Sadik Armagan | 0534e03 | 2020-10-27 17:30:18 +0000 | [diff] [blame] | 1 | // |
Ryan OShea | 238ecd9 | 2023-03-07 11:44:23 +0000 | [diff] [blame] | 2 | // Copyright © 2020, 2023 Arm Ltd and Contributors. All rights reserved. |
Sadik Armagan | 0534e03 | 2020-10-27 17:30:18 +0000 | [diff] [blame] | 3 | // SPDX-License-Identifier: MIT |
| 4 | // |
| 5 | |
| 6 | #pragma once |
| 7 | |
Jan Eilers | 187b3a7 | 2020-11-19 17:50:34 +0000 | [diff] [blame] | 8 | #include "TestUtils.hpp" |
| 9 | |
Sadik Armagan | 0534e03 | 2020-10-27 17:30:18 +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 | 0534e03 | 2020-10-27 17:30:18 +0000 | [diff] [blame] | 12 | |
| 13 | #include <flatbuffers/flatbuffers.h> |
Sadik Armagan | 0534e03 | 2020-10-27 17:30:18 +0000 | [diff] [blame] | 14 | #include <tensorflow/lite/kernels/register.h> |
Sadik Armagan | 0534e03 | 2020-10-27 17:30:18 +0000 | [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 | |
Sadik Armagan | 0534e03 | 2020-10-27 17:30:18 +0000 | [diff] [blame] | 19 | #include <doctest/doctest.h> |
| 20 | |
| 21 | namespace |
| 22 | { |
| 23 | |
| 24 | std::vector<char> CreateElementwiseUnaryTfLiteModel(tflite::BuiltinOperator unaryOperatorCode, |
| 25 | tflite::TensorType tensorType, |
| 26 | const std::vector <int32_t>& tensorShape) |
| 27 | { |
| 28 | using namespace tflite; |
| 29 | flatbuffers::FlatBufferBuilder flatBufferBuilder; |
| 30 | |
| 31 | std::array<flatbuffers::Offset<tflite::Buffer>, 1> buffers; |
Ryan OShea | 238ecd9 | 2023-03-07 11:44:23 +0000 | [diff] [blame] | 32 | buffers[0] = CreateBuffer(flatBufferBuilder); |
Sadik Armagan | 0534e03 | 2020-10-27 17:30:18 +0000 | [diff] [blame] | 33 | |
| 34 | std::array<flatbuffers::Offset<Tensor>, 2> tensors; |
| 35 | tensors[0] = CreateTensor(flatBufferBuilder, |
| 36 | flatBufferBuilder.CreateVector<int32_t>(tensorShape.data(), tensorShape.size()), |
| 37 | tensorType); |
| 38 | tensors[1] = CreateTensor(flatBufferBuilder, |
| 39 | flatBufferBuilder.CreateVector<int32_t>(tensorShape.data(), tensorShape.size()), |
| 40 | tensorType); |
| 41 | |
| 42 | // create operator |
Keith Davis | 892fafe | 2020-11-26 17:40:35 +0000 | [diff] [blame] | 43 | const std::vector<int> operatorInputs{0}; |
| 44 | const std::vector<int> operatorOutputs{1}; |
Sadik Armagan | 0534e03 | 2020-10-27 17:30:18 +0000 | [diff] [blame] | 45 | flatbuffers::Offset <Operator> unaryOperator = |
| 46 | CreateOperator(flatBufferBuilder, |
| 47 | 0, |
| 48 | flatBufferBuilder.CreateVector<int32_t>(operatorInputs.data(), operatorInputs.size()), |
| 49 | flatBufferBuilder.CreateVector<int32_t>(operatorOutputs.data(), operatorOutputs.size())); |
| 50 | |
Keith Davis | 892fafe | 2020-11-26 17:40:35 +0000 | [diff] [blame] | 51 | const std::vector<int> subgraphInputs{0}; |
| 52 | const std::vector<int> subgraphOutputs{1}; |
Sadik Armagan | 0534e03 | 2020-10-27 17:30:18 +0000 | [diff] [blame] | 53 | flatbuffers::Offset <SubGraph> subgraph = |
| 54 | CreateSubGraph(flatBufferBuilder, |
| 55 | flatBufferBuilder.CreateVector(tensors.data(), tensors.size()), |
| 56 | flatBufferBuilder.CreateVector<int32_t>(subgraphInputs.data(), subgraphInputs.size()), |
| 57 | flatBufferBuilder.CreateVector<int32_t>(subgraphOutputs.data(), subgraphOutputs.size()), |
| 58 | flatBufferBuilder.CreateVector(&unaryOperator, 1)); |
| 59 | |
