Teresa Charlin | d5c0ed2 | 2022-04-25 18:23:41 +0100 | [diff] [blame] | 1 | // |
Ryan OShea | 238ecd9 | 2023-03-07 11:44:23 +0000 | [diff] [blame] | 2 | // Copyright © 2022-2023 Arm Ltd and Contributors. All rights reserved. |
Teresa Charlin | d5c0ed2 | 2022-04-25 18:23:41 +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> |
Teresa Charlin | d5c0ed2 | 2022-04-25 18:23:41 +0100 | [diff] [blame] | 12 | |
| 13 | #include <flatbuffers/flatbuffers.h> |
Teresa Charlin | d5c0ed2 | 2022-04-25 18:23:41 +0100 | [diff] [blame] | 14 | #include <tensorflow/lite/kernels/register.h> |
Teresa Charlin | d5c0ed2 | 2022-04-25 18:23:41 +0100 | [diff] [blame] | 15 | #include <tensorflow/lite/version.h> |
| 16 | |
| 17 | #include <doctest/doctest.h> |
| 18 | |
| 19 | namespace |
| 20 | { |
| 21 | |
| 22 | std::vector<char> CreateGatherNdTfLiteModel(tflite::TensorType tensorType, |
| 23 | std::vector<int32_t>& paramsShape, |
| 24 | std::vector<int32_t>& indicesShape, |
| 25 | const std::vector<int32_t>& expectedOutputShape, |
| 26 | float quantScale = 1.0f, |
| 27 | int quantOffset = 0) |
| 28 | { |
| 29 | using namespace tflite; |
| 30 | flatbuffers::FlatBufferBuilder flatBufferBuilder; |
| 31 | |
| 32 | std::vector<flatbuffers::Offset<tflite::Buffer>> buffers; |
Ryan OShea | 238ecd9 | 2023-03-07 11:44:23 +0000 | [diff] [blame] | 33 | buffers.push_back(CreateBuffer(flatBufferBuilder)); |
| 34 | buffers.push_back(CreateBuffer(flatBufferBuilder)); |
| 35 | buffers.push_back(CreateBuffer(flatBufferBuilder)); |
| 36 | buffers.push_back(CreateBuffer(flatBufferBuilder)); |
Teresa Charlin | d5c0ed2 | 2022-04-25 18:23:41 +0100 | [diff] [blame] | 37 | |
| 38 | auto quantizationParameters = |
| 39 | CreateQuantizationParameters(flatBufferBuilder, |
| 40 | 0, |
| 41 | 0, |
| 42 | flatBufferBuilder.CreateVector<float>({quantScale}), |
| 43 | flatBufferBuilder.CreateVector<int64_t>({quantOffset})); |
| 44 | |
| 45 | std::array<flatbuffers::Offset<Tensor>, 3> tensors; |
| 46 | tensors[0] = CreateTensor(flatBufferBuilder, |
| 47 | flatBufferBuilder.CreateVector<int32_t>(paramsShape.data(), |
| 48 | paramsShape.size()), |
| 49 | tensorType, |
Ryan OShea | 238ecd9 | 2023-03-07 11:44:23 +0000 | [diff] [blame] | 50 | 1, |
Teresa Charlin | d5c0ed2 | 2022-04-25 18:23:41 +0100 | [diff] [blame] | 51 | flatBufferBuilder.CreateString("params"), |
| 52 | quantizationParameters); |
| 53 | tensors[1] = CreateTensor(flatBufferBuilder, |
| 54 | flatBufferBuilder.CreateVector<int32_t>(indicesShape.data(), |
| 55 | indicesShape.size()), |
| 56 | ::tflite::TensorType_INT32, |
Ryan OShea | 238ecd9 | 2023-03-07 11:44:23 +0000 | [diff] [blame] | 57 | 2, |
Teresa Charlin | d5c0ed2 | 2022-04-25 18:23:41 +0100 | [diff] [blame] | 58 | flatBufferBuilder.CreateString("indices"), |
| 59 | quantizationParameters); |
| 60 | tensors[2] = CreateTensor(flatBufferBuilder, |
