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Diffstat (limited to 'src/backends/backendsCommon/test/ScatterNdEndToEndTestImpl.hpp')
| -rw-r--r-- | src/backends/backendsCommon/test/ScatterNdEndToEndTestImpl.hpp | 160 |
1 files changed, 160 insertions, 0 deletions
diff --git a/src/backends/backendsCommon/test/ScatterNdEndToEndTestImpl.hpp b/src/backends/backendsCommon/test/ScatterNdEndToEndTestImpl.hpp new file mode 100644 index 0000000000..3b796a0c21 --- /dev/null +++ b/src/backends/backendsCommon/test/ScatterNdEndToEndTestImpl.hpp @@ -0,0 +1,160 @@ +// +// Copyright © 2024 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> + +using namespace armnn; + +namespace +{ + +template<DataType ArmnnType, typename T = ResolveType<ArmnnType>> +INetworkPtr CreateScatterNdNetwork(const TensorInfo& shapeInfo, + const TensorInfo& indicesInfo, + const TensorInfo& updatesInfo, + const TensorInfo& outputInfo, + const std::vector<int32_t>& indicesData, + const std::vector<T>& updatesData, + const ScatterNdDescriptor& descriptor) +{ + INetworkPtr net(INetwork::Create()); + + IConnectableLayer* shapeLayer = net->AddInputLayer(0); + IConnectableLayer* indicesLayer = net->AddConstantLayer(ConstTensor(indicesInfo, indicesData)); + IConnectableLayer* updatesLayer = net->AddConstantLayer(ConstTensor(updatesInfo, updatesData)); + IConnectableLayer* scatterNdLayer = net->AddScatterNdLayer(descriptor, "scatterNd"); + IConnectableLayer* outputLayer = net->AddOutputLayer(0, "output"); + Connect(shapeLayer, scatterNdLayer, shapeInfo, 0, 0); + Connect(indicesLayer, scatterNdLayer, indicesInfo, 0, 1); + Connect(updatesLayer, scatterNdLayer, updatesInfo, 0, 2); + Connect(scatterNdLayer, outputLayer, outputInfo, 0, 0); + + return net; +} + +template<DataType ArmnnType, typename T = ResolveType<ArmnnType>> +void ScatterNd1DimUpdateWithInputEndToEnd(const std::vector<BackendId>& backends) +{ + float_t qScale = 1.f; + int32_t qOffset = 0; + + TensorInfo inputInfo({ 5 }, ArmnnType, qScale, qOffset, true); + TensorInfo indicesInfo({ 3, 1 }, DataType::Signed32, 1.0f, 0, true); + TensorInfo updatesInfo({ 3 }, ArmnnType, qScale, qOffset, true); + TensorInfo outputInfo({ 5 }, ArmnnType, qScale, qOffset, false); + + std::vector<T> inputData = armnnUtils::QuantizedVector<T>({ 0, 0, 0, 0, 0 }, qScale, qOffset); + std::vector<int32_t> indicesData{0, 1, 2}; + std::vector<T> updatesData = armnnUtils::QuantizedVector<T>({ 1, 2, 3 }, qScale, qOffset); + std::vector<T> expectedOutput = armnnUtils::QuantizedVector<T>({ 1, 2, 3, 0, 0 }, qScale, qOffset); + + armnn::ScatterNdDescriptor descriptor(armnn::ScatterNdFunction::Update, true); + + INetworkPtr net = CreateScatterNdNetwork<ArmnnType>(inputInfo, indicesInfo, updatesInfo, outputInfo, + indicesData, updatesData, descriptor); + + CHECK(net); + + std::map<int, std::vector<T>> inputTensorData = {{ 0, inputData }}; + std::map<int, std::vector<T>> expectedOutputData = {{ 0, expectedOutput }}; + + EndToEndLayerTestImpl<ArmnnType, ArmnnType>(std::move(net), inputTensorData, expectedOutputData, backends); +} + +template<DataType ArmnnType, typename T = ResolveType<ArmnnType>> +void ScatterNd1DimUpdateNoInputEndToEnd(const std::vector<BackendId>& backends) +{ + float_t qScale = 1.f; + int32_t qOffset = 0; + + TensorInfo shapeInfo({ 1 }, DataType::Signed32, 1.0f, 0, true); + TensorInfo indicesInfo({ 3, 1 }, DataType::Signed32, 1.0f, 0, true); + TensorInfo updatesInfo({ 3 }, ArmnnType, qScale, qOffset, true); + TensorInfo outputInfo({ 5 }, ArmnnType, qScale, qOffset, false); + + std::vector<int32_t> shapeData{ 5 }; + std::vector<int32_t> indicesData{ 0, 1, 2 }; + std::vector<T> updatesData = armnnUtils::QuantizedVector<T>({ 1, 2, 3 }, qScale, qOffset); + std::vector<T> expectedOutput = armnnUtils::QuantizedVector<T>({ 1, 2, 3, 0, 0 }, qScale, qOffset); + + armnn::ScatterNdDescriptor descriptor(armnn::ScatterNdFunction::Update, false); + + INetworkPtr net = CreateScatterNdNetwork<ArmnnType>(shapeInfo, indicesInfo, updatesInfo, outputInfo, + indicesData, updatesData, descriptor); + + CHECK(net); + + std::map<int, std::vector<int32_t>> inputTensorData = {{ 0, shapeData }}; + std::map<int, std::vector<T>> expectedOutputData = {{ 0, expectedOutput }}; + + EndToEndLayerTestImpl<DataType::Signed32, ArmnnType>(std::move(net), inputTensorData, expectedOutputData, backends); +} + +template<DataType ArmnnType, typename T = ResolveType<ArmnnType>> +void ScatterNd2DimUpdateWithInputEndToEnd(const std::vector<BackendId>& backends) +{ + float_t qScale = 1.f; + int32_t qOffset = 0; + + TensorInfo inputInfo({ 3, 3 }, ArmnnType, qScale, qOffset, true); + TensorInfo indicesInfo({ 3, 2 }, DataType::Signed32, 1.0f, 0, true); + TensorInfo updatesInfo({ 3 }, ArmnnType, qScale, qOffset, true); + TensorInfo outputInfo({ 3, 3 }, ArmnnType, qScale, qOffset, false); + + std::vector<T> inputData = armnnUtils::QuantizedVector<T>({ 1, 1, 1, 1, 1, 1, 1, 1, 1 }, qScale, qOffset); + std::vector<int32_t> indicesData{0, 0, 1, 1, 2, 2}; + std::vector<T> updatesData = armnnUtils::QuantizedVector<T>({ 1, 2, 3 }, qScale, qOffset); + std::vector<T> expectedOutput = armnnUtils::QuantizedVector<T>({ 1, 1, 1, 1, 2, 1, 1, 1, 3 }, qScale, qOffset); + + armnn::ScatterNdDescriptor descriptor(armnn::ScatterNdFunction::Update, true); + + INetworkPtr net = CreateScatterNdNetwork<ArmnnType>(inputInfo, indicesInfo, updatesInfo, outputInfo, + indicesData, updatesData, descriptor); + + CHECK(net); + + std::map<int, std::vector<T>> inputTensorData = {{ 0, inputData }}; + std::map<int, std::vector<T>> expectedOutputData = {{ 0, expectedOutput }}; + + EndToEndLayerTestImpl<ArmnnType, ArmnnType>(std::move(net), inputTensorData, expectedOutputData, backends); +} + +template<DataType ArmnnType, typename T = ResolveType<ArmnnType>> +void ScatterNd2DimUpdateNoInputEndToEnd(const std::vector<BackendId>& backends) +{ + float_t qScale = 1.f; + int32_t qOffset = 0; + + TensorInfo shapeInfo({ 2 }, DataType::Signed32, 1.0f, 0, true); + TensorInfo indicesInfo({ 3, 2 }, DataType::Signed32, 1.0f, 0, true); + TensorInfo updatesInfo({ 3 }, ArmnnType, qScale, qOffset, true); + TensorInfo outputInfo({ 3, 3 }, ArmnnType, qScale, qOffset, false); + + std::vector<int32_t> shapeData{ 3, 3 }; + std::vector<int32_t> indicesData{0, 0, 1, 1, 2, 2}; + std::vector<T> updatesData = armnnUtils::QuantizedVector<T>({ 1, 2, 3 }, qScale, qOffset); + std::vector<T> expectedOutput = armnnUtils::QuantizedVector<T>({ 1, 0, 0, 0, 2, 0, 0, 0, 3 }, qScale, qOffset); + + armnn::ScatterNdDescriptor descriptor(armnn::ScatterNdFunction::Update, false); + + INetworkPtr net = CreateScatterNdNetwork<ArmnnType>(shapeInfo, indicesInfo, updatesInfo, outputInfo, + indicesData, updatesData, descriptor); + + CHECK(net); + + std::map<int, std::vector<int32_t>> inputTensorData = {{ 0, shapeData }}; + std::map<int, std::vector<T>> expectedOutputData = {{ 0, expectedOutput }}; + + EndToEndLayerTestImpl<DataType::Signed32, ArmnnType>(std::move(net), inputTensorData, expectedOutputData, backends); +} + +} // anonymous namespace |