telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 1 | // |
| 2 | // Copyright © 2017 Arm Ltd. All rights reserved. |
David Beck | ecb56cd | 2018-09-05 12:52:57 +0100 | [diff] [blame] | 3 | // SPDX-License-Identifier: MIT |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 4 | // |
| 5 | |
| 6 | #pragma once |
| 7 | |
Matteo Martincigh | c601aa6 | 2019-10-29 15:03:22 +0000 | [diff] [blame] | 8 | #include "Schema.hpp" |
| 9 | |
keidav01 | 222c753 | 2019-03-14 17:12:10 +0000 | [diff] [blame] | 10 | #include <armnn/Descriptors.hpp> |
| 11 | #include <armnn/IRuntime.hpp> |
| 12 | #include <armnn/TypesUtils.hpp> |
Matteo Martincigh | c601aa6 | 2019-10-29 15:03:22 +0000 | [diff] [blame] | 13 | #include <armnn/BackendRegistry.hpp> |
Narumol Prangnawarat | ac2770a | 2020-04-01 16:51:23 +0100 | [diff] [blame] | 14 | #include <armnn/utility/Assert.hpp> |
keidav01 | 222c753 | 2019-03-14 17:12:10 +0000 | [diff] [blame] | 15 | |
Matteo Martincigh | c601aa6 | 2019-10-29 15:03:22 +0000 | [diff] [blame] | 16 | #include <armnnTfLiteParser/ITfLiteParser.hpp> |
| 17 | |
| 18 | #include <ResolveType.hpp> |
| 19 | |
| 20 | #include <test/TensorHelpers.hpp> |
| 21 | |
James Ward | 58dec6b | 2020-09-11 17:32:44 +0100 | [diff] [blame] | 22 | #include <fmt/format.h> |
keidav01 | 222c753 | 2019-03-14 17:12:10 +0000 | [diff] [blame] | 23 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 24 | #include "flatbuffers/idl.h" |
| 25 | #include "flatbuffers/util.h" |
keidav01 | 222c753 | 2019-03-14 17:12:10 +0000 | [diff] [blame] | 26 | #include "flatbuffers/flexbuffers.h" |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 27 | |
| 28 | #include <schema_generated.h> |
Matteo Martincigh | c601aa6 | 2019-10-29 15:03:22 +0000 | [diff] [blame] | 29 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 30 | #include <iostream> |
| 31 | |
| 32 | using armnnTfLiteParser::ITfLiteParser; |
Aron Virginas-Tar | c975f92 | 2019-10-23 17:38:17 +0100 | [diff] [blame] | 33 | using armnnTfLiteParser::ITfLiteParserPtr; |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 34 | |
Aron Virginas-Tar | c975f92 | 2019-10-23 17:38:17 +0100 | [diff] [blame] | 35 | using TensorRawPtr = const tflite::TensorT *; |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 36 | struct ParserFlatbuffersFixture |
| 37 | { |
Aron Virginas-Tar | 1d67a690 | 2018-11-19 10:58:30 +0000 | [diff] [blame] | 38 | ParserFlatbuffersFixture() : |
Aron Virginas-Tar | c975f92 | 2019-10-23 17:38:17 +0100 | [diff] [blame] | 39 | m_Parser(nullptr, &ITfLiteParser::Destroy), |
Aron Virginas-Tar | 1d67a690 | 2018-11-19 10:58:30 +0000 | [diff] [blame] | 40 | m_Runtime(armnn::IRuntime::Create(armnn::IRuntime::CreationOptions())), |
| 41 | m_NetworkIdentifier(-1) |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 42 | { |
Aron Virginas-Tar | c975f92 | 2019-10-23 17:38:17 +0100 | [diff] [blame] | 43 | ITfLiteParser::TfLiteParserOptions options; |
| 44 | options.m_StandInLayerForUnsupported = true; |
Sadik Armagan | d109a4d | 2020-07-28 10:42:13 +0100 | [diff] [blame] | 45 | options.m_InferAndValidate = true; |
Aron Virginas-Tar | c975f92 | 2019-10-23 17:38:17 +0100 | [diff] [blame] | 46 | |
| 47 | m_Parser.reset(ITfLiteParser::CreateRaw(armnn::Optional<ITfLiteParser::TfLiteParserOptions>(options))); |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 48 | } |
| 49 | |
| 50 | std::vector<uint8_t> m_GraphBinary; |
Aron Virginas-Tar | c975f92 | 2019-10-23 17:38:17 +0100 | [diff] [blame] | 51 | std::string m_JsonString; |
| 52 | ITfLiteParserPtr m_Parser; |
| 53 | armnn::IRuntimePtr m_Runtime; |
| 54 | armnn::NetworkId m_NetworkIdentifier; |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 55 | |
