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Diffstat (limited to 'src/armnnDeserializer/test/DeserializePooling2d.cpp')
| -rw-r--r-- | src/armnnDeserializer/test/DeserializePooling2d.cpp | 162 |
1 files changed, 162 insertions, 0 deletions
diff --git a/src/armnnDeserializer/test/DeserializePooling2d.cpp b/src/armnnDeserializer/test/DeserializePooling2d.cpp new file mode 100644 index 0000000000..ef30a84342 --- /dev/null +++ b/src/armnnDeserializer/test/DeserializePooling2d.cpp @@ -0,0 +1,162 @@ +// +// Copyright © 2017 Arm Ltd. All rights reserved. +// SPDX-License-Identifier: MIT +// + +#include <boost/test/unit_test.hpp> +#include "ParserFlatbuffersSerializeFixture.hpp" +#include "../Deserializer.hpp" + +#include <string> +#include <iostream> + +BOOST_AUTO_TEST_SUITE(Deserializer) + +struct Pooling2dFixture : public ParserFlatbuffersSerializeFixture +{ + explicit Pooling2dFixture(const std::string &inputShape, + const std::string &outputShape, + const std::string &dataType, + const std::string &dataLayout, + const std::string &poolingAlgorithm) + { + m_JsonString = R"( + { + inputIds: [0], + outputIds: [2], + layers: [ + { + layer_type: "InputLayer", + layer: { + base: { + layerBindingId: 0, + base: { + index: 0, + layerName: "InputLayer", + layerType: "Input", + inputSlots: [{ + index: 0, + connection: {sourceLayerIndex:0, outputSlotIndex:0 }, + }], + outputSlots: [ { + index: 0, + tensorInfo: { + dimensions: )" + inputShape + R"(, + dataType: )" + dataType + R"( + }}] + } + }}}, + { + layer_type: "Pooling2dLayer", + layer: { + base: { + index: 1, + layerName: "Pooling2dLayer", + layerType: "Pooling2d", + inputSlots: [{ + index: 0, + connection: {sourceLayerIndex:0, outputSlotIndex:0 }, + }], + outputSlots: [ { + index: 0, + tensorInfo: { + dimensions: )" + outputShape + R"(, + dataType: )" + dataType + R"( + + }}]}, + descriptor: { + poolType: )" + poolingAlgorithm + R"(, + outputShapeRounding: "Floor", + paddingMethod: Exclude, + dataLayout: )" + dataLayout + R"(, + padLeft: 0, + padRight: 0, + padTop: 0, + padBottom: 0, + poolWidth: 2, + poolHeight: 2, + strideX: 2, + strideY: 2 + } + }}, + { + layer_type: "OutputLayer", + layer: { + base:{ + layerBindingId: 0, + base: { + index: 2, + layerName: "OutputLayer", + layerType: "Output", + inputSlots: [{ + index: 0, + connection: {sourceLayerIndex:1, outputSlotIndex:0 }, + }], + outputSlots: [ { + index: 0, + tensorInfo: { + dimensions: )" + outputShape + R"(, + dataType: )" + dataType + R"( + }, + }], + }}}, + }] + } + )"; + SetupSingleInputSingleOutput("InputLayer", "OutputLayer"); + } +}; + +struct SimpleAvgPoolingFixture : Pooling2dFixture +{ + SimpleAvgPoolingFixture() : Pooling2dFixture("[ 1, 2, 2, 1 ]", "[ 1, 1, 1, 1 ]", + "Float32", "NHWC", "Average") {} +}; + +struct SimpleAvgPoolingFixture2 : Pooling2dFixture +{ + SimpleAvgPoolingFixture2() : Pooling2dFixture("[ 1, 2, 2, 1 ]", + "[ 1, 1, 1, 1 ]", + "QuantisedAsymm8", "NHWC", "Average") {} +}; + +struct SimpleMaxPoolingFixture : Pooling2dFixture +{ + SimpleMaxPoolingFixture() : Pooling2dFixture("[ 1, 1, 2, 2 ]", + "[ 1, 1, 1, 1 ]", + "Float32", "NCHW", "Max") {} +}; + +struct SimpleMaxPoolingFixture2 : Pooling2dFixture +{ + SimpleMaxPoolingFixture2() : Pooling2dFixture("[ 1, 1, 2, 2 ]", + "[ 1, 1, 1, 1 ]", + "QuantisedAsymm8", "NCHW", "Max") {} +}; + +BOOST_FIXTURE_TEST_CASE(PoolingQuantisedAsymm8Avg, SimpleAvgPoolingFixture) +{ + RunTest<4, armnn::DataType::Float32>(0, { 2, 3, 5, 2 }, { 3 }); +} + +BOOST_FIXTURE_TEST_CASE(PoolingFloat32Avg, SimpleAvgPoolingFixture2) +{ + RunTest<4, armnn::DataType::QuantisedAsymm8>(0, + { 20, 40, 60, 80 }, + { 50 }); +} + +BOOST_FIXTURE_TEST_CASE(PoolingQuantisedAsymm8Max, SimpleMaxPoolingFixture) +{ + RunTest<4, armnn::DataType::Float32>(0, { 2, 5, 5, 2 }, { 5 }); +} + +BOOST_FIXTURE_TEST_CASE(PoolingFloat32Max, SimpleMaxPoolingFixture2) +{ + RunTest<4, armnn::DataType::QuantisedAsymm8>(0, + { 20, 40, 60, 80 }, + { 80 }); +} + +BOOST_AUTO_TEST_SUITE_END() + |