IVGCVSW-2013 Add a UInt8 Reference Implementation for the PAD Operator
Change-Id: I41f3606198db1fda8d72aaf5169594ba9156eb38
diff --git a/src/backends/cl/test/ClLayerTests.cpp b/src/backends/cl/test/ClLayerTests.cpp
index a4f824a..d5e9419 100755
--- a/src/backends/cl/test/ClLayerTests.cpp
+++ b/src/backends/cl/test/ClLayerTests.cpp
@@ -248,9 +248,9 @@
ARMNN_AUTO_TEST_CASE(SimpleReshapeUint8, SimpleReshapeUint8Test)
// Pad
-ARMNN_AUTO_TEST_CASE(Pad2d, Pad2dTest)
-ARMNN_AUTO_TEST_CASE(Pad3d, Pad3dTest)
-ARMNN_AUTO_TEST_CASE(Pad4d, Pad4dTest)
+ARMNN_AUTO_TEST_CASE(PadFloat322d, PadFloat322dTest)
+ARMNN_AUTO_TEST_CASE(PadFloat323d, PadFloat323dTest)
+ARMNN_AUTO_TEST_CASE(PadFloat324d, PadFloat324dTest)
// Permute
ARMNN_AUTO_TEST_CASE(SimplePermuteFloat32, SimplePermuteFloat32Test)
diff --git a/src/backends/reference/RefWorkloadFactory.cpp b/src/backends/reference/RefWorkloadFactory.cpp
index 4d157d4..b1f9d6c 100644
--- a/src/backends/reference/RefWorkloadFactory.cpp
+++ b/src/backends/reference/RefWorkloadFactory.cpp
@@ -249,7 +249,7 @@
std::unique_ptr<IWorkload> RefWorkloadFactory::CreatePad(const PadQueueDescriptor& descriptor,
const WorkloadInfo& info) const
{
- return MakeWorkload<RefPadWorkload, NullWorkload>(descriptor, info);
+ return MakeWorkload<RefPadFloat32Workload, RefPadUint8Workload>(descriptor, info);
}
diff --git a/src/backends/reference/test/RefLayerTests.cpp b/src/backends/reference/test/RefLayerTests.cpp
index 259739b..9f044cd 100644
--- a/src/backends/reference/test/RefLayerTests.cpp
+++ b/src/backends/reference/test/RefLayerTests.cpp
@@ -213,9 +213,13 @@
ARMNN_AUTO_TEST_CASE(L2Normalization4d, L2Normalization4dTest)
// Pad
-ARMNN_AUTO_TEST_CASE(Pad2d, Pad2dTest)
-ARMNN_AUTO_TEST_CASE(Pad3d, Pad3dTest)
-ARMNN_AUTO_TEST_CASE(Pad4d, Pad4dTest)
+ARMNN_AUTO_TEST_CASE(PadFloat322d, PadFloat322dTest)
+ARMNN_AUTO_TEST_CASE(PadFloat323d, PadFloat323dTest)
+ARMNN_AUTO_TEST_CASE(PadFloat324d, PadFloat324dTest)
+
+ARMNN_AUTO_TEST_CASE(PadUint82d, PadUint82dTest)
+ARMNN_AUTO_TEST_CASE(PadUint83d, PadUint83dTest)
+ARMNN_AUTO_TEST_CASE(PadUint84d, PadUint84dTest)
ARMNN_AUTO_TEST_CASE(L2Normalization1dNhwc, L2Normalization1dNhwcTest)
ARMNN_AUTO_TEST_CASE(L2Normalization2dNhwc, L2Normalization2dNhwcTest)
diff --git a/src/backends/reference/workloads/Pad.cpp b/src/backends/reference/workloads/Pad.cpp
index 5c85931..a50fa23 100644
--- a/src/backends/reference/workloads/Pad.cpp
+++ b/src/backends/reference/workloads/Pad.cpp
@@ -5,24 +5,22 @@
#include "Pad.hpp"
#include "backends/WorkloadData.hpp"
-
#include <boost/numeric/conversion/cast.hpp>
#include "TensorBufferArrayView.hpp"
-
#include <cmath>
#include <cstddef>
#include <functional>
#include <limits>
#include <cassert>
-
namespace armnn
{
+template <typename T>
void Pad(const TensorInfo& inputInfo,
const TensorInfo& outputInfo,
std::vector<std::pair<unsigned int, unsigned int>> m_PadList,
- const float* inputData,
- float* outData)
+ const T* inputData,
+ T* outData)
{
unsigned int numOutputElements = outputInfo.GetNumElements();
@@ -30,10 +28,12 @@
TensorShape inputShape = inputInfo.GetShape();
unsigned int numInputDimensions = inputShape.GetNumDimensions();
