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-rwxr-xr-xsrc/backends/test/LayerTests.cpp402
1 files changed, 402 insertions, 0 deletions
diff --git a/src/backends/test/LayerTests.cpp b/src/backends/test/LayerTests.cpp
index d955e42c36..c28a1d46ad 100755
--- a/src/backends/test/LayerTests.cpp
+++ b/src/backends/test/LayerTests.cpp
@@ -3443,6 +3443,408 @@ float CalcInvL2Norm(std::initializer_list<float> elements)
} // anonymous namespace
+LayerTestResult<float, 2> Pad2dTest(armnn::IWorkloadFactory& workloadFactory)
+{
+ 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);
+
+
+ std::vector<float> inputValues
+ {
+
+ // 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
+ {
+
+ 0.0f, 0.0f, 0.0f, 0.0f, 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));
+
+ LayerTestResult<float, 2> result(outputTensorInfo);
+ result.outputExpected = MakeTensor<float, 2>(outputTensorInfo, std::vector<float>(expectedOutputValues));
+
+ std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo);
+ std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo);
+
+ 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));
+
+ descriptor.m_Parameters.m_PadList = PadList;
+ armnn::WorkloadInfo info;
+
+ AddInputToWorkload(descriptor, info, inputTensorInfo, inputHandle.get());
+ AddOutputToWorkload(descriptor, info, outputTensorInfo, outputHandle.get());
+
+ std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreatePad(descriptor, info);
+
+ inputHandle->Allocate();
+ outputHandle->Allocate();
+
+ CopyDataToITensorHandle(inputHandle.get(), &inputTensor[0][0]);
+
+ workloadFactory.Finalize();
+ workload->Execute();
+
+ CopyDataFromITensorHandle(&result.output[0][0], outputHandle.get());
+
+ return result;
+};
+
+LayerTestResult<float, 3> Pad3dTest(armnn::IWorkloadFactory& workloadFactory)
+{
+ 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);
+
+
+ std::vector<float> inputValues
+ {
+
+ // Channel 0, Height (2) x Width (2)
+ 0.0f, 4.0f,
+ 2.0f, 5.0f,
+
+ // Channel 1, Height (2) x Width (2)
+ 6.0f, 1.0f,
+ 5.0f, 2.0f
+ };
+
+ std::vector<float> expectedOutputValues
+ {
+
+ 0.0f, 0.0f, 0.0f, 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,
+
+
+ 0.0f, 0.0f, 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,
+
+
+ 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f,
+ 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f,
+ 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f,
+ 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));
+
+ LayerTestResult<float, 3> result(outputTensorInfo);
+ result.outputExpected = MakeTensor<float, 3>(outputTensorInfo, std::vector<float>(expectedOutputValues));
+
+ std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo);
+ std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo);
+
+ armnn::PadQueueDescriptor descriptor;
+
+ std::vector<std::pair<unsigned int, unsigned int>> PadList;
+ PadList.push_back(std::pair<unsigned int, unsigned int>(0,1));
+ PadList.push_back(std::pair<unsigned int, unsigned int>(2,1));
+ PadList.push_back(std::pair<unsigned int, unsigned int>(2,2));
+
+ descriptor.m_Parameters.m_PadList = PadList;
+ armnn::WorkloadInfo info;
+
+ AddInputToWorkload(descriptor, info, inputTensorInfo, inputHandle.get());
+ AddOutputToWorkload(descriptor, info, outputTensorInfo, outputHandle.get());
+
+ std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreatePad(descriptor, info);
+
+ inputHandle->Allocate();
+ outputHandle->Allocate();
+
+ CopyDataToITensorHandle(inputHandle.get(), &inputTensor[0][0][0]);
