Sadik Armagan | a274748 | 2021-02-09 10:28:54 +0000 | [diff] [blame] | 1 | // |
Colm Donelan | 7bcae3c | 2024-01-22 10:07:14 +0000 | [diff] [blame] | 2 | // Copyright © 2021, 2023-2024 Arm Ltd and Contributors. All rights reserved. |
Sadik Armagan | a274748 | 2021-02-09 10:28:54 +0000 | [diff] [blame] | 3 | // SPDX-License-Identifier: MIT |
| 4 | // |
| 5 | |
| 6 | #pragma once |
| 7 | |
| 8 | #include "TestUtils.hpp" |
| 9 | |
| 10 | #include <armnn_delegate.hpp> |
Matthew Sloyan | ebe392d | 2023-03-30 10:12:08 +0100 | [diff] [blame] | 11 | #include <DelegateTestInterpreter.hpp> |
Sadik Armagan | a274748 | 2021-02-09 10:28:54 +0000 | [diff] [blame] | 12 | |
Sadik Armagan | a274748 | 2021-02-09 10:28:54 +0000 | [diff] [blame] | 13 | #include <tensorflow/lite/version.h> |
| 14 | |
Sadik Armagan | a274748 | 2021-02-09 10:28:54 +0000 | [diff] [blame] | 15 | namespace |
| 16 | { |
| 17 | |
| 18 | std::vector<char> CreateReduceTfLiteModel(tflite::BuiltinOperator reduceOperatorCode, |
Teresa Charlin | 4d85adf | 2022-10-27 11:37:29 +0100 | [diff] [blame] | 19 | tflite::TensorType tensorType, |
| 20 | std::vector<int32_t>& input0TensorShape, |
| 21 | std::vector<int32_t>& input1TensorShape, |
| 22 | const std::vector <int32_t>& outputTensorShape, |
| 23 | std::vector<int32_t>& axisData, |
| 24 | const bool keepDims, |
| 25 | float quantScale = 1.0f, |
| 26 | int quantOffset = 0, |
| 27 | bool kTfLiteNoQuantizationForQuantized = false) |
Sadik Armagan | a274748 | 2021-02-09 10:28:54 +0000 | [diff] [blame] | 28 | { |
| 29 | using namespace tflite; |
| 30 | flatbuffers::FlatBufferBuilder flatBufferBuilder; |
| 31 | |
Ryan OShea | 238ecd9 | 2023-03-07 11:44:23 +0000 | [diff] [blame] | 32 | flatbuffers::Offset<tflite::Buffer> buffers[4] = { |
| 33 | CreateBuffer(flatBufferBuilder), |
| 34 | CreateBuffer(flatBufferBuilder), |
| 35 | CreateBuffer(flatBufferBuilder, |
| 36 | flatBufferBuilder.CreateVector(reinterpret_cast<const uint8_t*>(axisData.data()), |
| 37 | sizeof(int32_t) * axisData.size())), |
| 38 | CreateBuffer(flatBufferBuilder) |
| 39 | }; |
Sadik Armagan | a274748 | 2021-02-09 10:28:54 +0000 | [diff] [blame] | 40 | |
Teresa Charlin | 4d85adf | 2022-10-27 11:37:29 +0100 | [diff] [blame] | 41 | flatbuffers::Offset<tflite::QuantizationParameters> quantizationParametersAxis |
Ryan OShea | 238ecd9 | 2023-03-07 11:44:23 +0000 | [diff] [blame] | 42 | = CreateQuantizationParameters(flatBufferBuilder); |
Teresa Charlin | 4d85adf | 2022-10-27 11:37:29 +0100 | [diff] [blame] | 43 | |
| 44 | flatbuffers::Offset<tflite::QuantizationParameters> quantizationParameters; |
| 45 | |
Idriss Chaouch | 08ee1aa | 2023-09-13 13:53:37 +0100 | [diff] [blame] | 46 | if (kTfLiteNoQuantizationForQuantized && reduceOperatorCode == BuiltinOperator_REDUCE_PROD) |
Teresa Charlin | 4d85adf | 2022-10-27 11:37:29 +0100 | [diff] [blame] | 47 | { |
| 48 | if ((quantScale == 1 || quantScale == 0) && quantOffset == 0) |
| 49 | { |