- #ifndef NDEBUG
- unsigned int numOutputDimensions = outputShape.GetNumDimensions();
+ #ifndef NDEBUG
+
+ unsigned int numOutputDimensions = outputShape.GetNumDimensions();
assert(numInputDimensions == numOutputDimensions);
+
#endif
unsigned int inputBatches = 0;
@@ -51,29 +51,27 @@
}
switch(numInputDimensions) {
+
case 1:
inputWidth = inputShape[0];
for (unsigned int w = 0; w < inputWidth ; w++)
{
-
outData[w+std::get<0>(m_PadList[0])] = inputData[w];
-
}
break;
+
case 2 :
inputHeight = inputShape[0];
inputWidth = inputShape[1];
-
outputHeight = outputShape[0];
outputWidth = outputShape[1];
for (unsigned int h = 0; h < inputHeight; h++)
{
-
for (unsigned int w = 0; w < inputWidth ; w++)
{
outData[(h+std::get<0>(m_PadList[0]))*outputWidth
@@ -82,25 +80,22 @@
}
break;
+
case 3 :
inputChannels = inputShape[0];
inputHeight = inputShape[1];
inputWidth = inputShape[2];
-
outputChannels = outputShape[0];
outputHeight = outputShape[1];
outputWidth = outputShape[2];
for (unsigned int c = 0; c < inputChannels; c++)
{
-
for (unsigned int h = 0; h < inputHeight; h++)
{
-
for (unsigned int w = 0; w < inputWidth ; w++)
{
-
outData[(c+std::get<0>(m_PadList[0]))*outputHeight*outputWidth
+ (h+std::get<0>(m_PadList[1]))*outputWidth
+ (w+std::get<0>(m_PadList[2]))] = inputData[c * inputHeight * inputWidth
@@ -111,13 +106,13 @@
}
break;
+
case 4 :
inputBatches = inputShape[0];
inputChannels = inputShape[1];
inputHeight = inputShape[2];
inputWidth = inputShape[3];
-
outputChannels = outputShape[1];
outputHeight = outputShape[2];
outputWidth = outputShape[3];
@@ -126,13 +121,10 @@
{
for (unsigned int c = 0; c < inputChannels; c++)
{
-
for (unsigned int h = 0; h < inputHeight; h++)
{
-
for (unsigned int w = 0; w < inputWidth ; w++)
{
-
outData[(b+std::get<0>(m_PadList[0])) * outputChannels * outputHeight * outputWidth
+ (c+std::get<0>(m_PadList[1])) * outputHeight * outputWidth
+ (h+std::get<0>(m_PadList[2])) * outputWidth
@@ -141,7 +133,6 @@
+ c * inputHeight * inputWidth
+ h * inputWidth
+ w];
-
}
}
}
@@ -150,9 +141,20 @@
break;
default :
+
break;
}
-
}
-} //namespace armnn
+template void Pad<float>(const TensorInfo& inputInfo,
+ const TensorInfo& outputInfo,
+ std::vector<std::pair<unsigned int, unsigned int>> m_PadList,
+ const float* inputData,
+ float* outData);
+template void Pad<uint8_t>(const TensorInfo& inputInfo,
+ const TensorInfo& outputInfo,
+ std::vector<std::pair<unsigned int, unsigned int>> m_PadList,
+ const uint8_t* inputData,
+ uint8_t* outData);
+
+} //namespace armnn
\ No newline at end of file
diff --git a/src/backends/reference/workloads/Pad.hpp b/src/backends/reference/workloads/Pad.hpp
index ed80ef8..42318d6 100644
--- a/src/backends/reference/workloads/Pad.hpp
+++ b/src/backends/reference/workloads/Pad.hpp
@@ -12,9 +12,10 @@
namespace armnn
{
+template <typename T>
void Pad(const TensorInfo& inputInfo,
- const TensorInfo& outputInfo,
- std::vector<std::pair<unsigned int, unsigned int>> m_PadList,
- const float* inputData,
- float* outData);
+ const TensorInfo& outputInfo,
+ std::vector<std::pair<unsigned int, unsigned int>> m_PadList,
+ const T* inputData,
+ T* outData);
} //namespace armnn