| 56 | /// If the single-input-single-output overload of Setup() is called, these will store the input and output name |
| 57 | /// so they don't need to be passed to the single-input-single-output overload of RunTest(). |
| 58 | std::string m_SingleInputName; |
| 59 | std::string m_SingleOutputName; |
| 60 | |
| 61 | void Setup() |
| 62 | { |
| 63 | bool ok = ReadStringToBinary(); |
| 64 | if (!ok) { |
| 65 | throw armnn::Exception("LoadNetwork failed while reading binary input"); |
| 66 | } |
| 67 | |
Aron Virginas-Tar | 1d67a690 | 2018-11-19 10:58:30 +0000 | [diff] [blame] | 68 | armnn::INetworkPtr network = |
| 69 | m_Parser->CreateNetworkFromBinary(m_GraphBinary); |
| 70 | |
| 71 | if (!network) { |
| 72 | throw armnn::Exception("The parser failed to create an ArmNN network"); |
| 73 | } |
| 74 | |
| 75 | auto optimized = Optimize(*network, { armnn::Compute::CpuRef }, |
| 76 | m_Runtime->GetDeviceSpec()); |
| 77 | std::string errorMessage; |
| 78 | |
| 79 | armnn::Status ret = m_Runtime->LoadNetwork(m_NetworkIdentifier, move(optimized), errorMessage); |
| 80 | |
| 81 | if (ret != armnn::Status::Success) |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 82 | { |
Aron Virginas-Tar | 1d67a690 | 2018-11-19 10:58:30 +0000 | [diff] [blame] | 83 | throw armnn::Exception( |
James Ward | 58dec6b | 2020-09-11 17:32:44 +0100 | [diff] [blame] | 84 | fmt::format("The runtime failed to load the network. " |
| 85 | "Error was: {}. in {} [{}:{}]", |
| 86 | errorMessage, |
| 87 | __func__, |
| 88 | __FILE__, |
| 89 | __LINE__)); |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 90 | } |
| 91 | } |
| 92 | |
| 93 | void SetupSingleInputSingleOutput(const std::string& inputName, const std::string& outputName) |
| 94 | { |
| 95 | // Store the input and output name so they don't need to be passed to the single-input-single-output RunTest(). |
| 96 | m_SingleInputName = inputName; |
| 97 | m_SingleOutputName = outputName; |
| 98 | Setup(); |
| 99 | } |
| 100 | |
| 101 | bool ReadStringToBinary() |
| 102 | { |
Rob Hughes | ff3c426 | 2019-12-20 17:43:16 +0000 | [diff] [blame] | 103 | std::string schemafile(g_TfLiteSchemaText, g_TfLiteSchemaText + g_TfLiteSchemaText_len); |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 104 | |
| 105 | // parse schema first, so we can use it to parse the data after |
| 106 | flatbuffers::Parser parser; |
| 107 | |
Matthew Bentham | 6c8e8e7 | 2019-01-15 17:57:00 +0000 | [diff] [blame] | 108 | bool ok = parser.Parse(schemafile.c_str()); |
Narumol Prangnawarat | ac2770a | 2020-04-01 16:51:23 +0100 | [diff] [blame] | 109 | ARMNN_ASSERT_MSG(ok, "Failed to parse schema file"); |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 110 | |
| 111 | ok &= parser.Parse(m_JsonString.c_str()); |
Narumol Prangnawarat | ac2770a | 2020-04-01 16:51:23 +0100 | [diff] [blame] | 112 | ARMNN_ASSERT_MSG(ok, "Failed to parse json input"); |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 113 | |
| 114 | if (!ok) |
| 115 | { |
| 116 | return false; |
| 117 | } |
| 118 | |
| 119 | { |
| 120 | const uint8_t * bufferPtr = parser.builder_.GetBufferPointer(); |
| 121 | size_t size = static_cast<size_t>(parser.builder_.GetSize()); |
| 122 | m_GraphBinary.assign(bufferPtr, bufferPtr+size); |
| 123 | } |
| 124 | return ok; |
| 125 | } |
| 126 | |
| 127 | /// Executes the network with the given input tensor and checks the result against the given output tensor. |
keidav01 | 1b3e2ea | 2019-02-21 10:07:37 +0000 | [diff] [blame] | 128 | /// This assumes the network has a single input and a single output. |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 129 | template <std::size_t NumOutputDimensions, |
