Sadik Armagan | a274748 | 2021-02-09 10:28:54 +0000 | [diff] [blame] | 1 | // |
Ryan OShea | 238ecd9 | 2023-03-07 11:44:23 +0000 | [diff] [blame] | 2 | // Copyright © 2021, 2023 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> |
| 11 | |
| 12 | #include <flatbuffers/flatbuffers.h> |
| 13 | #include <tensorflow/lite/interpreter.h> |
| 14 | #include <tensorflow/lite/kernels/register.h> |
| 15 | #include <tensorflow/lite/model.h> |
Teresa Charlin | ad1b3d7 | 2023-03-14 12:10:28 +0000 | [diff] [blame^] | 16 | #include <schema_generated.h> |
Sadik Armagan | a274748 | 2021-02-09 10:28:54 +0000 | [diff] [blame] | 17 | #include <tensorflow/lite/version.h> |
| 18 | |
| 19 | #include <doctest/doctest.h> |
| 20 | |
| 21 | #include <string> |
| 22 | |
| 23 | namespace |
| 24 | { |
| 25 | |
| 26 | std::vector<char> CreateReduceTfLiteModel(tflite::BuiltinOperator reduceOperatorCode, |
Teresa Charlin | 4d85adf | 2022-10-27 11:37:29 +0100 | [diff] [blame] | 27 | tflite::TensorType tensorType, |
| 28 | std::vector<int32_t>& input0TensorShape, |
| 29 | std::vector<int32_t>& input1TensorShape, |
| 30 | const std::vector <int32_t>& outputTensorShape, |
| 31 | std::vector<int32_t>& axisData, |
| 32 | const bool keepDims, |
| 33 | float quantScale = 1.0f, |
| 34 | int quantOffset = 0, |
| 35 | bool kTfLiteNoQuantizationForQuantized = false) |
Sadik Armagan | a274748 | 2021-02-09 10:28:54 +0000 | [diff] [blame] | 36 | { |
| 37 | using namespace tflite; |
| 38 | flatbuffers::FlatBufferBuilder flatBufferBuilder; |
| 39 | |
Ryan OShea | 238ecd9 | 2023-03-07 11:44:23 +0000 | [diff] [blame] | 40 | flatbuffers::Offset<tflite::Buffer> buffers[4] = { |
| 41 | CreateBuffer(flatBufferBuilder), |
| 42 | CreateBuffer(flatBufferBuilder), |
| 43 | CreateBuffer(flatBufferBuilder, |
| 44 | flatBufferBuilder.CreateVector(reinterpret_cast<const uint8_t*>(axisData.data()), |
| 45 | sizeof(int32_t) * axisData.size())), |
| 46 | CreateBuffer(flatBufferBuilder) |
| 47 | }; |
Sadik Armagan | a274748 | 2021-02-09 10:28:54 +0000 | [diff] [blame] | 48 | |
Teresa Charlin | 4d85adf | 2022-10-27 11:37:29 +0100 | [diff] [blame] | 49 | flatbuffers::Offset<tflite::QuantizationParameters> quantizationParametersAxis |
Ryan OShea | 238ecd9 | 2023-03-07 11:44:23 +0000 | [diff] [blame] | 50 | = CreateQuantizationParameters(flatBufferBuilder); |
Teresa Charlin | 4d85adf | 2022-10-27 11:37:29 +0100 | [diff] [blame] | 51 | |
| 52 | flatbuffers::Offset<tflite::QuantizationParameters> quantizationParameters; |
| 53 | |
| 54 | if (kTfLiteNoQuantizationForQuantized) |
| 55 | { |
| 56 | if ((quantScale == 1 || quantScale == 0) && quantOffset == 0) |
| 57 | { |
| 58 | // Creates quantization parameter with quantization.type = kTfLiteNoQuantization |
| 59 | quantizationParameters = CreateQuantizationParameters(flatBufferBuilder); |
| 60 | } |
| 61 | else |
| 62 | { |