diff --git a/src/backends/reference/workloads/RefPadWorkload.cpp b/src/backends/reference/workloads/RefPadWorkload.cpp
index 233fbe4..b41c2de 100644
--- a/src/backends/reference/workloads/RefPadWorkload.cpp
+++ b/src/backends/reference/workloads/RefPadWorkload.cpp
@@ -10,28 +10,31 @@
#include "Profiling.hpp"
+#include "TypeUtils.hpp"
+
#include <vector>
namespace armnn
{
-RefPadWorkload::RefPadWorkload(const PadQueueDescriptor& descriptor, const WorkloadInfo& info)
- :BaseWorkload<PadQueueDescriptor>(descriptor, info) {}
-
-
-void RefPadWorkload::Execute() const
+template <armnn::DataType DataType>
+void RefPadWorkload<DataType>::Execute() const
{
+ using T = ResolveType<DataType>;
ARMNN_SCOPED_PROFILING_EVENT(Compute::CpuRef, "RefPadWorkload_Execute");
const TensorInfo& inputInfo = GetTensorInfo(m_Data.m_Inputs[0]);
const TensorInfo& outputInfo = GetTensorInfo(m_Data.m_Outputs[0]);
- const float* inputData = GetInputTensorDataFloat(0, m_Data);
- float* outputData = GetOutputTensorDataFloat(0, m_Data);
+ const T* inputData = GetInputTensorData<T>(0, m_Data);
+ T* outputData = GetOutputTensorData<T>(0, m_Data);
Pad(inputInfo, outputInfo, m_Data.m_Parameters.m_PadList, inputData, outputData);
}
+template class RefPadWorkload<DataType::Float32>;
+template class RefPadWorkload<DataType::QuantisedAsymm8>;
+
} //namespace armnn
\ No newline at end of file
diff --git a/src/backends/reference/workloads/RefPadWorkload.hpp b/src/backends/reference/workloads/RefPadWorkload.hpp
index 7ff117d..938fcf2 100644
--- a/src/backends/reference/workloads/RefPadWorkload.hpp
+++ b/src/backends/reference/workloads/RefPadWorkload.hpp
@@ -5,17 +5,32 @@
#pragma once
-#include "backends/Workload.hpp"
-#include "backends/WorkloadData.hpp"
+#include <backends/Workload.hpp>
+#include <backends/WorkloadData.hpp>
+
+#include <armnn/TypesUtils.hpp>
namespace armnn
{
-class RefPadWorkload : public BaseWorkload<PadQueueDescriptor>
+template <armnn::DataType DataType>
+class RefPadWorkload : public TypedWorkload<PadQueueDescriptor, DataType>
{
public:
- explicit RefPadWorkload (const PadQueueDescriptor& descriptor, const WorkloadInfo& info);
- virtual void Execute() const override;
+
+ static const std::string& GetName()
+ {
+ static const std::string name = std::string("RefPad") + GetDataTypeName(DataType) + "Workload";
+ return name;
+ }
+
+ using TypedWorkload<PadQueueDescriptor, DataType>::m_Data;
+ using TypedWorkload<PadQueueDescriptor, DataType>::TypedWorkload;
+
+ void Execute() const override;
};
+using RefPadFloat32Workload = RefPadWorkload<DataType::Float32>;
+using RefPadUint8Workload = RefPadWorkload<DataType::QuantisedAsymm8>;
+
} //namespace armnn
diff --git a/src/backends/reference/workloads/RefPermuteWorkload.hpp b/src/backends/reference/workloads/RefPermuteWorkload.hpp
index 841a080..50caa3e 100644
--- a/src/backends/reference/workloads/RefPermuteWorkload.hpp
+++ b/src/backends/reference/workloads/RefPermuteWorkload.hpp
@@ -31,4 +31,4 @@
using RefPermuteFloat32Workload = RefPermuteWorkload<DataType::Float32>;
using RefPermuteUint8Workload = RefPermuteWorkload<DataType::QuantisedAsymm8>;
-} //namespace armnn
+} //namespace armnn
