diff options
Diffstat (limited to 'src/backends/test/LayerTests.cpp')
-rw-r--r-- | src/backends/test/LayerTests.cpp | 183 |
1 files changed, 182 insertions, 1 deletions
diff --git a/src/backends/test/LayerTests.cpp b/src/backends/test/LayerTests.cpp index 8f06690018..4f6cb93670 100644 --- a/src/backends/test/LayerTests.cpp +++ b/src/backends/test/LayerTests.cpp @@ -4747,4 +4747,185 @@ LayerTestResult<float, 4> PermuteFloat32ValueSet2Test(armnn::IWorkloadFactory& w LayerTestResult<float, 4> PermuteFloat32ValueSet3Test(armnn::IWorkloadFactory& workloadFactory) { return PermuteFloat32ValueSet3TestCommon(workloadFactory); -};
\ No newline at end of file +}; + +namespace +{ +template <typename T, std::size_t InputDim, std::size_t OutputDim> +LayerTestResult<T, OutputDim> MeanTestHelper(armnn::IWorkloadFactory& workloadFactory, + const unsigned int* inputShape, + const std::vector<T>& inputData, + const std::vector<unsigned int>& axis, + bool keepDims, + const unsigned int* outputShape, + const std::vector<T>& outputData, + float scale = 1.0f, + int32_t offset = 0) +{ + auto dataType = (std::is_same<T, uint8_t>::value ? + armnn::DataType::QuantisedAsymm8 : + armnn::DataType::Float32); + + armnn::TensorInfo inputTensorInfo(InputDim, inputShape, dataType); + armnn::TensorInfo outputTensorInfo(OutputDim, outputShape, dataType); + + inputTensorInfo.SetQuantizationScale(scale); + inputTensorInfo.SetQuantizationOffset(offset); + + outputTensorInfo.SetQuantizationScale(scale); + outputTensorInfo.SetQuantizationOffset(offset); + + auto input = MakeTensor<T, InputDim>(inputTensorInfo, inputData); + + LayerTestResult<T, OutputDim> result(outputTensorInfo); + result.outputExpected = MakeTensor<T, OutputDim>(outputTensorInfo, outputData); + + std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo); + std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); + + armnn::MeanQueueDescriptor data; + data.m_Parameters.m_Axis = axis; + data.m_Parameters.m_KeepDims = keepDims; + armnn::WorkloadInfo info; + AddInputToWorkload(data, info, inputTensorInfo, inputHandle.get()); + AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get()); + + std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateMean(data, info); + + inputHandle->Allocate(); + outputHandle->Allocate(); + + CopyDataToITensorHandle(inputHandle.get(), input.origin()); + + workloadFactory.Finalize(); + workload->Execute(); + + CopyDataFromITensorHandle(result.output.origin(), outputHandle.get()); + + return result; +} +} // anonymous namespace + +LayerTestResult<uint8_t, 1> MeanUint8SimpleTest(armnn::IWorkloadFactory& workloadFactory) +{ + const unsigned int inputShape[] = { 3, 2 }; + const unsigned int outputShape[] = { 1 }; + + std::vector<uint8_t> input({ 1, 1, 2, 2, 3, 3 }); + std::vector<uint8_t> output({ 2 }); + + return MeanTestHelper<uint8_t, 2, 1>(workloadFactory, inputShape, input, {}, false, outputShape, output); +} + +LayerTestResult<uint8_t, 3> MeanUint8SimpleAxisTest(armnn::IWorkloadFactory& workloadFactory) +{ + const unsigned int inputShape[] = { 1, 1, 3, 2 }; + const unsigned int outputShape[] = { 1, 1, 2 }; + + std::vector<uint8_t> input({ 1, 1, 2, 2, 3, 3 }); + std::vector<uint8_t> output({ 2, 2 }); + + return MeanTestHelper<uint8_t, 4, 3>(workloadFactory, inputShape, input, {2}, false, outputShape, output); +} + +LayerTestResult<uint8_t, 4> MeanUint8KeepDimsTest(armnn::IWorkloadFactory& workloadFactory) +{ + const unsigned int inputShape[] = { 1, 1, 3, 2 }; + const unsigned int outputShape[] = { 1, 1, 1, 2 }; + + std::vector<uint8_t> input({ 1, 1, 2, 2, 3, 3 }); + std::vector<uint8_t> output({ 2, 2 }); + + return MeanTestHelper<uint8_t, 4, 