// // Copyright © 2017 Arm Ltd. All rights reserved. // SPDX-License-Identifier: MIT // #include #include #include #include #include #include #include #include #include #include #include BOOST_AUTO_TEST_SUITE(Compute_ArmComputeNeon) using FactoryType = armnn::NeonWorkloadFactory; // ============================================================================ // UNIT tests // Convolution ARMNN_AUTO_TEST_CASE(SimpleConvolution1d, Convolution1dTest, true) ARMNN_AUTO_TEST_CASE(SimpleConvolution2d, SimpleConvolution2d3x5Test, true) ARMNN_AUTO_TEST_CASE(SimpleConvolution2dSquare, SimpleConvolution2d3x3Test, true) ARMNN_AUTO_TEST_CASE(UnbiasedConvolution2d, SimpleConvolution2d3x5Test, false) ARMNN_AUTO_TEST_CASE(UnbiasedConvolution2dSquare, SimpleConvolution2d3x3Test, false) ARMNN_AUTO_TEST_CASE(SimpleConvolution2dAsymmetricPadding, Convolution2dAsymmetricPaddingTest) ARMNN_AUTO_TEST_CASE(SimpleConvolution2dSquareNhwc, SimpleConvolution2d3x3NhwcTest, false) namespace { armnn::Convolution2dDescriptor MakeConv2dDesc(uint32_t strideX, uint32_t strideY, uint32_t padLeft = 0, uint32_t padRight = 0, uint32_t padTop = 0, uint32_t padBottom = 0) { armnn::Convolution2dDescriptor result; result.m_StrideX = strideX; result.m_StrideY = strideY; result.m_PadLeft = padLeft; result.m_PadRight = padRight; result.m_PadTop = padTop; result.m_PadBottom = padBottom; result.m_BiasEnabled = true; return result; } } BOOST_AUTO_TEST_CASE(Conv2dUtils) { // The only preferred Neon convolution is 1x1 with padding=0 and stride size {1,2,3}. armnn::TensorShape shape1x1({ 1,1,1,1 }); armnn::TensorInfo info1x1(shape1x1, armnn::DataType::Float32); BOOST_TEST(armnn::IsNeonDirectConvolutionPreferred(info1x1, MakeConv2dDesc(1, 1))); BOOST_TEST(armnn::IsNeonDirectConvolutionPreferred(info1x1, MakeConv2dDesc(1, 2))); BOOST_TEST(armnn::IsNeonDirectConvolutionPreferred(info1x1, MakeConv2dDesc(1, 3))); BOOST_TEST(armnn::IsNeonDirectConvolutionPreferred(info1x1, MakeConv2dDesc(2, 1))); BOOST_TEST(armnn::IsNeonDirectConvolutionPreferred(info1x1, MakeConv2dDesc(2, 2))); BOOST_TEST(armnn::IsNeonDirectConvolutionPreferred(info1x1, MakeConv2dDesc(2, 3))); BOOST_TEST(armnn::IsNeonDirectConvolutionPreferred(info1x1, MakeConv2dDesc(3, 1))); BOOST_TEST(armnn::IsNeonDirectConvolutionPreferred(info1x1, MakeConv2dDesc(3, 2))); BOOST_TEST(armnn::IsNeonDirectConvolutionPreferred(info1x1, MakeConv2dDesc(3, 3))); BOOST_TEST(!armnn::IsNeonDirectConvolutionPreferred(info1x1, MakeConv2dDesc(4, 1))); BOOST_TEST(!armnn::IsNeonDirectConvolutionPreferred(info1x1, MakeConv2dDesc(4, 5))); BOOST_TEST(!armnn::IsNeonDirectConvolutionPreferred(info1x1, MakeConv2dDesc(3, 6))); // non zero padding is not preferred for direct convolution BOOST_TEST(!armnn::IsNeonDirectConvolutionPreferred(info1x1, MakeConv2dDesc(1, 1, 1, 0))); BOOST_TEST(!armnn::IsNeonDirectConvolutionPreferred(info1x1, MakeConv2dDesc(1, 1, 0, 1))); BOOST_TEST(!armnn::IsNeonDirectConvolutionPreferred(info1x1, MakeConv2dDesc(1, 