| 63 | // Creates quantization parameter with quantization.type != kTfLiteNoQuantization |
| 64 | quantizationParameters = CreateQuantizationParameters( |
| 65 | flatBufferBuilder, |
| 66 | 0, |
| 67 | 0, |
| 68 | flatBufferBuilder.CreateVector<float>({quantScale}), |
| 69 | flatBufferBuilder.CreateVector<int64_t>({quantOffset})); |
| 70 | } |
| 71 | } |
| 72 | else |
| 73 | { |
| 74 | quantizationParameters = CreateQuantizationParameters( |
| 75 | flatBufferBuilder, |
| 76 | 0, |
| 77 | 0, |
| 78 | flatBufferBuilder.CreateVector<float>({quantScale}), |
| 79 | flatBufferBuilder.CreateVector<int64_t>({quantOffset})); |
| 80 | } |
Sadik Armagan | a274748 | 2021-02-09 10:28:54 +0000 | [diff] [blame] | 81 | |
| 82 | std::array<flatbuffers::Offset<Tensor>, 3> tensors; |
| 83 | tensors[0] = CreateTensor(flatBufferBuilder, |
| 84 | flatBufferBuilder.CreateVector<int32_t>(input0TensorShape.data(), |
| 85 | input0TensorShape.size()), |
| 86 | tensorType, |
Ryan OShea | 238ecd9 | 2023-03-07 11:44:23 +0000 | [diff] [blame] | 87 | 1, |
Sadik Armagan | a274748 | 2021-02-09 10:28:54 +0000 | [diff] [blame] | 88 | flatBufferBuilder.CreateString("input"), |
| 89 | quantizationParameters); |
| 90 | |
| 91 | tensors[1] = CreateTensor(flatBufferBuilder, |
| 92 | flatBufferBuilder.CreateVector<int32_t>(input1TensorShape.data(), |
| 93 | input1TensorShape.size()), |
| 94 | ::tflite::TensorType_INT32, |
Ryan OShea | 238ecd9 | 2023-03-07 11:44:23 +0000 | [diff] [blame] | 95 | 2, |
Sadik Armagan | a274748 | 2021-02-09 10:28:54 +0000 | [diff] [blame] | 96 | flatBufferBuilder.CreateString("axis"), |
Teresa Charlin | 4d85adf | 2022-10-27 11:37:29 +0100 | [diff] [blame] | 97 | quantizationParametersAxis); |
Sadik Armagan | a274748 | 2021-02-09 10:28:54 +0000 | [diff] [blame] | 98 | |
| 99 | // Create output tensor |
| 100 | tensors[2] = CreateTensor(flatBufferBuilder, |
| 101 | flatBufferBuilder.CreateVector<int32_t>(outputTensorShape.data(), |
| 102 | outputTensorShape.size()), |
| 103 | tensorType, |
Ryan OShea | 238ecd9 | 2023-03-07 11:44:23 +0000 | [diff] [blame] | 104 | 3, |
Sadik Armagan | a274748 | 2021-02-09 10:28:54 +0000 | [diff] [blame] | 105 | flatBufferBuilder.CreateString("output"), |
| 106 | quantizationParameters); |
| 107 | |
Teresa Charlin | 4d85adf | 2022-10-27 11:37:29 +0100 | [diff] [blame] | 108 | // Create operator. Reduce operations MIN, MAX, SUM, MEAN, PROD uses ReducerOptions. |
Sadik Armagan | a274748 | 2021-02-09 10:28:54 +0000 | [diff] [blame] | 109 | tflite::BuiltinOptions operatorBuiltinOptionsType = tflite::BuiltinOptions_ReducerOptions; |
| 110 | flatbuffers::Offset<void> operatorBuiltinOptions = CreateReducerOptions(flatBufferBuilder, keepDims).Union(); |
| 111 | |
| 112 | const std::vector<int> operatorInputs{ {0, 1} }; |
| 113 | const std::vector<int> operatorOutputs{ 2 }; |
| 114 | flatbuffers::Offset <Operator> reduceOperator = |
| 115 | CreateOperator(flatBufferBuilder, |
