diff options
Diffstat (limited to 'src/backends/backendsCommon/test/ActivationTestImpl.hpp')
| -rw-r--r-- | src/backends/backendsCommon/test/ActivationTestImpl.hpp | 81 |
1 files changed, 39 insertions, 42 deletions
diff --git a/src/backends/backendsCommon/test/ActivationTestImpl.hpp b/src/backends/backendsCommon/test/ActivationTestImpl.hpp index 46c700ce02..ca6130299b 100644 --- a/src/backends/backendsCommon/test/ActivationTestImpl.hpp +++ b/src/backends/backendsCommon/test/ActivationTestImpl.hpp @@ -19,7 +19,7 @@ #include <algorithm> -template<typename T> +template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> LayerTestResult<T, 4> BoundedReLuTestCommon( armnn::IWorkloadFactory& workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, @@ -41,11 +41,9 @@ LayerTestResult<T, 4> BoundedReLuTestCommon( unsigned int outputChannels = inputChannels; unsigned int outputBatchSize = inputBatchSize; - armnn::TensorInfo inputTensorInfo({ inputBatchSize, inputChannels, inputHeight, inputWidth }, - armnn::GetDataType<T>()); + armnn::TensorInfo inputTensorInfo({ inputBatchSize, inputChannels, inputHeight, inputWidth }, ArmnnType); - armnn::TensorInfo outputTensorInfo({ outputBatchSize, outputChannels, outputHeight, outputWidth }, - armnn::GetDataType<T>()); + armnn::TensorInfo outputTensorInfo({ outputBatchSize, outputChannels, outputHeight, outputWidth }, ArmnnType); if(armnn::IsQuantizedType<T>()) { @@ -115,7 +113,7 @@ LayerTestResult<float, 4> BoundedReLuUpperAndLowerBoundTest( 0.999f, 1.0f, 0.89f, 1.0f, }; - return BoundedReLuTestCommon( + return BoundedReLuTestCommon<armnn::DataType::Float32>( workloadFactory, memoryManager, 1.0f, -1.0f, 1.0f, 0, 1.0f, 0, input, output, inputWidth, inputHeight, inputChannels, inputBatchSize); } @@ -146,7 +144,7 @@ LayerTestResult<float, 4> BoundedReLuUpperBoundOnlyTest( 0.999f, 1.2f, 0.89f, 6.0f, }; - return BoundedReLuTestCommon( + return BoundedReLuTestCommon<armnn::DataType::Float32>( workloadFactory, memoryManager, 6.0f, 0.0f, 1.0f, 0, 1.0f, 0, input, output, inputWidth, inputHeight, inputChannels, inputBatchSize); } @@ -176,10 +174,10 @@ LayerTestResult<uint8_t, 4> BoundedReLuUint8UpperBoundOnlyTest( float outputScale = 6.0f / 255.0f; int32_t outputOffset = 0; - return BoundedReLuTestCommon(workloadFactory, memoryManager, 6.0f, 0.0f, - inputScale, inputOffset, outputScale, outputOffset, - input, output, - inputWidth, inputHeight, inputChannels, inputBatchSize); + return BoundedReLuTestCommon<armnn::DataType::QuantisedAsymm8>( + workloadFactory, memoryManager, 6.0f, 0.0f, + inputScale, inputOffset, outputScale, outputOffset, + input, output, inputWidth, inputHeight, inputChannels, inputBatchSize); } LayerTestResult<uint8_t, 4> BoundedReLuUint8UpperAndLowerBoundTest( @@ -205,10 +203,10 @@ LayerTestResult<uint8_t, 4> BoundedReLuUint8UpperAndLowerBoundTest( int32_t inputOffset = 112; float inputScale = 0.0125f; - return BoundedReLuTestCommon(workloadFactory, memoryManager, 1.0f, -1.0f, - inputScale, inputOffset, inputScale, inputOffset, // Input/output scale & offset same. - input, output, - inputWidth, inputHeight, inputChannels, inputBatchSize); + return BoundedReLuTestCommon<armnn::DataType::QuantisedAsymm8>( + workloadFactory, memoryManager, 1.0f, -1.0f, + inputScale, inputOffset, inputScale, inputOffset, // Input/output scale & offset same. + input, output, inputWidth, inputHeight, inputChannels, inputBatchSize); } namespace @@ -303,7 +301,7 @@ LayerTestResult<float, 4> CompareBoundedReLuTest( return result; } -template<typename T> +template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> LayerTestResult<T,4> ConstantLinearActivationTestCommon( armnn::IWorkloadFactory& workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, @@ -320,8 +318,8 @@ LayerTestResult<T,4> ConstantLinearActivationTestCommon( unsigned int shape[] = {batchSize, inputChannels, inputHeight, inputWidth}; - inputTensorInfo = armnn::TensorInfo(4, shape, armnn::GetDataType<T>()); - outputTensorInfo = armnn::TensorInfo(4, shape, armnn::GetDataType<T>()); + inputTensorInfo = armnn::TensorInfo(4, shape, ArmnnType); + outputTensorInfo = armnn::TensorInfo(4, shape, ArmnnType); // Set quantization parameters if the requested type is a quantized type. if(armnn::IsQuantizedType<T>()) @@ -368,17 +366,18 @@ LayerTestResult<float, 4> ConstantLinearActivationTest( armnn::IWorkloadFactory& workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) { - return