| 50 | // Creates quantization parameter with quantization.type = kTfLiteNoQuantization |
| 51 | quantizationParameters = CreateQuantizationParameters(flatBufferBuilder); |
| 52 | } |
| 53 | else |
| 54 | { |
| 55 | // Creates quantization parameter with quantization.type != kTfLiteNoQuantization |
| 56 | quantizationParameters = CreateQuantizationParameters( |
| 57 | flatBufferBuilder, |
| 58 | 0, |
| 59 | 0, |
| 60 | flatBufferBuilder.CreateVector<float>({quantScale}), |
| 61 | flatBufferBuilder.CreateVector<int64_t>({quantOffset})); |
| 62 | } |
| 63 | } |
| 64 | else |
| 65 | { |
| 66 | quantizationParameters = CreateQuantizationParameters( |
| 67 | flatBufferBuilder, |
| 68 | 0, |
| 69 | 0, |
| 70 | flatBufferBuilder.CreateVector<float>({quantScale}), |
| 71 | flatBufferBuilder.CreateVector<int64_t>({quantOffset})); |
| 72 | } |
Sadik Armagan | a274748 | 2021-02-09 10:28:54 +0000 | [diff] [blame] | 73 | |
| 74 | std::array<flatbuffers::Offset<Tensor>, 3> tensors; |
| 75 | tensors[0] = CreateTensor(flatBufferBuilder, |
| 76 | flatBufferBuilder.CreateVector<int32_t>(input0TensorShape.data(), |
| 77 | input0TensorShape.size()), |
| 78 | tensorType, |
Ryan OShea | 238ecd9 | 2023-03-07 11:44:23 +0000 | [diff] [blame] | 79 | 1, |
Sadik Armagan | a274748 | 2021-02-09 10:28:54 +0000 | [diff] [blame] | 80 | flatBufferBuilder.CreateString("input"), |
| 81 | quantizationParameters); |
| 82 | |
| 83 | tensors[1] = CreateTensor(flatBufferBuilder, |
| 84 | flatBufferBuilder.CreateVector<int32_t>(input1TensorShape.data(), |
| 85 | input1TensorShape.size()), |
| 86 | ::tflite::TensorType_INT32, |
Ryan OShea | 238ecd9 | 2023-03-07 11:44:23 +0000 | [diff] [blame] | 87 | 2, |
Sadik Armagan | a274748 | 2021-02-09 10:28:54 +0000 | [diff] [blame] | 88 | flatBufferBuilder.CreateString("axis"), |
Teresa Charlin | 4d85adf | 2022-10-27 11:37:29 +0100 | [diff] [blame] | 89 | quantizationParametersAxis); |
Sadik Armagan | a274748 | 2021-02-09 10:28:54 +0000 | [diff] [blame] | 90 | |
| 91 | // Create output tensor |
| 92 | tensors[2] = CreateTensor(flatBufferBuilder, |
| 93 | flatBufferBuilder.CreateVector<int32_t>(outputTensorShape.data(), |
| 94 | outputTensorShape.size()), |
| 95 | tensorType, |
Ryan OShea | 238ecd9 | 2023-03-07 11:44:23 +0000 | [diff] [blame] | 96 | 3, |
Sadik Armagan | a274748 | 2021-02-09 10:28:54 +0000 | [diff] [blame] | 97 | flatBufferBuilder.CreateString("output"), |
| 98 | quantizationParameters); |
| 99 | |
Teresa Charlin | 4d85adf | 2022-10-27 11:37:29 +0100 | [diff] [blame] | 100 | // Create operator. Reduce operations MIN, MAX, SUM, MEAN, PROD uses ReducerOptions. |
Sadik Armagan | a274748 | 2021-02-09 10:28:54 +0000 | [diff] [blame] | 101 | tflite::BuiltinOptions operatorBuiltinOptionsType = tflite::BuiltinOptions_ReducerOptions; |
| 102 | flatbuffers::Offset<void> operatorBuiltinOptions = CreateReducerOptions(flatBufferBuilder, keepDims).Union(); |
| 103 | |
| 104 | const std::vector<int> operatorInputs{ {0, 1} }; |