| 116 | 0, |
| 117 | flatBufferBuilder.CreateVector<int32_t>(operatorInputs.data(), operatorInputs.size()), |
| 118 | flatBufferBuilder.CreateVector<int32_t>(operatorOutputs.data(), operatorOutputs.size()), |
| 119 | operatorBuiltinOptionsType, |
| 120 | operatorBuiltinOptions); |
| 121 | |
| 122 | const std::vector<int> subgraphInputs{ {0, 1} }; |
| 123 | const std::vector<int> subgraphOutputs{ 2 }; |
| 124 | flatbuffers::Offset <SubGraph> subgraph = |
| 125 | CreateSubGraph(flatBufferBuilder, |
| 126 | flatBufferBuilder.CreateVector(tensors.data(), tensors.size()), |
| 127 | flatBufferBuilder.CreateVector<int32_t>(subgraphInputs.data(), subgraphInputs.size()), |
| 128 | flatBufferBuilder.CreateVector<int32_t>(subgraphOutputs.data(), subgraphOutputs.size()), |
| 129 | flatBufferBuilder.CreateVector(&reduceOperator, 1)); |
| 130 | |
| 131 | flatbuffers::Offset <flatbuffers::String> modelDescription = |
| 132 | flatBufferBuilder.CreateString("ArmnnDelegate: Reduce Operator Model"); |
| 133 | flatbuffers::Offset <OperatorCode> operatorCode = CreateOperatorCode(flatBufferBuilder, reduceOperatorCode); |
| 134 | |
| 135 | flatbuffers::Offset <Model> flatbufferModel = |
| 136 | CreateModel(flatBufferBuilder, |
| 137 | TFLITE_SCHEMA_VERSION, |
| 138 | flatBufferBuilder.CreateVector(&operatorCode, 1), |
| 139 | flatBufferBuilder.CreateVector(&subgraph, 1), |
| 140 | modelDescription, |
Ryan OShea | 238ecd9 | 2023-03-07 11:44:23 +0000 | [diff] [blame] | 141 | flatBufferBuilder.CreateVector(buffers, 4)); |
Sadik Armagan | a274748 | 2021-02-09 10:28:54 +0000 | [diff] [blame] | 142 | |
| 143 | flatBufferBuilder.Finish(flatbufferModel); |
| 144 | |
| 145 | return std::vector<char>(flatBufferBuilder.GetBufferPointer(), |
| 146 | flatBufferBuilder.GetBufferPointer() + flatBufferBuilder.GetSize()); |
| 147 | } |
| 148 | |
| 149 | template <typename T> |
| 150 | void ReduceTest(tflite::BuiltinOperator reduceOperatorCode, |
| 151 | tflite::TensorType tensorType, |
| 152 | std::vector<armnn::BackendId>& backends, |
| 153 | std::vector<int32_t>& input0Shape, |
| 154 | std::vector<int32_t>& input1Shape, |
| 155 | std::vector<int32_t>& expectedOutputShape, |
| 156 | std::vector<T>& input0Values, |
| 157 | std::vector<int32_t>& input1Values, |
| 158 | std::vector<T>& expectedOutputValues, |
| 159 | const bool keepDims, |
| 160 | float quantScale = 1.0f, |
| 161 | int quantOffset = 0) |
| 162 | { |
| 163 | using namespace tflite; |
Teresa Charlin | 4d85adf | 2022-10-27 11:37:29 +0100 | [diff] [blame] | 164 | std::vector<char> modelBufferArmNN = CreateReduceTfLiteModel(reduceOperatorCode, |
| 165 | tensorType, |
| 166 | input0Shape, |
| 167 | input1Shape, |
| 168 | expectedOutputShape, |
| 169 | input1Values, |
| 170 | keepDims, |
| 171 | quantScale, |
| 172 | quantOffset, |
| 173 | false); |
| 174 | std::vector<char> modelBufferTFLite = CreateReduceTfLiteModel(reduceOperatorCode, |