4>(workloadFactory, inputShape, input, {2}, true, outputShape, output); +} + +LayerTestResult<uint8_t, 4> MeanUint8MultipleDimsTest(armnn::IWorkloadFactory& workloadFactory) +{ + const unsigned int inputShape[] = { 2, 3, 1, 2 }; + const unsigned int outputShape[] = { 1, 3, 1, 1 }; + + std::vector<uint8_t> input({ 1, 2, 3, 4, 5, 6, 1, 2, 3, 4, 5, 6}); + std::vector<uint8_t> output({ 1, 3, 5 }); + + return MeanTestHelper<uint8_t, 4, 4>(workloadFactory, inputShape, input, {0, 3}, true, outputShape, output); +} + +LayerTestResult<uint8_t, 1> MeanVtsUint8Test(armnn::IWorkloadFactory& workloadFactory) +{ + const unsigned int inputShape[] = {4, 3, 2}; + const unsigned int outputShape[] = { 2 }; + + std::vector<uint8_t> input({1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24}); + std::vector<uint8_t> output({12, 13}); + + return MeanTestHelper<uint8_t, 3, 1>(workloadFactory, inputShape, input, {0, 1}, false, outputShape, + output, 0.8f, 5); +} + +LayerTestResult<float, 1> MeanFloatSimpleTest(armnn::IWorkloadFactory& workloadFactory) +{ + const unsigned int inputShape[] = { 3, 2 }; + const unsigned int outputShape[] = { 1 }; + + std::vector<float> input({ 1., 1., 2., 2., 3., 3. }); + std::vector<float> output({ 2. }); + + return MeanTestHelper<float, 2, 1>(workloadFactory, inputShape, input, {}, false, outputShape, output); +} + +LayerTestResult<float, 3> MeanFloatSimpleAxisTest(armnn::IWorkloadFactory& workloadFactory) +{ + const unsigned int inputShape[] = { 2, 3, 1, 2 }; + const unsigned int outputShape[] = { 3, 1, 2 }; + + std::vector<float> input({ 1., 2., 3., 4., 5., 6., 1., 2., 3., 4., 5., 6.}); + std::vector<float> output({ 1., 2., 3., 4., 5., 6. }); + + return MeanTestHelper<float, 4, 3>(workloadFactory, inputShape, input, {0}, false, outputShape, output); +} + +LayerTestResult<float, 4> MeanFloatKeepDimsTest(armnn::IWorkloadFactory& workloadFactory) +{ + const unsigned int inputShape[] = { 1, 1, 3, 2 }; + const unsigned int outputShape[] = { 1, 1, 1, 2 }; + + std::vector<float> input({ 1., 1., 2., 2., 3., 3. }); + std::vector<float> output({ 2., 2. }); + + return MeanTestHelper<float, 4, 4>(workloadFactory, inputShape, input, {2}, true, outputShape, output); +} + +LayerTestResult<float, 4> MeanFloatMultipleDimsTest(armnn::IWorkloadFactory& workloadFactory) +{ + const unsigned int inputShape[] = { 2, 3, 1, 2 }; + const unsigned int outputShape[] = { 1, 3, 1, 1 }; + + std::vector<float> input({ 1., 2., 3., 4., 5., 6., 1., 2., 3., 4., 5., 6.}); + std::vector<float> output({ 1.5, 3.5, 5.5 }); + + return MeanTestHelper<float, 4, 4>(workloadFactory, inputShape, input, {0, 3}, true, outputShape, output); +} + +LayerTestResult<float, 1> MeanVtsFloat1Test(armnn::IWorkloadFactory& workloadFactory) +{ + const unsigned int inputShape[] = {4, 3, 2}; + const unsigned int outputShape[] = { 2 }; + + std::vector<float> input({1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 9.0f, 10.0f, 11.0f, 12.0f, 13.0f, 14.0f, + 15.0f, 16.0f, 17.0f, 18.0f, 19.0f, 20.0f, 21.0f, 22.0f, 23.0f, 24.0f}); + std::vector<float> output({12.0f, 13.0f}); + + return MeanTestHelper<float, 3, 1>(workloadFactory, inputShape, input, {0, 1}, false, outputShape, output); +} + +LayerTestResult<float, 3> MeanVtsFloat2Test(armnn::IWorkloadFactory& workloadFactory) +{ + const unsigned int inputShape[] = {4, 3, 2}; + const unsigned int outputShape[] = {1, 3, 1 }; + + std::vector<float> input({1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 9.0f, 10.0f, 11.0f, 12.0f, 13.0f, 14.0f, + 15.0f, 16.0f, 17.0f, 18.0f, 19.0f, 20.0f, 21.0f, 22.0f, 23.0f, 24.0f}); + std::vector<float> output({10.5f, 12.5f, 14.5f}); + + return MeanTestHelper<float, 3, 3>(workloadFactory, inputShape, input, {0, 2}, true, outputShape, output); +} |