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author | Aron Virginas-Tar <Aron.Virginas-Tar@arm.com> | 2019-08-28 18:08:46 +0100 |
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committer | mike.kelly <mike.kelly@arm.com> | 2019-08-30 10:58:54 +0000 |
commit | 00d306e4db5153a4f4d280de4d4cf3e03788fefb (patch) | |
tree | 329c15f71c662e199a24dc0812bf95cb389ddbd8 /src/backends/backendsCommon/test/layerTests/RsqrtTestImpl.cpp | |
parent | 08b518687d2bf2683a2c5f571d3e76d71d67d048 (diff) | |
download | armnn-00d306e4db5153a4f4d280de4d4cf3e03788fefb.tar.gz |
IVGCVSW-3381 Break up LayerTests.hpp into more manageable files
Signed-off-by: Aron Virginas-Tar <Aron.Virginas-Tar@arm.com>
Change-Id: Icf39434f09fd340ad664cb3b97b8bee6d9da4838
Diffstat (limited to 'src/backends/backendsCommon/test/layerTests/RsqrtTestImpl.cpp')
-rw-r--r-- | src/backends/backendsCommon/test/layerTests/RsqrtTestImpl.cpp | 256 |
1 files changed, 256 insertions, 0 deletions
diff --git a/src/backends/backendsCommon/test/layerTests/RsqrtTestImpl.cpp b/src/backends/backendsCommon/test/layerTests/RsqrtTestImpl.cpp new file mode 100644 index 0000000000..c835ff2eec --- /dev/null +++ b/src/backends/backendsCommon/test/layerTests/RsqrtTestImpl.cpp @@ -0,0 +1,256 @@ +// +// Copyright © 2017 Arm Ltd. All rights reserved. +// SPDX-License-Identifier: MIT +// + +#include "ReshapeTestImpl.hpp" + +#include <armnn/ArmNN.hpp> + +#include <backendsCommon/test/DataTypeUtils.hpp> +#include <backendsCommon/test/TensorCopyUtils.hpp> +#include <backendsCommon/test/WorkloadTestUtils.hpp> + +#include <test/TensorHelpers.hpp> + +namespace +{ + +template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> +LayerTestResult<T, 2> Rsqrt2dTestCommon( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::TensorInfo inputTensorInfo, + const armnn::TensorInfo outputTensorInfo, + const std::vector<float>& inputValues, + const std::vector<float>& expectedOutputValues) +{ + auto inputTensor = MakeTensor<T, 2>(inputTensorInfo, ConvertToDataType<ArmnnType>(inputValues,inputTensorInfo)); + + LayerTestResult<T, 2> result(outputTensorInfo); + + result.outputExpected = MakeTensor<T, 2>(outputTensorInfo, + ConvertToDataType<ArmnnType>(expectedOutputValues,outputTensorInfo)); + + std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo); + std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); + + armnn::RsqrtQueueDescriptor descriptor; + + armnn::WorkloadInfo info; + + AddInputToWorkload(descriptor, info, inputTensorInfo, inputHandle.get()); + AddOutputToWorkload(descriptor, info, outputTensorInfo, outputHandle.get()); + + std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateRsqrt(descriptor, info); + + inputHandle->Allocate(); + outputHandle->Allocate(); + + CopyDataToITensorHandle(inputHandle.get(), &inputTensor[0][0]); + + workload->PostAllocationConfigure(); + workload->Execute(); + + CopyDataFromITensorHandle(&result.output[0][0], outputHandle.get()); + + return result; +} + +} // anonymous namespace + +template<armnn::DataType ArmnnType, typename T> +LayerTestResult<T, 2> Rsqrt2dTest( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) +{ + const armnn::TensorShape inputShape{ 2, 2 }; + const armnn::TensorShape outputShape{ 2, 2 }; + + armnn::TensorInfo inputTensorInfo(inputShape, ArmnnType); + inputTensorInfo.SetQuantizationScale(0.1f); + inputTensorInfo.SetQuantizationOffset(0); + + armnn::TensorInfo outputTensorInfo(outputShape, ArmnnType); + outputTensorInfo.SetQuantizationScale(0.1f); + outputTensorInfo.SetQuantizationOffset(0); + + std::vector<float> inputValues + { + 1.f, 4.f, + 16.f, 25.f + }; + + std::vector<float> expectedOutputValues + { + 1.f, 0.5f, + 0.25f, 0.2f + }; + + return Rsqrt2dTestCommon<ArmnnType>(workloadFactory, memoryManager, + inputTensorInfo, outputTensorInfo, + inputValues, expectedOutputValues); +} + +template<armnn::DataType ArmnnType, typename T> +LayerTestResult<T, 3> Rsqrt3dTest( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) +{ + const armnn::TensorShape inputShape{ 3, 1, 2 }; + const armnn::TensorShape outputShape{ 3, 1, 2 }; + + armnn::TensorInfo inputTensorInfo(inputShape, ArmnnType); + inputTensorInfo.SetQuantizationScale(0.1f); + inputTensorInfo.SetQuantizationOffset(0); + + armnn::TensorInfo outputTensorInfo(outputShape, ArmnnType); + outputTensorInfo.SetQuantizationScale(0.1f); + outputTensorInfo.SetQuantizationOffset(0); + + std::vector<float> inputValues + { + 1.f, 4.f, 16.f, + 25.f, 64.f, 100.f + }; + + std::vector<float> expectedOutputValues + { + 1.f, 0.5f, 0.25f, + 0.2f, 0.125f, 0.1f + }; + + auto inputTensor = MakeTensor<T, 3>(inputTensorInfo, ConvertToDataType<ArmnnType>(inputValues,inputTensorInfo)); + + LayerTestResult<T, 3> result(outputTensorInfo); + result.outputExpected = MakeTensor<T, 3>(outputTensorInfo, + ConvertToDataType<ArmnnType>(expectedOutputValues,outputTensorInfo)); + + std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo); + std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); + + armnn::RsqrtQueueDescriptor descriptor; + + armnn::WorkloadInfo info; + + AddInputToWorkload(descriptor, info, inputTensorInfo, inputHandle.get()); + AddOutputToWorkload(descriptor, info, outputTensorInfo, outputHandle.get()); + + std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateRsqrt(descriptor, info); + + inputHandle->Allocate(); + outputHandle->Allocate(); + + CopyDataToITensorHandle(inputHandle.get(), &inputTensor[0][0][0]); + + workload->PostAllocationConfigure(); + workload->Execute(); + + CopyDataFromITensorHandle(&result.output[0][0][0], outputHandle.get()); + + return result; +} + +template<armnn::DataType ArmnnType, typename T> +LayerTestResult<T, 2> RsqrtZeroTest( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) +{ + const armnn::TensorShape inputShape{ 1, 2 }; + const armnn::TensorShape outputShape{ 1, 2 }; + + armnn::TensorInfo inputTensorInfo(inputShape, ArmnnType); + inputTensorInfo.SetQuantizationScale(0.1f); + + armnn::TensorInfo outputTensorInfo(outputShape, ArmnnType); + outputTensorInfo.SetQuantizationScale(0.1f); + + std::vector<float> inputValues + { + 0.f, -0.f + }; + + std::vector<float> expectedOutputValues + { + INFINITY, -INFINITY + }; + + return Rsqrt2dTestCommon<ArmnnType>(workloadFactory, memoryManager, + inputTensorInfo, outputTensorInfo, + inputValues, expectedOutputValues); +} + +template<armnn::DataType ArmnnType, typename T> +LayerTestResult<T, 2> RsqrtNegativeTest( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) +{ + const armnn::TensorShape inputShape{ 1, 2 }; + const armnn::TensorShape outputShape{ 1, 2 }; + + armnn::TensorInfo inputTensorInfo(inputShape, ArmnnType); + inputTensorInfo.SetQuantizationScale(0.1f); + inputTensorInfo.SetQuantizationOffset(0); + + armnn::TensorInfo outputTensorInfo(outputShape, ArmnnType); + outputTensorInfo.SetQuantizationScale(0.1f); + outputTensorInfo.SetQuantizationOffset(0); + + std::vector<float> inputValues + { + -25.f, -16.f + }; + + std::vector<float> expectedOutputValues + { + -NAN, -NAN + }; + + return Rsqrt2dTestCommon<ArmnnType>(workloadFactory, memoryManager, + inputTensorInfo, outputTensorInfo, + inputValues, expectedOutputValues); +} + +// +// Explicit template specializations +// + +template LayerTestResult<armnn::ResolveType<armnn::DataType::Float32>, 2> +Rsqrt2dTest<armnn::DataType::Float32>( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager); + +template LayerTestResult<armnn::ResolveType<armnn::DataType::QuantisedAsymm8>, 2> +Rsqrt2dTest<armnn::DataType::QuantisedAsymm8>( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager); + +template LayerTestResult<armnn::ResolveType<armnn::DataType::QuantisedSymm16>, 2> +Rsqrt2dTest<armnn::DataType::QuantisedSymm16>( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager); + +template LayerTestResult<armnn::ResolveType<armnn::DataType::Float32>, 3> +Rsqrt3dTest<armnn::DataType::Float32>( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager); + +template LayerTestResult<armnn::ResolveType<armnn::DataType::QuantisedAsymm8>, 3> +Rsqrt3dTest<armnn::DataType::QuantisedAsymm8>( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager); + +template LayerTestResult<armnn::ResolveType<armnn::DataType::QuantisedSymm16>, 3> +Rsqrt3dTest<armnn::DataType::QuantisedSymm16>( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager); + +template LayerTestResult<armnn::ResolveType<armnn::DataType::Float32>, 2> +RsqrtZeroTest<armnn::DataType::Float32>( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager); + +template LayerTestResult<armnn::ResolveType<armnn::DataType::Float32>, 2> +RsqrtNegativeTest<armnn::DataType::Float32>( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager); 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