Sadik Armagan | 6e36a64 | 2020-11-10 21:18:41 +0000 | [diff] [blame] | 1 | // |
Colm Donelan | 7bcae3c | 2024-01-22 10:07:14 +0000 | [diff] [blame] | 2 | // Copyright © 2020, 2023-2024 Arm Ltd and Contributors. All rights reserved. |
Sadik Armagan | 6e36a64 | 2020-11-10 21:18:41 +0000 | [diff] [blame] | 3 | // SPDX-License-Identifier: MIT |
| 4 | // |
| 5 | |
| 6 | #pragma once |
| 7 | |
Sadik Armagan | f0a6dec | 2021-03-25 07:46:55 +0000 | [diff] [blame] | 8 | #include "TestUtils.hpp" |
| 9 | |
Sadik Armagan | 6e36a64 | 2020-11-10 21:18:41 +0000 | [diff] [blame] | 10 | #include <armnn_delegate.hpp> |
Matthew Sloyan | ebe392d | 2023-03-30 10:12:08 +0100 | [diff] [blame] | 11 | #include <DelegateTestInterpreter.hpp> |
Sadik Armagan | 6e36a64 | 2020-11-10 21:18:41 +0000 | [diff] [blame] | 12 | |
Sadik Armagan | 6e36a64 | 2020-11-10 21:18:41 +0000 | [diff] [blame] | 13 | #include <tensorflow/lite/version.h> |
| 14 | |
Sadik Armagan | 6e36a64 | 2020-11-10 21:18:41 +0000 | [diff] [blame] | 15 | namespace |
| 16 | { |
| 17 | |
| 18 | template <typename T> |
| 19 | std::vector<char> CreateFullyConnectedTfLiteModel(tflite::TensorType tensorType, |
| 20 | tflite::ActivationFunctionType activationType, |
| 21 | const std::vector <int32_t>& inputTensorShape, |
| 22 | const std::vector <int32_t>& weightsTensorShape, |
| 23 | const std::vector <int32_t>& biasTensorShape, |
Sadik Armagan | f0a6dec | 2021-03-25 07:46:55 +0000 | [diff] [blame] | 24 | std::vector <int32_t>& outputTensorShape, |
| 25 | std::vector <T>& weightsData, |
| 26 | bool constantWeights = true, |
Sadik Armagan | 6e36a64 | 2020-11-10 21:18:41 +0000 | [diff] [blame] | 27 | float quantScale = 1.0f, |
| 28 | int quantOffset = 0, |
| 29 | float outputQuantScale = 2.0f, |
| 30 | int outputQuantOffset = 0) |
| 31 | { |
| 32 | using namespace tflite; |
| 33 | flatbuffers::FlatBufferBuilder flatBufferBuilder; |
Ryan OShea | 238ecd9 | 2023-03-07 11:44:23 +0000 | [diff] [blame] | 34 | std::array<flatbuffers::Offset<tflite::Buffer>, 5> buffers; |
| 35 | buffers[0] = CreateBuffer(flatBufferBuilder); |
| 36 | buffers[1] = CreateBuffer(flatBufferBuilder); |
Sadik Armagan | 6e36a64 | 2020-11-10 21:18:41 +0000 | [diff] [blame] | 37 | |
| 38 | auto biasTensorType = ::tflite::TensorType_FLOAT32; |
Narumol Prangnawarat | 55518ca | 2020-11-20 14:50:54 +0000 | [diff] [blame] | 39 | if (tensorType == ::tflite::TensorType_INT8) |
Sadik Armagan | 6e36a64 | 2020-11-10 21:18:41 +0000 | [diff] [blame] | 40 | { |
| 41 | biasTensorType = ::tflite::TensorType_INT32; |
Sadik Armagan | f0a6dec | 2021-03-25 07:46:55 +0000 | [diff] [blame] | 42 | } |
| 43 | if (constantWeights) |
| 44 | { |
Ryan OShea | 238ecd9 | 2023-03-07 11:44:23 +0000 | [diff] [blame] | 45 | buffers[2] = CreateBuffer(flatBufferBuilder, |
Sadik Armagan | f0a6dec | 2021-03-25 07:46:55 +0000 | [diff] [blame] | 46 | flatBufferBuilder.CreateVector(reinterpret_cast<const uint8_t*>(weightsData.data()), |
| 47 | sizeof(T) * weightsData.size())); |
Sadik Armagan | 6e36a64 | 2020-11-10 21:18:41 +0000 | [diff] [blame] | 48 | |