1, 1, 1))); // 2x2 filter not preferred for direct convolution armnn::TensorShape shape2x2({ 1,1,2,2 }); armnn::TensorInfo info2x2(shape2x2, armnn::DataType::Float32); BOOST_TEST(!armnn::IsNeonDirectConvolutionPreferred(info2x2, MakeConv2dDesc(1, 1))); } // Depthwise Convolution ARMNN_AUTO_TEST_CASE(DepthwiseConvolution2dDepthMul1, DepthwiseConvolution2dDepthMul1Test, true) ARMNN_AUTO_TEST_CASE(DepthwiseConvolution2dDepthNhwc, DepthwiseConvolution2dDepthNhwcTest, false) ARMNN_AUTO_TEST_CASE(UnbiasedDepthwiseConvolution2dDepthMul1, DepthwiseConvolution2dDepthMul1Test, false) ARMNN_AUTO_TEST_CASE(DepthwiseConvolution2dDepthMul1Uint8, DepthwiseConvolution2dDepthMul1Uint8Test, true) ARMNN_AUTO_TEST_CASE(UnbiasedDepthwiseConvolution2dDepthMul1Uint8, DepthwiseConvolution2dDepthMul1Uint8Test, false) ARMNN_AUTO_TEST_CASE(DepthwiseConvolution2dAsymmetric, DepthwiseConvolution2dAsymmetricTest, true) ARMNN_AUTO_TEST_CASE(UnbiasedDepthwiseConvolution2dAsymmetric, DepthwiseConvolution2dAsymmetricTest, false) namespace { armnn::DepthwiseConvolution2dDescriptor MakeDepthwiseConv2dDesc(uint32_t strideX, uint32_t strideY, uint32_t depthMultiplier = 1, uint32_t padLeft = 0, uint32_t padRight = 0, uint32_t padTop = 0, uint32_t padBottom = 0) { boost::ignore_unused(depthMultiplier); armnn::DepthwiseConvolution2dDescriptor desc; desc.m_PadLeft = padLeft; desc.m_PadRight = padRight; desc.m_PadTop = padTop; desc.m_PadBottom = padBottom; desc.m_StrideX = strideX; desc.m_StrideY = strideY; desc.m_BiasEnabled = false; return desc; } armnn::TensorInfo CreateOutputTensorInfo(const armnn::TensorInfo& inputInfo, const armnn::TensorInfo& weightsInfo, const armnn::DepthwiseConvolution2dDescriptor& descriptor, armnn::DataType dataType) { const armnn::TensorShape& inputShape = inputInfo.GetShape(); const armnn::TensorShape& filterShape = weightsInfo.GetShape(); unsigned int inWidth = inputShape[3]; unsigned int inHeight = inputShape[2]; unsigned int inBatchSize = inputShape[0]; unsigned int filterWidth = filterShape[3]; unsigned int readWidth = (inWidth + descriptor.m_PadLeft + descriptor.m_PadRight) - (filterWidth); unsigned int outWidth = 1u + (readWidth / descriptor.m_StrideX); unsigned int filterHeight = filterShape[2]; unsigned int readHeight = (inHeight + descriptor.m_PadTop + descriptor.m_PadBottom) - (filterHeight); unsigned int outHeight = 1u + (readHeight / descriptor.m_StrideY); unsigned int depthMultiplier = filterShape[0]; unsigned int outChannels = filterShape[1] * depthMultiplier; unsigned int outBatchSize = inBatchSize; armnn::TensorShape outputShape({outBatchSize, outChannels, outHeight, outWidth}); return armnn::TensorInfo(outputShape, dataType); } } BOOST_AUTO_TEST_CASE(DepthwiseConv2dUtils) { const armnn::DataType dataType = armnn::DataType::Float32; armnn::TensorInfo inputInfo({1, 1, 10, 10 }, dataType); armnn::TensorInfo outputInfo; armnn::TensorInfo weightsInfo3x3({ 1, 