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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/ConstantTestImpl.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/ConstantTestImpl.cpp')
-rw-r--r-- | src/backends/backendsCommon/test/layerTests/ConstantTestImpl.cpp | 154 |
1 files changed, 154 insertions, 0 deletions
diff --git a/src/backends/backendsCommon/test/layerTests/ConstantTestImpl.cpp b/src/backends/backendsCommon/test/layerTests/ConstantTestImpl.cpp new file mode 100644 index 0000000000..c3cacd5810 --- /dev/null +++ b/src/backends/backendsCommon/test/layerTests/ConstantTestImpl.cpp @@ -0,0 +1,154 @@ +// +// Copyright © 2017 Arm Ltd. All rights reserved. +// SPDX-License-Identifier: MIT +// + +#include "ConstantTestImpl.hpp" + +#include <Permute.hpp> +#include <ResolveType.hpp> + +#include <armnn/ArmNN.hpp> + +#include <backendsCommon/CpuTensorHandle.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, 4> ConstantTestImpl( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + float qScale, + int32_t qOffset) +{ + constexpr unsigned int inputWidth = 3; + constexpr unsigned int inputHeight = 4; + constexpr unsigned int inputChannels = 3; + constexpr unsigned int inputBatchSize = 2; + + constexpr unsigned int outputWidth = inputWidth; + constexpr unsigned int outputHeight = inputHeight; + constexpr unsigned int outputChannels = inputChannels; + constexpr unsigned int outputBatchSize = inputBatchSize; + + armnn::TensorInfo inputTensorInfo({ inputBatchSize, inputChannels, inputHeight, inputWidth }, + ArmnnType, qScale, qOffset); + + armnn::TensorInfo outputTensorInfo({ outputBatchSize, outputChannels, outputHeight, outputWidth }, + ArmnnType, qScale, qOffset); + + // Set quantization parameters if the requested type is a quantized type. + if(armnn::IsQuantizedType<T>()) + { + inputTensorInfo.SetQuantizationScale(qScale); + inputTensorInfo.SetQuantizationOffset(qOffset); + outputTensorInfo.SetQuantizationScale(qScale); + outputTensorInfo.SetQuantizationOffset(qOffset); + } + + auto input = MakeTensor<T, 4>(inputTensorInfo, std::vector<T>( + QuantizedVector<T>(qScale, qOffset, { + // Batch 0, Channel 0 + 235.0f, 46.0f, 178.0f, + 100.0f, 123.0f, 19.0f, + 172.0f, 74.0f, 250.0f, + 6.0f, 195.0f, 80.0f, + + // Batch 0, Channel 1 + 113.0f, 95.0f, 202.0f, + 77.0f, 114.0f, 71.0f, + 122.0f, 246.0f, 166.0f, + 82.0f, 28.0f, 37.0f, + + // Batch 0, Channel 2 + 56.0f, 170.0f, 162.0f, + 194.0f, 89.0f, 254.0f, + 12.0f, 209.0f, 200.0f, + 1.0f, 64.0f, 54.0f, + + // Batch 1, Channel 0 + 67.0f, 90.0f, 49.0f, + 7.0f, 163.0f, 18.0f, + 25.0f, 117.0f, 103.0f, + 247.0f, 59.0f, 189.0f, + + // Batch 1, Channel 1 + 239.0f, 104.0f, 199.0f, + 17.0f, 124.0f, 153.0f, + 222.0f, 217.0f, 75.0f, + 32.0f, 126.0f, 21.0f, + + // Batch 1, Channel 2 + 97.0f, 145.0f, 215.0f, + 115.0f, 116.0f, 238.0f, + 226.0f, 16.0f, 132.0f, + 92.0f, 125.0f, 88.0f, + }))); + + LayerTestResult<T, 4> result(outputTensorInfo); + result.outputExpected = input; + + std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); + + armnn::ScopedCpuTensorHandle constantTensor(inputTensorInfo); + AllocateAndCopyDataToITensorHandle(&constantTensor, &input[0][0][0][0]); + + armnn::ConstantQueueDescriptor descriptor; + descriptor.m_LayerOutput = &constantTensor; + + armnn::WorkloadInfo info; + AddOutputToWorkload(descriptor, info, outputTensorInfo, outputHandle.get()); + + std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateConstant(descriptor, info); + + outputHandle->Allocate(); + + workload->PostAllocationConfigure(); + workload->Execute(); + + CopyDataFromITensorHandle(&result.output[0][0][0][0], outputHandle.get()); + return result; +} + +} // anonymous namespace + +LayerTestResult<float, 4> ConstantTest( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) +{ + return ConstantTestImpl<armnn::DataType::Float32>(workloadFactory, memoryManager, 0.0f, 0); +} + +LayerTestResult<int16_t, 4> ConstantInt16SimpleQuantizationScaleNoOffsetTest( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) +{ + return ConstantTestImpl<armnn::DataType::QuantisedSymm16>(workloadFactory, memoryManager, 1.0f, 0); +} + +LayerTestResult<uint8_t, 4> ConstantUint8SimpleQuantizationScaleNoOffsetTest( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) +{ + return ConstantTestImpl<armnn::DataType::QuantisedAsymm8>(workloadFactory, memoryManager, 1.0f, 0); +} + +LayerTestResult<uint8_t, 4> ConstantUint8CustomQuantizationScaleAndOffsetTest( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) +{ + return ConstantTestImpl<armnn::DataType::QuantisedAsymm8>(workloadFactory, memoryManager, 2e-6f, 1); +} + +LayerTestResult<int16_t, 4> ConstantInt16CustomQuantizationScaleAndOffsetTest( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) +{ + return ConstantTestImpl<armnn::DataType::QuantisedSymm16>(workloadFactory, memoryManager, 2e-6f, 1); +} |