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Diffstat (limited to 'src/backends/backendsCommon/test/GatherNdEndToEndTestImpl.hpp')
| -rw-r--r-- | src/backends/backendsCommon/test/GatherNdEndToEndTestImpl.hpp | 161 |
1 files changed, 161 insertions, 0 deletions
diff --git a/src/backends/backendsCommon/test/GatherNdEndToEndTestImpl.hpp b/src/backends/backendsCommon/test/GatherNdEndToEndTestImpl.hpp new file mode 100644 index 0000000000..0eea91190e --- /dev/null +++ b/src/backends/backendsCommon/test/GatherNdEndToEndTestImpl.hpp @@ -0,0 +1,161 @@ +// +// Copyright © 2022 Arm Ltd and Contributors. All rights reserved. +// SPDX-License-Identifier: MIT +// + +#pragma once + +#include <CommonTestUtils.hpp> + +#include <armnn/INetwork.hpp> +#include <ResolveType.hpp> + +#include <doctest/doctest.h> + +namespace{ + +armnn::INetworkPtr CreateGatherNdNetwork(const armnn::TensorInfo& paramsInfo, + const armnn::TensorInfo& indicesInfo, + const armnn::TensorInfo& outputInfo, + const std::vector<int32_t>& indicesData) +{ + armnn::INetworkPtr net(armnn::INetwork::Create()); + + armnn::IConnectableLayer* paramsLayer = net->AddInputLayer(0); + armnn::IConnectableLayer* indicesLayer = net->AddConstantLayer(armnn::ConstTensor(indicesInfo, indicesData)); + armnn::IConnectableLayer* gatherNdLayer = net->AddGatherNdLayer("gatherNd"); + armnn::IConnectableLayer* outputLayer = net->AddOutputLayer(0, "output"); + Connect(paramsLayer, gatherNdLayer, paramsInfo, 0, 0); + Connect(indicesLayer, gatherNdLayer, indicesInfo, 0, 1); + Connect(gatherNdLayer, outputLayer, outputInfo, 0, 0); + + return net; +} + +template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> +void GatherNdEndToEnd(const std::vector<BackendId>& backends) +{ + armnn::TensorInfo paramsInfo({ 2, 3, 8, 4 }, ArmnnType); + armnn::TensorInfo indicesInfo({ 2, 2 }, armnn::DataType::Signed32); + armnn::TensorInfo outputInfo({ 2, 8, 4 }, ArmnnType); + + paramsInfo.SetQuantizationScale(1.0f); + paramsInfo.SetQuantizationOffset(0); + paramsInfo.SetConstant(true); + indicesInfo.SetConstant(true); + outputInfo.SetQuantizationScale(1.0f); + outputInfo.SetQuantizationOffset(0); + + // Creates structures for input & output. + std::vector<T> paramsData{ + 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, + 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, + + 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, + 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, + + 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, + 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, + + 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, + 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, + + 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, + 144, 145, 146, 147, 148, 149, 150, 151, 152, 153, 154, 155, 156, 157, 158, 159, + + 160, 161, 162, 163, 164, 165, 166, 167, 168, 169, 170, 171, 172, 173, 174, 175, + 176, 177, 178, 179, 180, 181, 182, 183, 184, 185, 186, 187, 188, 189, 190, 191 + }; + + std::vector<int32_t> indicesData{ + { 1, 2, 1, 1}, + }; + + std::vector<T> expectedOutput{ + 160, 161, 162, 163, 164, 165, 166, 167, 168, 169, 170, 171, 172, 173, 174, 175, + 176, 177, 178, 179, 180, 181, 182, 183, 184, 185, 186, 187, 188, 189, 190, 191, + + 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, + 144, 145, 146, 147, 148, 149, 150, 151, 152, 153, 154, 155, 156, 157, 158, 159 + }; + + // Builds up the structure of the network + armnn::INetworkPtr net = CreateGatherNdNetwork(paramsInfo, indicesInfo, outputInfo, indicesData); + + CHECK(net); + + std::map<int, std::vector<T>> inputTensorData = {{ 0, paramsData }}; + std::map<int, std::vector<T>> expectedOutputData = {{ 0, expectedOutput }}; + + EndToEndLayerTestImpl<ArmnnType, ArmnnType>(move(net), inputTensorData, expectedOutputData, backends); +} + +template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> +void GatherNdMultiDimEndToEnd(const std::vector<BackendId>& backends) +{ + armnn::TensorInfo paramsInfo({ 5, 5, 2 }, ArmnnType); + armnn::TensorInfo indicesInfo({ 2, 2, 3, 2 }, armnn::DataType::Signed32); + armnn::TensorInfo outputInfo({ 2, 2, 3, 2 }, ArmnnType); + + paramsInfo.SetQuantizationScale(1.0f); + paramsInfo.SetQuantizationOffset(0); + paramsInfo.SetConstant(true); + indicesInfo.SetConstant(true); + outputInfo.SetQuantizationScale(1.0f); + outputInfo.SetQuantizationOffset(0); + + // Creates structures for input & output. + std::vector<T> paramsData{ + 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, + 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, + 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, + 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, + 40, 41, 42, 43, 44, 45, 46, 47, 48, 49 + }; + + std::vector<int32_t> indicesData{ + 0, 0, + 3, 3, + 4, 4, + + 0, 0, + 1, 1, + 2, 2, + + 4, 4, + 3, 3, + 0, 0, + + 2, 2, + 1, 1, + 0, 0 + }; + + std::vector<T> expectedOutput{ + 0, 1, + 36, 37, + 48, 49, + + 0, 1, + 12, 13, + 24, 25, + + 48, 49, + 36, 37, + 0, 1, + + 24, 25, + 12, 13, + 0, 1 + }; + + // Builds up the structure of the network + armnn::INetworkPtr net = CreateGatherNdNetwork(paramsInfo, indicesInfo, outputInfo, indicesData); + + std::map<int, std::vector<T>> inputTensorData = {{ 0, paramsData }}; + std::map<int, std::vector<T>> expectedOutputData = {{ 0, expectedOutput }}; + + EndToEndLayerTestImpl<ArmnnType, ArmnnType>(move(net), inputTensorData, expectedOutputData, backends); +} + +} // anonymous namespace |