1, 3, 3 }, dataType); armnn::TensorInfo biasesInfo; armnn::DepthwiseConvolution2dDescriptor descriptor; armnn::NeonLayerSupport layerSupport; // Strides supported: 1,2,3 descriptor = MakeDepthwiseConv2dDesc(1, 1); outputInfo = CreateOutputTensorInfo(inputInfo, weightsInfo3x3, descriptor, dataType); BOOST_TEST(layerSupport.IsDepthwiseConvolutionSupported(inputInfo, outputInfo, descriptor, weightsInfo3x3, biasesInfo)); descriptor = MakeDepthwiseConv2dDesc(1, 2); outputInfo = CreateOutputTensorInfo(inputInfo, weightsInfo3x3, descriptor, dataType); BOOST_TEST(layerSupport.IsDepthwiseConvolutionSupported(inputInfo, outputInfo, descriptor, weightsInfo3x3, biasesInfo)); descriptor = MakeDepthwiseConv2dDesc(1, 3); outputInfo = CreateOutputTensorInfo(inputInfo, weightsInfo3x3, descriptor, dataType); BOOST_TEST(layerSupport.IsDepthwiseConvolutionSupported(inputInfo, outputInfo, descriptor, weightsInfo3x3, biasesInfo)); descriptor = MakeDepthwiseConv2dDesc(2, 1); outputInfo = CreateOutputTensorInfo(inputInfo, weightsInfo3x3, descriptor, dataType); BOOST_TEST(layerSupport.IsDepthwiseConvolutionSupported(inputInfo, outputInfo, descriptor, weightsInfo3x3, biasesInfo)); descriptor = MakeDepthwiseConv2dDesc(2, 2); outputInfo = CreateOutputTensorInfo(inputInfo, weightsInfo3x3, descriptor, dataType); BOOST_TEST(layerSupport.IsDepthwiseConvolutionSupported(inputInfo, outputInfo, descriptor, weightsInfo3x3, biasesInfo)); descriptor = MakeDepthwiseConv2dDesc(2, 3); outputInfo = CreateOutputTensorInfo(inputInfo, weightsInfo3x3, descriptor, dataType); BOOST_TEST(layerSupport.IsDepthwiseConvolutionSupported(inputInfo, outputInfo, descriptor, weightsInfo3x3, biasesInfo)); descriptor = MakeDepthwiseConv2dDesc(3, 1); outputInfo = CreateOutputTensorInfo(inputInfo, weightsInfo3x3, descriptor, dataType); BOOST_TEST(layerSupport.IsDepthwiseConvolutionSupported(inputInfo, outputInfo, descriptor, weightsInfo3x3, biasesInfo)); descriptor = MakeDepthwiseConv2dDesc(3, 2); outputInfo = CreateOutputTensorInfo(inputInfo, weightsInfo3x3, descriptor, dataType); BOOST_TEST(layerSupport.IsDepthwiseConvolutionSupported(inputInfo, outputInfo, descriptor, weightsInfo3x3, biasesInfo)); descriptor = MakeDepthwiseConv2dDesc(3, 3); outputInfo = CreateOutputTensorInfo(inputInfo, weightsInfo3x3, descriptor, dataType); BOOST_TEST(layerSupport.IsDepthwiseConvolutionSupported(inputInfo, outputInfo, descriptor, weightsInfo3x3, biasesInfo)); // Supported stride 4 descriptor = MakeDepthwiseConv2dDesc(4, 1); outputInfo = CreateOutputTensorInfo(inputInfo, weightsInfo3x3, descriptor, dataType); BOOST_TEST(layerSupport.IsDepthwiseConvolutionSupported(inputInfo, outputInfo, descriptor, weightsInfo3x3, biasesInfo)); // Supported weights shape 1x1 armnn::TensorInfo weightsInfo1x1({ 1, 1, 1, 1 }, armnn::DataType::Float32); descriptor = MakeDepthwiseConv2dDesc(1, 1); outputInfo = CreateOutputTensorInfo(inputInfo, weightsInfo1x1, descriptor, dataType); BOOST_TEST(layerSupport.IsDepthwiseConvolutionSupported(inputInfo, outputInfo, descriptor, weightsInfo1x1, biasesInfo)); // Supported shape 2x2 armnn::TensorInfo weightsInfo2x2({ 1, 1, 2, 2 }, armnn::DataType::Float32); descriptor = MakeDepthwiseConv2dDesc(1, 1); outputInfo = CreateOutputTensorInfo(inputInfo, weightsInfo2x2, descriptor, dataType); BOOST_TEST(layerSupport.IsDepthwiseConvolutionSupported(inputInfo, outputInfo, descriptor, weightsInfo2x2, biasesInfo)); // Asymmetric padding descriptor = MakeDepthwiseConv2dDesc(1, 1, 1, 1, 2, 1, 2); outputInfo = CreateOutputTensorInfo(inputInfo, weightsInfo3x3, descriptor, dataType); BOOST_TEST(layerSupport.IsDepthwiseConvolutionSupported(inputInfo, outputInfo, descriptor, weightsInfo3x3, biasesInfo)); } // Pooling ARMNN_AUTO_TEST_CASE(SimpleMaxPooling2dSize3x3Stride2x4, SimpleMaxPooling2dSize3x3Stride2x4Test, true) ARMNN_AUTO_TEST_CASE(SimpleMaxPooling2dSize3x3Stride2x4Uint8, SimpleMaxPooling2dSize3x3Stride2x4Uint8Test, true) ARMNN_AUTO_TEST_CASE(SimpleAveragePooling2d, SimpleAveragePooling2dTest) ARMNN_AUTO_TEST_CASE(SimpleAveragePooling2dNhwc, SimpleAveragePooling2dNhwcTest) ARMNN_AUTO_TEST_CASE(SimpleAveragePooling2dUint8, SimpleAveragePooling2dUint8Test) ARMNN_AUTO_TEST_CASE(LargeTensorsAveragePooling2d, LargeTensorsAveragePooling2dTest) ARMNN_AUTO_TEST_CASE(LargeTensorsAveragePooling2dUint8, LargeTensorsAveragePooling2dUint8Test) ARMNN_AUTO_TEST_CASE(SimpleL2Pooling2d, SimpleL2Pooling2dTest) ARMNN_AUTO_TEST_CASE(UNSUPPORTED_SimpleL2Pooling2dUint8, SimpleL2Pooling2dUint8Test) ARMNN_AUTO_TEST_CASE(L2Pooling2dSize3Stride1, L2Pooling2dSize3Stride1Test) ARMNN_AUTO_TEST_CASE(UNSUPPORTED_L2Pooling2dSize3Stride1Uint8, L2Pooling2dSize3Stride1Uint8Test) ARMNN_AUTO_TEST_CASE(L2Pooling2dSize3Stride3, L2Pooling2dSize3Stride3Test) ARMNN_AUTO_TEST_CASE(UNSUPPORTED_L2Pooling2dSize3Stride3Uint8, L2Pooling2dSize3Stride3Uint8Test) ARMNN_AUTO_TEST_CASE(L2Pooling2dSize3Stride4, L2Pooling2dSize3Stride4Test) ARMNN_AUTO_TEST_CASE(UNSUPPORTED_L2Pooling2dSize3Stride4Uint8, L2Pooling2dSize3Stride4Uint8Test) ARMNN_AUTO_TEST_CASE(L2Pooling2dSize7, L2Pooling2dSize7Test) ARMNN_AUTO_TEST_CASE(UNSUPPORTED_L2Pooling2dSize7Uint8, L2Pooling2dSize7Uint8Test) ARMNN_AUTO_TEST_CASE(L2Pooling2dSize9, L2Pooling2dSize9Test) ARMNN_AUTO_TEST_CASE(UNSUPPORTED_L2Pooling2dSize9Uint8, L2Pooling2dSize9Uint8Test) // Ignore padding values for pooling but count padding fields into the divisor ARMNN_AUTO_TEST_CASE(IgnorePaddingSimpleMaxPooling2d, IgnorePaddingSimpleMaxPooling2dTest) ARMNN_AUTO_TEST_CASE(IgnorePaddingSimpleMaxPooling2dUint8, IgnorePaddingSimpleMaxPooling2dUint8Test) ARMNN_AUTO_TEST_CASE(IgnorePaddingMaxPooling2dSize3, IgnorePaddingMaxPooling2dSize3Test) ARMNN_AUTO_TEST_CASE(IgnorePaddingMaxPooling2dSize3Uint8, IgnorePaddingMaxPooling2dSize3Uint8Test) ARMNN_AUTO_TEST_CASE(IgnorePaddingSimpleAveragePooling2d, IgnorePaddingSimpleAveragePooling2dTest) ARMNN_AUTO_TEST_CASE(IgnorePaddingSimpleAveragePooling2dUint8, IgnorePaddingSimpleAveragePooling2dUint8Test) ARMNN_AUTO_TEST_CASE(IgnorePaddingSimpleAveragePooling2dNoPadding, IgnorePaddingSimpleAveragePooling2dNoPaddingTest) ARMNN_AUTO_TEST_CASE(IgnorePaddingSimpleAveragePooling2dNoPaddingUint8, IgnorePaddingSimpleAveragePooling2dNoPaddingUint8Test) ARMNN_AUTO_TEST_CASE(IgnorePaddingAveragePooling2dSize3, IgnorePaddingAveragePooling2dSize3Test) ARMNN_AUTO_TEST_CASE(IgnorePaddingAveragePooling2dSize3Uint8, IgnorePaddingAveragePooling2dSize3Uint8Test) ARMNN_AUTO_TEST_CASE(IgnorePaddingAveragePooling2dSize3x2Stride2x2, IgnorePaddingAveragePooling2dSize3x2Stride2x2Test, false) ARMNN_AUTO_TEST_CASE(IgnorePaddingAveragePooling2dSize3x2Stride2x2NoPadding, IgnorePaddingAveragePooling2dSize3x2Stride2x2Test, true) ARMNN_AUTO_TEST_CASE(IgnorePaddingSimpleL2Pooling2d, IgnorePaddingSimpleL2Pooling2dTest) ARMNN_AUTO_TEST_CASE(UNSUPPORTED_IgnorePaddingSimpleL2Pooling2dUint8, IgnorePaddingSimpleL2Pooling2dUint8Test) ARMNN_AUTO_TEST_CASE(IgnorePaddingL2Pooling2dSize3, IgnorePaddingL2Pooling2dSize3Test) ARMNN_AUTO_TEST_CASE(UNSUPPORTED_IgnorePaddingL2Pooling2dSize3Uint8, IgnorePaddingL2Pooling2dSize3Uint8Test) // Activation ARMNN_AUTO_TEST_CASE(ConstantLinearActivation, ConstantLinearActivationTest) ARMNN_AUTO_TEST_CASE(SimpleSoftmaxBeta1, SimpleSoftmaxTest, 1.0f) ARMNN_AUTO_TEST_CASE(SimpleSoftmaxBeta2, SimpleSoftmaxTest, 2.0f) ARMNN_AUTO_TEST_CASE(SimpleSoftmaxBeta1Uint8, SimpleSoftmaxUint8Test, 1.0f) ARMNN_AUTO_TEST_CASE(SimpleSoftmaxBeta2Uint8, SimpleSoftmaxUint8Test, 2.0f) ARMNN_AUTO_TEST_CASE(ReLu1Uint8, BoundedReLuUint8UpperAndLowerBoundTest) ARMNN_AUTO_TEST_CASE(ReLu6Uint8, BoundedReLuUint8UpperBoundOnlyTest) // Softmax BOOST_AUTO_TEST_CASE(Softmax4dSupport) { const unsigned int numDimensions = 4u; std::array dimensionSizes; dimensionSizes.fill(1u); const armnn::TensorInfo inputInfo(numDimensions, &dimensionSizes.front(), armnn::DataType::Float32); const armnn::TensorInfo outputInfo(numDimensions, &dimensionSizes.front(), armnn::DataType::Float32); // 4D Softmax should be reported as unsupported on the NEON backend armnn::NeonLayerSupport layerSupport; BOOST_TEST(!layerSupport.IsSoftmaxSupported(inputInfo, outputInfo, armnn::SoftmaxDescriptor())); } // Splitter ARMNN_AUTO_TEST_CASE(SimpleSplitter, SplitterTest) ARMNN_AUTO_TEST_CASE(SimpleSplitterUint8, SplitterUint8Test) ARMNN_AUTO_TEST_CASE(CopyViaSplitter, CopyViaSplitterTest) ARMNN_AUTO_TEST_CASE(CopyViaSplitterUint8, CopyViaSplitterUint8Test) // Merger ARMNN_AUTO_TEST_CASE(SimpleMerger, MergerTest) ARMNN_AUTO_TEST_CASE(MergerUint8, MergerUint8Test) // Fully Connected ARMNN_AUTO_TEST_CASE(SimpleFullyConnected, FullyConnectedFloat32Test, false, false) ARMNN_AUTO_TEST_CASE(SimpleFullyConnectedWithBias, FullyConnectedFloat32Test, true, false) ARMNN_AUTO_TEST_CASE(SimpleFullyConnectedWithTranspose, FullyConnectedFloat32Test, false, true) ARMNN_AUTO_TEST_CASE(FullyConnectedLarge, FullyConnectedLargeTest, false) ARMNN_AUTO_TEST_CASE(FullyConnectedLargeTransposed, FullyConnectedLargeTest, true) ARMNN_AUTO_TEST_CASE(FullyConnectedUint8, FullyConnectedUint8Test, false) ARMNN_AUTO_TEST_CASE(FullyConnectedBiasedUint8, FullyConnectedUint8Test, true) // Add