James Conroy | 3982548 | 2021-05-27 17:44:50 +0100 | [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. |
James Conroy | 3982548 | 2021-05-27 17:44:50 +0100 | [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> |
James Conroy | 3982548 | 2021-05-27 17:44:50 +0100 | [diff] [blame] | 12 | |
| 13 | #include <flatbuffers/flatbuffers.h> |
James Conroy | 3982548 | 2021-05-27 17:44:50 +0100 | [diff] [blame] | 14 | #include <tensorflow/lite/kernels/register.h> |
James Conroy | 3982548 | 2021-05-27 17:44:50 +0100 | [diff] [blame] | 15 | #include <tensorflow/lite/version.h> |
| 16 | |
Matthew Sloyan | ebe392d | 2023-03-30 10:12:08 +0100 | [diff] [blame] | 17 | #include <schema_generated.h> |
| 18 | |
James Conroy | 3982548 | 2021-05-27 17:44:50 +0100 | [diff] [blame] | 19 | #include <doctest/doctest.h> |
| 20 | |
| 21 | namespace |
| 22 | { |
| 23 | |
| 24 | std::vector<char> CreatePreluTfLiteModel(tflite::BuiltinOperator preluOperatorCode, |
| 25 | tflite::TensorType tensorType, |
| 26 | const std::vector<int32_t>& inputShape, |
| 27 | const std::vector<int32_t>& alphaShape, |
| 28 | const std::vector<int32_t>& outputShape, |
| 29 | std::vector<float>& alphaData, |
| 30 | bool alphaIsConstant) |
| 31 | { |
| 32 | using namespace tflite; |
| 33 | flatbuffers::FlatBufferBuilder flatBufferBuilder; |
| 34 | |
| 35 | std::vector<flatbuffers::Offset<tflite::Buffer>> buffers; |
Ryan OShea | 238ecd9 | 2023-03-07 11:44:23 +0000 | [diff] [blame] | 36 | buffers.push_back(CreateBuffer(flatBufferBuilder)); |
| 37 | buffers.push_back(CreateBuffer(flatBufferBuilder)); |
James Conroy | 3982548 | 2021-05-27 17:44:50 +0100 | [diff] [blame] | 38 | buffers.push_back(CreateBuffer(flatBufferBuilder, flatBufferBuilder.CreateVector( |
| 39 | reinterpret_cast<const uint8_t *>(alphaData.data()), sizeof(float) * alphaData.size()))); |
Ryan OShea | 238ecd9 | 2023-03-07 11:44:23 +0000 | [diff] [blame] | 40 | buffers.push_back(CreateBuffer(flatBufferBuilder)); |
| 41 | |
James Conroy | 3982548 | 2021-05-27 17:44:50 +0100 | [diff] [blame] | 42 | |
| 43 | auto quantizationParameters = |
| 44 | CreateQuantizationParameters(flatBufferBuilder, |
| 45 | 0, |
| 46 | 0, |
| 47 | flatBufferBuilder.CreateVector<float>({ 1.0f }), |
| 48 | flatBufferBuilder.CreateVector<int64_t>({ 0 })); |
| 49 | |
| 50 | auto inputTensor = CreateTensor(flatBufferBuilder, |
| 51 | flatBufferBuilder.CreateVector<int32_t>(inputShape.data(), |
| 52 | inputShape.size()), |
| 53 | tensorType, |
Ryan OShea | 238ecd9 | 2023-03-07 11:44:23 +0000 | [diff] [blame] | 54 | 1, |
James Conroy | 3982548 | 2021-05-27 17:44:50 +0100 | [diff] [blame] | 55 | flatBufferBuilder.CreateString("input"), |
| 56 | quantizationParameters); |
| 57 | |
| 58 | auto alphaTensor = CreateTensor(flatBufferBuilder, |
| 59 | flatBufferBuilder.CreateVector<int32_t>(alphaShape.data(), |
| 60 | alphaShape.size()), |
| 61 | tensorType, |
Ryan OShea | 238ecd9 | 2023-03-07 11:44:23 +0000 | [diff] [blame] | 62 | 2, |
James Conroy | 3982548 | 2021-05-27 17:44:50 +0100 | [diff] [blame] | 63 | flatBufferBuilder.CreateString("alpha"), |
| 64 | quantizationParameters); |
| 65 | |