\ No newline at end of file
diff --git a/src/backends/test/LayerTests.cpp b/src/backends/test/LayerTests.cpp
index 95f2a32..e762152 100755
--- a/src/backends/test/LayerTests.cpp
+++ b/src/backends/test/LayerTests.cpp
@@ -3441,123 +3441,120 @@
} // anonymous namespace
-LayerTestResult<float, 2> Pad2dTest(armnn::IWorkloadFactory& workloadFactory)
+template<typename T>
+LayerTestResult<T, 2> Pad2dTestCommon(armnn::IWorkloadFactory& workloadFactory, float qScale, int32_t qOffset)
{
- const armnn::TensorShape inputShape{ 3, 3 };
- const armnn::TensorShape outputShape{ 7, 7 };
+ const armnn::TensorShape inputShape{ 3, 3 };
+ const armnn::TensorShape outputShape{ 7, 7 };
- const armnn::TensorInfo inputTensorInfo(inputShape, armnn::DataType::Float32);
- const armnn::TensorInfo outputTensorInfo(outputShape, armnn::DataType::Float32);
+ const armnn::TensorInfo inputTensorInfo(inputShape, armnn::GetDataType<T>());
+ const armnn::TensorInfo outputTensorInfo(outputShape, armnn::GetDataType<T>());
-
- std::vector<float> inputValues
+ std::vector<T> inputValues(
+ QuantizedVector<T>(qScale, qOffset,
{
+ // Height (3) x Width (3)
+ 4, 8, 6,
+ 7, 4, 4,
+ 3, 2, 4
+ }));
- // Height (3) x Width (3)
- 4.0f, 8.0f, 6.0f,
- 7.0f, 4.0f, 4.0f,
- 3.0f, 2.0f, 4.0f
-
- };
-
- std::vector<float> expectedOutputValues
+ std::vector<T> expectedOutputValues(
+ QuantizedVector<T>(qScale, qOffset,
{
+ 0, 0, 0, 0, 0, 0, 0,
+ 0, 0, 0, 0, 0, 0, 0,
+ 0, 0, 4, 8, 6, 0, 0,
+ 0, 0, 7, 4, 4, 0, 0,
+ 0, 0, 3, 2, 4, 0, 0,
+ 0, 0, 0, 0, 0, 0, 0,
+ 0, 0, 0, 0, 0, 0, 0
+ }));
- 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 4.0f, 8.0f, 6.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 7.0f, 4.0f, 4.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 3.0f, 2.0f, 4.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f
+ auto inputTensor = MakeTensor<T, 2>(inputTensorInfo, std::vector<T>(inputValues));
- };
+ LayerTestResult<T, 2> result(outputTensorInfo);
+ result.outputExpected = MakeTensor<T, 2>(outputTensorInfo, std::vector<T>(expectedOutputValues));
- auto inputTensor = MakeTensor<float, 2>(inputTensorInfo, std::vector<float>(inputValues));
+ std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo);
+ std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo);
- LayerTestResult<float, 2> result(outputTensorInfo);
- result.outputExpected = MakeTensor<float, 2>(outputTensorInfo, std::vector<float>(expectedOutputValues));
+ armnn::PadQueueDescriptor descriptor;
- std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo);
- std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo);
+ std::vector<std::pair<unsigned int, unsigned int>> PadList;
+ PadList.push_back(std::pair<unsigned int, unsigned int>(2,2));
+ PadList.push_back(std::pair<unsigned int, unsigned int>(2,2));
- armnn::PadQueueDescriptor descriptor;
+ descriptor.m_Parameters.m_PadList = PadList;
+ armnn::WorkloadInfo info;
- std::vector<std::pair<unsigned int, unsigned int>> PadList;
- PadList.push_back(std::pair<unsigned int, unsigned int>(2,2));
- PadList.push_back(std::pair<unsigned int, unsigned int>(2,2));
+ AddInputToWorkload(descriptor, info, inputTensorInfo, inputHandle.get());