Rob Hughes | fc6bf05 | 2019-12-16 17:10:51 +0000 | [diff] [blame] | 130 | armnn::DataType ArmnnType> |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 131 | void RunTest(size_t subgraphId, |
Rob Hughes | fc6bf05 | 2019-12-16 17:10:51 +0000 | [diff] [blame] | 132 | const std::vector<armnn::ResolveType<ArmnnType>>& inputData, |
| 133 | const std::vector<armnn::ResolveType<ArmnnType>>& expectedOutputData); |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 134 | |
| 135 | /// Executes the network with the given input tensors and checks the results against the given output tensors. |
| 136 | /// This overload supports multiple inputs and multiple outputs, identified by name. |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 137 | template <std::size_t NumOutputDimensions, |
Rob Hughes | fc6bf05 | 2019-12-16 17:10:51 +0000 | [diff] [blame] | 138 | armnn::DataType ArmnnType> |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 139 | void RunTest(size_t subgraphId, |
Rob Hughes | fc6bf05 | 2019-12-16 17:10:51 +0000 | [diff] [blame] | 140 | const std::map<std::string, std::vector<armnn::ResolveType<ArmnnType>>>& inputData, |
| 141 | const std::map<std::string, std::vector<armnn::ResolveType<ArmnnType>>>& expectedOutputData); |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 142 | |
keidav01 | 1b3e2ea | 2019-02-21 10:07:37 +0000 | [diff] [blame] | 143 | /// Multiple Inputs, Multiple Outputs w/ Variable Datatypes and different dimension sizes. |
| 144 | /// Executes the network with the given input tensors and checks the results against the given output tensors. |
| 145 | /// This overload supports multiple inputs and multiple outputs, identified by name along with the allowance for |
| 146 | /// the input datatype to be different to the output |
| 147 | template <std::size_t NumOutputDimensions, |
| 148 | armnn::DataType ArmnnType1, |
Rob Hughes | fc6bf05 | 2019-12-16 17:10:51 +0000 | [diff] [blame] | 149 | armnn::DataType ArmnnType2> |
keidav01 | 1b3e2ea | 2019-02-21 10:07:37 +0000 | [diff] [blame] | 150 | void RunTest(size_t subgraphId, |
Rob Hughes | fc6bf05 | 2019-12-16 17:10:51 +0000 | [diff] [blame] | 151 | const std::map<std::string, std::vector<armnn::ResolveType<ArmnnType1>>>& inputData, |
Sadik Armagan | d109a4d | 2020-07-28 10:42:13 +0100 | [diff] [blame] | 152 | const std::map<std::string, std::vector<armnn::ResolveType<ArmnnType2>>>& expectedOutputData, |
| 153 | bool isDynamic = false); |
keidav01 | 1b3e2ea | 2019-02-21 10:07:37 +0000 | [diff] [blame] | 154 | |
Sadik Armagan | 2686849 | 2021-01-22 14:25:31 +0000 | [diff] [blame] | 155 | /// Multiple Inputs with different DataTypes, Multiple Outputs w/ Variable DataTypes |
| 156 | /// Executes the network with the given input tensors and checks the results against the given output tensors. |
| 157 | /// This overload supports multiple inputs and multiple outputs, identified by name along with the allowance for |
| 158 | /// the input datatype to be different to the output |
| 159 | template <std::size_t NumOutputDimensions, |
| 160 | armnn::DataType inputType1, |
| 161 | armnn::DataType inputType2, |
| 162 | armnn::DataType outputType> |
| 163 | void RunTest(size_t subgraphId, |
| 164 | const std::map<std::string, std::vector<armnn::ResolveType<inputType1>>>& input1Data, |
| 165 | const std::map<std::string, std::vector<armnn::ResolveType<inputType2>>>& input2Data, |
| 166 | const std::map<std::string, std::vector<armnn::ResolveType<outputType>>>& expectedOutputData); |
keidav01 | 1b3e2ea | 2019-02-21 10:07:37 +0000 | [diff] [blame] | 167 | |
| 168 | /// Multiple Inputs, Multiple Outputs w/ Variable Datatypes and different dimension sizes. |
| 169 | /// Executes the network with the given input tensors and checks the results against the given output tensors. |
