diff options
Diffstat (limited to 'src/backends/backendsCommon/test/layerTests/Conv2dTestImpl.cpp')
| -rw-r--r-- | src/backends/backendsCommon/test/layerTests/Conv2dTestImpl.cpp | 194 |
1 files changed, 71 insertions, 123 deletions
diff --git a/src/backends/backendsCommon/test/layerTests/Conv2dTestImpl.cpp b/src/backends/backendsCommon/test/layerTests/Conv2dTestImpl.cpp index 98264ee928..99f1436c98 100644 --- a/src/backends/backendsCommon/test/layerTests/Conv2dTestImpl.cpp +++ b/src/backends/backendsCommon/test/layerTests/Conv2dTestImpl.cpp @@ -1659,10 +1659,9 @@ LayerTestResult<T, 4> DepthwiseConvolution2dAsymmetricTestImpl( unsigned int inputChannels = armnn::numeric_cast<unsigned int>(inputShape[1]); unsigned int inputHeight = armnn::numeric_cast<unsigned int>(inputShape[2]); unsigned int inputWidth = armnn::numeric_cast<unsigned int>(inputShape[3]); - unsigned int kernelChanMul = armnn::numeric_cast<unsigned int>(kernelShape[0]); - unsigned int kernelChannels = armnn::numeric_cast<unsigned int>(kernelShape[1]); - unsigned int kernelHeight = armnn::numeric_cast<unsigned int>(kernelShape[2]); - unsigned int kernelWidth = armnn::numeric_cast<unsigned int>(kernelShape[3]); + unsigned int kernelHeight = armnn::numeric_cast<unsigned int>(kernelShape[1]); + unsigned int kernelWidth = armnn::numeric_cast<unsigned int>(kernelShape[2]); + unsigned int kernelChannels = armnn::numeric_cast<unsigned int>(kernelShape[3]); unsigned int outputNum = armnn::numeric_cast<unsigned int>(outputExpectedShape[0]); unsigned int outputChannels = armnn::numeric_cast<unsigned int>(outputExpectedShape[1]); unsigned int outputHeight = armnn::numeric_cast<unsigned int>(outputExpectedShape[2]); @@ -1677,7 +1676,7 @@ LayerTestResult<T, 4> DepthwiseConvolution2dAsymmetricTestImpl( armnnUtils::GetTensorInfo(inputNum, inputChannels, inputHeight, inputWidth, layout, ArmnnType); armnn::TensorInfo outputTensorInfo = armnnUtils::GetTensorInfo(outputNum, outputChannels, outputHeight, outputWidth, layout, ArmnnType); - armnn::TensorInfo kernelDesc({kernelChanMul, kernelChannels, kernelHeight, kernelWidth}, ArmnnType); + armnn::TensorInfo kernelDesc({1, kernelHeight, kernelWidth, kernelChannels}, ArmnnType); armnn::TensorInfo biasDesc({static_cast<unsigned int>(bias.size())}, ArmnnBType); // Set quantization parameters if the requested type is a quantized type. @@ -1792,19 +1791,17 @@ LayerTestResult<T, 4> DepthwiseConvolution2dDepthMul1TestImpl( unsigned int kernelHeight = 3; unsigned int kernelWidth = 3; - unsigned int kernelChannels = inputChannels; - unsigned int kernelDepthMultiplier = 1; unsigned int outputHeight = 1; unsigned int outputWidth = 1; - unsigned int outputChannels = kernelChannels; + unsigned int outputChannels = inputChannels; unsigned int outputNum = inputNum; armnn::TensorInfo inputTensorInfo = armnnUtils::GetTensorInfo(inputNum, inputChannels, inputHeight, inputWidth, layout, ArmnnType); armnn::TensorInfo outputTensorInfo = armnnUtils::GetTensorInfo(outputNum, outputChannels, outputHeight, outputWidth, layout, ArmnnType); - armnn::TensorInfo