+ AddOutputToWorkload(descriptor, info, outputTensorInfo, outputHandle.get());
- descriptor.m_Parameters.m_PadList = PadList;
- armnn::WorkloadInfo info;
+ std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreatePad(descriptor, info);
- AddInputToWorkload(descriptor, info, inputTensorInfo, inputHandle.get());
- AddOutputToWorkload(descriptor, info, outputTensorInfo, outputHandle.get());
+ inputHandle->Allocate();
+ outputHandle->Allocate();
- std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreatePad(descriptor, info);
+ CopyDataToITensorHandle(inputHandle.get(), &inputTensor[0][0]);
- inputHandle->Allocate();
- outputHandle->Allocate();
+ workloadFactory.Finalize();
+ workload->Execute();
- CopyDataToITensorHandle(inputHandle.get(), &inputTensor[0][0]);
+ CopyDataFromITensorHandle(&result.output[0][0], outputHandle.get());
- workloadFactory.Finalize();
- workload->Execute();
+ return result;
+}
- CopyDataFromITensorHandle(&result.output[0][0], outputHandle.get());
-
- return result;
-};
-
-LayerTestResult<float, 3> Pad3dTest(armnn::IWorkloadFactory& workloadFactory)
+template <typename T>
+LayerTestResult<T, 3> Pad3dTestCommon(armnn::IWorkloadFactory& workloadFactory, float qScale, int32_t qOffset)
{
const armnn::TensorShape inputShape{ 2, 2, 2 };
const armnn::TensorShape outputShape{ 3, 5, 6 };
- const armnn::TensorInfo inputTensorInfo(inputShape, armnn::DataType::Float32);
- const armnn::TensorInfo outputTensorInfo(outputShape, armnn::DataType::Float32);
+ const armnn::TensorInfo inputTensorInfo(inputShape, armnn::GetDataType<T>());
+ const armnn::TensorInfo outputTensorInfo(outputShape, armnn::GetDataType<T>());
-
- std::vector<float> inputValues
+ std::vector<T> inputValues(
+ QuantizedVector<T>(qScale,qOffset,
{
-
// Channel 0, Height (2) x Width (2)
- 0.0f, 4.0f,
- 2.0f, 5.0f,
+ 0, 4,
+ 2, 5,
// Channel 1, Height (2) x Width (2)
- 6.0f, 1.0f,
- 5.0f, 2.0f
- };
+ 6, 1,
+ 5, 2
+ }));
- std::vector<float> expectedOutputValues
+ std::vector<T> expectedOutputValues(
+ QuantizedVector<T>(qScale,qOffset,
{
- 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 4.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 2.0f, 5.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f,
+ 0, 0, 0, 0, 0, 0,
+ 0, 0, 0, 0, 0, 0,
+ 0, 0, 0, 4, 0, 0,
+ 0, 0, 2, 5, 0, 0,
+ 0, 0, 0, 0, 0, 0,
+ 0, 0, 0, 0, 0, 0,
+ 0, 0, 0, 0, 0, 0,
+ 0, 0, 6, 1, 0, 0,
+ 0, 0, 5, 2, 0, 0,
+ 0, 0, 0, 0, 0, 0,
- 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 6.0f, 1.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 5.0f, 2.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f,
+ 0, 0, 0, 0, 0, 0,
+ 0, 0, 0, 0, 0, 0,
+ 0, 0, 0, 0, 0, 0,
+ 0, 0, 0, 0, 0, 0,
+ 0, 0, 0, 0, 0, 0
+ }));
- 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f
+ auto inputTensor = MakeTensor<T, 3>(inputTensorInfo, std::vector<T>(inputValues));
- };
-
- auto inputTensor = MakeTensor<float, 3>(inputTensorInfo, std::vector<float>(inputValues));
-
- LayerTestResult<float, 3> result(outputTensorInfo);
- result.outputExpected = MakeTensor<float, 3>(outputTensorInfo, std::vector<float>(expectedOutputValues));
+ LayerTestResult<T, 3> result(outputTensorInfo);