+
+ workloadFactory.Finalize();
+ workload->Execute();
+
+ CopyDataFromITensorHandle(&result.output[0][0][0], outputHandle.get());
+
+ return result;
+};
+
+LayerTestResult<float, 4> Pad4dTest(armnn::IWorkloadFactory& workloadFactory)
+{
+ 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);
+
+ std::vector<float> inputValues
+ {
+ // Batch 0, Channel 0, Height (3) x Width (2)
+ 0.0f, 1.0f,
+ 2.0f, 3.0f,
+ 4.0f, 5.0f,
+
+ // Batch 0, Channel 1, Height (3) x Width (2)
+ 6.0f, 7.0f,
+ 8.0f, 9.0f,
+ 10.0f, 11.0f,
+
+ // Batch 1, Channel 0, Height (3) x Width (2)
+ 12.0f, 13.0f,
+ 14.0f, 15.0f,
+ 16.0f, 17.0f,
+
+ // Batch 1, Channel 1, Height (3) x Width (2)
+ 18.0f, 19.0f,
+ 20.0f, 21.0f,
+ 22.0f, 23.0f
+
+ };
+
+ std::vector<float> expectedOutputValues
+ {
+ 0.0f, 0.0f, 0.0f, 0.0f,
+ 0.0f, 0.0f, 0.0f, 0.0f,
+ 0.0f, 0.0f, 0.0f, 0.0f,
+ 0.0f, 0.0f, 0.0f, 0.0f,
+ 0.0f, 0.0f, 0.0f, 0.0f,
+ 0.0f, 0.0f, 0.0f, 0.0f,
+ 0.0f, 0.0f, 0.0f, 0.0f,
+
+
+ 0.0f, 0.0f, 0.0f, 0.0f,
+ 0.0f, 0.0f, 0.0f, 0.0f,
+ 0.0f, 0.0f, 0.0f, 0.0f,
+ 0.0f, 0.0f, 0.0f, 0.0f,
+ 0.0f, 0.0f, 0.0f, 0.0f,
+ 0.0f, 0.0f, 0.0f, 0.0f,
+ 0.0f, 0.0f, 0.0f, 0.0f,
+
+
+ 0.0f, 0.0f, 0.0f, 0.0f,
+ 0.0f, 0.0f, 0.0f, 0.0f,
+ 0.0f, 0.0f, 0.0f, 0.0f,
+ 0.0f, 0.0f, 0.0f, 0.0f,
+ 0.0f, 0.0f, 0.0f, 0.0f,
+ 0.0f, 0.0f, 0.0f, 0.0f,
+ 0.0f, 0.0f, 0.0f, 0.0f,
+
+
+ 0.0f, 0.0f, 0.0f, 0.0f,
+ 0.0f, 0.0f, 0.0f, 0.0f,
+ 0.0f, 0.0f, 0.0f, 0.0f,
+ 0.0f, 0.0f, 0.0f, 0.0f,
+ 0.0f, 0.0f, 0.0f, 0.0f,
+ 0.0f, 0.0f, 0.0f, 0.0f,
+ 0.0f, 0.0f, 0.0f, 0.0f,
+
+
+ 0.0f, 0.0f, 0.0f, 0.0f,
+ 0.0f, 0.0f, 0.0f, 0.0f,
+ 0.0f, 0.0f, 0.0f, 0.0f,
+ 0.0f, 0.0f, 0.0f, 0.0f,
+ 0.0f, 0.0f, 0.0f, 0.0f,
+ 0.0f, 0.0f, 0.0f, 0.0f,
+ 0.0f, 0.0f, 0.0f, 0.0f,
+
+
+ 0.0f, 0.0f, 0.0f, 0.0f,
+ 0.0f, 0.0f, 0.0f, 0.0f,
+ 0.0f, 0.0f, 0.0f, 0.0f,
+ 0.0f, 0.0f, 0.0f, 0.0f,
+ 0.0f, 0.0f, 0.0f, 0.0f,
+ 0.0f, 0.0f, 0.0f, 0.0f,
+ 0.0f, 0.0f, 0.0f, 0.0f,
+
+
+ 0.0f, 0.0f, 0.0f, 0.0f,
+ 0.0f, 0.0f, 0.0f, 0.0f,
+ 0.0f, 0.0f, 0.0f, 0.0f,
+ 0.0f, 0.0f, 0.0f, 0.0f,
+ 0.0f, 0.0f, 0.0f, 0.0f,
+ 0.0f, 0.0f, 0.0f, 0.0f,
+ 0.0f, 0.0f, 0.0f, 0.0f,
+
+
+ 0.0f, 0.0f, 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
+
+ };
+
+ 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));
+
+ std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo);
+ std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo);
+
+ armnn::PadQueueDescriptor descriptor;
+
+ std::vector<std::pair<unsigned int, unsigned int>> PadList;
+ PadList.push_back(std::pair<unsigned int, unsigned int>(1,1));
+ PadList.push_back(std::pair<unsigned int, unsigned int>(2,1));
+ PadList.push_back(std::pair<unsigned int, unsigned int>(3,1));
+ PadList.push_back(std::pair<unsigned int, unsigned int>(1,1));
+
+ descriptor.m_Parameters.m_PadList = PadList;
+ armnn::WorkloadInfo info;
+
+ AddInputToWorkload(descriptor, info, inputTensorInfo, inputHandle.get());
+ AddOutputToWorkload(descriptor, info, outputTensorInfo, outputHandle.get());
+
+ std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreatePad(descriptor, info);
+
+ inputHandle->Allocate();
+ outputHandle->Allocate();
+
+ CopyDataToITensorHandle(inputHandle.get(), &inputTensor[0][0][0][0]);
+
+ workloadFactory.Finalize();
+
+ workload->Execute();
+
+ CopyDataFromITensorHandle(&result.output[0][0][0][0], outputHandle.get());
+
+ return result;
+};
+
LayerTestResult<float, 4> L2Normalization1dTest(armnn::IWorkloadFactory& workloadFactory)
{
// Width: 1
generated by cgit v1.2.1 (git 2.23.0) at 2024-05-17 05:05:44 +0000