diff options
author | Aron Virginas-Tar <Aron.Virginas-Tar@arm.com> | 2019-08-28 18:08:46 +0100 |
---|---|---|
committer | mike.kelly <mike.kelly@arm.com> | 2019-08-30 10:58:54 +0000 |
commit | 00d306e4db5153a4f4d280de4d4cf3e03788fefb (patch) | |
tree | 329c15f71c662e199a24dc0812bf95cb389ddbd8 /src/backends/backendsCommon/test/layerTests/PreluTestImpl.hpp | |
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/PreluTestImpl.hpp')
-rw-r--r-- | src/backends/backendsCommon/test/layerTests/PreluTestImpl.hpp | 97 |
1 files changed, 97 insertions, 0 deletions
diff --git a/src/backends/backendsCommon/test/layerTests/PreluTestImpl.hpp b/src/backends/backendsCommon/test/layerTests/PreluTestImpl.hpp new file mode 100644 index 0000000000..18a5bd035c --- /dev/null +++ b/src/backends/backendsCommon/test/layerTests/PreluTestImpl.hpp @@ -0,0 +1,97 @@ +// +// Copyright © 2017 Arm Ltd. All rights reserved. +// SPDX-License-Identifier: MIT +// + +#pragma once + +#include "LayerTestResult.hpp" + +#include <ResolveType.hpp> + +#include <armnn/ArmNN.hpp> + +#include <backendsCommon/IBackendInternal.hpp> +#include <backendsCommon/WorkloadFactory.hpp> + +#include <backendsCommon/test/TensorCopyUtils.hpp> +#include <backendsCommon/test/WorkloadTestUtils.hpp> + +#include <test/TensorHelpers.hpp> + +template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> +LayerTestResult<T, 4> PreluTest( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) +{ + armnn::TensorInfo inputTensorInfo ({ 1, 2, 2, 3 }, ArmnnType); + armnn::TensorInfo alphaTensorInfo ({ 1, 1, 1, 3 }, ArmnnType); + armnn::TensorInfo outputTensorInfo({ 1, 2, 2, 3 }, ArmnnType); + + if (armnn::IsQuantizedType<T>()) + { + inputTensorInfo.SetQuantizationScale(0.25f); + inputTensorInfo.SetQuantizationOffset(128); + alphaTensorInfo.SetQuantizationScale(0.25f); + alphaTensorInfo.SetQuantizationOffset(50); + outputTensorInfo.SetQuantizationScale(0.5f); + outputTensorInfo.SetQuantizationOffset(120); + } + + std::vector<float> inputData + { + // Expected quantized values: + // 128, 128, 128, 132, 132, 132, 124, 124, 124, 120, 120, 120 + 0.0f, 0.0f, 0.0f, 1.0f, 1.0f, 1.0f, -1.0f, -1.0f, -1.0f, -2.0f, -2.0f, -2.0f + }; + std::vector<float> alphaData + { + // Expected quantized values: + // 50, 54, 58 + 0.0f, 1.0f, 2.0f + }; + std::vector<float> outputExpectedData = + { + // Expected quantized values: + // 20, 120, 120, 122, 122, 122, 120, 118, 116, 120, 116, 112 + 0.0f, 0.0f, 0.0f, 1.0f, 1.0f, 1.0f, 0.0f, -1.0f, -2.0f, 0.0f, -2.0f, -4.0f + }; + + auto input = MakeTensor<T, 4>(inputTensorInfo, QuantizedVector<T>(inputTensorInfo.GetQuantizationScale(), + inputTensorInfo.GetQuantizationOffset(), + inputData)); + auto alpha = MakeTensor<T, 4>(alphaTensorInfo, QuantizedVector<T>(alphaTensorInfo.GetQuantizationScale(), + alphaTensorInfo.GetQuantizationOffset(), + alphaData)); + + LayerTestResult<T, 4> result(outputTensorInfo); + result.outputExpected = MakeTensor<T, 4>(outputTensorInfo, + QuantizedVector<T>(outputTensorInfo.GetQuantizationScale(), + outputTensorInfo.GetQuantizationOffset(), + outputExpectedData)); + + std::unique_ptr <armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo); + std::unique_ptr <armnn::ITensorHandle> alphaHandle = workloadFactory.CreateTensorHandle(alphaTensorInfo); + std::unique_ptr <armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); + + armnn::PreluQueueDescriptor descriptor; + armnn::WorkloadInfo info; + AddInputToWorkload (descriptor, info, inputTensorInfo, inputHandle.get()); + AddInputToWorkload (descriptor, info, alphaTensorInfo, alphaHandle.get()); + AddOutputToWorkload(descriptor, info, outputTensorInfo, outputHandle.get()); + + std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreatePrelu(descriptor, info); + + inputHandle->Allocate(); + alphaHandle->Allocate(); + outputHandle->Allocate(); + + CopyDataToITensorHandle(inputHandle.get(), &input[0][0][0][0]); + CopyDataToITensorHandle(alphaHandle.get(), &alpha[0][0][0][0]); + + workload->Execute(); + + CopyDataFromITensorHandle(&result.output[0][0][0][0], outputHandle.get()); + + return result; +} |