Sadik Armagan | dc032fc | 2021-01-19 17:24:21 +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 | dc032fc | 2021-01-19 17:24:21 +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 | dc032fc | 2021-01-19 17:24:21 +0000 | [diff] [blame] | 12 | |
Sadik Armagan | dc032fc | 2021-01-19 17:24:21 +0000 | [diff] [blame] | 13 | #include <tensorflow/lite/version.h> |
| 14 | |
Sadik Armagan | dc032fc | 2021-01-19 17:24:21 +0000 | [diff] [blame] | 15 | namespace |
| 16 | { |
| 17 | |
| 18 | template <typename InputT, typename OutputT> |
| 19 | std::vector<char> CreateArgMinMaxTfLiteModel(tflite::BuiltinOperator argMinMaxOperatorCode, |
| 20 | tflite::TensorType tensorType, |
| 21 | const std::vector<int32_t>& inputTensorShape, |
| 22 | const std::vector<int32_t>& axisTensorShape, |
| 23 | const std::vector<int32_t>& outputTensorShape, |
| 24 | const std::vector<OutputT> axisValue, |
| 25 | tflite::TensorType outputType, |
| 26 | float quantScale = 1.0f, |
| 27 | int quantOffset = 0) |
| 28 | { |
| 29 | using namespace tflite; |
| 30 | flatbuffers::FlatBufferBuilder flatBufferBuilder; |
| 31 | |
| 32 | auto quantizationParameters = |
| 33 | CreateQuantizationParameters(flatBufferBuilder, |
| 34 | 0, |
| 35 | 0, |
| 36 | flatBufferBuilder.CreateVector<float>({ quantScale }), |
| 37 | flatBufferBuilder.CreateVector<int64_t>({ quantOffset })); |
| 38 | |
| 39 | auto inputTensor = CreateTensor(flatBufferBuilder, |
| 40 | flatBufferBuilder.CreateVector<int32_t>(inputTensorShape.data(), |
| 41 | inputTensorShape.size()), |
| 42 | tensorType, |
Ryan OShea | 238ecd9 | 2023-03-07 11:44:23 +0000 | [diff] [blame] | 43 | 1, |
Sadik Armagan | dc032fc | 2021-01-19 17:24:21 +0000 | [diff] [blame] | 44 | flatBufferBuilder.CreateString("input"), |
| 45 | quantizationParameters); |
| 46 | |
| 47 | auto axisTensor = CreateTensor(flatBufferBuilder, |
| 48 | flatBufferBuilder.CreateVector<int32_t>(axisTensorShape.data(), |
| 49 | axisTensorShape.size()), |
| 50 | tflite::TensorType_INT32, |
Ryan OShea | 238ecd9 | 2023-03-07 11:44:23 +0000 | [diff] [blame] | 51 | 2, |
Sadik Armagan | dc032fc | 2021-01-19 17:24:21 +0000 | [diff] [blame] | 52 | flatBufferBuilder.CreateString("axis")); |
| 53 | |
| 54 | auto outputTensor = CreateTensor(flatBufferBuilder, |
| 55 | flatBufferBuilder.CreateVector<int32_t>(outputTensorShape.data(), |
| 56 | outputTensorShape.size()), |
| 57 | outputType, |
Ryan OShea | 238ecd9 | 2023-03-07 11:44:23 +0000 | [diff] [blame] | 58 | 3, |
Sadik Armagan | dc032fc | 2021-01-19 17:24:21 +0000 | [diff] [blame] | 59 | flatBufferBuilder.CreateString("output"), |
| 60 | quantizationParameters); |
| 61 | |
| 62 | std::vector<flatbuffers::Offset<Tensor>> tensors = { inputTensor, axisTensor, outputTensor }; |
| 63 | |
| 64 | std::vector<flatbuffers::Offset<tflite::Buffer>> buffers; |
Ryan OShea | 238ecd9 | 2023-03-07 11:44:23 +0000 | [diff] [blame] | 65 | buffers.push_back(CreateBuffer(flatBufferBuilder)); |
| 66 | buffers.push_back(CreateBuffer(flatBufferBuilder)); |
Sadik Armagan | dc032fc | 2021-01-19 17:24:21 +0000 | [diff] [blame] | 67 | buffers.push_back( |
| 68 | CreateBuffer(flatBufferBuilder, |
| 69 | flatBufferBuilder.CreateVector(reinterpret_cast<const uint8_t*>(axisValue.data()), |
| 70 | sizeof(OutputT)))); |