Sadik Armagan | f0a6dec | 2021-03-25 07:46:55 +0000 | [diff] [blame] | 49 | if (tensorType == ::tflite::TensorType_INT8) |
| 50 | { |
| 51 | std::vector<int32_t> biasData = { 10 }; |
Ryan OShea | 238ecd9 | 2023-03-07 11:44:23 +0000 | [diff] [blame] | 52 | buffers[3] = CreateBuffer(flatBufferBuilder, |
Sadik Armagan | f0a6dec | 2021-03-25 07:46:55 +0000 | [diff] [blame] | 53 | flatBufferBuilder.CreateVector(reinterpret_cast<const uint8_t*>(biasData.data()), |
| 54 | sizeof(int32_t) * biasData.size())); |
| 55 | |
| 56 | } |
| 57 | else |
| 58 | { |
| 59 | std::vector<float> biasData = { 10 }; |
Ryan OShea | 238ecd9 | 2023-03-07 11:44:23 +0000 | [diff] [blame] | 60 | buffers[3] = CreateBuffer(flatBufferBuilder, |
Sadik Armagan | f0a6dec | 2021-03-25 07:46:55 +0000 | [diff] [blame] | 61 | flatBufferBuilder.CreateVector(reinterpret_cast<const uint8_t*>(biasData.data()), |
| 62 | sizeof(float) * biasData.size())); |
| 63 | } |
Sadik Armagan | 6e36a64 | 2020-11-10 21:18:41 +0000 | [diff] [blame] | 64 | } |
| 65 | else |
| 66 | { |
Ryan OShea | 238ecd9 | 2023-03-07 11:44:23 +0000 | [diff] [blame] | 67 | buffers[2] = CreateBuffer(flatBufferBuilder); |
| 68 | buffers[3] = CreateBuffer(flatBufferBuilder); |
Sadik Armagan | 6e36a64 | 2020-11-10 21:18:41 +0000 | [diff] [blame] | 69 | } |
Ryan OShea | 238ecd9 | 2023-03-07 11:44:23 +0000 | [diff] [blame] | 70 | buffers[4] = CreateBuffer(flatBufferBuilder); |
Sadik Armagan | 6e36a64 | 2020-11-10 21:18:41 +0000 | [diff] [blame] | 71 | |
| 72 | auto quantizationParameters = |
| 73 | CreateQuantizationParameters(flatBufferBuilder, |
| 74 | 0, |
| 75 | 0, |
| 76 | flatBufferBuilder.CreateVector<float>({ quantScale }), |
| 77 | flatBufferBuilder.CreateVector<int64_t>({ quantOffset })); |
| 78 | |
| 79 | auto outputQuantizationParameters = |
| 80 | CreateQuantizationParameters(flatBufferBuilder, |
| 81 | 0, |
| 82 | 0, |
| 83 | flatBufferBuilder.CreateVector<float>({ outputQuantScale }), |
| 84 | flatBufferBuilder.CreateVector<int64_t>({ outputQuantOffset })); |
| 85 | |
| 86 | std::array<flatbuffers::Offset<Tensor>, 4> tensors; |
| 87 | tensors[0] = CreateTensor(flatBufferBuilder, |
| 88 | flatBufferBuilder.CreateVector<int32_t>(inputTensorShape.data(), |
| 89 | inputTensorShape.size()), |
| 90 | tensorType, |
Ryan OShea | 238ecd9 | 2023-03-07 11:44:23 +0000 | [diff] [blame] | 91 | 1, |
Sadik Armagan | 6e36a64 | 2020-11-10 21:18:41 +0000 | [diff] [blame] | 92 | flatBufferBuilder.CreateString("input_0"), |
| 93 | quantizationParameters); |
| 94 | tensors[1] = CreateTensor(flatBufferBuilder, |
| 95 | flatBufferBuilder.CreateVector<int32_t>(weightsTensorShape.data(), |
| 96 | weightsTensorShape.size()), |
| 97 | tensorType, |
Ryan OShea | 238ecd9 | 2023-03-07 11:44:23 +0000 | [diff] [blame] | 98 | 2, |
Sadik Armagan | 6e36a64 | 2020-11-10 21:18:41 +0000 | [diff] [blame] | 99 | flatBufferBuilder.CreateString("weights"), |
| 100 | quantizationParameters); |
| 101 | tensors[2] = CreateTensor(flatBufferBuilder, |