kernelDesc({kernelDepthMultiplier, kernelChannels, kernelHeight, kernelWidth}, + armnn::TensorInfo kernelDesc({1, kernelHeight, kernelWidth, outputChannels}, ArmnnType); armnn::TensorInfo biasDesc({ outputChannels }, ArmnnBType); @@ -1955,7 +1952,7 @@ LayerTestResult<T, 4> DepthwiseConvolution2dTestImpl( inputBatchSize, inputChannels, inputHeight, inputWidth, layout, ArmnnType); armnn::TensorInfo outputTensorInfo = armnnUtils::GetTensorInfo( outputBatchSize, outputChannels, outputHeight, outputWidth, layout, ArmnnType); - armnn::TensorInfo kernelDesc({depthMultiplier, inputChannels, kernelHeight, kernelWidth}, + armnn::TensorInfo kernelDesc({1, kernelHeight, kernelWidth, outputChannels}, ArmnnType); armnn::TensorInfo biasDesc({outputChannels}, ArmnnBType); @@ -2040,33 +2037,18 @@ LayerTestResult<T, 4> DepthwiseConvolution2dTestImpl( // Manually calculated. std::vector<T> originalOutputImage = std::vector<T>( QuantizedVector<T>({ - 3.5f, 3.5f, 3.5f, 3.5f, 3.5f, 3.5f, 3.5f, - 6.0f, 6.0f, 6.0f, 6.0f, 6.0f, 6.0f, 6.0f, - 5.0f, 5.0f, 5.0f, 5.0f, 5.0f, 5.0f, 5.0f, - 6.5f, 6.5f, 6.5f, 6.5f, 6.5f, 6.5f, 6.5f, - 6.5f, 6.5f, 6.5f, 6.5f, 6.5f, 6.5f, 6.5f, - 5.0f, 5.0f, 5.0f, 5.0f, 5.0f, 5.0f, 5.0f, - - -0.5f, -0.5f, -0.5f, -0.5f, -0.5f, -0.5f, -0.5f, - 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, - -0.5f, -0.5f, -0.5f, -0.5f, -0.5f, -0.5f, -0.5f, - -0.5f, -0.5f, -0.5f, -0.5f, -0.5f, -0.5f, -0.5f, - -0.5f, -0.5f, -0.5f, -0.5f, -0.5f, -0.5f, -0.5f, - -0.5f, -0.5f, -0.5f, -0.5f, -0.5f, -0.5f, -0.5f, - - 8.0f, 8.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, - 10.0f, 10.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, - 10.0f, 10.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, - 10.0f, 10.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, - 10.0f, 10.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, - 8.0f, 8.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, - - 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, - 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, - 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, - 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, - 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, - 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f + 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, + 5, 5, 5, 5, 5, 5, 5, 5.5, 5.5, 5.5, 5.5, 5.5, 5.5, 5.5, + 5.5, 5.5, 5.5, 5.5, 5.5, 5.5, 5.5, 5, 5, 5, 5, 5, 5, 5, + 2.5, 2.5, 2.5, 2.5, 2.5, 2.5, 2.5, 3.5, 3.5, 3.5, 3.5, 3.5, 3.5, 3.5, + 4.5, 4.5, 4.5, 4.5, 4.5, 4.5, 4.5, 6, 6, 6, 6, 6, 6, 6, + 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, + 1, 3, 0, 0, 0, 0, 0, 2, 4, 0, 0, 0, 0, 0, + 2, 4, 0, 0, 0, 0, 0, 2, 4, 0, 0, 0, 0, 0, + 2, 4, 0, 0, 0, 0, 0, 2, 4, 0, 0, 0, 0, 0, + 2, 4, 0, 0, 0, 0, 0, 3, 5, 0, 0, 0, 0, 0, + 3, 5, 0, 0, 0, 0, 0, 3, 5, 0, 0, 0, 0, 0, + 3, 5, 0, 0, 0, 0, 0, 3, 5, 0, 0, 0, 0, 0 }, outputTensorInfo.GetQuantizationScale(), outputTensorInfo.GetQuantizationOffset())); @@ -2170,10 +2152,9 @@ LayerTestResult<T, 4> DepthwiseConvolution2dTestImpl( unsigned int outputChannels = armnn::numeric_cast<unsigned