| 170 | /// This overload supports multiple inputs and multiple outputs, identified by name along with the allowance for |
| 171 | /// the input datatype to be different to the output |
| 172 | template<armnn::DataType ArmnnType1, |
Rob Hughes | fc6bf05 | 2019-12-16 17:10:51 +0000 | [diff] [blame] | 173 | armnn::DataType ArmnnType2> |
keidav01 | 1b3e2ea | 2019-02-21 10:07:37 +0000 | [diff] [blame] | 174 | void RunTest(std::size_t subgraphId, |
Rob Hughes | fc6bf05 | 2019-12-16 17:10:51 +0000 | [diff] [blame] | 175 | const std::map<std::string, std::vector<armnn::ResolveType<ArmnnType1>>>& inputData, |
| 176 | const std::map<std::string, std::vector<armnn::ResolveType<ArmnnType2>>>& expectedOutputData); |
keidav01 | 1b3e2ea | 2019-02-21 10:07:37 +0000 | [diff] [blame] | 177 | |
keidav01 | 222c753 | 2019-03-14 17:12:10 +0000 | [diff] [blame] | 178 | static inline std::string GenerateDetectionPostProcessJsonString( |
| 179 | const armnn::DetectionPostProcessDescriptor& descriptor) |
| 180 | { |
| 181 | flexbuffers::Builder detectPostProcess; |
| 182 | detectPostProcess.Map([&]() { |
| 183 | detectPostProcess.Bool("use_regular_nms", descriptor.m_UseRegularNms); |
| 184 | detectPostProcess.Int("max_detections", descriptor.m_MaxDetections); |
| 185 | detectPostProcess.Int("max_classes_per_detection", descriptor.m_MaxClassesPerDetection); |
| 186 | detectPostProcess.Int("detections_per_class", descriptor.m_DetectionsPerClass); |
| 187 | detectPostProcess.Int("num_classes", descriptor.m_NumClasses); |
| 188 | detectPostProcess.Float("nms_score_threshold", descriptor.m_NmsScoreThreshold); |
| 189 | detectPostProcess.Float("nms_iou_threshold", descriptor.m_NmsIouThreshold); |
| 190 | detectPostProcess.Float("h_scale", descriptor.m_ScaleH); |
| 191 | detectPostProcess.Float("w_scale", descriptor.m_ScaleW); |
| 192 | detectPostProcess.Float("x_scale", descriptor.m_ScaleX); |
| 193 | detectPostProcess.Float("y_scale", descriptor.m_ScaleY); |
| 194 | }); |
| 195 | detectPostProcess.Finish(); |
| 196 | |
| 197 | // Create JSON string |
| 198 | std::stringstream strStream; |
| 199 | std::vector<uint8_t> buffer = detectPostProcess.GetBuffer(); |
| 200 | std::copy(buffer.begin(), buffer.end(),std::ostream_iterator<int>(strStream,",")); |
| 201 | |
| 202 | return strStream.str(); |
| 203 | } |
| 204 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 205 | void CheckTensors(const TensorRawPtr& tensors, size_t shapeSize, const std::vector<int32_t>& shape, |
| 206 | tflite::TensorType tensorType, uint32_t buffer, const std::string& name, |
| 207 | const std::vector<float>& min, const std::vector<float>& max, |
| 208 | const std::vector<float>& scale, const std::vector<int64_t>& zeroPoint) |
| 209 | { |
| 210 | BOOST_CHECK(tensors); |
| 211 | BOOST_CHECK_EQUAL(shapeSize, tensors->shape.size()); |
| 212 | BOOST_CHECK_EQUAL_COLLECTIONS(shape.begin(), shape.end(), tensors->shape.begin(), tensors->shape.end()); |
| 213 | BOOST_CHECK_EQUAL(tensorType, tensors->type); |
| 214 | BOOST_CHECK_EQUAL(buffer, tensors->buffer); |
| 215 | BOOST_CHECK_EQUAL(name, tensors->name); |
| 216 | BOOST_CHECK(tensors->quantization); |
| 217 | BOOST_CHECK_EQUAL_COLLECTIONS(min.begin(), min.end(), tensors->quantization.get()->min.begin(), |
| 218 | tensors->quantization.get()->min.end()); |
| 219 | BOOST_CHECK_EQUAL_COLLECTIONS(max.begin(), max.end(), tensors->quantization.get()->max.begin(), |
| 220 | tensors->quantization.get()->max.end()); |
| 221 | BOOST_CHECK_EQUAL_COLLECTIONS(scale.begin(), scale.end(), tensors->quantization.get()->scale.begin(), |
| 222 | tensors->quantization.get()->scale.end()); |
| 223 | BOOST_CHECK_EQUAL_COLLECTIONS(zeroPoint.begin(), zeroPoint.end(), |
| 224 | tensors->quantization.get()->zero_point.begin(), |