| 66 | auto outputTensor = CreateTensor(flatBufferBuilder, |
| 67 | flatBufferBuilder.CreateVector<int32_t>(outputShape.data(), |
| 68 | outputShape.size()), |
| 69 | tensorType, |
Ryan OShea | 238ecd9 | 2023-03-07 11:44:23 +0000 | [diff] [blame] | 70 | 3, |
James Conroy | 3982548 | 2021-05-27 17:44:50 +0100 | [diff] [blame] | 71 | flatBufferBuilder.CreateString("output"), |
| 72 | quantizationParameters); |
| 73 | |
| 74 | std::vector<flatbuffers::Offset<Tensor>> tensors = { inputTensor, alphaTensor, outputTensor }; |
| 75 | |
| 76 | const std::vector<int> operatorInputs{0, 1}; |
| 77 | const std::vector<int> operatorOutputs{2}; |
| 78 | flatbuffers::Offset <Operator> preluOperator = |
| 79 | CreateOperator(flatBufferBuilder, |
| 80 | 0, |
| 81 | flatBufferBuilder.CreateVector<int32_t>(operatorInputs.data(), operatorInputs.size()), |
| 82 | flatBufferBuilder.CreateVector<int32_t>(operatorOutputs.data(), operatorOutputs.size())); |
| 83 | |
| 84 | std::vector<int> subgraphInputs{0}; |
| 85 | if (!alphaIsConstant) |
| 86 | { |
| 87 | subgraphInputs.push_back(1); |
| 88 | } |
| 89 | |
| 90 | const std::vector<int> subgraphOutputs{2}; |
| 91 | flatbuffers::Offset <SubGraph> subgraph = |
| 92 | CreateSubGraph(flatBufferBuilder, |
| 93 | flatBufferBuilder.CreateVector(tensors.data(), tensors.size()), |
| 94 | flatBufferBuilder.CreateVector<int32_t>(subgraphInputs.data(), subgraphInputs.size()), |
| 95 | flatBufferBuilder.CreateVector<int32_t>(subgraphOutputs.data(), subgraphOutputs.size()), |
| 96 | flatBufferBuilder.CreateVector(&preluOperator, 1)); |
| 97 | |
| 98 | flatbuffers::Offset <flatbuffers::String> modelDescription = |
| 99 | flatBufferBuilder.CreateString("ArmnnDelegate: Prelu Operator Model"); |
| 100 | flatbuffers::Offset <OperatorCode> opCode = CreateOperatorCode(flatBufferBuilder, preluOperatorCode); |
| 101 | |
| 102 | flatbuffers::Offset <Model> flatbufferModel = |
| 103 | CreateModel(flatBufferBuilder, |
| 104 | TFLITE_SCHEMA_VERSION, |
| 105 | flatBufferBuilder.CreateVector(&opCode, 1), |
| 106 | flatBufferBuilder.CreateVector(&subgraph, 1), |
| 107 | modelDescription, |
| 108 | flatBufferBuilder.CreateVector(buffers.data(), buffers.size())); |
| 109 | |
Matthew Sloyan | ebe392d | 2023-03-30 10:12:08 +0100 | [diff] [blame] | 110 | flatBufferBuilder.Finish(flatbufferModel, armnnDelegate::FILE_IDENTIFIER); |
James Conroy | 3982548 | 2021-05-27 17:44:50 +0100 | [diff] [blame] | 111 | |
| 112 | return std::vector<char>(flatBufferBuilder.GetBufferPointer(), |
| 113 | flatBufferBuilder.GetBufferPointer() + flatBufferBuilder.GetSize()); |
| 114 | } |
| 115 | |
| 116 | void PreluTest(tflite::BuiltinOperator preluOperatorCode, |
| 117 | tflite::TensorType tensorType, |
| 118 | const std::vector<armnn::BackendId>& backends, |
| 119 | const std::vector<int32_t>& inputShape, |
| 120 | const std::vector<int32_t>& alphaShape, |
| 121 | std::vector<int32_t>& outputShape, |
| 122 | std::vector<float>& inputData, |
| 123 | std::vector<float>& alphaData, |
| 124 | std::vector<float>& expectedOutput, |
| 125 | bool alphaIsConstant) |
| 126 | { |
Matthew Sloyan | ebe392d | 2023-03-30 10:12:08 +0100 | [diff] [blame] | 127 | using namespace delegateTestInterpreter; |
