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author | Nattapat Chaimanowong <nattapat.chaimanowong@arm.com> | 2019-04-01 17:04:53 +0100 |
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committer | Ruomei Yan <ruomei.yan@arm.com> | 2019-04-02 10:00:17 +0000 |
commit | a0beb3b8aeb8bbea906609e0f50a250c33cde10b (patch) | |
tree | 543352916c2424bef670619dcdd0f7f78e754678 /src/backends/backendsCommon/test/QuantizeTestImpl.hpp | |
parent | 2ab0bfa335896cc5f514732e181b0bcceb44b141 (diff) | |
download | armnn-a0beb3b8aeb8bbea906609e0f50a250c33cde10b.tar.gz |
IVGCVSW-2872 Unit tests for Quantize layer and reference workload
Change-Id: I291c08cb6e359453978b398255cf8ff051ed2686
Signed-off-by: Nattapat Chaimanowong <nattapat.chaimanowong@arm.com>
Diffstat (limited to 'src/backends/backendsCommon/test/QuantizeTestImpl.hpp')
-rw-r--r-- | src/backends/backendsCommon/test/QuantizeTestImpl.hpp | 126 |
1 files changed, 126 insertions, 0 deletions
diff --git a/src/backends/backendsCommon/test/QuantizeTestImpl.hpp b/src/backends/backendsCommon/test/QuantizeTestImpl.hpp new file mode 100644 index 0000000000..fee68f073e --- /dev/null +++ b/src/backends/backendsCommon/test/QuantizeTestImpl.hpp @@ -0,0 +1,126 @@ +// +// Copyright © 2017 Arm Ltd. All rights reserved. +// SPDX-License-Identifier: MIT +// +#pragma once + +#include "WorkloadTestUtils.hpp" + +#include <test/TensorHelpers.hpp> + +#include <armnn/ArmNN.hpp> +#include <armnn/Tensor.hpp> +#include <armnn/TypesUtils.hpp> + +#include <backendsCommon/CpuTensorHandle.hpp> +#include <backendsCommon/IBackendInternal.hpp> +#include <backendsCommon/WorkloadFactory.hpp> + + +namespace +{ + +template<typename T, std::size_t Dim> +LayerTestResult<T, Dim> QuantizeTestImpl( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::TensorInfo& inputTensorInfo, + const armnn::TensorInfo& outputTensorInfo, + const std::vector<float>& inputData, + const std::vector<T>& expectedOutputData, + armnn::QuantizeQueueDescriptor descriptor) +{ + boost::multi_array<float, Dim> input = MakeTensor<float, Dim>(inputTensorInfo, inputData); + + LayerTestResult<T, Dim> ret(outputTensorInfo); + ret.outputExpected = MakeTensor<T, Dim>(outputTensorInfo, expectedOutputData); + + std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo); + std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); + + armnn::WorkloadInfo info; + AddInputToWorkload(descriptor, info, inputTensorInfo, inputHandle.get()); + AddOutputToWorkload(descriptor, info, outputTensorInfo, outputHandle.get()); + + std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateQuantize(descriptor, info); + + inputHandle->Allocate(); + outputHandle->Allocate(); + + CopyDataToITensorHandle(inputHandle.get(), input.data()); + + ExecuteWorkload(*workload, memoryManager); + + CopyDataFromITensorHandle(ret.output.data(), outputHandle.get()); + + return ret; +} + +template <armnn::DataType ArmnnOutputType, typename T = armnn::ResolveType<ArmnnOutputType>> +LayerTestResult<T, 4> QuantizeSimpleTest( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) +{ + armnn::QuantizeQueueDescriptor desc; + + const armnn::TensorInfo inputTensorInfo({1, 2, 2, 3}, armnn::DataType::Float32); + const armnn::TensorInfo outputTensorInfo({1, 2, 2, 3}, ArmnnOutputType, 0.5f, 1); + + std::vector<float> inputData = std::vector<float>( + { + 1.0f, 2.0f, 3.0f, + 4.0f, 5.0f, 6.0f, + 7.0f, 8.0f, 9.0f, + 10.0f, 11.0f, 12.0f, + }); + + std::vector<T> expectedOutputData = std::vector<T>( + { + 3, 5, 7, + 9, 11, 13, + 15, 17, 19, + 21, 23, 25, + }); + + return QuantizeTestImpl<T, 4>(workloadFactory, + memoryManager, + inputTensorInfo, + outputTensorInfo, + inputData, + expectedOutputData, + desc); +} + +template <armnn::DataType ArmnnOutputType, typename T = armnn::ResolveType<ArmnnOutputType>> +LayerTestResult<T, 4> QuantizeClampTest( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) +{ + armnn::QuantizeQueueDescriptor desc; + + const armnn::TensorInfo inputTensorInfo({1, 1, 2, 1}, armnn::DataType::Float32); + const armnn::TensorInfo outputTensorInfo({1, 1, 2, 1}, ArmnnOutputType, 0.0001f, 0); + + const T max = std::numeric_limits<T>::max(); + const T min = std::numeric_limits<T>::lowest(); + + std::vector<float> inputData = std::vector<float>( + { + -100.0f, 100.0f + }); + + std::vector<T> expectedOutputData = std::vector<T>( + { + min, max + }); + + return QuantizeTestImpl<T, 4>(workloadFactory, + memoryManager, + inputTensorInfo, + outputTensorInfo, + inputData, + expectedOutputData, + desc); +} + +} // anonymous namespace |