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-rwxr-xr-xsrc/backends/test/LayerTests.cpp577
1 files changed, 293 insertions, 284 deletions
diff --git a/src/backends/test/LayerTests.cpp b/src/backends/test/LayerTests.cpp
index 95f2a32297..e762152b67 100755
--- a/src/backends/test/LayerTests.cpp
+++ b/src/backends/test/LayerTests.cpp
@@ -3441,123 +3441,120 @@ float CalcInvL2Norm(std::initializer_list<float> elements)
} // 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::TensorInfo inputTensorInfo(inputShape, armnn::DataType::Float32);
- const armnn::TensorInfo outputTensorInfo(outputShape, armnn::DataType::Float32);
+ const armnn::TensorShape inputShape{ 3, 3 };
+ const armnn::TensorShape outputShape{ 7, 7 };
+ 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<float, 2>(inputTensorInfo, std::vector<float>(inputValues));
+ auto inputTensor = MakeTensor<T, 2>(inputTensorInfo, std::vector<T>(inputValues));
- LayerTestResult<float, 2> result(outputTensorInfo);
- result.outputExpected = MakeTensor<float, 2>(outputTensorInfo, std::vector<float>(expectedOutputValues));
+ LayerTestResult<T, 2> result(outputTensorInfo);
+ result.outputExpected = MakeTensor<T, 2>(outputTensorInfo, std::vector<T>(expectedOutputValues));
- std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo);
- std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo);
+ std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo);
+ std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo);
- armnn::PadQueueDescriptor descriptor;
+ armnn::PadQueueDescriptor descriptor;
- 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));
+ 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));
- descriptor.m_Parameters.m_PadList = PadList;
- armnn::WorkloadInfo info;
+ descriptor.m_Parameters.m_PadList = PadList;
+ armnn::WorkloadInfo info;
- AddInputToWorkload(descriptor, info, inputTensorInfo, inputHandle.get());
- AddOutputToWorkload(descriptor, info, outputTensorInfo, outputHandle.get());
+ AddInputToWorkload(descriptor, info, inputTensorInfo, inputHandle.get());
+ AddOutputToWorkload(descriptor, info, outputTensorInfo, outputHandle.get());
- std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreatePad(descriptor, info);
+ std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreatePad(descriptor, info);
- inputHandle->Allocate();
- outputHandle->Allocate();
+ inputHandle->Allocate();
+ outputHandle->Allocate();
- CopyDataToITensorHandle(inputHandle.get(), &inputTensor[0][0]);
+ CopyDataToITensorHandle(inputHandle.get(), &inputTensor[0][0]);
- workloadFactory.Finalize();
- workload->Execute();
+ workloadFactory.Finalize();
+ workload->Execute();
- CopyDataFromITensorHandle(&result.output[0][0], outputHandle.get());
+ CopyDataFromITensorHandle(&result.output[0][0], outputHandle.get());
- return result;
-};
+ 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,
- 0.0f, 0.0f, 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, 6, 1, 0, 0,
+ 0, 0, 5, 2, 0, 0,
+ 0, 0, 0, 0, 0, 0,
+ 0, 0, 0, 0, 0, 0,
+ 0, 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<float, 3>(inputTensorInfo, std::vector<float>(inputValues));
+ auto inputTensor = MakeTensor<T, 3>(inputTensorInfo, std::vector<T>(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 @@ LayerTestResult<float, 3> Pad3dTest(armnn::IWorkloadFactory& workloadFactory)
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,
-
-
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
-
-
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
-
-
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
-
-
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
-
-
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
-
-
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
-
-
- 0.0f, 0.0f, 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,
-
-
- 0.0f, 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,
-
-
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
-
-
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
-
-
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
- 0.0f, 0.0f, 0.0f, 0.0f,
-
-
- 0.0f, 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
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 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, 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, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+
+ 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, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0,
+ 0, 0, 0, 0
+ }));
- };
+ auto inputTensor = MakeTensor<T, 4>(inputTensorInfo, std::vector<T>(inputValues));
- 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 @@ LayerTestResult<float, 4> Pad4dTest(armnn::IWorkloadFactory& workloadFactory)
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)
{
generated by cgit v1.2.1 (git 2.23.0) at 2024-05-15 00:03:06 +0000