James Conroy | 3982548 | 2021-05-27 17:44:50 +0100 | [diff] [blame] | 128 | |
| 129 | std::vector<char> modelBuffer = CreatePreluTfLiteModel(preluOperatorCode, |
| 130 | tensorType, |
| 131 | inputShape, |
| 132 | alphaShape, |
| 133 | outputShape, |
| 134 | alphaData, |
| 135 | alphaIsConstant); |
| 136 | |
James Conroy | 3982548 | 2021-05-27 17:44:50 +0100 | [diff] [blame] | 137 | |
Matthew Sloyan | ebe392d | 2023-03-30 10:12:08 +0100 | [diff] [blame] | 138 | // Setup interpreter with just TFLite Runtime. |
| 139 | auto tfLiteInterpreter = DelegateTestInterpreter(modelBuffer); |
| 140 | CHECK(tfLiteInterpreter.AllocateTensors() == kTfLiteOk); |
James Conroy | 3982548 | 2021-05-27 17:44:50 +0100 | [diff] [blame] | 141 | |
Matthew Sloyan | ebe392d | 2023-03-30 10:12:08 +0100 | [diff] [blame] | 142 | // Setup interpreter with Arm NN Delegate applied. |
| 143 | auto armnnInterpreter = DelegateTestInterpreter(modelBuffer, backends); |
| 144 | CHECK(armnnInterpreter.AllocateTensors() == kTfLiteOk); |
James Conroy | 3982548 | 2021-05-27 17:44:50 +0100 | [diff] [blame] | 145 | |
Matthew Sloyan | ebe392d | 2023-03-30 10:12:08 +0100 | [diff] [blame] | 146 | CHECK(armnnInterpreter.FillInputTensor<float>(inputData, 0) == kTfLiteOk); |
| 147 | CHECK(tfLiteInterpreter.FillInputTensor<float>(inputData, 0) == kTfLiteOk); |
James Conroy | 3982548 | 2021-05-27 17:44:50 +0100 | [diff] [blame] | 148 | |
| 149 | // Set alpha data if not constant |
Matthew Sloyan | ebe392d | 2023-03-30 10:12:08 +0100 | [diff] [blame] | 150 | if (!alphaIsConstant) |
James Conroy | 3982548 | 2021-05-27 17:44:50 +0100 | [diff] [blame] | 151 | { |
Matthew Sloyan | ebe392d | 2023-03-30 10:12:08 +0100 | [diff] [blame] | 152 | CHECK(tfLiteInterpreter.FillInputTensor<float>(alphaData, 1) == kTfLiteOk); |
| 153 | CHECK(armnnInterpreter.FillInputTensor<float>(alphaData, 1) == kTfLiteOk); |
James Conroy | 3982548 | 2021-05-27 17:44:50 +0100 | [diff] [blame] | 154 | } |
Matthew Sloyan | ebe392d | 2023-03-30 10:12:08 +0100 | [diff] [blame] | 155 | |
| 156 | CHECK(tfLiteInterpreter.Invoke() == kTfLiteOk); |
| 157 | std::vector<float> tfLiteOutputValues = tfLiteInterpreter.GetOutputResult<float>(0); |
| 158 | |
| 159 | CHECK(armnnInterpreter.Invoke() == kTfLiteOk); |
| 160 | std::vector<float> armnnOutputValues = armnnInterpreter.GetOutputResult<float>(0); |
| 161 | |
| 162 | armnnDelegate::CompareOutputData<float>(tfLiteOutputValues, armnnOutputValues, expectedOutput); |
| 163 | |
| 164 | // Don't compare shapes on dynamic output tests, as output shape gets cleared. |
| 165 | if(!outputShape.empty()) |
| 166 | { |
| 167 | std::vector<int32_t> tfLiteOutputShape = tfLiteInterpreter.GetOutputShape(0); |
| 168 | std::vector<int32_t> armnnOutputShape = armnnInterpreter.GetOutputShape(0); |
| 169 | armnnDelegate::CompareOutputShape(tfLiteOutputShape, armnnOutputShape, outputShape); |
| 170 | } |
| 171 | |
| 172 | tfLiteInterpreter.Cleanup(); |
| 173 | armnnInterpreter.Cleanup(); |
James Conroy | 3982548 | 2021-05-27 17:44:50 +0100 | [diff] [blame] | 174 | } |
| 175 | } // anonymous namespace |