| 102 | flatBufferBuilder.CreateVector<int32_t>(biasTensorShape.data(), |
| 103 | biasTensorShape.size()), |
| 104 | biasTensorType, |
Ryan OShea | 238ecd9 | 2023-03-07 11:44:23 +0000 | [diff] [blame] | 105 | 3, |
Sadik Armagan | 6e36a64 | 2020-11-10 21:18:41 +0000 | [diff] [blame] | 106 | flatBufferBuilder.CreateString("bias"), |
| 107 | quantizationParameters); |
| 108 | |
| 109 | tensors[3] = CreateTensor(flatBufferBuilder, |
| 110 | flatBufferBuilder.CreateVector<int32_t>(outputTensorShape.data(), |
| 111 | outputTensorShape.size()), |
| 112 | tensorType, |
Ryan OShea | 238ecd9 | 2023-03-07 11:44:23 +0000 | [diff] [blame] | 113 | 4, |
Sadik Armagan | 6e36a64 | 2020-11-10 21:18:41 +0000 | [diff] [blame] | 114 | flatBufferBuilder.CreateString("output"), |
| 115 | outputQuantizationParameters); |
| 116 | |
| 117 | |
| 118 | // create operator |
| 119 | tflite::BuiltinOptions operatorBuiltinOptionsType = BuiltinOptions_FullyConnectedOptions; |
| 120 | flatbuffers::Offset<void> operatorBuiltinOptions = |
| 121 | CreateFullyConnectedOptions(flatBufferBuilder, |
| 122 | activationType, |
| 123 | FullyConnectedOptionsWeightsFormat_DEFAULT, false).Union(); |
| 124 | |
Keith Davis | 892fafe | 2020-11-26 17:40:35 +0000 | [diff] [blame] | 125 | const std::vector<int> operatorInputs{0, 1, 2}; |
| 126 | const std::vector<int> operatorOutputs{3}; |
Sadik Armagan | 6e36a64 | 2020-11-10 21:18:41 +0000 | [diff] [blame] | 127 | flatbuffers::Offset <Operator> fullyConnectedOperator = |
| 128 | CreateOperator(flatBufferBuilder, |
| 129 | 0, |
| 130 | flatBufferBuilder.CreateVector<int32_t>(operatorInputs.data(), operatorInputs.size()), |
| 131 | flatBufferBuilder.CreateVector<int32_t>(operatorOutputs.data(), operatorOutputs.size()), |
| 132 | operatorBuiltinOptionsType, operatorBuiltinOptions); |
| 133 | |
Keith Davis | 892fafe | 2020-11-26 17:40:35 +0000 | [diff] [blame] | 134 | const std::vector<int> subgraphInputs{0, 1, 2}; |
| 135 | const std::vector<int> subgraphOutputs{3}; |
Sadik Armagan | 6e36a64 | 2020-11-10 21:18:41 +0000 | [diff] [blame] | 136 | flatbuffers::Offset <SubGraph> subgraph = |
| 137 | CreateSubGraph(flatBufferBuilder, |
| 138 | flatBufferBuilder.CreateVector(tensors.data(), tensors.size()), |
| 139 | flatBufferBuilder.CreateVector<int32_t>(subgraphInputs.data(), subgraphInputs.size()), |
| 140 | flatBufferBuilder.CreateVector<int32_t>(subgraphOutputs.data(), subgraphOutputs.size()), |
| 141 | flatBufferBuilder.CreateVector(&fullyConnectedOperator, 1)); |
| 142 | |
| 143 | flatbuffers::Offset <flatbuffers::String> modelDescription = |
| 144 | flatBufferBuilder.CreateString("ArmnnDelegate: FullyConnected Operator Model"); |
| 145 | flatbuffers::Offset <OperatorCode> operatorCode = CreateOperatorCode(flatBufferBuilder, |
| 146 | tflite::BuiltinOperator_FULLY_CONNECTED); |
| 147 | |
| 148 | flatbuffers::Offset <Model> flatbufferModel = |
| 149 | CreateModel(flatBufferBuilder, |
| 150 | TFLITE_SCHEMA_VERSION, |
| 151 | flatBufferBuilder.CreateVector(&operatorCode, 1), |
| 152 | flatBufferBuilder.CreateVector(&subgraph, 1), |
