diff options
Diffstat (limited to 'src/armnn/backends/test/Pooling2dTestImpl.hpp')
-rw-r--r-- | src/armnn/backends/test/Pooling2dTestImpl.hpp | 77 |
1 files changed, 77 insertions, 0 deletions
diff --git a/src/armnn/backends/test/Pooling2dTestImpl.hpp b/src/armnn/backends/test/Pooling2dTestImpl.hpp index fc84ddb2ca..ab9fd6d6fb 100644 --- a/src/armnn/backends/test/Pooling2dTestImpl.hpp +++ b/src/armnn/backends/test/Pooling2dTestImpl.hpp @@ -720,6 +720,83 @@ LayerTestResult<T, 4> SimpleMaxPooling2dSize2x2Stride2x2TestCommon(armnn::IWorkl return SimplePooling2dTestImpl<T>(workloadFactory, descriptor, qScale, qOffset, input, outputExpected); } +// +// Tests max pooling with the following parameters: +// +// Pooling size: 3x2 +// Stride: (2,2) +// input size: 3x2 +// channels: 1 +// batch size: 1 +// +template<typename T> +LayerTestResult<T, 4> IgnorePaddingAveragePooling2dSize3x2Stride2x2TestCommon( + armnn::IWorkloadFactory& workloadFactory, + bool forceNoPadding, + float qScale = 1.0f, + int32_t qOffset = 0) +{ + armnn::Pooling2dDescriptor descriptor; + descriptor.m_PoolType = armnn::PoolingAlgorithm::Average; + descriptor.m_PoolWidth = 3; + descriptor.m_PoolHeight = 2; + descriptor.m_StrideX = 2; + descriptor.m_StrideY = 2; + descriptor.m_PadLeft = (forceNoPadding) ? 0 : 1; + descriptor.m_PadRight = descriptor.m_PadLeft; + descriptor.m_PadTop = 0; + descriptor.m_PadBottom = 0; + descriptor.m_OutputShapeRounding = armnn::OutputShapeRounding::Floor; + descriptor.m_PaddingMethod = armnn::PaddingMethod::IgnoreValue; + + unsigned int inputWidth = 3; + unsigned int inputHeight = 2; + unsigned int outputWidth = + (inputWidth + descriptor.m_PadLeft + descriptor.m_PadRight + descriptor.m_StrideX - descriptor.m_PoolWidth) / + descriptor.m_StrideX; + unsigned int outputHeight = + (inputHeight + descriptor.m_PadTop + descriptor.m_PadBottom + descriptor.m_StrideY - descriptor.m_PoolHeight) / + descriptor.m_StrideY; + unsigned int channels = 1; + unsigned int batchSize = 1; + + std::vector<float> inputData = { + 3.0f, 6.0f, 9.0f, + 12.0f, 15.0f, 18.0f, + }; + + std::vector<float> expectedOutputDataWithPadding = { + 6.0f, 8.0f, + }; + + std::vector<float> expectedOutputDataNoPadding = { + 10.5f, + }; + + armnn::TensorInfo inputTensorInfo({ batchSize, channels, inputHeight, inputWidth }, armnn::GetDataType<T>()); + + // Scale and offset should match input - we're just calculating average values. + armnn::TensorInfo outputTensorInfo({ batchSize, channels, outputHeight, outputWidth }, armnn::GetDataType<T>()); + + // Set quantization parameters if the requested type is a quantized type. + if(armnn::IsQuantizedType<T>()) + { + inputTensorInfo.SetQuantizationScale(qScale); + inputTensorInfo.SetQuantizationOffset(qOffset); + outputTensorInfo.SetQuantizationScale(qScale); + outputTensorInfo.SetQuantizationOffset(qOffset); + } + + auto input = MakeTensor<T, 4>(inputTensorInfo, QuantizedVector<T>(qScale, qOffset, inputData)); + + auto outputExpected = MakeTensor<T, 4>(outputTensorInfo, + forceNoPadding ? QuantizedVector<T>(qScale, qOffset, expectedOutputDataNoPadding) : + QuantizedVector<T>(qScale, qOffset, expectedOutputDataWithPadding)); + + return SimplePooling2dTestImpl<T>(workloadFactory, descriptor, qScale, qOffset, input, outputExpected); +} + + template<typename T> LayerTestResult<T, 4> IgnorePaddingSimpleMaxPooling2dTestCommon(armnn::IWorkloadFactory& workloadFactory, float qScale = 1.0f, |