| 60 | flatbuffers::Offset <flatbuffers::String> modelDescription = |
| 61 | flatBufferBuilder.CreateString("ArmnnDelegate: Elementwise Unary Operator Model"); |
| 62 | flatbuffers::Offset <OperatorCode> operatorCode = CreateOperatorCode(flatBufferBuilder, unaryOperatorCode); |
| 63 | |
| 64 | flatbuffers::Offset <Model> flatbufferModel = |
| 65 | CreateModel(flatBufferBuilder, |
| 66 | TFLITE_SCHEMA_VERSION, |
| 67 | flatBufferBuilder.CreateVector(&operatorCode, 1), |
| 68 | flatBufferBuilder.CreateVector(&subgraph, 1), |
| 69 | modelDescription, |
| 70 | flatBufferBuilder.CreateVector(buffers.data(), buffers.size())); |
| 71 | |
Matthew Sloyan | ebe392d | 2023-03-30 10:12:08 +0100 | [diff] [blame] | 72 | flatBufferBuilder.Finish(flatbufferModel, armnnDelegate::FILE_IDENTIFIER); |
Sadik Armagan | 0534e03 | 2020-10-27 17:30:18 +0000 | [diff] [blame] | 73 | |
| 74 | return std::vector<char>(flatBufferBuilder.GetBufferPointer(), |
| 75 | flatBufferBuilder.GetBufferPointer() + flatBufferBuilder.GetSize()); |
| 76 | } |
| 77 | |
| 78 | void ElementwiseUnaryFP32Test(tflite::BuiltinOperator unaryOperatorCode, |
| 79 | std::vector<armnn::BackendId>& backends, |
| 80 | std::vector<float>& inputValues, |
| 81 | std::vector<float>& expectedOutputValues) |
| 82 | { |
Matthew Sloyan | ebe392d | 2023-03-30 10:12:08 +0100 | [diff] [blame] | 83 | using namespace delegateTestInterpreter; |
Jan Eilers | 187b3a7 | 2020-11-19 17:50:34 +0000 | [diff] [blame] | 84 | std::vector<int32_t> inputShape { { 3, 1, 2} }; |
Sadik Armagan | 0534e03 | 2020-10-27 17:30:18 +0000 | [diff] [blame] | 85 | std::vector<char> modelBuffer = CreateElementwiseUnaryTfLiteModel(unaryOperatorCode, |
| 86 | ::tflite::TensorType_FLOAT32, |
| 87 | inputShape); |
| 88 | |
Matthew Sloyan | ebe392d | 2023-03-30 10:12:08 +0100 | [diff] [blame] | 89 | // Setup interpreter with just TFLite Runtime. |
| 90 | auto tfLiteInterpreter = DelegateTestInterpreter(modelBuffer); |
| 91 | CHECK(tfLiteInterpreter.AllocateTensors() == kTfLiteOk); |
| 92 | CHECK(tfLiteInterpreter.FillInputTensor<float>(inputValues, 0) == kTfLiteOk); |
| 93 | CHECK(tfLiteInterpreter.Invoke() == kTfLiteOk); |
| 94 | std::vector<float> tfLiteOutputValues = tfLiteInterpreter.GetOutputResult<float>(0); |
| 95 | std::vector<int32_t> tfLiteOutputShape = tfLiteInterpreter.GetOutputShape(0); |
Sadik Armagan | 0534e03 | 2020-10-27 17:30:18 +0000 | [diff] [blame] | 96 | |
Matthew Sloyan | ebe392d | 2023-03-30 10:12:08 +0100 | [diff] [blame] | 97 | // Setup interpreter with Arm NN Delegate applied. |
| 98 | auto armnnInterpreter = DelegateTestInterpreter(modelBuffer, backends); |
| 99 | CHECK(armnnInterpreter.AllocateTensors() == kTfLiteOk); |
| 100 | CHECK(armnnInterpreter.FillInputTensor<float>(inputValues, 0) == kTfLiteOk); |
| 101 | CHECK(armnnInterpreter.Invoke() == kTfLiteOk); |
| 102 | std::vector<float> armnnOutputValues = armnnInterpreter.GetOutputResult<float>(0); |
| 103 | std::vector<int32_t> armnnOutputShape = armnnInterpreter.GetOutputShape(0); |
Sadik Armagan | 67e95f2 | 2020-10-29 16:14:54 +0000 | [diff] [blame] | 104 | |
Matthew Sloyan | ebe392d | 2023-03-30 10:12:08 +0100 | [diff] [blame] | 105 | armnnDelegate::CompareOutputData<float>(tfLiteOutputValues, armnnOutputValues, expectedOutputValues); |
| 106 | armnnDelegate::CompareOutputShape(tfLiteOutputShape, armnnOutputShape, inputShape); |
