnType, armnn::DataType ArmnnBType, typename T = armnn::ResolveType<ArmnnType>>
- LayerTestResult<T, 4> StridedTransposeConvolution2dTestImpl(
- armnn::IWorkloadFactory& workloadFactory,
- const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
- bool biasEnabled,
- const armnn::DataLayout layout)
+template<armnn::DataType ArmnnType, armnn::DataType ArmnnBType, typename T = armnn::ResolveType<ArmnnType>>
+LayerTestResult<T, 4> StridedTransposeConvolution2dTest(
+ armnn::IWorkloadFactory& workloadFactory,
+ const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
+ bool biasEnabled,
+ const armnn::DataLayout layout)
{
using namespace armnn;
@@ -468,31 +466,96 @@
// swizzle data if needed
if (layout == armnn::DataLayout::NHWC)
{
- constexpr size_t dataTypeSize = sizeof(float);
- const armnn::PermutationVector nchwToNhwc = { 0, 3, 1, 2 };
-
- std::vector<float> 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(expectedOutputData.size());
- armnnUtils::Permute(outputInfo.GetShape(), nchwToNhwc, expectedOutputData.data(), tmp.data(), dataTypeSize);
- expectedOutputData = tmp;
+ SwizzleData(inputInfo, inputData, outputInfo, expectedOutputData, weightsInfo, weightsData);
}
- return TransposeConvolution2dTestImpl<ArmnnType, ArmnnBType>(workloadFactory,
- memoryManager,
- descriptor,
- inputInfo,
- inputData,
- outputInfo,
- expectedOutputData,
- weightsInfo,
- weightsData,
- biasesInfo,
- biasesData);
-}
\ No newline at end of file
+ return TransposeConvolution2dTest<ArmnnType, ArmnnBType>(workloadFactory,
+ memoryManager,
+ descriptor,
+ inputInfo,
+ inputData,
+ outputInfo,
+ expectedOutputData,
+ weightsInfo,
+ weightsData,
+ biasesInfo,
+ biasesData);
+}
+
+template<armnn::DataType ArmnnType, armnn::DataType ArmnnBType, typename T = armnn::ResolveType<ArmnnType>>
+LayerTestResult<T, 4> MultiChannelTransposeConvolution2dTest(
+ armnn::IWorkloadFactory& workloadFactory,
+ const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
+ const armnn::DataLayout layout)
+{
+ using namespace armnn;
+
+ TensorShape inputShape = MakeTensorShape(1, 1, 2, 2, layout);
+ TensorShape outputShape = MakeTensorShape(1, 2, 5, 5, layout);
+
+ TensorShape weightsShape = MakeTensorShape(1, 2, 3, 3, layout);
+ TensorShape biasesShape = { 2 };
+
+ TensorInfo inputInfo(inputShape, ArmnnType);
+ TensorInfo outputInfo(outputShape, ArmnnType);
+ TensorInfo weightsInfo(weightsShape, ArmnnType);
+ TensorInfo biasesInfo(biasesShape, ArmnnBType);
+
+ std::vector<float> inputData =
+ {
+ 1.f, 2.f,
+ 3.f, 4.f,
+ };
+
+ std::vector<float> weightsData =
+ {
+ 1.f, 3.f, 5.f,
+ 7.f, 9.f, 11.f,
+ 13.f, 15.f, 17.f,
+
+ 2.f, 4.f, 6.f,
+ 8.f, 10.f, 12.f,
+ 14.f, 16.f, 18.f
+ };
+
+ std::vector<float> biasesData = { -1.5f, -2.0f };
+
+ std::vector<float> expectedOutputData =
+ {
+ -0.5f, 1.5f, 5.5f, 4.5f, 8.5f,
+ 5.5f, 7.5f, 23.5f, 16.5f, 20.5f,
+ 14.5f, 22.5f, 60.5f, 40.5f, 52.5f,
+ 19.5f, 25.5f, 59.5f, 34.5f, 42.5f,
+ 37.5f, 43.5f, 101.5f, 58.5f, 66.5f,
+
+ 0.0f, 2.0f, 8.0f, 6.0f, 10.0f,
+ 6.0f, 8.0f, 26.0f, 18.0f, 22.0f,
+ 18.0f, 26.0f, 70.0f, 46.0f, 58.0f,
+ 22.0f, 28.0f, 66.0f, 38.0f, 46.0f,
+ 40.0f, 46.0f, 108.0f, 62.0f, 70.0f,
+ };
+
+ TransposeConvolution2dDescriptor descriptor;
+ descriptor.m_StrideX = 2;
+ descriptor.m_StrideY = 2;
+ descriptor.m_BiasEnabled = true;
+ descriptor.m_DataLayout = layout;
+
+ // swizzle data if needed
+ if (layout == armnn::DataLayout::NHWC)
+ {
+ SwizzleData(inputInfo, inputData, outputInfo, expectedOutputData, weightsInfo, weightsData);
+ }
+
+ return TransposeConvolution2dTest<ArmnnType, ArmnnBType>(workloadFactory,
+ memoryManager,
+ descriptor,
+ inputInfo,
+ inputData,
+ outputInfo,
+ expectedOutputData,
+ weightsInfo,
+ weightsData,
+ biasesInfo,
+ biasesData);
+}