| 61 | flatBufferBuilder.CreateVector<int32_t>(expectedOutputShape.data(), |
| 62 | expectedOutputShape.size()), |
| 63 | tensorType, |
Ryan OShea | 238ecd9 | 2023-03-07 11:44:23 +0000 | [diff] [blame] | 64 | 3, |
Teresa Charlin | d5c0ed2 | 2022-04-25 18:23:41 +0100 | [diff] [blame] | 65 | flatBufferBuilder.CreateString("output"), |
| 66 | quantizationParameters); |
| 67 | |
| 68 | |
| 69 | // create operator |
| 70 | tflite::BuiltinOptions operatorBuiltinOptionsType = tflite::BuiltinOptions_GatherNdOptions; |
| 71 | flatbuffers::Offset<void> operatorBuiltinOptions = CreateGatherNdOptions(flatBufferBuilder).Union(); |
| 72 | |
| 73 | const std::vector<int> operatorInputs{{0, 1}}; |
| 74 | const std::vector<int> operatorOutputs{2}; |
| 75 | flatbuffers::Offset<Operator> controlOperator = |
| 76 | CreateOperator(flatBufferBuilder, |
| 77 | 0, |
| 78 | flatBufferBuilder.CreateVector<int32_t>(operatorInputs.data(), |
| 79 | operatorInputs.size()), |
| 80 | flatBufferBuilder.CreateVector<int32_t>(operatorOutputs.data(), |
| 81 | operatorOutputs.size()), |
| 82 | operatorBuiltinOptionsType, |
| 83 | operatorBuiltinOptions); |
| 84 | |
| 85 | const std::vector<int> subgraphInputs{{0, 1}}; |
| 86 | const std::vector<int> subgraphOutputs{2}; |
| 87 | flatbuffers::Offset<SubGraph> subgraph = |
| 88 | CreateSubGraph(flatBufferBuilder, |
| 89 | flatBufferBuilder.CreateVector(tensors.data(), tensors.size()), |
| 90 | flatBufferBuilder.CreateVector<int32_t>(subgraphInputs.data(), |
| 91 | subgraphInputs.size()), |
| 92 | flatBufferBuilder.CreateVector<int32_t>(subgraphOutputs.data(), |
| 93 | subgraphOutputs.size()), |
| 94 | flatBufferBuilder.CreateVector(&controlOperator, 1)); |
| 95 | |
| 96 | flatbuffers::Offset<flatbuffers::String> modelDescription = |
| 97 | flatBufferBuilder.CreateString("ArmnnDelegate: GATHER_ND Operator Model"); |
| 98 | flatbuffers::Offset<OperatorCode> operatorCode = CreateOperatorCode(flatBufferBuilder, |
| 99 | BuiltinOperator_GATHER_ND); |
| 100 | |
| 101 | flatbuffers::Offset<Model> flatbufferModel = |
| 102 | CreateModel(flatBufferBuilder, |
| 103 | TFLITE_SCHEMA_VERSION, |
| 104 | flatBufferBuilder.CreateVector(&operatorCode, 1), |
| 105 | flatBufferBuilder.CreateVector(&subgraph, 1), |
| 106 | modelDescription, |
| 107 | flatBufferBuilder.CreateVector(buffers.data(), buffers.size())); |
| 108 | |
Matthew Sloyan | ebe392d | 2023-03-30 10:12:08 +0100 | [diff] [blame] | 109 | flatBufferBuilder.Finish(flatbufferModel, armnnDelegate::FILE_IDENTIFIER); |
Teresa Charlin | d5c0ed2 | 2022-04-25 18:23:41 +0100 | [diff] [blame] | 110 | |
| 111 | return std::vector<char>(flatBufferBuilder.GetBufferPointer(), |
| 112 | flatBufferBuilder.GetBufferPointer() + flatBufferBuilder.GetSize()); |
| 113 | } |
| 114 | |
| 115 | template<typename T> |
| 116 | void GatherNdTest(tflite::TensorType tensorType, |
| 117 | std::vector<armnn::BackendId>& backends, |