| 175 | tensorType, |
| 176 | input0Shape, |
| 177 | input1Shape, |
| 178 | expectedOutputShape, |
| 179 | input1Values, |
| 180 | keepDims, |
| 181 | quantScale, |
| 182 | quantOffset, |
| 183 | true); |
Sadik Armagan | a274748 | 2021-02-09 10:28:54 +0000 | [diff] [blame] | 184 | |
Teresa Charlin | 4d85adf | 2022-10-27 11:37:29 +0100 | [diff] [blame] | 185 | const Model* tfLiteModelArmNN = GetModel(modelBufferArmNN.data()); |
| 186 | const Model* tfLiteModelTFLite = GetModel(modelBufferTFLite.data()); |
Sadik Armagan | a274748 | 2021-02-09 10:28:54 +0000 | [diff] [blame] | 187 | |
| 188 | // Create TfLite Interpreters |
| 189 | std::unique_ptr<Interpreter> armnnDelegateInterpreter; |
Teresa Charlin | 4d85adf | 2022-10-27 11:37:29 +0100 | [diff] [blame] | 190 | CHECK(InterpreterBuilder(tfLiteModelArmNN, ::tflite::ops::builtin::BuiltinOpResolver()) |
Sadik Armagan | a274748 | 2021-02-09 10:28:54 +0000 | [diff] [blame] | 191 | (&armnnDelegateInterpreter) == kTfLiteOk); |
| 192 | CHECK(armnnDelegateInterpreter != nullptr); |
| 193 | CHECK(armnnDelegateInterpreter->AllocateTensors() == kTfLiteOk); |
| 194 | |
| 195 | std::unique_ptr<Interpreter> tfLiteInterpreter; |
Teresa Charlin | 4d85adf | 2022-10-27 11:37:29 +0100 | [diff] [blame] | 196 | CHECK(InterpreterBuilder(tfLiteModelTFLite, ::tflite::ops::builtin::BuiltinOpResolver()) |
Sadik Armagan | a274748 | 2021-02-09 10:28:54 +0000 | [diff] [blame] | 197 | (&tfLiteInterpreter) == kTfLiteOk); |
| 198 | CHECK(tfLiteInterpreter != nullptr); |
| 199 | CHECK(tfLiteInterpreter->AllocateTensors() == kTfLiteOk); |
| 200 | |
| 201 | // Create the ArmNN Delegate |
| 202 | armnnDelegate::DelegateOptions delegateOptions(backends); |
| 203 | std::unique_ptr<TfLiteDelegate, decltype(&armnnDelegate::TfLiteArmnnDelegateDelete)> |
| 204 | theArmnnDelegate(armnnDelegate::TfLiteArmnnDelegateCreate(delegateOptions), |
| 205 | armnnDelegate::TfLiteArmnnDelegateDelete); |
| 206 | CHECK(theArmnnDelegate != nullptr); |
| 207 | |
| 208 | // Modify armnnDelegateInterpreter to use armnnDelegate |
| 209 | CHECK(armnnDelegateInterpreter->ModifyGraphWithDelegate(theArmnnDelegate.get()) == kTfLiteOk); |
| 210 | |
| 211 | // Set input data |
| 212 | armnnDelegate::FillInput<T>(tfLiteInterpreter, 0, input0Values); |
| 213 | armnnDelegate::FillInput<T>(armnnDelegateInterpreter, 0, input0Values); |
| 214 | |
| 215 | // Run EnqueWorkload |
| 216 | CHECK(tfLiteInterpreter->Invoke() == kTfLiteOk); |
| 217 | CHECK(armnnDelegateInterpreter->Invoke() == kTfLiteOk); |
| 218 | |
| 219 | // Compare output data |
| 220 | armnnDelegate::CompareOutputData<T>(tfLiteInterpreter, |
| 221 | armnnDelegateInterpreter, |
| 222 | expectedOutputShape, |
| 223 | expectedOutputValues); |
| 224 | |
| 225 | armnnDelegateInterpreter.reset(nullptr); |
| 226 | } |
| 227 | |
| 228 | } // anonymous namespace |