int>(originalOutputExpectedShape[1]); unsigned int outputNum = armnn::numeric_cast<unsigned int>(originalOutputExpectedShape[0]); - unsigned int kernelHeight = armnn::numeric_cast<unsigned int>(originalKernelShape[2]); - unsigned int kernelWidth = armnn::numeric_cast<unsigned int>(originalKernelShape[3]); - unsigned int kernelChannels = armnn::numeric_cast<unsigned int>(originalKernelShape[1]); - unsigned int kernelDepthMul = armnn::numeric_cast<unsigned int>(originalKernelShape[0]); + unsigned int kernelHeight = armnn::numeric_cast<unsigned int>(originalKernelShape[1]); + unsigned int kernelWidth = armnn::numeric_cast<unsigned int>(originalKernelShape[2]); + unsigned int kernelChannels = armnn::numeric_cast<unsigned int>(originalKernelShape[3]); bool biasEnabled = bias.size() > 0; @@ -2192,7 +2173,7 @@ LayerTestResult<T, 4> DepthwiseConvolution2dTestImpl( armnnUtils::GetTensorInfo(2*outputNum, outputChannels, outputHeight, outputWidth, layout, ArmnnType); // Kernel must be NCHW layout always, independently of the layout of the input and output for depthwise convolution. - armnn::TensorInfo kernelDesc({kernelDepthMul, kernelChannels, kernelHeight, kernelWidth}, ArmnnType); + armnn::TensorInfo kernelDesc({1, kernelHeight, kernelWidth, kernelChannels}, ArmnnType); armnn::TensorInfo biasDesc({static_cast<unsigned int>(bias.size())}, ArmnnBType); @@ -2332,9 +2313,9 @@ LayerTestResult<T, 4> DepthwiseConvolution2dAsymmetricTestCommon( inputTensorInfo.GetQuantizationOffset()); // Use a depth multiplier of 1 on a 2-channel 4x4 kernel. - armnn::TensorInfo kernelTensorInfo({ 1, 2, 4, 4 }, ArmnnType); - auto kernel = QuantizedVector<T>( - { + // Weights layout for depthwise: [1,H,W,I*M] + armnn::TensorInfo kernelTensorInfo({ 1, 4, 4, 2 }, ArmnnType); + auto kernel = QuantizedVector<T>({ 32, 31, 30, 29, 28, 27, 26, 25, 24, 23, 22, 21, @@ -2353,17 +2334,10 @@ LayerTestResult<T, 4> DepthwiseConvolution2dAsymmetricTestCommon( armnn::TensorInfo outputTensorInfo({ 1, 2, 5, 5 }, ArmnnType); auto expectedOutput = QuantizedVector<T>( { - 1062, 1580, 1850, 1530, 1117, - 2140, 3108, 3500, 2842, 2042, - 3580, 5068, 5460, 4342, 3062, - 3618, 5072, 5390, 4248, 2971, - 3074, 4282, 4510, 3533, 2457, - - 1550, 2284, 2362, 1955, 1428, - 2910, 4206, 4342, 3528, 2536, - 3390, 4886, 5022, 4068, 2916, - 3566, 5056, 5182, 4133, 2922, - 3100, 4352, 4452, 3517, 2465 + 396, 664, 820, 756, 602, 1016, 1608, 1880, 1652, 1268, 1976, 2968, 3240, 2732, + 2028, 2628, 3808, 4060, 3312, 2390, 2596, 3700, 3900, 3130, 2226, 2817, 4186, + 4330, 3609, 2651, 5414, 7864, 8120, 6626, 4780, 6314, 9144, 9400, 7646, 5500, + 6759, 9610, 9850, 7875, 5579, 5935, 8348, 8540, 6757, 4742 }, outputTensorInfo.GetQuantizationScale(), outputTensorInfo.GetQuantizationOffset()); @@ -2420,9 +2394,8 @@ LayerTestResult<T, 4> DepthwiseConvolution2dNhwcTestCommon( inputTensorInfo.GetQuantizationScale(), inputTensorInfo.GetQuantizationOffset()); - armnn::TensorInfo kernelTensorInfo({ 1, 2, 4, 4 }, ArmnnType); - auto kernel = QuantizedVector<T>( - { + armnn::TensorInfo kernelTensorInfo({ 1, 4, 4, 2 }, ArmnnType); + auto