Ryan OShea | 238ecd9 | 2023-03-07 11:44:23 +0000 | [diff] [blame] | 71 | buffers.push_back(CreateBuffer(flatBufferBuilder)); |
Sadik Armagan | dc032fc | 2021-01-19 17:24:21 +0000 | [diff] [blame] | 72 | |
| 73 | std::vector<int32_t> operatorInputs = {{ 0, 1 }}; |
| 74 | std::vector<int> subgraphInputs = {{ 0, 1 }}; |
| 75 | |
| 76 | tflite::BuiltinOptions operatorBuiltinOptionsType = BuiltinOptions_ArgMaxOptions; |
| 77 | flatbuffers::Offset<void> operatorBuiltinOptions = CreateArgMaxOptions(flatBufferBuilder, outputType).Union(); |
| 78 | |
| 79 | if (argMinMaxOperatorCode == tflite::BuiltinOperator_ARG_MIN) |
| 80 | { |
| 81 | operatorBuiltinOptionsType = BuiltinOptions_ArgMinOptions; |
| 82 | operatorBuiltinOptions = CreateArgMinOptions(flatBufferBuilder, outputType).Union(); |
| 83 | } |
| 84 | |
| 85 | // create operator |
Keith Davis | bbc876c | 2021-01-27 13:12:03 +0000 | [diff] [blame] | 86 | const std::vector<int32_t> operatorOutputs{ 2 }; |
Sadik Armagan | dc032fc | 2021-01-19 17:24:21 +0000 | [diff] [blame] | 87 | flatbuffers::Offset <Operator> argMinMaxOperator = |
| 88 | CreateOperator(flatBufferBuilder, |
| 89 | 0, |
| 90 | flatBufferBuilder.CreateVector<int32_t>(operatorInputs.data(), operatorInputs.size()), |
| 91 | flatBufferBuilder.CreateVector<int32_t>(operatorOutputs.data(), operatorOutputs.size()), |
| 92 | operatorBuiltinOptionsType, |
| 93 | operatorBuiltinOptions); |
| 94 | |
Keith Davis | bbc876c | 2021-01-27 13:12:03 +0000 | [diff] [blame] | 95 | const std::vector<int> subgraphOutputs{ 2 }; |
Sadik Armagan | dc032fc | 2021-01-19 17:24:21 +0000 | [diff] [blame] | 96 | flatbuffers::Offset <SubGraph> subgraph = |
| 97 | CreateSubGraph(flatBufferBuilder, |
| 98 | flatBufferBuilder.CreateVector(tensors.data(), tensors.size()), |
| 99 | flatBufferBuilder.CreateVector<int32_t>(subgraphInputs.data(), subgraphInputs.size()), |
| 100 | flatBufferBuilder.CreateVector<int32_t>(subgraphOutputs.data(), subgraphOutputs.size()), |
| 101 | flatBufferBuilder.CreateVector(&argMinMaxOperator, 1)); |
| 102 | |
| 103 | flatbuffers::Offset <flatbuffers::String> modelDescription = |
| 104 | flatBufferBuilder.CreateString("ArmnnDelegate: ArgMinMax Operator Model"); |
| 105 | flatbuffers::Offset <OperatorCode> operatorCode = CreateOperatorCode(flatBufferBuilder, |
| 106 | argMinMaxOperatorCode); |
| 107 | |
| 108 | flatbuffers::Offset <Model> flatbufferModel = |
| 109 | CreateModel(flatBufferBuilder, |
| 110 | TFLITE_SCHEMA_VERSION, |
| 111 | flatBufferBuilder.CreateVector(&operatorCode, 1), |
| 112 | flatBufferBuilder.CreateVector(&subgraph, 1), |
| 113 | modelDescription, |
| 114 | flatBufferBuilder.CreateVector(buffers.data(), buffers.size())); |
| 115 | |
Matthew Sloyan | ebe392d | 2023-03-30 10:12:08 +0100 | [diff] [blame] | 116 | flatBufferBuilder.Finish(flatbufferModel, armnnDelegate::FILE_IDENTIFIER); |
Sadik Armagan | dc032fc | 2021-01-19 17:24:21 +0000 | [diff] [blame] | 117 | |
| 118 | return std::vector<char>(flatBufferBuilder.GetBufferPointer(), |
| 119 | flatBufferBuilder.GetBufferPointer() + flatBufferBuilder.GetSize()); |
| 120 | } |
| 121 | |
| 122 | template <typename InputT, typename OutputT> |
| 123 | void ArgMinMaxTest(tflite::BuiltinOperator argMinMaxOperatorCode, |
| 124 | tflite::TensorType tensorType, |
