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Diffstat (limited to 'src/backends/backendsCommon/test/RankEndToEndTestImpl.hpp')
| -rw-r--r-- | src/backends/backendsCommon/test/RankEndToEndTestImpl.hpp | 64 |
1 files changed, 64 insertions, 0 deletions
diff --git a/src/backends/backendsCommon/test/RankEndToEndTestImpl.hpp b/src/backends/backendsCommon/test/RankEndToEndTestImpl.hpp new file mode 100644 index 0000000000..a67bd46982 --- /dev/null +++ b/src/backends/backendsCommon/test/RankEndToEndTestImpl.hpp @@ -0,0 +1,64 @@ +// +// Copyright © 2020 Arm Ltd and Contributors. All rights reserved. +// SPDX-License-Identifier: MIT +// + +#pragma once + +#include "CommonTestUtils.hpp" + +#include <armnn/INetwork.hpp> +#include <armnn/TypesUtils.hpp> + +#include <ResolveType.hpp> + +namespace +{ + +armnn::INetworkPtr CreateRankNetwork(const armnn::TensorInfo& inputTensorInfo, + const armnn::TensorInfo& outputTensorInfo) +{ + armnn::INetworkPtr network(armnn::INetwork::Create()); + + armnn::IConnectableLayer* inputLayer = network->AddInputLayer(0, "Input"); + armnn::IConnectableLayer* rankLayer = network->AddRankLayer("Rank"); + armnn::IConnectableLayer* outputLayer = network->AddOutputLayer(0, "Output"); + + Connect(inputLayer, rankLayer, inputTensorInfo, 0, 0); + Connect(rankLayer, outputLayer, outputTensorInfo, 0, 0); + + return network; +} + +template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> +void RankEndToEnd(const std::vector<armnn::BackendId>& backends) +{ + using namespace armnn; + + std::vector<float> floatInputData{ + 1, 2, 3, 4, 5, + 11, 12, 13, 14, 15, + 21, 22, 23, 24, 25 + }; + std::vector<T> inputData = armnnUtils::QuantizedVector<T>(floatInputData); + + std::vector<int32_t> expectedOutputData{ 4 }; + + TensorInfo inputInfo ({ 1, 1, 5, 3 }, ArmnnType); + TensorShape outputShape (Dimensionality::Scalar); + TensorInfo outputInfo(outputShape, DataType::Signed32); + + armnn::INetworkPtr network = CreateRankNetwork(inputInfo, outputInfo); + + BOOST_TEST_CHECKPOINT("create a network"); + + std::map<int, std::vector<T>> inputTensorData = {{ 0, inputData }}; + std::map<int, std::vector<int32_t>> expectedOutputTensorData = {{ 0, expectedOutputData }}; + + EndToEndLayerTestImpl<ArmnnType, DataType::Signed32>(move(network), + inputTensorData, + expectedOutputTensorData, + backends); +} + +} // anonymous namespace
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