1 //
2 // Copyright © 2020, 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
CreateComparisonTfLiteModel(tflite::BuiltinOperator comparisonOperatorCode,tflite::TensorType tensorType,const std::vector<int32_t> & input0TensorShape,const std::vector<int32_t> & input1TensorShape,const std::vector<int32_t> & outputTensorShape,float quantScale=1.0f,int quantOffset=0)24 std::vector<char> CreateComparisonTfLiteModel(tflite::BuiltinOperator comparisonOperatorCode,
25 tflite::TensorType tensorType,
26 const std::vector <int32_t>& input0TensorShape,
27 const std::vector <int32_t>& input1TensorShape,
28 const std::vector <int32_t>& outputTensorShape,
29 float quantScale = 1.0f,
30 int quantOffset = 0)
31 {
32 using namespace tflite;
33 flatbuffers::FlatBufferBuilder flatBufferBuilder;
34
35 std::vector<flatbuffers::Offset<tflite::Buffer>> buffers;
36 buffers.push_back(CreateBuffer(flatBufferBuilder));
37 buffers.push_back(CreateBuffer(flatBufferBuilder));
38 buffers.push_back(CreateBuffer(flatBufferBuilder));
39 buffers.push_back(CreateBuffer(flatBufferBuilder));
40
41 auto quantizationParameters =
42 CreateQuantizationParameters(flatBufferBuilder,
43 0,
44 0,
45 flatBufferBuilder.CreateVector<float>({ quantScale }),
46 flatBufferBuilder.CreateVector<int64_t>({ quantOffset }));
47
48 std::array<flatbuffers::Offset<Tensor>, 3> tensors;
49 tensors[0] = CreateTensor(flatBufferBuilder,
50 flatBufferBuilder.CreateVector<int32_t>(input0TensorShape.data(),
51 input0TensorShape.size()),
52 tensorType,
53 1,
54 flatBufferBuilder.CreateString("input_0"),
55 quantizationParameters);
56 tensors[1] = CreateTensor(flatBufferBuilder,
57 flatBufferBuilder.CreateVector<int32_t>(input1TensorShape.data(),
58 input1TensorShape.size()),
59 tensorType,
60 2,
61 flatBufferBuilder.CreateString("input_1"),
62 quantizationParameters);
63 tensors[2] = CreateTensor(flatBufferBuilder,
64 flatBufferBuilder.CreateVector<int32_t>(outputTensorShape.data(),
65 outputTensorShape.size()),
66 ::tflite::TensorType_BOOL,
67 3);
68
69 // create operator
70 tflite::BuiltinOptions operatorBuiltinOptionsType = BuiltinOptions_EqualOptions;;
71 flatbuffers::Offset<void> operatorBuiltinOptions = CreateEqualOptions(flatBufferBuilder).Union();
72 switch (comparisonOperatorCode)
73 {
74 case BuiltinOperator_EQUAL:
75 {
76 operatorBuiltinOptionsType = BuiltinOptions_EqualOptions;
77 operatorBuiltinOptions = CreateEqualOptions(flatBufferBuilder).Union();
78 break;
79 }
80 case BuiltinOperator_NOT_EQUAL:
81 {
82 operatorBuiltinOptionsType = BuiltinOptions_NotEqualOptions;
83 operatorBuiltinOptions = CreateNotEqualOptions(flatBufferBuilder).Union();
84 break;
85 }
86 case BuiltinOperator_GREATER:
87 {
88 operatorBuiltinOptionsType = BuiltinOptions_GreaterOptions;
89 operatorBuiltinOptions = CreateGreaterOptions(flatBufferBuilder).Union();
90 break;
91 }
92 case BuiltinOperator_GREATER_EQUAL:
93 {
94 operatorBuiltinOptionsType = BuiltinOptions_GreaterEqualOptions;
95 operatorBuiltinOptions = CreateGreaterEqualOptions(flatBufferBuilder).Union();
96 break;
97 }
98 case BuiltinOperator_LESS:
99 {
100 operatorBuiltinOptionsType = BuiltinOptions_LessOptions;
101 operatorBuiltinOptions = CreateLessOptions(flatBufferBuilder).Union();
102 break;
103 }
104 case BuiltinOperator_LESS_EQUAL:
105 {
106 operatorBuiltinOptionsType = BuiltinOptions_LessEqualOptions;
107 operatorBuiltinOptions = CreateLessEqualOptions(flatBufferBuilder).Union();
108 break;
109 }
110 default:
111 break;
112 }
113 const std::vector<int32_t> operatorInputs{0, 1};
114 const std::vector<int32_t> operatorOutputs{2};
115 flatbuffers::Offset <Operator> comparisonOperator =
116 CreateOperator(flatBufferBuilder,
117 0,
118 flatBufferBuilder.CreateVector<int32_t>(operatorInputs.data(), operatorInputs.size()),
119 flatBufferBuilder.CreateVector<int32_t>(operatorOutputs.data(), operatorOutputs.size()),
120 operatorBuiltinOptionsType,
121 operatorBuiltinOptions);
122
123 const std::vector<int> subgraphInputs{0, 1};