| 153 | modelDescription, |
| 154 | flatBufferBuilder.CreateVector(buffers.data(), buffers.size())); |
| 155 | |
Matthew Sloyan | ebe392d | 2023-03-30 10:12:08 +0100 | [diff] [blame] | 156 | flatBufferBuilder.Finish(flatbufferModel, armnnDelegate::FILE_IDENTIFIER); |
Sadik Armagan | 6e36a64 | 2020-11-10 21:18:41 +0000 | [diff] [blame] | 157 | |
| 158 | return std::vector<char>(flatBufferBuilder.GetBufferPointer(), |
| 159 | flatBufferBuilder.GetBufferPointer() + flatBufferBuilder.GetSize()); |
| 160 | } |
| 161 | |
| 162 | template <typename T> |
Colm Donelan | 7bcae3c | 2024-01-22 10:07:14 +0000 | [diff] [blame] | 163 | void FullyConnectedTest(tflite::TensorType tensorType, |
Sadik Armagan | 6e36a64 | 2020-11-10 21:18:41 +0000 | [diff] [blame] | 164 | tflite::ActivationFunctionType activationType, |
| 165 | const std::vector <int32_t>& inputTensorShape, |
| 166 | const std::vector <int32_t>& weightsTensorShape, |
| 167 | const std::vector <int32_t>& biasTensorShape, |
Sadik Armagan | f0a6dec | 2021-03-25 07:46:55 +0000 | [diff] [blame] | 168 | std::vector <int32_t>& outputTensorShape, |
| 169 | std::vector <T>& inputValues, |
| 170 | std::vector <T>& expectedOutputValues, |
| 171 | std::vector <T>& weightsData, |
Colm Donelan | 7bcae3c | 2024-01-22 10:07:14 +0000 | [diff] [blame] | 172 | const std::vector<armnn::BackendId>& backends = {}, |
Sadik Armagan | f0a6dec | 2021-03-25 07:46:55 +0000 | [diff] [blame] | 173 | bool constantWeights = true, |
Sadik Armagan | 6e36a64 | 2020-11-10 21:18:41 +0000 | [diff] [blame] | 174 | float quantScale = 1.0f, |
| 175 | int quantOffset = 0) |
| 176 | { |
Matthew Sloyan | ebe392d | 2023-03-30 10:12:08 +0100 | [diff] [blame] | 177 | using namespace delegateTestInterpreter; |
Sadik Armagan | 6e36a64 | 2020-11-10 21:18:41 +0000 | [diff] [blame] | 178 | |
| 179 | std::vector<char> modelBuffer = CreateFullyConnectedTfLiteModel(tensorType, |
| 180 | activationType, |
| 181 | inputTensorShape, |
| 182 | weightsTensorShape, |
| 183 | biasTensorShape, |
| 184 | outputTensorShape, |
| 185 | weightsData, |
Sadik Armagan | f0a6dec | 2021-03-25 07:46:55 +0000 | [diff] [blame] | 186 | constantWeights, |
Sadik Armagan | 6e36a64 | 2020-11-10 21:18:41 +0000 | [diff] [blame] | 187 | quantScale, |
| 188 | quantOffset); |
Sadik Armagan | f0a6dec | 2021-03-25 07:46:55 +0000 | [diff] [blame] | 189 | |
Matthew Sloyan | ebe392d | 2023-03-30 10:12:08 +0100 | [diff] [blame] | 190 | // Setup interpreter with just TFLite Runtime. |
| 191 | auto tfLiteInterpreter = DelegateTestInterpreter(modelBuffer); |
| 192 | CHECK(tfLiteInterpreter.AllocateTensors() == kTfLiteOk); |
Sadik Armagan | 6e36a64 | 2020-11-10 21:18:41 +0000 | [diff] [blame] | 193 | |
Matthew Sloyan | ebe392d | 2023-03-30 10:12:08 +0100 | [diff] [blame] | 194 | // Setup interpreter with Arm NN Delegate applied. |
Colm Donelan | 7bcae3c | 2024-01-22 10:07:14 +0000 | [diff] [blame] | 195 | auto armnnInterpreter = DelegateTestInterpreter(modelBuffer, CaptureAvailableBackends(backends)); |