| 225 | tensors->quantization.get()->zero_point.end()); |
| 226 | } |
Sadik Armagan | 2686849 | 2021-01-22 14:25:31 +0000 | [diff] [blame] | 227 | |
| 228 | private: |
| 229 | /// Fills the InputTensors with given input data |
| 230 | template <armnn::DataType dataType> |
| 231 | void FillInputTensors(armnn::InputTensors& inputTensors, |
| 232 | const std::map<std::string, std::vector<armnn::ResolveType<dataType>>>& inputData, |
| 233 | size_t subgraphId); |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 234 | }; |
| 235 | |
Sadik Armagan | 2686849 | 2021-01-22 14:25:31 +0000 | [diff] [blame] | 236 | /// Fills the InputTensors with given input data |
| 237 | template <armnn::DataType dataType> |
| 238 | void ParserFlatbuffersFixture::FillInputTensors( |
| 239 | armnn::InputTensors& inputTensors, |
| 240 | const std::map<std::string, std::vector<armnn::ResolveType<dataType>>>& inputData, |
| 241 | size_t subgraphId) |
| 242 | { |
| 243 | for (auto&& it : inputData) |
| 244 | { |
| 245 | armnn::BindingPointInfo bindingInfo = m_Parser->GetNetworkInputBindingInfo(subgraphId, it.first); |
| 246 | armnn::VerifyTensorInfoDataType(bindingInfo.second, dataType); |
| 247 | inputTensors.push_back({ bindingInfo.first, armnn::ConstTensor(bindingInfo.second, it.second.data()) }); |
| 248 | } |
| 249 | } |
| 250 | |
keidav01 | 1b3e2ea | 2019-02-21 10:07:37 +0000 | [diff] [blame] | 251 | /// Single Input, Single Output |
| 252 | /// Executes the network with the given input tensor and checks the result against the given output tensor. |
| 253 | /// This overload assumes the network has a single input and a single output. |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 254 | template <std::size_t NumOutputDimensions, |
Rob Hughes | fc6bf05 | 2019-12-16 17:10:51 +0000 | [diff] [blame] | 255 | armnn::DataType armnnType> |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 256 | void ParserFlatbuffersFixture::RunTest(size_t subgraphId, |
Rob Hughes | fc6bf05 | 2019-12-16 17:10:51 +0000 | [diff] [blame] | 257 | const std::vector<armnn::ResolveType<armnnType>>& inputData, |
| 258 | const std::vector<armnn::ResolveType<armnnType>>& expectedOutputData) |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 259 | { |
keidav01 | 1b3e2ea | 2019-02-21 10:07:37 +0000 | [diff] [blame] | 260 | RunTest<NumOutputDimensions, armnnType>(subgraphId, |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 261 | { { m_SingleInputName, inputData } }, |
| 262 | { { m_SingleOutputName, expectedOutputData } }); |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 263 | } |
| 264 | |
keidav01 | 1b3e2ea | 2019-02-21 10:07:37 +0000 | [diff] [blame] | 265 | /// Multiple Inputs, Multiple Outputs |
| 266 | /// Executes the network with the given input tensors and checks the results against the given output tensors. |
| 267 | /// This overload supports multiple inputs and multiple outputs, identified by name. |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 268 | template <std::size_t NumOutputDimensions, |
Rob Hughes | fc6bf05 | 2019-12-16 17:10:51 +0000 | [diff] [blame] | 269 | armnn::DataType armnnType> |
Nattapat Chaimanowong | 649dd95 | 2019-01-22 16:10:44 +0000 | [diff] [blame] | 270 | void ParserFlatbuffersFixture::RunTest(size_t subgraphId, |
Rob Hughes | fc6bf05 | 2019-12-16 17:10:51 +0000 | [diff] [blame] | 271 | const std::map<std::string, std::vector<armnn::ResolveType<armnnType>>>& inputData, |
| 272 | const std::map<std::string, std::vector<armnn::ResolveType<armnnType>>>& expectedOutputData) |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 273 | { |
keidav01 | 1b3e2ea | 2019-02-21 10:07:37 +0000 | [diff] [blame] | 274 | RunTest<NumOutputDimensions, armnnType, armnnType>(subgraphId, inputData, expectedOutputData); |
