xref: /aosp_15_r20/external/armnn/src/armnnTfLiteParser/test/Constant.cpp (revision 89c4ff92f2867872bb9e2354d150bf0c8c502810)
1 //
2 // Copyright © 2017 Arm Ltd and Contributors. All rights reserved.
3 // SPDX-License-Identifier: MIT
4 //
5 
6 #include "ParserFlatbuffersFixture.hpp"
7 
8 
9 using armnnTfLiteParser::TfLiteParserImpl;
10 
11 TEST_SUITE("TensorflowLiteParser_Constant")
12 {
13 struct ConstantAddFixture : public ParserFlatbuffersFixture
14 {
ConstantAddFixtureConstantAddFixture15     explicit ConstantAddFixture(const std::string & inputShape,
16                                 const std::string & outputShape,
17                                 const std::string & constShape,
18                                 const std::string & constData)
19     {
20         m_JsonString = R"(
21             {
22                 "version": 3,
23                 "operator_codes": [ { "builtin_code": "ADD" } ],
24                 "subgraphs": [ {
25                     "tensors": [
26                         {
27                             "shape": )" + constShape + R"( ,
28                             "type": "UINT8",
29                             "buffer": 3,
30                             "name": "ConstTensor",
31                             "quantization": {
32                                 "min": [ 0.0 ],
33                                 "max": [ 255.0 ],
34                                 "scale": [ 1.0 ],
35                                 "zero_point": [ 0 ],
36                             }
37                         },
38                         {
39                             "shape": )" + inputShape + R"(,
40                             "type": "UINT8",
41                             "buffer": 1,
42                             "name": "InputTensor",
43                             "quantization": {
44                                 "min": [ 0.0 ],
45                                 "max": [ 255.0 ],
46                                 "scale": [ 1.0 ],
47                                 "zero_point": [ 0 ],
48                             }
49                         },
50                         {
51                             "shape": )" + outputShape + R"( ,
52                             "type": "UINT8",
53                             "buffer": 2,
54                             "name": "OutputTensor",
55                             "quantization": {
56                                 "min": [ 0.0 ],
57                                 "max": [ 255.0 ],
58                                 "scale": [ 1.0 ],
59                                 "zero_point": [ 0 ],
60                             }
61                         }
62                     ],
63                 "inputs": [ 1 ],
64                 "outputs": [ 2 ],
65                 "operators": [
66                     {
67                         "opcode_index": 0,
68                         "inputs": [ 1, 0 ],
69                         "outputs": [ 2 ],
70                         "builtin_options_type": "AddOptions",
71                         "builtin_options": {
72                         },
73                         "custom_options_format": "FLEXBUFFERS"
74                     }
75                 ],
76               } ],
77               "buffers" : [
78                   { },
79                   { },
80                   { },
81                   { "data": )" + constData + R"(, },
82               ]
83             }
84       )";
85       Setup();
86     }
87 };
88 
89 
90 struct SimpleConstantAddFixture : ConstantAddFixture
91 {
SimpleConstantAddFixtureSimpleConstantAddFixture92     SimpleConstantAddFixture()
93         : ConstantAddFixture("[ 2, 2 ]",        // inputShape
94                              "[ 2, 2 ]",        // outputShape
95                              "[ 2, 2 ]",        // constShape
96                              "[  4,5, 6,7 ]")   // constData
97     {}
98 };
99 
100 TEST_CASE_FIXTURE(SimpleConstantAddFixture, "SimpleConstantAdd")
101 {
102     RunTest<2, armnn::DataType::QAsymmU8>(
103                 0,
104                 {{"InputTensor", { 0, 1, 2, 3 }}},
105                 {{"OutputTensor", { 4, 6, 8, 10 }}}
106                 );
107 }
108 
109 }
110