| 105 | const std::vector<int> operatorOutputs{ 2 }; |
| 106 | flatbuffers::Offset <Operator> reduceOperator = |
| 107 | CreateOperator(flatBufferBuilder, |
| 108 | 0, |
| 109 | flatBufferBuilder.CreateVector<int32_t>(operatorInputs.data(), operatorInputs.size()), |
| 110 | flatBufferBuilder.CreateVector<int32_t>(operatorOutputs.data(), operatorOutputs.size()), |
| 111 | operatorBuiltinOptionsType, |
| 112 | operatorBuiltinOptions); |
| 113 | |
| 114 | const std::vector<int> subgraphInputs{ {0, 1} }; |
| 115 | const std::vector<int> subgraphOutputs{ 2 }; |
| 116 | flatbuffers::Offset <SubGraph> subgraph = |
| 117 | CreateSubGraph(flatBufferBuilder, |
| 118 | flatBufferBuilder.CreateVector(tensors.data(), tensors.size()), |
| 119 | flatBufferBuilder.CreateVector<int32_t>(subgraphInputs.data(), subgraphInputs.size()), |
| 120 | flatBufferBuilder.CreateVector<int32_t>(subgraphOutputs.data(), subgraphOutputs.size()), |
| 121 | flatBufferBuilder.CreateVector(&reduceOperator, 1)); |
| 122 | |
| 123 | flatbuffers::Offset <flatbuffers::String> modelDescription = |
| 124 | flatBufferBuilder.CreateString("ArmnnDelegate: Reduce Operator Model"); |
| 125 | flatbuffers::Offset <OperatorCode> operatorCode = CreateOperatorCode(flatBufferBuilder, reduceOperatorCode); |
| 126 | |
| 127 | flatbuffers::Offset <Model> flatbufferModel = |
| 128 | CreateModel(flatBufferBuilder, |
| 129 | TFLITE_SCHEMA_VERSION, |
| 130 | flatBufferBuilder.CreateVector(&operatorCode, 1), |
| 131 | flatBufferBuilder.CreateVector(&subgraph, 1), |
| 132 | modelDescription, |
Ryan OShea | 238ecd9 | 2023-03-07 11:44:23 +0000 | [diff] [blame] | 133 | flatBufferBuilder.CreateVector(buffers, 4)); |
Sadik Armagan | a274748 | 2021-02-09 10:28:54 +0000 | [diff] [blame] | 134 | |
Matthew Sloyan | ebe392d | 2023-03-30 10:12:08 +0100 | [diff] [blame] | 135 | flatBufferBuilder.Finish(flatbufferModel, armnnDelegate::FILE_IDENTIFIER); |
Sadik Armagan | a274748 | 2021-02-09 10:28:54 +0000 | [diff] [blame] | 136 | |
| 137 | return std::vector<char>(flatBufferBuilder.GetBufferPointer(), |
| 138 | flatBufferBuilder.GetBufferPointer() + flatBufferBuilder.GetSize()); |
| 139 | } |
| 140 | |
| 141 | template <typename T> |
| 142 | void ReduceTest(tflite::BuiltinOperator reduceOperatorCode, |
| 143 | tflite::TensorType tensorType, |
Sadik Armagan | a274748 | 2021-02-09 10:28:54 +0000 | [diff] [blame] | 144 | std::vector<int32_t>& input0Shape, |
| 145 | std::vector<int32_t>& input1Shape, |
| 146 | std::vector<int32_t>& expectedOutputShape, |
| 147 | std::vector<T>& input0Values, |
| 148 | std::vector<int32_t>& input1Values, |
| 149 | std::vector<T>& expectedOutputValues, |
| 150 | const bool keepDims, |
Colm Donelan | 7bcae3c | 2024-01-22 10:07:14 +0000 | [diff] [blame] | 151 | const std::vector<armnn::BackendId>& backends = {}, |
Sadik Armagan | a274748 | 2021-02-09 10:28:54 +0000 | [diff] [blame] | 152 | float quantScale = 1.0f, |
| 153 | int quantOffset = 0) |
| 154 | { |