| 275 | } |
| 276 | |
| 277 | /// Multiple Inputs, Multiple Outputs w/ Variable Datatypes |
| 278 | /// Executes the network with the given input tensors and checks the results against the given output tensors. |
| 279 | /// This overload supports multiple inputs and multiple outputs, identified by name along with the allowance for |
| 280 | /// the input datatype to be different to the output |
| 281 | template <std::size_t NumOutputDimensions, |
| 282 | armnn::DataType armnnType1, |
Rob Hughes | fc6bf05 | 2019-12-16 17:10:51 +0000 | [diff] [blame] | 283 | armnn::DataType armnnType2> |
keidav01 | 1b3e2ea | 2019-02-21 10:07:37 +0000 | [diff] [blame] | 284 | void ParserFlatbuffersFixture::RunTest(size_t subgraphId, |
Rob Hughes | fc6bf05 | 2019-12-16 17:10:51 +0000 | [diff] [blame] | 285 | const std::map<std::string, std::vector<armnn::ResolveType<armnnType1>>>& inputData, |
Sadik Armagan | d109a4d | 2020-07-28 10:42:13 +0100 | [diff] [blame] | 286 | const std::map<std::string, std::vector<armnn::ResolveType<armnnType2>>>& expectedOutputData, |
| 287 | bool isDynamic) |
keidav01 | 1b3e2ea | 2019-02-21 10:07:37 +0000 | [diff] [blame] | 288 | { |
Rob Hughes | fc6bf05 | 2019-12-16 17:10:51 +0000 | [diff] [blame] | 289 | using DataType2 = armnn::ResolveType<armnnType2>; |
| 290 | |
Aron Virginas-Tar | 1d67a690 | 2018-11-19 10:58:30 +0000 | [diff] [blame] | 291 | // Setup the armnn input tensors from the given vectors. |
| 292 | armnn::InputTensors inputTensors; |
Sadik Armagan | 2686849 | 2021-01-22 14:25:31 +0000 | [diff] [blame] | 293 | FillInputTensors<armnnType1>(inputTensors, inputData, subgraphId); |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 294 | |
Aron Virginas-Tar | 1d67a690 | 2018-11-19 10:58:30 +0000 | [diff] [blame] | 295 | // Allocate storage for the output tensors to be written to and setup the armnn output tensors. |
keidav01 | 1b3e2ea | 2019-02-21 10:07:37 +0000 | [diff] [blame] | 296 | std::map<std::string, boost::multi_array<DataType2, NumOutputDimensions>> outputStorage; |
Aron Virginas-Tar | 1d67a690 | 2018-11-19 10:58:30 +0000 | [diff] [blame] | 297 | armnn::OutputTensors outputTensors; |
| 298 | for (auto&& it : expectedOutputData) |
| 299 | { |
Narumol Prangnawarat | 386681a | 2019-04-29 16:40:55 +0100 | [diff] [blame] | 300 | armnn::LayerBindingId outputBindingId = m_Parser->GetNetworkOutputBindingInfo(subgraphId, it.first).first; |
| 301 | armnn::TensorInfo outputTensorInfo = m_Runtime->GetOutputTensorInfo(m_NetworkIdentifier, outputBindingId); |
| 302 | |
| 303 | // Check that output tensors have correct number of dimensions (NumOutputDimensions specified in test) |
| 304 | auto outputNumDimensions = outputTensorInfo.GetNumDimensions(); |
| 305 | BOOST_CHECK_MESSAGE((outputNumDimensions == NumOutputDimensions), |
James Ward | 58dec6b | 2020-09-11 17:32:44 +0100 | [diff] [blame] | 306 | fmt::format("Number of dimensions expected {}, but got {} for output layer {}", |
| 307 | NumOutputDimensions, |
| 308 | outputNumDimensions, |
| 309 | it.first)); |
Narumol Prangnawarat | 386681a | 2019-04-29 16:40:55 +0100 | [diff] [blame] | 310 | |
| 311 | armnn::VerifyTensorInfoDataType(outputTensorInfo, armnnType2); |
| 312 | outputStorage.emplace(it.first, MakeTensor<DataType2, NumOutputDimensions>(outputTensorInfo)); |
Aron Virginas-Tar | 1d67a690 | 2018-11-19 10:58:30 +0000 | [diff] [blame] | 313 | outputTensors.push_back( |
Narumol Prangnawarat | 386681a | 2019-04-29 16:40:55 +0100 | [diff] [blame] | 314 | { outputBindingId, armnn::Tensor(outputTensorInfo, outputStorage.at(it.first).data()) }); |