+ result.outputExpected = MakeTensor<T, 3>(outputTensorInfo, std::vector<T>(expectedOutputValues));
std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo);
std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo);
@@ -3588,227 +3585,209 @@
CopyDataFromITensorHandle(&result.output[0][0][0], outputHandle.get());
return result;
-};
+}
-LayerTestResult<float, 4> Pad4dTest(armnn::IWorkloadFactory& workloadFactory)
+template <typename T>
+LayerTestResult<T, 4> Pad4dTestCommon(armnn::IWorkloadFactory& workloadFactory, float qScale, int32_t qOffset)
{
const armnn::TensorShape inputShape{ 2, 2, 3, 2 };
const armnn::TensorShape outputShape{ 4, 5, 7, 4 };
- const armnn::TensorInfo inputTensorInfo(inputShape, armnn::DataType::Float32);
- const armnn::TensorInfo outputTensorInfo(outputShape, armnn::DataType::Float32);
+ const armnn::TensorInfo inputTensorInfo(inputShape, armnn::GetDataType<T>());
+ const armnn::TensorInfo outputTensorInfo(outputShape, armnn::GetDataType<T>());
- std::vector<float> inputValues
+ std::vector<T> inputValues(
+ QuantizedVector<T>(qScale,qOffset,
{
// Batch 0, Channel 0, Height (3) x Width (2)
- 0.0f, 1.0f,
- 2.0f, 3.0f,
- 4.0f, 5.0f,
+ 0, 1,
+ 2, 3,
+ 4, 5,
// Batch 0, Channel 1, Height (3) x Width (2)
- 6.0f, 7.0f,
- 8.0f, 9.0f,
- 10.0f, 11.0f,
+ 6, 7,
+ 8, 9,
+ 10, 11,
// Batch 1, Channel 0, Height (3) x Width (2)
- 12.0f, 13.0f,
- 14.0f, 15.0f,
- 16.0f, 17.0f,
+ 12, 13,
+ 14, 15,
+ 16, 17,
// Batch 1, Channel 1, Height (3) x Width (2)
- 18.0f, 19.0f,
- 20.0f, 21.0f,
- 22.0f, 23.0f
+ 18, 19,
+ 20, 21,
+ 22, 23
+ }));
- };
-
- std::vector<float> expectedOutputValues
+ std::vector<T> expectedOutputValues(
+ QuantizedVector<T>(qScale,qOffset,
{
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 1, 0,
+ 0, 2, 3, 0,
+ 0, 4, 5, 0,
+ 0, 0, 0, 0,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 6, 7, 0,
+ 0, 8, 9, 0,
+ 0, 10, 11, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 12, 13, 0,
+ 0, 14, 15, 0,
+ 0, 16, 17, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 18, 19, 0,
+ 0, 20, 21, 0,
+ 0, 22, 23, 0,
+ 0, 0, 0, 0,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 1.0f, 0.0f,
- 0.0f, 2.0f, 3.0f, 0.0f,
- 0.0f, 4.0f, 5.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 6.0f, 7.0f, 0.0f,
- 0.0f, 8.0f, 9.0f, 0.0f,
- 0.0f, 10.0f, 11.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0
+ }));
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
+ auto inputTensor = MakeTensor<T, 4>(inputTensorInfo, std::vector<T>(inputValues));
-
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
-
-
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 12.0f, 13.0f, 0.0f,
- 0.0f, 14.0f, 15.0f, 0.0f,
- 0.0f, 16.0f, 17.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
-
-
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 18.0f, 19.0f, 0.0f,
- 0.0f, 20.0f, 21.0f, 0.0f,
- 0.0f, 22.0f, 23.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
-
-
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
-
-
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
-
-
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
-
-
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