| 118 | std::vector<int32_t>& paramsShape, |
| 119 | std::vector<int32_t>& indicesShape, |
| 120 | std::vector<int32_t>& expectedOutputShape, |
| 121 | std::vector<T>& paramsValues, |
| 122 | std::vector<int32_t>& indicesValues, |
| 123 | std::vector<T>& expectedOutputValues, |
| 124 | float quantScale = 1.0f, |
| 125 | int quantOffset = 0) |
| 126 | { |
Matthew Sloyan | ebe392d | 2023-03-30 10:12:08 +0100 | [diff] [blame] | 127 | using namespace delegateTestInterpreter; |
Teresa Charlin | d5c0ed2 | 2022-04-25 18:23:41 +0100 | [diff] [blame] | 128 | std::vector<char> modelBuffer = CreateGatherNdTfLiteModel(tensorType, |
| 129 | paramsShape, |
| 130 | indicesShape, |
| 131 | expectedOutputShape, |
| 132 | quantScale, |
| 133 | quantOffset); |
Matthew Sloyan | ebe392d | 2023-03-30 10:12:08 +0100 | [diff] [blame] | 134 | // Setup interpreter with just TFLite Runtime. |
| 135 | auto tfLiteInterpreter = DelegateTestInterpreter(modelBuffer); |
| 136 | CHECK(tfLiteInterpreter.AllocateTensors() == kTfLiteOk); |
| 137 | CHECK(tfLiteInterpreter.FillInputTensor<T>(paramsValues, 0) == kTfLiteOk); |
| 138 | CHECK(tfLiteInterpreter.FillInputTensor<int32_t>(indicesValues, 1) == kTfLiteOk); |
| 139 | CHECK(tfLiteInterpreter.Invoke() == kTfLiteOk); |
| 140 | std::vector<T> tfLiteOutputValues = tfLiteInterpreter.GetOutputResult<T>(0); |
| 141 | std::vector<int32_t> tfLiteOutputShape = tfLiteInterpreter.GetOutputShape(0); |
Teresa Charlin | d5c0ed2 | 2022-04-25 18:23:41 +0100 | [diff] [blame] | 142 | |
Matthew Sloyan | ebe392d | 2023-03-30 10:12:08 +0100 | [diff] [blame] | 143 | // Setup interpreter with Arm NN Delegate applied. |
| 144 | auto armnnInterpreter = DelegateTestInterpreter(modelBuffer, backends); |
| 145 | CHECK(armnnInterpreter.AllocateTensors() == kTfLiteOk); |
| 146 | CHECK(armnnInterpreter.FillInputTensor<T>(paramsValues, 0) == kTfLiteOk); |
| 147 | CHECK(armnnInterpreter.FillInputTensor<int32_t>(indicesValues, 1) == kTfLiteOk); |
| 148 | CHECK(armnnInterpreter.Invoke() == kTfLiteOk); |
| 149 | std::vector<T> armnnOutputValues = armnnInterpreter.GetOutputResult<T>(0); |
| 150 | std::vector<int32_t> armnnOutputShape = armnnInterpreter.GetOutputShape(0); |
Teresa Charlin | d5c0ed2 | 2022-04-25 18:23:41 +0100 | [diff] [blame] | 151 | |
Matthew Sloyan | ebe392d | 2023-03-30 10:12:08 +0100 | [diff] [blame] | 152 | armnnDelegate::CompareOutputData<T>(tfLiteOutputValues, armnnOutputValues, expectedOutputValues); |
| 153 | armnnDelegate::CompareOutputShape(tfLiteOutputShape, armnnOutputShape, expectedOutputShape); |
Teresa Charlin | d5c0ed2 | 2022-04-25 18:23:41 +0100 | [diff] [blame] | 154 | |
Matthew Sloyan | ebe392d | 2023-03-30 10:12:08 +0100 | [diff] [blame] | 155 | tfLiteInterpreter.Cleanup(); |
| 156 | armnnInterpreter.Cleanup(); |
Teresa Charlin | d5c0ed2 | 2022-04-25 18:23:41 +0100 | [diff] [blame] | 157 | } |
| 158 | } // anonymous namespace |