Sadik Armagan | 0534e03 | 2020-10-27 17:30:18 +0000 | [diff] [blame] | 107 | |
Matthew Sloyan | ebe392d | 2023-03-30 10:12:08 +0100 | [diff] [blame] | 108 | tfLiteInterpreter.Cleanup(); |
| 109 | armnnInterpreter.Cleanup(); |
Matthew Sloyan | c8eb955 | 2020-11-26 10:54:22 +0000 | [diff] [blame] | 110 | } |
| 111 | |
| 112 | void ElementwiseUnaryBoolTest(tflite::BuiltinOperator unaryOperatorCode, |
| 113 | std::vector<armnn::BackendId>& backends, |
| 114 | std::vector<int32_t>& inputShape, |
| 115 | std::vector<bool>& inputValues, |
| 116 | std::vector<bool>& expectedOutputValues) |
| 117 | { |
Matthew Sloyan | ebe392d | 2023-03-30 10:12:08 +0100 | [diff] [blame] | 118 | using namespace delegateTestInterpreter; |
Matthew Sloyan | c8eb955 | 2020-11-26 10:54:22 +0000 | [diff] [blame] | 119 | std::vector<char> modelBuffer = CreateElementwiseUnaryTfLiteModel(unaryOperatorCode, |
| 120 | ::tflite::TensorType_BOOL, |
| 121 | inputShape); |
| 122 | |
Matthew Sloyan | ebe392d | 2023-03-30 10:12:08 +0100 | [diff] [blame] | 123 | // Setup interpreter with just TFLite Runtime. |
| 124 | auto tfLiteInterpreter = DelegateTestInterpreter(modelBuffer); |
| 125 | CHECK(tfLiteInterpreter.AllocateTensors() == kTfLiteOk); |
| 126 | CHECK(tfLiteInterpreter.FillInputTensor(inputValues, 0) == kTfLiteOk); |
| 127 | CHECK(tfLiteInterpreter.Invoke() == kTfLiteOk); |
| 128 | std::vector<bool> tfLiteOutputValues = tfLiteInterpreter.GetOutputResult(0); |
| 129 | std::vector<int32_t> tfLiteOutputShape = tfLiteInterpreter.GetOutputShape(0); |
Matthew Sloyan | c8eb955 | 2020-11-26 10:54:22 +0000 | [diff] [blame] | 130 | |
Matthew Sloyan | ebe392d | 2023-03-30 10:12:08 +0100 | [diff] [blame] | 131 | // Setup interpreter with Arm NN Delegate applied. |
| 132 | auto armnnInterpreter = DelegateTestInterpreter(modelBuffer, backends); |
| 133 | CHECK(armnnInterpreter.AllocateTensors() == kTfLiteOk); |
| 134 | CHECK(armnnInterpreter.FillInputTensor(inputValues, 0) == kTfLiteOk); |
| 135 | CHECK(armnnInterpreter.Invoke() == kTfLiteOk); |
| 136 | std::vector<bool> armnnOutputValues = armnnInterpreter.GetOutputResult(0); |
| 137 | std::vector<int32_t> armnnOutputShape = armnnInterpreter.GetOutputShape(0); |
Matthew Sloyan | c8eb955 | 2020-11-26 10:54:22 +0000 | [diff] [blame] | 138 | |
Matthew Sloyan | ebe392d | 2023-03-30 10:12:08 +0100 | [diff] [blame] | 139 | armnnDelegate::CompareData(expectedOutputValues, armnnOutputValues, expectedOutputValues.size()); |
| 140 | armnnDelegate::CompareData(expectedOutputValues, tfLiteOutputValues, expectedOutputValues.size()); |
| 141 | armnnDelegate::CompareData(tfLiteOutputValues, armnnOutputValues, expectedOutputValues.size()); |
Matthew Sloyan | c8eb955 | 2020-11-26 10:54:22 +0000 | [diff] [blame] | 142 | |
Matthew Sloyan | ebe392d | 2023-03-30 10:12:08 +0100 | [diff] [blame] | 143 | armnnDelegate::CompareOutputShape(tfLiteOutputShape, armnnOutputShape, inputShape); |
Matthew Sloyan | c8eb955 | 2020-11-26 10:54:22 +0000 | [diff] [blame] | 144 | |
Matthew Sloyan | ebe392d | 2023-03-30 10:12:08 +0100 | [diff] [blame] | 145 | tfLiteInterpreter.Cleanup(); |
| 146 | armnnInterpreter.Cleanup(); |
Sadik Armagan | 0534e03 | 2020-10-27 17:30:18 +0000 | [diff] [blame] | 147 | } |
| 148 | |
| 149 | } // anonymous namespace |
| 150 | |
| 151 | |
| 152 | |
| 153 | |