ARMNN_AUTO_TEST_CASE(SimpleAdd, AdditionTest) ARMNN_AUTO_TEST_CASE(AddBroadcast, AdditionBroadcastTest) ARMNN_AUTO_TEST_CASE(AddBroadcast1Element, AdditionBroadcast1ElementTest) // Sub ARMNN_AUTO_TEST_CASE(SimpleSub, SubtractionTest) // Mul ARMNN_AUTO_TEST_CASE(SimpleMultiplication, MultiplicationTest) ARMNN_AUTO_TEST_CASE(MultiplicationBroadcast1Element, MultiplicationBroadcast1ElementTest) ARMNN_AUTO_TEST_CASE(MultiplicationBroadcast1DVector, MultiplicationBroadcast1DVectorTest) // Batch Norm ARMNN_AUTO_TEST_CASE(BatchNorm, BatchNormTest) ARMNN_AUTO_TEST_CASE(BatchNormNhwc, BatchNormNhwcTest) // Constant ARMNN_AUTO_TEST_CASE(Constant, ConstantTest) ARMNN_AUTO_TEST_CASE(ConstantUint8, ConstantTestUint8) // Concatenation ARMNN_AUTO_TEST_CASE(Concatenation1d, Concatenation1dTest) ARMNN_AUTO_TEST_CASE(Concatenation1dUint8, Concatenation1dUint8Test) ARMNN_AUTO_TEST_CASE(Concatenation2dDim0, Concatenation2dDim0Test) ARMNN_AUTO_TEST_CASE(Concatenation2dDim0Uint8, Concatenation2dDim0Uint8Test) ARMNN_AUTO_TEST_CASE(Concatenation2dDim1, Concatenation2dDim1Test) ARMNN_AUTO_TEST_CASE(Concatenation2dDim1Uint8, Concatenation2dDim1Uint8Test) ARMNN_AUTO_TEST_CASE(Concatenation2dDim0DiffInputDims, Concatenation2dDim0DiffInputDimsTest) ARMNN_AUTO_TEST_CASE(Concatenation2dDim0DiffInputDimsUint8, Concatenation2dDim0DiffInputDimsUint8Test) ARMNN_AUTO_TEST_CASE(Concatenation2dDim1DiffInputDims, Concatenation2dDim1DiffInputDimsTest) ARMNN_AUTO_TEST_CASE(Concatenation2dDim1DiffInputDimsUint8, Concatenation2dDim1DiffInputDimsUint8Test) ARMNN_AUTO_TEST_CASE(Concatenation3dDim0, Concatenation3dDim0Test) ARMNN_AUTO_TEST_CASE(Concatenation3dDim0Uint8, Concatenation3dDim0Uint8Test) ARMNN_AUTO_TEST_CASE(Concatenation3dDim1, Concatenation3dDim1Test) ARMNN_AUTO_TEST_CASE(Concatenation3dDim1Uint8, Concatenation3dDim1Uint8Test) ARMNN_AUTO_TEST_CASE(Concatenation3dDim2, Concatenation3dDim2Test) ARMNN_AUTO_TEST_CASE(Concatenation3dDim2Uint8, Concatenation3dDim2Uint8Test) ARMNN_AUTO_TEST_CASE(Concatenation3dDim0DiffInputDims, Concatenation3dDim0DiffInputDimsTest) ARMNN_AUTO_TEST_CASE(Concatenation3dDim0DiffInputDimsUint8, Concatenation3dDim0DiffInputDimsUint8Test) ARMNN_AUTO_TEST_CASE(Concatenation3dDim1DiffInputDims, Concatenation3dDim1DiffInputDimsTest) ARMNN_AUTO_TEST_CASE(Concatenation3dDim1DiffInputDimsUint8, Concatenation3dDim1DiffInputDimsUint8Test) ARMNN_AUTO_TEST_CASE(Concatenation3dDim2DiffInputDims, Concatenation3dDim2DiffInputDimsTest) ARMNN_AUTO_TEST_CASE(Concatenation3dDim2DiffInputDimsUint8, Concatenation3dDim2DiffInputDimsUint8Test) // L2 Normalization