Sadik Armagan | dc032fc | 2021-01-19 17:24:21 +0000 | [diff] [blame] | 125 | const std::vector<int32_t>& inputShape, |
| 126 | const std::vector<int32_t>& axisShape, |
| 127 | std::vector<int32_t>& outputShape, |
| 128 | std::vector<InputT>& inputValues, |
| 129 | std::vector<OutputT>& expectedOutputValues, |
| 130 | OutputT axisValue, |
| 131 | tflite::TensorType outputType, |
| 132 | float quantScale = 1.0f, |
Colm Donelan | eff204a | 2023-11-28 15:46:09 +0000 | [diff] [blame] | 133 | int quantOffset = 0, |
| 134 | const std::vector<armnn::BackendId>& backends = {}) |
Sadik Armagan | dc032fc | 2021-01-19 17:24:21 +0000 | [diff] [blame] | 135 | { |
Matthew Sloyan | ebe392d | 2023-03-30 10:12:08 +0100 | [diff] [blame] | 136 | using namespace delegateTestInterpreter; |
Sadik Armagan | dc032fc | 2021-01-19 17:24:21 +0000 | [diff] [blame] | 137 | std::vector<char> modelBuffer = CreateArgMinMaxTfLiteModel<InputT, OutputT>(argMinMaxOperatorCode, |
| 138 | tensorType, |
| 139 | inputShape, |
| 140 | axisShape, |
| 141 | outputShape, |
| 142 | {axisValue}, |
| 143 | outputType, |
| 144 | quantScale, |
| 145 | quantOffset); |
| 146 | |
Matthew Sloyan | ebe392d | 2023-03-30 10:12:08 +0100 | [diff] [blame] | 147 | // Setup interpreter with just TFLite Runtime. |
| 148 | auto tfLiteInterpreter = DelegateTestInterpreter(modelBuffer); |
| 149 | CHECK(tfLiteInterpreter.AllocateTensors() == kTfLiteOk); |
| 150 | CHECK(tfLiteInterpreter.FillInputTensor<InputT>(inputValues, 0) == kTfLiteOk); |
| 151 | CHECK(tfLiteInterpreter.Invoke() == kTfLiteOk); |
| 152 | std::vector<OutputT> tfLiteOutputValues = tfLiteInterpreter.GetOutputResult<OutputT>(0); |
| 153 | std::vector<int32_t> tfLiteOutputShape = tfLiteInterpreter.GetOutputShape(0); |
Sadik Armagan | dc032fc | 2021-01-19 17:24:21 +0000 | [diff] [blame] | 154 | |
Matthew Sloyan | ebe392d | 2023-03-30 10:12:08 +0100 | [diff] [blame] | 155 | // Setup interpreter with Arm NN Delegate applied. |
Colm Donelan | eff204a | 2023-11-28 15:46:09 +0000 | [diff] [blame] | 156 | auto armnnInterpreter = DelegateTestInterpreter(modelBuffer, CaptureAvailableBackends(backends)); |
Matthew Sloyan | ebe392d | 2023-03-30 10:12:08 +0100 | [diff] [blame] | 157 | CHECK(armnnInterpreter.AllocateTensors() == kTfLiteOk); |
| 158 | CHECK(armnnInterpreter.FillInputTensor<InputT>(inputValues, 0) == kTfLiteOk); |
| 159 | CHECK(armnnInterpreter.Invoke() == kTfLiteOk); |
| 160 | std::vector<OutputT> armnnOutputValues = armnnInterpreter.GetOutputResult<OutputT>(0); |
| 161 | std::vector<int32_t> armnnOutputShape = armnnInterpreter.GetOutputShape(0); |
Sadik Armagan | dc032fc | 2021-01-19 17:24:21 +0000 | [diff] [blame] | 162 | |
Matthew Sloyan | ebe392d | 2023-03-30 10:12:08 +0100 | [diff] [blame] | 163 | armnnDelegate::CompareOutputData<OutputT>(tfLiteOutputValues, armnnOutputValues, expectedOutputValues); |
| 164 | armnnDelegate::CompareOutputShape(tfLiteOutputShape, armnnOutputShape, outputShape); |
Sadik Armagan | dc032fc | 2021-01-19 17:24:21 +0000 | [diff] [blame] | 165 | |
Matthew Sloyan | ebe392d | 2023-03-30 10:12:08 +0100 | [diff] [blame] | 166 | tfLiteInterpreter.Cleanup(); |
| 167 | armnnInterpreter.Cleanup(); |
Sadik Armagan | dc032fc | 2021-01-19 17:24:21 +0000 | [diff] [blame] | 168 | } |
| 169 | |
| 170 | } // anonymous namespace |