Matthew Sloyan | ebe392d | 2023-03-30 10:12:08 +0100 | [diff] [blame] | 196 | CHECK(armnnInterpreter.AllocateTensors() == kTfLiteOk); |
Sadik Armagan | 6e36a64 | 2020-11-10 21:18:41 +0000 | [diff] [blame] | 197 | |
Matthew Sloyan | ebe392d | 2023-03-30 10:12:08 +0100 | [diff] [blame] | 198 | CHECK(tfLiteInterpreter.FillInputTensor<T>(inputValues, 0) == kTfLiteOk); |
| 199 | CHECK(armnnInterpreter.FillInputTensor<T>(inputValues, 0) == kTfLiteOk); |
Sadik Armagan | 6e36a64 | 2020-11-10 21:18:41 +0000 | [diff] [blame] | 200 | |
Sadik Armagan | f0a6dec | 2021-03-25 07:46:55 +0000 | [diff] [blame] | 201 | if (!constantWeights) |
Sadik Armagan | 6e36a64 | 2020-11-10 21:18:41 +0000 | [diff] [blame] | 202 | { |
Matthew Sloyan | ebe392d | 2023-03-30 10:12:08 +0100 | [diff] [blame] | 203 | CHECK(tfLiteInterpreter.FillInputTensor<T>(weightsData, 1) == kTfLiteOk); |
| 204 | CHECK(armnnInterpreter.FillInputTensor<T>(weightsData, 1) == kTfLiteOk); |
Sadik Armagan | f0a6dec | 2021-03-25 07:46:55 +0000 | [diff] [blame] | 205 | |
| 206 | if (tensorType == ::tflite::TensorType_INT8) |
| 207 | { |
| 208 | std::vector <int32_t> biasData = {10}; |
Matthew Sloyan | ebe392d | 2023-03-30 10:12:08 +0100 | [diff] [blame] | 209 | CHECK(tfLiteInterpreter.FillInputTensor<int32_t>(biasData, 2) == kTfLiteOk); |
| 210 | CHECK(armnnInterpreter.FillInputTensor<int32_t>(biasData, 2) == kTfLiteOk); |
Sadik Armagan | f0a6dec | 2021-03-25 07:46:55 +0000 | [diff] [blame] | 211 | } |
| 212 | else |
| 213 | { |
| 214 | std::vector<float> biasData = {10}; |
Matthew Sloyan | ebe392d | 2023-03-30 10:12:08 +0100 | [diff] [blame] | 215 | CHECK(tfLiteInterpreter.FillInputTensor<float>(biasData, 2) == kTfLiteOk); |
| 216 | CHECK(armnnInterpreter.FillInputTensor<float>(biasData, 2) == kTfLiteOk); |
Sadik Armagan | f0a6dec | 2021-03-25 07:46:55 +0000 | [diff] [blame] | 217 | } |
Sadik Armagan | 6e36a64 | 2020-11-10 21:18:41 +0000 | [diff] [blame] | 218 | } |
| 219 | |
Matthew Sloyan | ebe392d | 2023-03-30 10:12:08 +0100 | [diff] [blame] | 220 | CHECK(tfLiteInterpreter.Invoke() == kTfLiteOk); |
| 221 | std::vector<T> tfLiteOutputValues = tfLiteInterpreter.GetOutputResult<T>(0); |
| 222 | std::vector<int32_t> tfLiteOutputShape = tfLiteInterpreter.GetOutputShape(0); |
Sadik Armagan | 6e36a64 | 2020-11-10 21:18:41 +0000 | [diff] [blame] | 223 | |
Matthew Sloyan | ebe392d | 2023-03-30 10:12:08 +0100 | [diff] [blame] | 224 | CHECK(armnnInterpreter.Invoke() == kTfLiteOk); |
| 225 | std::vector<T> armnnOutputValues = armnnInterpreter.GetOutputResult<T>(0); |
| 226 | std::vector<int32_t> armnnOutputShape = armnnInterpreter.GetOutputShape(0); |
| 227 | |
| 228 | armnnDelegate::CompareOutputData<T>(tfLiteOutputValues, armnnOutputValues, expectedOutputValues); |
| 229 | armnnDelegate::CompareOutputShape(tfLiteOutputShape, armnnOutputShape, outputTensorShape); |
| 230 | |
| 231 | tfLiteInterpreter.Cleanup(); |
| 232 | armnnInterpreter.Cleanup(); |
Sadik Armagan | 6e36a64 | 2020-11-10 21:18:41 +0000 | [diff] [blame] | 233 | } |
| 234 | |
| 235 | } // anonymous namespace |