ARMNN_AUTO_TEST_CASE(L2Normalization1d, L2Normalization1dTest) ARMNN_AUTO_TEST_CASE(L2Normalization2d, L2Normalization2dTest) ARMNN_AUTO_TEST_CASE(L2Normalization3d, L2Normalization3dTest) ARMNN_AUTO_TEST_CASE(L2Normalization4d, L2Normalization4dTest) ARMNN_AUTO_TEST_CASE(L2Normalization1dNhwc, L2Normalization1dNhwcTest) ARMNN_AUTO_TEST_CASE(L2Normalization2dNhwc, L2Normalization2dNhwcTest) ARMNN_AUTO_TEST_CASE(L2Normalization3dNhwc, L2Normalization3dNhwcTest) ARMNN_AUTO_TEST_CASE(L2Normalization4dNhwc, L2Normalization4dNhwcTest) // Floor ARMNN_AUTO_TEST_CASE(SimpleFloor, SimpleFloorTest) // Reshape ARMNN_AUTO_TEST_CASE(SimpleReshapeFloat32, SimpleReshapeFloat32Test) ARMNN_AUTO_TEST_CASE(SimpleReshapeUint8, SimpleReshapeUint8Test) // Permute ARMNN_AUTO_TEST_CASE(SimplePermuteFloat32, SimplePermuteFloat32Test) ARMNN_AUTO_TEST_CASE(SimplePermuteUint8, SimplePermuteUint8Test) ARMNN_AUTO_TEST_CASE(PermuteFloat32ValueSet1, PermuteFloat32ValueSet1Test) ARMNN_AUTO_TEST_CASE(PermuteFloat32ValueSet2, PermuteFloat32ValueSet2Test) ARMNN_AUTO_TEST_CASE(PermuteFloat32ValueSet3, PermuteFloat32ValueSet3Test) // Lstm ARMNN_AUTO_TEST_CASE(LstmLayerFloat32WithCifgWithPeepholeNoProjection, LstmLayerFloat32WithCifgWithPeepholeNoProjectionTest) ARMNN_AUTO_TEST_CASE(LstmLayerFloat32NoCifgNoPeepholeNoProjection, LstmLayerFloat32NoCifgNoPeepholeNoProjectionTest) ARMNN_AUTO_TEST_CASE(LstmLayerFloat32NoCifgWithPeepholeWithProjection, LstmLayerFloat32NoCifgWithPeepholeWithProjectionTest) // Normalization ARMNN_AUTO_TEST_CASE(SimpleNormalizationAcross, SimpleNormalizationAcrossTest) ARMNN_AUTO_TEST_CASE(SimpleNormalizationWithin, SimpleNormalizationWithinTest) ARMNN_AUTO_TEST_CASE(SimpleNormalizationAcrossNhwc, SimpleNormalizationAcrossNhwcTest) // ============================================================================ // COMPARE tests ARMNN_COMPARE_REF_AUTO_TEST_CASE(CompareConv2dWithReference, CompareConvolution2dTest) ARMNN_COMPARE_REF_AUTO_TEST_CASE(CompareDepthwiseConv2dWithReferenceFloat32, CompareDepthwiseConvolution2dTest) ARMNN_COMPARE_REF_AUTO_TEST_CASE(CompareDepthwiseConv2dWithReferenceUint8, CompareDepthwiseConvolution2dTest) ARMNN_COMPARE_REF_AUTO_TEST_CASE(CompareNormalizationWithinWithReference, CompareNormalizationTest, armnn::NormalizationAlgorithmChannel::Within, armnn::NormalizationAlgorithmMethod::LocalBrightness) ARMNN_COMPARE_REF_AUTO_TEST_CASE(CompareNormalizationAcrossWithReference, CompareNormalizationTest, armnn::NormalizationAlgorithmChannel::Across, armnn::NormalizationAlgorithmMethod::LocalBrightness) ARMNN_COMPARE_REF_AUTO_TEST_CASE(CompareMaxPooling2dWithReference, ComparePooling2dTest, armnn::PoolingAlgorithm::Max) ARMNN_COMPARE_REF_AUTO_TEST_CASE(CompareMaxPooling2dWithReferenceUint8, ComparePooling2dUint8Test, armnn::PoolingAlgorithm::Max) ARMNN_COMPARE_REF_AUTO_TEST_CASE(CompareAveragePooling2dWithReference, ComparePooling2dTest, armnn::PoolingAlgorithm::Average) ARMNN_COMPARE_REF_AUTO_TEST_CASE(CompareAveragePooling2dWithReferenceUint8, ComparePooling2dUint8Test, armnn::PoolingAlgorithm::Average) ARMNN_COMPARE_REF_AUTO_TEST_CASE(CompareL2Pooling2dWithReference, ComparePooling2dTest, armnn::PoolingAlgorithm::L2) ARMNN_COMPARE_REF_AUTO_TEST_CASE(UNSUPPORTED_CompareL2Pooling2dWithReferenceUint8, ComparePooling2dUint8Test, armnn::PoolingAlgorithm::L2) ARMNN_COMPARE_REF_AUTO_TEST_CASE(CompareSoftmaxBeta1WithReference, CompareSoftmaxTest, 