124 const std::vector<int> subgraphOutputs{2};
125 flatbuffers::Offset <SubGraph> subgraph =
126 CreateSubGraph(flatBufferBuilder,
127 flatBufferBuilder.CreateVector(tensors.data(), tensors.size()),
128 flatBufferBuilder.CreateVector<int32_t>(subgraphInputs.data(), subgraphInputs.size()),
129 flatBufferBuilder.CreateVector<int32_t>(subgraphOutputs.data(), subgraphOutputs.size()),
130 flatBufferBuilder.CreateVector(&comparisonOperator, 1));
131
132 flatbuffers::Offset <flatbuffers::String> modelDescription =
133 flatBufferBuilder.CreateString("ArmnnDelegate: Comparison Operator Model");
134 flatbuffers::Offset <OperatorCode> operatorCode = CreateOperatorCode(flatBufferBuilder, comparisonOperatorCode);
135
136 flatbuffers::Offset <Model> flatbufferModel =
137 CreateModel(flatBufferBuilder,
138 TFLITE_SCHEMA_VERSION,
139 flatBufferBuilder.CreateVector(&operatorCode, 1),
140 flatBufferBuilder.CreateVector(&subgraph, 1),
141 modelDescription,
142 flatBufferBuilder.CreateVector(buffers.data(), buffers.size()));
143
144 flatBufferBuilder.Finish(flatbufferModel, armnnDelegate::FILE_IDENTIFIER);
145
146 return std::vector<char>(flatBufferBuilder.GetBufferPointer(),
147 flatBufferBuilder.GetBufferPointer() + flatBufferBuilder.GetSize());
148 }
149
150 template <typename T>
ComparisonTest(tflite::BuiltinOperator comparisonOperatorCode,tflite::TensorType tensorType,std::vector<armnn::BackendId> & backends,std::vector<int32_t> & input0Shape,std::vector<int32_t> & input1Shape,std::vector<int32_t> & outputShape,std::vector<T> & input0Values,std::vector<T> & input1Values,std::vector<bool> & expectedOutputValues,float quantScale=1.0f,int quantOffset=0)151 void ComparisonTest(tflite::BuiltinOperator comparisonOperatorCode,
152 tflite::TensorType tensorType,
153 std::vector<armnn::BackendId>& backends,
154 std::vector<int32_t>& input0Shape,
155 std::vector<int32_t>& input1Shape,
156 std::vector<int32_t>& outputShape,
157 std::vector<T>& input0Values,
158 std::vector<T>& input1Values,
159 std::vector<bool>& expectedOutputValues,
160 float quantScale = 1.0f,
161 int quantOffset = 0)
162 {
163 using namespace delegateTestInterpreter;
164 std::vector<char> modelBuffer = CreateComparisonTfLiteModel(comparisonOperatorCode,
165 tensorType,
166 input0Shape,
167 input1Shape,
168 outputShape,
169 quantScale,
170 quantOffset);
171
172 // Setup interpreter with just TFLite Runtime.
173 auto tfLiteInterpreter = DelegateTestInterpreter(modelBuffer);
174 CHECK(tfLiteInterpreter.AllocateTensors() == kTfLiteOk);
175 CHECK(tfLiteInterpreter.FillInputTensor<T>(input0Values, 0) == kTfLiteOk);
176 CHECK(tfLiteInterpreter.FillInputTensor<T>(input1Values, 1) == kTfLiteOk);
177 CHECK(tfLiteInterpreter.Invoke() == kTfLiteOk);
178 std::vector<bool> tfLiteOutputValues = tfLiteInterpreter.GetOutputResult(0);
179 std::vector<int32_t> tfLiteOutputShape = tfLiteInterpreter.GetOutputShape(0);
180
181 // Setup interpreter with Arm NN Delegate applied.
182 auto armnnInterpreter = DelegateTestInterpreter(modelBuffer, backends);
183 CHECK(armnnInterpreter.AllocateTensors() == kTfLiteOk);
184 CHECK(armnnInterpreter.FillInputTensor<T>(input0Values, 0) == kTfLiteOk);
185 CHECK(armnnInterpreter.FillInputTensor<T>(input1Values, 1) == kTfLiteOk);
186 CHECK(armnnInterpreter.Invoke() == kTfLiteOk);
187 std::vector<bool> armnnOutputValues = armnnInterpreter.GetOutputResult(0);
188 std::vector<int32_t> armnnOutputShape = armnnInterpreter.GetOutputShape(0);
189
190 armnnDelegate::CompareData(expectedOutputValues, armnnOutputValues, expectedOutputValues.size());
191 armnnDelegate::CompareData(expectedOutputValues, tfLiteOutputValues, expectedOutputValues.size());
192 armnnDelegate::CompareData(tfLiteOutputValues, armnnOutputValues, expectedOutputValues.size());
193
194 armnnDelegate::CompareOutputShape(tfLiteOutputShape, armnnOutputShape, outputShape);
195
196 tfLiteInterpreter.Cleanup();
197 armnnInterpreter.Cleanup();
198 }
199
200 } // anonymous namespace