ConstantLinearActivationTestCommon<float>(workloadFactory, memoryManager); + return ConstantLinearActivationTestCommon<armnn::DataType::Float32>(workloadFactory, memoryManager); } LayerTestResult<uint8_t, 4> ConstantLinearActivationUint8Test( armnn::IWorkloadFactory& workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) { - return ConstantLinearActivationTestCommon<uint8_t>(workloadFactory, memoryManager, 4.0f, 3); + return ConstantLinearActivationTestCommon<armnn::DataType::QuantisedAsymm8>( + workloadFactory, memoryManager, 4.0f, 3); } -template<typename T> +template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> LayerTestResult<T, 4> SimpleActivationTest( armnn::IWorkloadFactory& workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, @@ -400,10 +399,8 @@ LayerTestResult<T, 4> SimpleActivationTest( constexpr static unsigned int outputChannels = inputChannels; constexpr static unsigned int outputBatchSize = inputBatchSize; - armnn::TensorInfo inputTensorInfo({ inputBatchSize, inputChannels, inputHeight, inputWidth }, - armnn::GetDataType<T>()); - armnn::TensorInfo outputTensorInfo({ outputBatchSize, outputChannels, outputHeight, outputWidth }, - armnn::GetDataType<T>()); + armnn::TensorInfo inputTensorInfo({ inputBatchSize, inputChannels, inputHeight, inputWidth }, ArmnnType); + armnn::TensorInfo outputTensorInfo({ outputBatchSize, outputChannels, outputHeight, outputWidth }, ArmnnType); // Set quantization parameters if the requested type is a quantized type. if(armnn::IsQuantizedType<T>()) @@ -448,7 +445,7 @@ LayerTestResult<T, 4> SimpleActivationTest( return result; } -template<typename T> +template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> LayerTestResult<T, 4> SimpleSigmoidTestCommon( armnn::IWorkloadFactory& workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, @@ -470,32 +467,32 @@ LayerTestResult<T, 4> SimpleSigmoidTestCommon( std::vector<float> outputExpectedData(inputData.size()); std::transform(inputData.begin(), inputData.end(), outputExpectedData.begin(), f); - return SimpleActivationTest<T>(workloadFactory, - memoryManager, - armnn::ActivationFunction::Sigmoid, - 0.f, - 0.f, - qScale, - qOffset, - inputData, - outputExpectedData); + return SimpleActivationTest<ArmnnType>(workloadFactory, + memoryManager, + armnn::ActivationFunction::Sigmoid, + 0.f, + 0.f, + qScale, + qOffset, + inputData, + outputExpectedData); } LayerTestResult<float, 4> SimpleSigmoidTest( armnn::IWorkloadFactory& workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) { - return SimpleSigmoidTestCommon<float>(workloadFactory, memoryManager, 0.0f, 0); + return SimpleSigmoidTestCommon<armnn::DataType::Float32>(workloadFactory, memoryManager, 0.0f, 0); } LayerTestResult<uint8_t, 4> SimpleSigmoidUint8Test( armnn::IWorkloadFactory& workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) { - return SimpleSigmoidTestCommon<uint8_t>(workloadFactory, memoryManager, 0.1f, 50); + return SimpleSigmoidTestCommon<armnn::DataType::QuantisedAsymm8>(workloadFactory, memoryManager, 0.1f, 50); } -template<typename T> +template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> LayerTestResult<T,4> CompareActivationTestImpl( armnn::IWorkloadFactory& workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, @@ -517,8 +514,8 @@ LayerTestResult<T,4> CompareActivationTestImpl( unsigned int shape[] = {batchSize, channels, height, width}; - inputTensorInfo = armnn::TensorInfo(4, shape, armnn::GetDataType<T>()); - outputTensorInfo = armnn::TensorInfo(4, shape, armnn::GetDataType<T>()); + inputTensorInfo = armnn::TensorInfo(4, shape, ArmnnType); + outputTensorInfo = armnn::TensorInfo(4, shape, ArmnnType); // Set quantization parameters if the requested type is a quantized type. if(armnn::IsQuantizedType<T>()) @@ -596,7 +593,7 @@ LayerTestResult<float,4> CompareActivationTest( armnn::ActivationFunction f, unsigned int batchSize) { - return CompareActivationTestImpl<float>( + return CompareActivationTestImpl<armnn::DataType::Float32>( workloadFactory, memoryManager, refWorkloadFactory, f, batchSize); } @@ -606,6 +603,6 @@ LayerTestResult<uint8_t,4> CompareActivationUint8Test( armnn::IWorkloadFactory& refWorkloadFactory, armnn::ActivationFunction f) { - return CompareActivationTestImpl<uint8_t>( + return CompareActivationTestImpl<armnn::DataType::QuantisedAsymm8>( workloadFactory, memoryManager, refWorkloadFactory, f, 5, 0.1f, 50); } |