Aron Virginas-Tar | 1d67a690 | 2018-11-19 10:58:30 +0000 | [diff] [blame] | 315 | } |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 316 | |
Aron Virginas-Tar | 1d67a690 | 2018-11-19 10:58:30 +0000 | [diff] [blame] | 317 | m_Runtime->EnqueueWorkload(m_NetworkIdentifier, inputTensors, outputTensors); |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 318 | |
Aron Virginas-Tar | 1d67a690 | 2018-11-19 10:58:30 +0000 | [diff] [blame] | 319 | // Compare each output tensor to the expected values |
| 320 | for (auto&& it : expectedOutputData) |
| 321 | { |
Jim Flynn | b4d7eae | 2019-05-01 14:44:27 +0100 | [diff] [blame] | 322 | armnn::BindingPointInfo bindingInfo = m_Parser->GetNetworkOutputBindingInfo(subgraphId, it.first); |
Sadik Armagan | d109a4d | 2020-07-28 10:42:13 +0100 | [diff] [blame] | 323 | auto outputExpected = MakeTensor<DataType2, NumOutputDimensions>(bindingInfo.second, it.second, isDynamic); |
| 324 | BOOST_TEST(CompareTensors(outputExpected, outputStorage[it.first], false, isDynamic)); |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 325 | } |
| 326 | } |
keidav01 | 1b3e2ea | 2019-02-21 10:07:37 +0000 | [diff] [blame] | 327 | |
| 328 | /// Multiple Inputs, Multiple Outputs w/ Variable Datatypes and different dimension sizes. |
| 329 | /// Executes the network with the given input tensors and checks the results against the given output tensors. |
| 330 | /// This overload supports multiple inputs and multiple outputs, identified by name along with the allowance for |
| 331 | /// the input datatype to be different to the output. |
| 332 | template <armnn::DataType armnnType1, |
Rob Hughes | fc6bf05 | 2019-12-16 17:10:51 +0000 | [diff] [blame] | 333 | armnn::DataType armnnType2> |
keidav01 | 1b3e2ea | 2019-02-21 10:07:37 +0000 | [diff] [blame] | 334 | void ParserFlatbuffersFixture::RunTest(std::size_t subgraphId, |
Rob Hughes | fc6bf05 | 2019-12-16 17:10:51 +0000 | [diff] [blame] | 335 | const std::map<std::string, std::vector<armnn::ResolveType<armnnType1>>>& inputData, |
| 336 | const std::map<std::string, std::vector<armnn::ResolveType<armnnType2>>>& expectedOutputData) |
keidav01 | 1b3e2ea | 2019-02-21 10:07:37 +0000 | [diff] [blame] | 337 | { |
Rob Hughes | fc6bf05 | 2019-12-16 17:10:51 +0000 | [diff] [blame] | 338 | using DataType2 = armnn::ResolveType<armnnType2>; |
| 339 | |
keidav01 | 1b3e2ea | 2019-02-21 10:07:37 +0000 | [diff] [blame] | 340 | // Setup the armnn input tensors from the given vectors. |
| 341 | armnn::InputTensors inputTensors; |
Sadik Armagan | 2686849 | 2021-01-22 14:25:31 +0000 | [diff] [blame] | 342 | FillInputTensors<armnnType1>(inputTensors, inputData, subgraphId); |
keidav01 | 1b3e2ea | 2019-02-21 10:07:37 +0000 | [diff] [blame] | 343 | |
| 344 | armnn::OutputTensors outputTensors; |
| 345 | outputTensors.reserve(expectedOutputData.size()); |
| 346 | std::map<std::string, std::vector<DataType2>> outputStorage; |
| 347 | for (auto&& it : expectedOutputData) |
| 348 | { |
Jim Flynn | b4d7eae | 2019-05-01 14:44:27 +0100 | [diff] [blame] | 349 | armnn::BindingPointInfo bindingInfo = m_Parser->GetNetworkOutputBindingInfo(subgraphId, it.first); |
keidav01 | 1b3e2ea | 2019-02-21 10:07:37 +0000 | [diff] [blame] | 350 | armnn::VerifyTensorInfoDataType(bindingInfo.second, armnnType2); |
| 351 | |
| 352 | std::vector<DataType2> out(it.second.size()); |
| 353 | outputStorage.emplace(it.first, out); |
| 354 | outputTensors.push_back({ bindingInfo.first, |
| 355 | armnn::Tensor(bindingInfo.second, |
| 356 | outputStorage.at(it.first).data()) }); |
| 357 | } |
| 358 | |
| 359 | m_Runtime->EnqueueWorkload(m_NetworkIdentifier, inputTensors, outputTensors); |
| 360 | |
| 361 | // Checks the results. |
| 362 | for (auto&& it : expectedOutputData) |
| 363 | { |