Matthew Sloyan | ebe392d | 2023-03-30 10:12:08 +0100 | [diff] [blame] | 155 | using namespace delegateTestInterpreter; |
Teresa Charlin | 4d85adf | 2022-10-27 11:37:29 +0100 | [diff] [blame] | 156 | std::vector<char> modelBufferArmNN = CreateReduceTfLiteModel(reduceOperatorCode, |
| 157 | tensorType, |
| 158 | input0Shape, |
| 159 | input1Shape, |
| 160 | expectedOutputShape, |
| 161 | input1Values, |
| 162 | keepDims, |
| 163 | quantScale, |
| 164 | quantOffset, |
| 165 | false); |
| 166 | std::vector<char> modelBufferTFLite = CreateReduceTfLiteModel(reduceOperatorCode, |
| 167 | tensorType, |
| 168 | input0Shape, |
| 169 | input1Shape, |
| 170 | expectedOutputShape, |
| 171 | input1Values, |
| 172 | keepDims, |
| 173 | quantScale, |
| 174 | quantOffset, |
| 175 | true); |
Sadik Armagan | a274748 | 2021-02-09 10:28:54 +0000 | [diff] [blame] | 176 | |
Matthew Sloyan | ebe392d | 2023-03-30 10:12:08 +0100 | [diff] [blame] | 177 | // Setup interpreter with just TFLite Runtime. |
| 178 | auto tfLiteInterpreter = DelegateTestInterpreter(modelBufferTFLite); |
| 179 | CHECK(tfLiteInterpreter.AllocateTensors() == kTfLiteOk); |
| 180 | CHECK(tfLiteInterpreter.FillInputTensor<T>(input0Values, 0) == kTfLiteOk); |
| 181 | CHECK(tfLiteInterpreter.Invoke() == kTfLiteOk); |
| 182 | std::vector<T> tfLiteOutputValues = tfLiteInterpreter.GetOutputResult<T>(0); |
| 183 | std::vector<int32_t> tfLiteOutputShape = tfLiteInterpreter.GetOutputShape(0); |
Sadik Armagan | a274748 | 2021-02-09 10:28:54 +0000 | [diff] [blame] | 184 | |
Matthew Sloyan | ebe392d | 2023-03-30 10:12:08 +0100 | [diff] [blame] | 185 | // Setup interpreter with Arm NN Delegate applied. |
Colm Donelan | 7bcae3c | 2024-01-22 10:07:14 +0000 | [diff] [blame] | 186 | auto armnnInterpreter = DelegateTestInterpreter(modelBufferArmNN, CaptureAvailableBackends(backends)); |
Matthew Sloyan | ebe392d | 2023-03-30 10:12:08 +0100 | [diff] [blame] | 187 | CHECK(armnnInterpreter.AllocateTensors() == kTfLiteOk); |
| 188 | CHECK(armnnInterpreter.FillInputTensor<T>(input0Values, 0) == kTfLiteOk); |
| 189 | CHECK(armnnInterpreter.Invoke() == kTfLiteOk); |
| 190 | std::vector<T> armnnOutputValues = armnnInterpreter.GetOutputResult<T>(0); |
| 191 | std::vector<int32_t> armnnOutputShape = armnnInterpreter.GetOutputShape(0); |
Sadik Armagan | a274748 | 2021-02-09 10:28:54 +0000 | [diff] [blame] | 192 | |
Matthew Sloyan | ebe392d | 2023-03-30 10:12:08 +0100 | [diff] [blame] | 193 | armnnDelegate::CompareOutputData<T>(tfLiteOutputValues, armnnOutputValues, expectedOutputValues); |
| 194 | armnnDelegate::CompareOutputShape(tfLiteOutputShape, armnnOutputShape, expectedOutputShape); |
Sadik Armagan | a274748 | 2021-02-09 10:28:54 +0000 | [diff] [blame] | 195 | |
Matthew Sloyan | ebe392d | 2023-03-30 10:12:08 +0100 | [diff] [blame] | 196 | tfLiteInterpreter.Cleanup(); |
| 197 | armnnInterpreter.Cleanup(); |
Sadik Armagan | a274748 | 2021-02-09 10:28:54 +0000 | [diff] [blame] | 198 | } |
| 199 | |
| 200 | } // anonymous namespace |