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-rw-r--r--src/backends/neon/test/NeonLayerTests.cpp484
1 files changed, 484 insertions, 0 deletions
diff --git a/src/backends/neon/test/NeonLayerTests.cpp b/src/backends/neon/test/NeonLayerTests.cpp
new file mode 100644
index 0000000000..2d4ee996a4
--- /dev/null
+++ b/src/backends/neon/test/NeonLayerTests.cpp
@@ -0,0 +1,484 @@
+//
+// Copyright © 2017 Arm Ltd. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+
+#include <armnn/test/TensorHelpers.hpp>
+#include <armnn/test/UnitTests.hpp>
+
+#include <backends/CpuTensorHandle.hpp>
+#include <backends/neon/NeonLayerSupport.hpp>
+#include <backends/neon/NeonWorkloadFactory.hpp>
+#include <backends/reference/RefWorkloadFactory.hpp>
+#include <backends/test/ActivationFixture.hpp>
+#include <backends/test/LayerTests.hpp>
+#include <backends/test/TensorCopyUtils.hpp>
+#include <backends/test/WorkloadTestUtils.hpp>
+
+#include <boost/test/unit_test.hpp>
+
+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(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;
+
+ // Strides supported: 1,2,3
+ descriptor = MakeDepthwiseConv2dDesc(1, 1);
+ outputInfo = CreateOutputTensorInfo(inputInfo, weightsInfo3x3, descriptor, dataType);
+ BOOST_TEST(armnn::IsDepthwiseConvolutionSupportedNeon(inputInfo, outputInfo, descriptor,
+ weightsInfo3x3, biasesInfo));
+
+ descriptor = MakeDepthwiseConv2dDesc(1, 2);
+ outputInfo = CreateOutputTensorInfo(inputInfo, weightsInfo3x3, descriptor, dataType);
+ BOOST_TEST(armnn::IsDepthwiseConvolutionSupportedNeon(inputInfo, outputInfo, descriptor,
+ weightsInfo3x3, biasesInfo));
+
+ descriptor = MakeDepthwiseConv2dDesc(1, 3);
+ outputInfo = CreateOutputTensorInfo(inputInfo, weightsInfo3x3, descriptor, dataType);
+ BOOST_TEST(armnn::IsDepthwiseConvolutionSupportedNeon(inputInfo, outputInfo, descriptor,
+ weightsInfo3x3, biasesInfo));
+
+ descriptor = MakeDepthwiseConv2dDesc(2, 1);
+ outputInfo = CreateOutputTensorInfo(inputInfo, weightsInfo3x3, descriptor, dataType);
+ BOOST_TEST(armnn::IsDepthwiseConvolutionSupportedNeon(inputInfo, outputInfo, descriptor,
+ weightsInfo3x3, biasesInfo));
+
+ descriptor = MakeDepthwiseConv2dDesc(2, 2);
+ outputInfo = CreateOutputTensorInfo(inputInfo, weightsInfo3x3, descriptor, dataType);
+ BOOST_TEST(armnn::IsDepthwiseConvolutionSupportedNeon(inputInfo, outputInfo, descriptor,
+ weightsInfo3x3, biasesInfo));
+
+ descriptor = MakeDepthwiseConv2dDesc(2, 3);
+ outputInfo = CreateOutputTensorInfo(inputInfo, weightsInfo3x3, descriptor, dataType);
+ BOOST_TEST(armnn::IsDepthwiseConvolutionSupportedNeon(inputInfo, outputInfo, descriptor,
+ weightsInfo3x3, biasesInfo));
+
+ descriptor = MakeDepthwiseConv2dDesc(3, 1);
+ outputInfo = CreateOutputTensorInfo(inputInfo, weightsInfo3x3, descriptor, dataType);
+ BOOST_TEST(armnn::IsDepthwiseConvolutionSupportedNeon(inputInfo, outputInfo, descriptor,
+ weightsInfo3x3, biasesInfo));
+
+ descriptor = MakeDepthwiseConv2dDesc(3, 2);
+ outputInfo = CreateOutputTensorInfo(inputInfo, weightsInfo3x3, descriptor, dataType);
+ BOOST_TEST(armnn::IsDepthwiseConvolutionSupportedNeon(inputInfo, outputInfo, descriptor,
+ weightsInfo3x3, biasesInfo));
+
+ descriptor = MakeDepthwiseConv2dDesc(3, 3);
+ outputInfo = CreateOutputTensorInfo(inputInfo, weightsInfo3x3, descriptor, dataType);
+ BOOST_TEST(armnn::IsDepthwiseConvolutionSupportedNeon(inputInfo, outputInfo, descriptor,
+ weightsInfo3x3, biasesInfo));
+
+ // Supported stride 4
+ descriptor = MakeDepthwiseConv2dDesc(4, 1);
+ outputInfo = CreateOutputTensorInfo(inputInfo, weightsInfo3x3, descriptor, dataType);
+ BOOST_TEST(armnn::IsDepthwiseConvolutionSupportedNeon(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(armnn::IsDepthwiseConvolutionSupportedNeon(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(armnn::IsDepthwiseConvolutionSupportedNeon(inputInfo, outputInfo, descriptor,
+ weightsInfo2x2, biasesInfo));
+
+ // Asymmetric padding
+ descriptor = MakeDepthwiseConv2dDesc(1, 1, 1, 1, 2, 1, 2);
+ outputInfo = CreateOutputTensorInfo(inputInfo, weightsInfo3x3, descriptor, dataType);
+ BOOST_TEST(armnn::IsDepthwiseConvolutionSupportedNeon(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<unsigned int, numDimensions> 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
+ BOOST_TEST(!armnn::IsSoftmaxSupportedNeon(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)
+
+// 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<float>)
+ARMNN_COMPARE_REF_AUTO_TEST_CASE(CompareDepthwiseConv2dWithReferenceUint8, CompareDepthwiseConvolution2dTest<uint8_t>)
+
+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()
generated by cgit v1.2.1 (git 2.23.0) at 2024-06-03 21:43:07 +0000