Rob Hughes | fc6bf05 | 2019-12-16 17:10:51 +0000 | [diff] [blame] | 364 | std::vector<armnn::ResolveType<armnnType2>> out = outputStorage.at(it.first); |
keidav01 | 1b3e2ea | 2019-02-21 10:07:37 +0000 | [diff] [blame] | 365 | { |
| 366 | for (unsigned int i = 0; i < out.size(); ++i) |
| 367 | { |
| 368 | BOOST_TEST(it.second[i] == out[i], boost::test_tools::tolerance(0.000001f)); |
| 369 | } |
| 370 | } |
| 371 | } |
Aron Virginas-Tar | c975f92 | 2019-10-23 17:38:17 +0100 | [diff] [blame] | 372 | } |
Sadik Armagan | 2686849 | 2021-01-22 14:25:31 +0000 | [diff] [blame] | 373 | |
| 374 | /// Multiple Inputs with different DataTypes, Multiple Outputs w/ Variable DataTypes |
| 375 | /// Executes the network with the given input tensors and checks the results against the given output tensors. |
| 376 | /// This overload supports multiple inputs and multiple outputs, identified by name along with the allowance for |
| 377 | /// the input datatype to be different to the output |
| 378 | template <std::size_t NumOutputDimensions, |
| 379 | armnn::DataType inputType1, |
| 380 | armnn::DataType inputType2, |
| 381 | armnn::DataType outputType> |
| 382 | void ParserFlatbuffersFixture::RunTest(size_t subgraphId, |
| 383 | const std::map<std::string, std::vector<armnn::ResolveType<inputType1>>>& input1Data, |
| 384 | const std::map<std::string, std::vector<armnn::ResolveType<inputType2>>>& input2Data, |
| 385 | const std::map<std::string, std::vector<armnn::ResolveType<outputType>>>& expectedOutputData) |
| 386 | { |
| 387 | using DataType2 = armnn::ResolveType<outputType>; |
| 388 | |
| 389 | // Setup the armnn input tensors from the given vectors. |
| 390 | armnn::InputTensors inputTensors; |
| 391 | FillInputTensors<inputType1>(inputTensors, input1Data, subgraphId); |
| 392 | FillInputTensors<inputType2>(inputTensors, input2Data, subgraphId); |
| 393 | |
| 394 | // Allocate storage for the output tensors to be written to and setup the armnn output tensors. |
| 395 | std::map<std::string, boost::multi_array<DataType2, NumOutputDimensions>> outputStorage; |
| 396 | armnn::OutputTensors outputTensors; |
| 397 | for (auto&& it : expectedOutputData) |
| 398 | { |
| 399 | armnn::LayerBindingId outputBindingId = m_Parser->GetNetworkOutputBindingInfo(subgraphId, it.first).first; |
| 400 | armnn::TensorInfo outputTensorInfo = m_Runtime->GetOutputTensorInfo(m_NetworkIdentifier, outputBindingId); |
| 401 | |
| 402 | // Check that output tensors have correct number of dimensions (NumOutputDimensions specified in test) |
| 403 | auto outputNumDimensions = outputTensorInfo.GetNumDimensions(); |
| 404 | BOOST_CHECK_MESSAGE((outputNumDimensions == NumOutputDimensions), |
| 405 | fmt::format("Number of dimensions expected {}, but got {} for output layer {}", |
| 406 | NumOutputDimensions, |
| 407 | outputNumDimensions, |
| 408 | it.first)); |
| 409 | |
| 410 | armnn::VerifyTensorInfoDataType(outputTensorInfo, outputType); |
| 411 | outputStorage.emplace(it.first, MakeTensor<DataType2, NumOutputDimensions>(outputTensorInfo)); |
| 412 | outputTensors.push_back( |
| 413 | { outputBindingId, armnn::Tensor(outputTensorInfo, outputStorage.at(it.first).data()) }); |
| 414 | } |
| 415 | |
| 416 | m_Runtime->EnqueueWorkload(m_NetworkIdentifier, inputTensors, outputTensors); |
| 417 | |
| 418 | // Compare each output tensor to the expected values |
| 419 | for (auto&& it : expectedOutputData) |
| 420 | { |
| 421 | armnn::BindingPointInfo bindingInfo = m_Parser->GetNetworkOutputBindingInfo(subgraphId, it.first); |
| 422 | auto outputExpected = MakeTensor<DataType2, NumOutputDimensions>(bindingInfo.second, it.second); |
| 423 | BOOST_TEST(CompareTensors(outputExpected, outputStorage[it.first], false)); |
| 424 | } |
| 425 | } |