1.0f) ARMNN_COMPARE_REF_AUTO_TEST_CASE(CompareSoftmaxBeta2WithReference, CompareSoftmaxTest, 2.0f) ARMNN_COMPARE_REF_AUTO_TEST_CASE(CompareSoftmaxUint8Beta1WithReference, CompareSoftmaxUint8Test, 1.0f) ARMNN_COMPARE_REF_AUTO_TEST_CASE(CompareSoftmaxUint8Beta2WithReference, CompareSoftmaxUint8Test, 2.0f) ARMNN_COMPARE_REF_AUTO_TEST_CASE(CompareAddition, CompareAdditionTest) ARMNN_COMPARE_REF_AUTO_TEST_CASE(CompareMultiplicationWithReference, CompareMultiplicationTest) ARMNN_COMPARE_REF_AUTO_TEST_CASE(CompareBatchNorm, CompareBatchNormTest) ARMNN_COMPARE_REF_AUTO_TEST_CASE(ReLu1, CompareBoundedReLuTest, 1.0f, -1.0f) ARMNN_COMPARE_REF_AUTO_TEST_CASE(ReLu6, CompareBoundedReLuTest, 6.0f, 0.0f) // ============================================================================ // FIXTURE tests ARMNN_COMPARE_REF_FIXTURE_TEST_CASE(CompareSigmoidActivationWithReference, ActivationFixture, CompareActivationTest, armnn::ActivationFunction::Sigmoid, 5u) ARMNN_COMPARE_REF_FIXTURE_TEST_CASE(CompareTanhActivationWithReference, ActivationFixture, CompareActivationTest, armnn::ActivationFunction::TanH, 5u) ARMNN_COMPARE_REF_FIXTURE_TEST_CASE(CompareLinearActivationWithReference, ActivationFixture, CompareActivationTest, armnn::ActivationFunction::Linear, 5u) ARMNN_COMPARE_REF_FIXTURE_TEST_CASE(CompareReLuActivationWithReference, ActivationFixture, CompareActivationTest, armnn::ActivationFunction::ReLu, 5u) ARMNN_COMPARE_REF_FIXTURE_TEST_CASE(CompareBoundedReLuActivationWithReference, ActivationFixture, CompareActivationTest, armnn::ActivationFunction::BoundedReLu, 5u) ARMNN_COMPARE_REF_FIXTURE_TEST_CASE(CompareBoundedReLuActivationWithReferenceUint8, ActivationFixture, CompareActivationUint8Test, armnn::ActivationFunction::BoundedReLu) ARMNN_COMPARE_REF_FIXTURE_TEST_CASE(CompareSoftReLuActivationWithReference, ActivationFixture, CompareActivationTest, armnn::ActivationFunction::SoftReLu, 1u) ARMNN_COMPARE_REF_FIXTURE_TEST_CASE(CompareLeakyReLuActivationWithReference, ActivationFixture, CompareActivationTest, armnn::ActivationFunction::LeakyReLu, 5u) ARMNN_COMPARE_REF_FIXTURE_TEST_CASE(CompareAbsActivationWithReference, ActivationFixture, CompareActivationTest, armnn::ActivationFunction::Abs, 5u) ARMNN_COMPARE_REF_FIXTURE_TEST_CASE(CompareSqrtActivationWithReference, PositiveActivationFixture, CompareActivationTest, armnn::ActivationFunction::Sqrt, 5u) ARMNN_COMPARE_REF_FIXTURE_TEST_CASE(CompareSquareActivationWithReference, ActivationFixture, CompareActivationTest, armnn::ActivationFunction::Square, 5u) BOOST_AUTO_TEST_SUITE_END()