1 //
2 // Copyright © 2021, 2023 Arm Ltd and Contributors. All rights reserved.
3 // SPDX-License-Identifier: MIT
4 //
5
6 #pragma once
7
8 #include "TestUtils.hpp"
9
10 #include <armnn_delegate.hpp>
11 #include <DelegateTestInterpreter.hpp>
12
13 #include <flatbuffers/flatbuffers.h>
14 #include <tensorflow/lite/kernels/register.h>
15 #include <tensorflow/lite/version.h>
16
17 #include <schema_generated.h>
18
19 #include <doctest/doctest.h>
20
21 namespace
22 {
23
CreatePackTfLiteModel(tflite::BuiltinOperator packOperatorCode,tflite::TensorType tensorType,std::vector<int32_t> & inputTensorShape,const std::vector<int32_t> & outputTensorShape,const int32_t inputTensorNum,unsigned int axis=0,float quantScale=1.0f,int quantOffset=0)24 std::vector<char> CreatePackTfLiteModel(tflite::BuiltinOperator packOperatorCode,
25 tflite::TensorType tensorType,
26 std::vector<int32_t>& inputTensorShape,
27 const std::vector <int32_t>& outputTensorShape,
28 const int32_t inputTensorNum,
29 unsigned int axis = 0,
30 float quantScale = 1.0f,
31 int quantOffset = 0)
32 {
33 using namespace tflite;
34 flatbuffers::FlatBufferBuilder flatBufferBuilder;
35
36 std::vector<flatbuffers::Offset<tflite::Buffer>> buffers;
37 buffers.push_back(CreateBuffer(flatBufferBuilder));
38 buffers.push_back(CreateBuffer(flatBufferBuilder));
39
40 auto quantizationParameters =
41 CreateQuantizationParameters(flatBufferBuilder,
42 0,
43 0,
44 flatBufferBuilder.CreateVector<float>({ quantScale }),
45 flatBufferBuilder.CreateVector<int64_t>({ quantOffset }));
46
47 std::vector<int32_t> operatorInputs{};
48 const std::vector<int32_t> operatorOutputs{inputTensorNum};
49 std::vector<int> subgraphInputs{};
50 const std::vector<int> subgraphOutputs{inputTensorNum};
51
52 std::vector<flatbuffers::Offset<Tensor>> tensors(inputTensorNum + 1);
53 for (int i = 0; i < inputTensorNum; ++i)
54 {
55 tensors[i] = CreateTensor(flatBufferBuilder,
56 flatBufferBuilder.CreateVector<int32_t>(inputTensorShape.data(),
57 inputTensorShape.size()),
58 tensorType,
59 1,
60 flatBufferBuilder.CreateString("input" + std::to_string(i)),
61 quantizationParameters);
62
63 // Add number of inputs to vector.
64 operatorInputs.push_back(i);
65 subgraphInputs.push_back(i);
66 }
67
68 // Create output tensor
69 tensors[inputTensorNum] = CreateTensor(flatBufferBuilder,
70 flatBufferBuilder.CreateVector<int32_t>(outputTensorShape.data(),
71 outputTensorShape.size()),
72 tensorType,
73 0,
74 flatBufferBuilder.CreateString("output"),
75 quantizationParameters);
76
77 // create operator
78 tflite::BuiltinOptions operatorBuiltinOptionsType = tflite::BuiltinOptions_PackOptions;
79 flatbuffers::Offset<void> operatorBuiltinOptions =
80 CreatePackOptions(flatBufferBuilder, inputTensorNum, axis).Union();
81
82 flatbuffers::Offset <Operator> packOperator =
83 CreateOperator(flatBufferBuilder,
84 0,
85 flatBufferBuilder.CreateVector<int32_t>(operatorInputs.data(), operatorInputs.size()),
86 flatBufferBuilder.CreateVector<int32_t>(operatorOutputs.data(), operatorOutputs.size()),
87 operatorBuiltinOptionsType,
88 operatorBuiltinOptions);
89
90 flatbuffers::Offset <SubGraph> subgraph =
91 CreateSubGraph(flatBufferBuilder,
92 flatBufferBuilder.CreateVector(tensors.data(), tensors.size()),
