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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/FullyConnectedTestImpl.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/FullyConnectedTestImpl.hpp')
-rw-r--r-- | src/backends/backendsCommon/test/FullyConnectedTestImpl.hpp | 190 |
1 files changed, 0 insertions, 190 deletions
diff --git a/src/backends/backendsCommon/test/FullyConnectedTestImpl.hpp b/src/backends/backendsCommon/test/FullyConnectedTestImpl.hpp deleted file mode 100644 index 402a3e6d51..0000000000 --- a/src/backends/backendsCommon/test/FullyConnectedTestImpl.hpp +++ /dev/null @@ -1,190 +0,0 @@ -// -// Copyright © 2017 Arm Ltd. All rights reserved. -// SPDX-License-Identifier: MIT -// - -#include <ResolveType.hpp> -#include "WorkloadTestUtils.hpp" -#include <backendsCommon/IBackendInternal.hpp> - -LayerTestResult<float, 2> FullyConnectedFloat32Test( - armnn::IWorkloadFactory& workloadFactory, - const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, - bool biasEnabled, - bool transposeWeights) -{ - unsigned int inputWidth = 1; - unsigned int inputHeight = 1; - unsigned int inputChannels = 5; - unsigned int inputNum = 2; - - unsigned int outputChannels = 3; - unsigned int outputNum = 2; - - // Define the tensor descriptors. - armnn::TensorInfo inputTensorInfo; - armnn::TensorInfo outputTensorInfo; - armnn::TensorInfo weightsDesc; - armnn::TensorInfo biasesDesc; - - unsigned int inputShape[] = { inputNum, inputChannels, inputHeight, inputWidth }; - unsigned int outputShape[] = { outputNum, outputChannels }; - unsigned int weightsShape[] = { inputChannels, outputChannels }; - if (transposeWeights) - { - std::swap(weightsShape[0], weightsShape[1]); - } - unsigned int biasShape[] = { outputChannels }; - - inputTensorInfo = armnn::TensorInfo(4, inputShape, armnn::DataType::Float32); - outputTensorInfo = armnn::TensorInfo(2, outputShape, armnn::DataType::Float32); - weightsDesc = armnn::TensorInfo(2, weightsShape, armnn::DataType::Float32); - biasesDesc = armnn::TensorInfo(1, biasShape, armnn::DataType::Float32); - - LayerTestResult<float, 2> result(outputTensorInfo); - - boost::multi_array<float, 4> input = MakeTensor<float, 4>(inputTensorInfo, std::vector<float>( - { - 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, - - 5.0f, 4.0f, 3.0f, 2.0f, 1.0f - }) - ); - - boost::multi_array<float, 2> weights = MakeTensor<float, 2>(weightsDesc, std::vector<float>( - { - .5f, 2.f, .5f, - .5f, 2.f, 1.f, - .5f, 2.f, 2.f, - .5f, 2.f, 3.f, - .5f, 2.f, 4.f - })); - - if (transposeWeights) - { - weights = MakeTensor<float, 2>(weightsDesc, std::vector<float>( - { - .5f, .5f, .5f, .5f, .5f, - 2.f, 2.f, 2.f, 2.f, 2.f, - .5f, 1.f, 2.f, 3.f, 4.f - })); - } - - - std::vector<float> biasValues({0.f, 0.f, 0.f}); - if (biasEnabled) - { - biasValues = std::vector<float>({10.f, 20.f, 30.f}); - } - boost::multi_array<float, 1> bias = MakeTensor<float, 1>(biasesDesc, biasValues); - - result = SimpleFullyConnectedTestImpl<float>( - workloadFactory, - memoryManager, - inputTensorInfo, outputTensorInfo, - weightsDesc, biasesDesc, - weights, bias, input, - biasEnabled, transposeWeights - ); - - result.outputExpected = MakeTensor<float, 2>(outputTensorInfo, std::vector<float>( - { - 0.5f + 1.0f + 1.5f + 2.0f + 2.5f + biasValues[0], - 2.0f + 4.0f + 6.0f + 8.0f + 10.f + biasValues[1], - 0.5f + 2.0f + 6.0f + 12.f + 20.f + biasValues[2], - - 2.5f + 2.0f + 1.5f + 1.0f + 0.5f + biasValues[0], - 10.0f + 8.0f + 6.0f + 4.0f + 2.f + biasValues[1], - 2.5f + 4.0f + 6.0f + 6.f + 4.f + biasValues[2] - }) - ); - - return result; -} - -// -// ArmNN variant of the AndroidNN fully_connected_float_large test. -// -// Tests the fully connected layer with large values, optionally transposing weights. -// Note this is templated for consistency, but the nature of this tests makes it unlikely to be useful in Uint8 mode. -// -template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> -LayerTestResult<T, 2> FullyConnectedLargeTestCommon( - armnn::IWorkloadFactory& workloadFactory, - const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, - bool transposeWeights, - float qScale = 0.0f, - int32_t qOffset = 0) -{ - unsigned int inputWidth = 1; - unsigned int inputHeight = 1; - unsigned int inputChannels = 5; - unsigned int inputNum = 1; - - unsigned int outputChannels = 1; - unsigned int outputNum = 1; - - // Define the tensor descriptors. - armnn::TensorInfo inputTensorInfo; - armnn::TensorInfo outputTensorInfo; - armnn::TensorInfo weightsDesc; - armnn::TensorInfo biasesDesc; - - unsigned int inputShape[] = { inputNum, inputChannels, inputHeight, inputWidth }; - unsigned int outputShape[] = { outputNum, outputChannels }; - unsigned int weightsShape[] = { inputChannels, outputChannels }; - if (transposeWeights) - { - std::swap(weightsShape[0], weightsShape[1]); - } - - unsigned int biasShape[] = { outputChannels }; - - inputTensorInfo = armnn::TensorInfo(4, inputShape, ArmnnType); - outputTensorInfo = armnn::TensorInfo(2, outputShape, ArmnnType); - weightsDesc = armnn::TensorInfo(2, weightsShape, ArmnnType); - biasesDesc = armnn::TensorInfo(1, biasShape, ArmnnType); - - // 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); - } - - LayerTestResult<T, 2> result(outputTensorInfo); - - boost::multi_array<T, 4> input = MakeTensor<T, 4>(inputTensorInfo, - QuantizedVector<T>(qScale, qOffset, { - 1.0f, 10.0f, 100.0f, 1000.0f, 10000.0f, - }) - ); - - boost::multi_array<T, 2> weights = MakeTensor<T, 2>(weightsDesc, - QuantizedVector<T>(qScale, qOffset, { - 2.0f, 3.0f, 4.0f, 5.0f, 6.0f - }) - ); - - std::vector<T> biasValues({900000.f}); - boost::multi_array<T, 1> bias = MakeTensor<T, 1>(biasesDesc, biasValues); - - result = SimpleFullyConnectedTestImpl<T>( - workloadFactory, - memoryManager, - inputTensorInfo, outputTensorInfo, - weightsDesc, biasesDesc, - weights, bias, input, - true, transposeWeights - ); - - result.outputExpected = MakeTensor<T, 2>(outputTensorInfo, - QuantizedVector<T>(qScale, qOffset, { - 965432.0f, - }) - ); - - return result; -} |