-
-
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
-
-
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f
-
- };
-
- auto inputTensor = MakeTensor<float, 4>(inputTensorInfo, std::vector<float>(inputValues));
-
- LayerTestResult<float, 4> result(outputTensorInfo);
- result.outputExpected = MakeTensor<float, 4>(outputTensorInfo, std::vector<float>(expectedOutputValues));
+ LayerTestResult<T, 4> result(outputTensorInfo);
+ result.outputExpected = MakeTensor<T, 4>(outputTensorInfo, std::vector<T>(expectedOutputValues));
std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo);
std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo);
@@ -3841,7 +3820,37 @@
CopyDataFromITensorHandle(&result.output[0][0][0][0], outputHandle.get());
return result;
-};
+}
+
+LayerTestResult<uint8_t, 2> PadUint82dTest(armnn::IWorkloadFactory& workloadFactory)
+{
+ return Pad2dTestCommon<uint8_t>(workloadFactory, 1.0f, 0);
+}
+
+LayerTestResult<uint8_t, 3> PadUint83dTest(armnn::IWorkloadFactory& workloadFactory)
+{
+ return Pad3dTestCommon<uint8_t>(workloadFactory, 1.0f, 0);
+}
+
+LayerTestResult<uint8_t, 4> PadUint84dTest(armnn::IWorkloadFactory& workloadFactory)
+{
+ return Pad4dTestCommon<uint8_t>(workloadFactory, 1.0f, 0);
+}
+
+LayerTestResult<float, 2> PadFloat322dTest(armnn::IWorkloadFactory& workloadFactory)
+{
+ return Pad2dTestCommon<float>(workloadFactory, 0.0f, 0);
+}
+
+LayerTestResult<float, 3> PadFloat323dTest(armnn::IWorkloadFactory& workloadFactory)
+{
+ return Pad3dTestCommon<float>(workloadFactory, 0.0f, 0);
+}
+
+LayerTestResult<float, 4> PadFloat324dTest(armnn::IWorkloadFactory& workloadFactory)
+{
+ return Pad4dTestCommon<float>(workloadFactory, 0.0f, 0);
+}
LayerTestResult<float, 4> L2Normalization1dTest(armnn::IWorkloadFactory& workloadFactory)
{
diff --git a/src/backends/test/LayerTests.hpp b/src/backends/test/LayerTests.hpp
index 925e3e6..5790869 100644
--- a/src/backends/test/LayerTests.hpp
+++ b/src/backends/test/LayerTests.hpp
@@ -353,10 +353,13 @@
LayerTestResult<float, 4> SimplePermuteFloat32Test(armnn::IWorkloadFactory& workloadFactory);
LayerTestResult<uint8_t, 4> SimplePermuteUint8Test(armnn::IWorkloadFactory& workloadFactory);
-LayerTestResult<float, 2> Pad2dTest(armnn::IWorkloadFactory& workloadFactory);
-LayerTestResult<float, 3> Pad3dTest(armnn::IWorkloadFactory& workloadFactory);
-LayerTestResult<float, 4> Pad4dTest(armnn::IWorkloadFactory& workloadFactory);
+LayerTestResult<uint8_t, 2> PadUint82dTest(armnn::IWorkloadFactory& workloadFactory);
+LayerTestResult<uint8_t, 3> PadUint83dTest(armnn::IWorkloadFactory& workloadFactory);
+LayerTestResult<uint8_t, 4> PadUint84dTest(armnn::IWorkloadFactory& workloadFactory);
+LayerTestResult<float, 2> PadFloat322dTest(armnn::IWorkloadFactory& workloadFactory);
+LayerTestResult<float, 3> PadFloat323dTest(armnn::IWorkloadFactory& workloadFactory);
+LayerTestResult<float, 4> PadFloat324dTest(armnn::IWorkloadFactory& workloadFactory);
LayerTestResult<float, 4> PermuteFloat32ValueSet1Test(armnn::IWorkloadFactory& workloadFactory);
LayerTestResult<float, 4> PermuteFloat32ValueSet2Test(armnn::IWorkloadFactory& workloadFactory);