93 flatBufferBuilder.CreateVector<int32_t>(subgraphInputs.data(), subgraphInputs.size()),
94 flatBufferBuilder.CreateVector<int32_t>(subgraphOutputs.data(), subgraphOutputs.size()),
95 flatBufferBuilder.CreateVector(&packOperator, 1));
96
97 flatbuffers::Offset <flatbuffers::String> modelDescription =
98 flatBufferBuilder.CreateString("ArmnnDelegate: Pack Operator Model");
99 flatbuffers::Offset <OperatorCode> operatorCode = CreateOperatorCode(flatBufferBuilder, packOperatorCode);
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
109 flatBufferBuilder.Finish(flatbufferModel, armnnDelegate::FILE_IDENTIFIER);
110
111 return std::vector<char>(flatBufferBuilder.GetBufferPointer(),
112 flatBufferBuilder.GetBufferPointer() + flatBufferBuilder.GetSize());
113 }
114
115 template <typename T>
PackTest(tflite::BuiltinOperator packOperatorCode,tflite::TensorType tensorType,std::vector<armnn::BackendId> & backends,std::vector<int32_t> & inputShape,std::vector<int32_t> & expectedOutputShape,std::vector<std::vector<T>> & inputValues,std::vector<T> & expectedOutputValues,unsigned int axis=0,float quantScale=1.0f,int quantOffset=0)116 void PackTest(tflite::BuiltinOperator packOperatorCode,
117 tflite::TensorType tensorType,
118 std::vector<armnn::BackendId>& backends,
119 std::vector<int32_t>& inputShape,
120 std::vector<int32_t>& expectedOutputShape,
121 std::vector<std::vector<T>>& inputValues,
122 std::vector<T>& expectedOutputValues,
123 unsigned int axis = 0,
124 float quantScale = 1.0f,
125 int quantOffset = 0)
126 {
127 using namespace delegateTestInterpreter;
128 std::vector<char> modelBuffer = CreatePackTfLiteModel(packOperatorCode,
129 tensorType,
130 inputShape,
131 expectedOutputShape,
132 inputValues.size(),
133 axis,
134 quantScale,
135 quantOffset);
136
137 // Setup interpreter with just TFLite Runtime.
138 auto tfLiteInterpreter = DelegateTestInterpreter(modelBuffer);
139 CHECK(tfLiteInterpreter.AllocateTensors() == kTfLiteOk);
140
141 // Setup interpreter with Arm NN Delegate applied.
142 auto armnnInterpreter = DelegateTestInterpreter(modelBuffer, backends);
143 CHECK(armnnInterpreter.AllocateTensors() == kTfLiteOk);
144
145 // Set input data for all input tensors.
146 for (unsigned int i = 0; i < inputValues.size(); ++i)
147 {
148 auto inputTensorValues = inputValues[i];
149 CHECK(tfLiteInterpreter.FillInputTensor<T>(inputTensorValues, i) == kTfLiteOk);
150 CHECK(armnnInterpreter.FillInputTensor<T>(inputTensorValues, i) == kTfLiteOk);
151 }
152
153 CHECK(tfLiteInterpreter.Invoke() == kTfLiteOk);
154 std::vector<T> tfLiteOutputValues = tfLiteInterpreter.GetOutputResult<T>(0);
155 std::vector<int32_t> tfLiteOutputShape = tfLiteInterpreter.GetOutputShape(0);
156
157 CHECK(armnnInterpreter.Invoke() == kTfLiteOk);
158 std::vector<T> armnnOutputValues = armnnInterpreter.GetOutputResult<T>(0);
159 std::vector<int32_t> armnnOutputShape = armnnInterpreter.GetOutputShape(0);
160
161 armnnDelegate::CompareOutputData<T>(tfLiteOutputValues, armnnOutputValues, expectedOutputValues);
162 armnnDelegate::CompareOutputShape(tfLiteOutputShape, armnnOutputShape, expectedOutputShape);
163
164 tfLiteInterpreter.Cleanup();
165 armnnInterpreter.Cleanup();
166 }
167
168 } // anonymous namespace