kernel = QuantizedVector<T>({ 32, 31, 30, 29, 28, 27, 26, 25, 24, 23, 22, 21, @@ -2439,17 +2412,17 @@ LayerTestResult<T, 4> DepthwiseConvolution2dNhwcTestCommon( armnn::TensorInfo outputTensorInfo({ 1, 2, 5, 5}, ArmnnType); auto expectedOutput = QuantizedVector<T>( { - 1062, 1580, 1850, 1530, 1117, - 2140, 3108, 3500, 2842, 2042, - 3580, 5068, 5460, 4342, 3062, - 3618, 5072, 5390, 4248, 2971, - 3074, 4282, 4510, 3533, 2457, - - 1550, 2284, 2362, 1955, 1428, - 2910, 4206, 4342, 3528, 2536, - 3390, 4886, 5022, 4068, 2916, - 3566, 5056, 5182, 4133, 2922, - 3100, 4352, 4452, 3517, 2465 + 396,664,820,756,602, + 1016,1608,1880,1652,1268, + 1976,2968,3240,2732,2028, + 2628,3808,4060,3312,2390, + 2596,3700,3900,3130,2226, + + 2817,4186,4330,3609,2651, + 5414,7864,8120,6626,4780, + 6314,9144,9400,7646,5500, + 6759,9610,9850,7875,5579, + 5935,8348,8540,6757,4742 }, outputTensorInfo.GetQuantizationScale(), outputTensorInfo.GetQuantizationOffset()); @@ -2504,9 +2477,8 @@ LayerTestResult<T, 4> SimpleDepthwiseConvolution2d3x3Dilation3x3NhwcTestCommon( inputTensorInfo.GetQuantizationScale(), inputTensorInfo.GetQuantizationOffset()); - armnn::TensorInfo kernelTensorInfo({ 1, 1, 3, 3 }, ArmnnType); - auto kernel = QuantizedVector<T>( - { + armnn::TensorInfo kernelTensorInfo({ 1, 3, 3, 1}, ArmnnType); + auto kernel = QuantizedVector<T>({ 1, 2, 3, 4, 5, 6, 7, 8, 9 @@ -2671,7 +2643,7 @@ LayerTestResult<T, 4> DepthwiseConvolution2d3x3Dilation3x3Test( 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 }; - armnn::TensorInfo kernelTensorInfo({ 1, 1, 3, 3}, ArmnnType); + armnn::TensorInfo kernelTensorInfo({ 1, 3, 3, 1}, ArmnnType); std::vector<float> kernelNoQuantizedValues = { 1, 2, 3, @@ -2740,7 +2712,7 @@ LayerTestResult<T, 4> DepthwiseConvolution2d2x3x3Dilation3x3Test( 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 }; - armnn::TensorInfo kernelTensorInfo({ 1, 2, 3, 3}, ArmnnType); + armnn::TensorInfo kernelTensorInfo({ 1, 3, 3, 2}, ArmnnType); std::vector<float> kernelNoQuantizedValues = { 1, 2, 3, @@ -2757,15 +2729,9 @@ LayerTestResult<T, 4> DepthwiseConvolution2d2x3x3Dilation3x3Test( armnn::TensorInfo outputTensorInfo({ 1, 2, 4, 4}, ArmnnType); std::vector<float> outputExpectedNoQuantizedValues = { - 6., 5., 5., 5., - 6., 5., 5., 5., - 6., 5., 5., 5., - 3., 2., 2., 2., + 2, 9, 9, 9, 2, 9, 9, 9, 2, 9, 9, 9, 5, 3, 3, 3, 3, - 6., 5., 5., 5., - 6., 5., 5., 5., - 6., 5., 5., 5., - 3., 2., 2., 2. + 1, 1, 1, 3, 1, 1, 1, 3, 1, 1, 1, 6, 4, 4, 4 }; return DepthwiseConvolution2d3x3DilationTestCommon<ArmnnType, ArmnnBType>( @@ -2804,7 +2770,7 @@ LayerTestResult<T, 4> DepthwiseConvolution2dMult4Test( 27.0, 28.0, 29.0 }; - armnn::TensorInfo kernelTensorInfo({ 4, 2, 2, 2}, ArmnnType); + armnn::TensorInfo kernelTensorInfo({ 1, 2, 2, 8}, ArmnnType); std::vector<float> kernelNoQuantizedValues = { @@ -2836,29 +2802,10 @@ LayerTestResult<T, 4> DepthwiseConvolution2dMult4Test( armnn::TensorInfo outputTensorInfo({ 1, 8, 2, 2}, ArmnnType); std::vector<float> outputExpectedNoQuantizedValues = { - 10.f, 10.f, - 10.f, 10.f, - - 1.f, 1.f, - 1.f, 1.f, - - 2.f, 2.f, - 2.f, 2.f, - - 3.f, 3.f, - 3.f, 3.f, - - 23.f, 24.f, - 26.f, 27.f, - - 2.5f, 2.6000001f, - 2.8f, 2.9f, - - 4.2000003f, 4.4f, - 4.8f, 5.f, - - 6.6000004f, 6.9f, - 7.5000005f, 7.8f + 4.5f, 4.5f, 4.5f, 4.5f, 5.5f, 5.5f, 5.5f, 5.5f, + 2.5f, 2.5f, 2.5f, 2.5f, 3.5f, 3.5f, 3.5f, 3.5f, + 10.05f, 10.5f, 11.4f, 11.85f, 12.75f, 13.3f, 14.4f, 14.95f, + 5.25f, 5.5f, 6.0f, 6.25f, 7.45f, 7.8f, 8.5f, 8.85f }; @@ -2898,7 +2845,7 @@ LayerTestResult<T, 4> DepthwiseConvolution2dMult2Test( 27.0, 28.0, 29.0 }; - armnn::TensorInfo kernelTensorInfo({ 2, 2, 2, 2}, ArmnnType); + armnn::TensorInfo kernelTensorInfo({ 1, 2, 2, 4}, ArmnnType); std::vector<float> kernelNoQuantizedValues = { @@ -2919,17 +2866,10 @@ LayerTestResult<T, 4> DepthwiseConvolution2dMult2Test( armnn::TensorInfo outputTensorInfo({ 1, 4, 2, 2}, ArmnnType); std::vector<float> outputExpectedNoQuantizedValues = { - 10.f, 10.f, - 10.f, 10.f, - - 1.f, 1.f, - 1.f, 1.f, - - 4.2000003f, 4.4f, - 4.8f, 5.f, - - 6.6000004f, 6.9f, - 7.5000005f, 7.8f + 4.5f, 4.5f, 4.5f, 4.5f, + 5.5f, 5.5f, 5.5f, 5.5f, + 5.25f, 5.5f, 6.0f, 6.25f, + 7.65f, 8.0f, 8.7f, 9.05f }; @@ -2984,7 +2924,7 @@ LayerTestResult<T, 4> CompareDepthwiseConvolution2dTestImpl( std::vector<unsigned int> inputShape; std::vector<unsigned int> outputShape; - std::vector<unsigned int> kernelShape{ channelMultiplier, inputChannels, kernelHeight, kernelWidth }; + std::vector<unsigned int> kernelShape{ 1, kernelHeight, kernelWidth, outputChannels }; std::vector<unsigned int> biasShape{ outputChannels }; switch (layout.GetDataLayout()) { @@ -3609,6 +3549,14 @@ LayerTestResult<float, 4> DepthwiseConvolution2dDepthMul64Test( } armnn::TensorInfo kernelTensorInfo({ 64, 1, 2, 2 }, armnn::DataType::Float32); + // permute from [O,1,H,W] --> [1,H,W,O] + armnn::PermutationVector permutationVector {3,0,1,2}; + kernelTensorInfo = armnnUtils::Permuted(kernelTensorInfo, permutationVector); + std::vector<float> kernelPermuted(kernelTensorInfo.GetNumElements()); + armnnUtils::Permute(kernelTensorInfo.GetShape(), permutationVector, + kernelData.data(), kernelPermuted.data(), + GetDataTypeSize(kernelTensorInfo.GetDataType())); + std::vector<float> expectedOutputData(64, 0.f); armnn::TensorInfo outputTensorInfo({ 1, 64, 1, 1 }, armnn::DataType::Float32); @@ -3617,7 +3565,7 @@ LayerTestResult<float, 4> DepthwiseConvolution2dDepthMul64Test( memoryManager, tensorHandleFactory, input, - kernelData, + kernelPermuted, std::vector<float>(), expectedOutputData, inputTensorInfo.GetShape(), @@ -3713,8 +3661,8 @@ LayerTestResult<uint8_t, 4> DepthwiseConvolution2dPerAxisQuantTest( TensorInfo outputInfo({ 1, 2, 2, 4 }, inputType, 1.0f, 128); // N H W C const std::vector<float> quantScales{ 1.0f, 0.5f, 1.0f, 0.5f }; - const unsigned int quantDimension = 0; - TensorInfo kernelInfo({ 2, 2, 2, 2 }, kernelType, quantScales, quantDimension); // M I H W + const unsigned int quantDimension = 3; + TensorInfo kernelInfo({ 1, 2, 2, 4 }, kernelType, quantScales, quantDimension); // [1, H, W, I*M] const std::vector<float> biasQuantScales{ 0.5f, 0.25f, 0.5f, 0.25f }; constexpr unsigned int biasQuantDimension = 0; |