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
CreateUnpackTfLiteModel(tflite::BuiltinOperator unpackOperatorCode,tflite::TensorType tensorType,std::vector<int32_t> & inputTensorShape,const std::vector<int32_t> & outputTensorShape,const int32_t outputTensorNum,unsigned int axis=0,float quantScale=1.0f,int quantOffset=0)24 std::vector<char> CreateUnpackTfLiteModel(tflite::BuiltinOperator unpackOperatorCode,
25 tflite::TensorType tensorType,
26 std::vector<int32_t>& inputTensorShape,
27 const std::vector <int32_t>& outputTensorShape,
28 const int32_t outputTensorNum,
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
41 auto quantizationParameters =
42 CreateQuantizationParameters(flatBufferBuilder,
43 0,
44 0,
45 flatBufferBuilder.CreateVector<float>({ quantScale }),
46 flatBufferBuilder.CreateVector<int64_t>({ quantOffset }));
47
48 const std::vector<int32_t> operatorInputs{ 0 };
49 std::vector<int32_t> operatorOutputs{};
50 const std::vector<int> subgraphInputs{ 0 };
51 std::vector<int> subgraphOutputs{};
52
53 std::vector<flatbuffers::Offset<Tensor>> tensors(outputTensorNum + 1);
54
55 // Create input tensor
56 tensors[0] = CreateTensor(flatBufferBuilder,
57 flatBufferBuilder.CreateVector<int32_t>(inputTensorShape.data(),
58 inputTensorShape.size()),
59 tensorType,
60 1,
61 flatBufferBuilder.CreateString("input"),
62 quantizationParameters);
63
64 for (int i = 0; i < outputTensorNum; ++i)
65 {
66 tensors[i + 1] = CreateTensor(flatBufferBuilder,
67 flatBufferBuilder.CreateVector<int32_t>(outputTensorShape.data(),
68 outputTensorShape.size()),
69 tensorType,
70 (i + 2),
71 flatBufferBuilder.CreateString("output" + std::to_string(i)),
72 quantizationParameters);
73
74 buffers.push_back(CreateBuffer(flatBufferBuilder));
75 operatorOutputs.push_back(i + 1);
76 subgraphOutputs.push_back(i + 1);
77 }
78
79 // create operator
80 tflite::BuiltinOptions operatorBuiltinOptionsType = tflite::BuiltinOptions_UnpackOptions;
81 flatbuffers::Offset<void> operatorBuiltinOptions =
82 CreateUnpackOptions(flatBufferBuilder, outputTensorNum, axis).Union();
83
84 flatbuffers::Offset <Operator> unpackOperator =
85 CreateOperator(flatBufferBuilder,
86 0,
87 flatBufferBuilder.CreateVector<int32_t>(operatorInputs.data(), operatorInputs.size()),
88 flatBufferBuilder.CreateVector<int32_t>(operatorOutputs.data(), operatorOutputs.size()),
89 operatorBuiltinOptionsType,
90 operatorBuiltinOptions);
91
92 flatbuffers::Offset <SubGraph> subgraph =
93 CreateSubGraph(flatBufferBuilder,
94 flatBufferBuilder.CreateVector(tensors.data(), tensors.size()),
95 flatBufferBuilder.CreateVector<int32_t>(subgraphInputs.data(), subgraphInputs.size()),
96 flatBufferBuilder.CreateVector<int32_t>(subgraphOutputs.data(), subgraphOutputs.size()),
97 flatBufferBuilder.CreateVector(&unpackOperator, 1));
98
99 flatbuffers::Offset <flatbuffers::String> modelDescription =
100 flatBufferBuilder.CreateString("ArmnnDelegate: Unpack Operator Model");
101 flatbuffers::Offset <OperatorCode> operatorCode = CreateOperatorCode(flatBufferBuilder, unpackOperatorCode);
102
103 flatbuffers::Offset <Model> flatbufferModel =
104 CreateModel(flatBufferBuilder,
105 TFLITE_SCHEMA_VERSION,
106 flatBufferBuilder.CreateVector(&operatorCode, 1),
107 flatBufferBuilder.CreateVector(&subgraph, 1),
108 modelDescription,
109 flatBufferBuilder.CreateVector(buffers));
110
111 flatBufferBuilder.Finish(flatbufferModel, armnnDelegate::FILE_IDENTIFIER);
112
113 return std::vector<char>(flatBufferBuilder.GetBufferPointer(),
114 flatBufferBuilder.GetBufferPointer() + flatBufferBuilder.GetSize());
115 }
116
117 template <typename T>
UnpackTest(tflite::BuiltinOperator unpackOperatorCode,tflite::TensorType tensorType,std::vector<armnn::BackendId> & backends,std::vector<int32_t> & inputShape,std::vector<int32_t> & expectedOutputShape,std::vector<T> & inputValues,std::vector<std::vector<T>> & expectedOutputValues,unsigned int axis=0,float quantScale=1.0f,int quantOffset=0)118 void UnpackTest(tflite::BuiltinOperator unpackOperatorCode,
119 tflite::TensorType tensorType,
120 std::vector<armnn::BackendId>& backends,
121 std::vector<int32_t>& inputShape,
122 std::vector<int32_t>& expectedOutputShape,
123 std::vector<T>& inputValues,
124 std::vector<std::vector<T>>& expectedOutputValues,
125 unsigned int axis = 0,
126 float quantScale = 1.0f,
127 int quantOffset = 0)
128 {
129 using namespace delegateTestInterpreter;
130 std::vector<char> modelBuffer = CreateUnpackTfLiteModel(unpackOperatorCode,
131 tensorType,
132 inputShape,
133 expectedOutputShape,
134 expectedOutputValues.size(),
135 axis,
136 quantScale,
137 quantOffset);
138
139 // Setup interpreter with just TFLite Runtime.
140 auto tfLiteInterpreter = DelegateTestInterpreter(modelBuffer);
141 CHECK(tfLiteInterpreter.AllocateTensors() == kTfLiteOk);
142 CHECK(tfLiteInterpreter.FillInputTensor<T>(inputValues, 0) == kTfLiteOk);
143 CHECK(tfLiteInterpreter.Invoke() == kTfLiteOk);
144
145 // Setup interpreter with Arm NN Delegate applied.
146 auto armnnInterpreter = DelegateTestInterpreter(modelBuffer, backends);
147 CHECK(armnnInterpreter.AllocateTensors() == kTfLiteOk);
148 CHECK(armnnInterpreter.FillInputTensor<T>(inputValues, 0) == kTfLiteOk);
149 CHECK(armnnInterpreter.Invoke() == kTfLiteOk);
150
151 // Compare output data
152 for (unsigned int i = 0; i < expectedOutputValues.size(); ++i)
153 {
154 std::vector<T> tfLiteOutputValues = tfLiteInterpreter.GetOutputResult<T>(i);
155 std::vector<int32_t> tfLiteOutputShape = tfLiteInterpreter.GetOutputShape(i);
156
157 std::vector<T> armnnOutputValues = armnnInterpreter.GetOutputResult<T>(i);
158 std::vector<int32_t> armnnOutputShape = armnnInterpreter.GetOutputShape(i);
159
160 armnnDelegate::CompareOutputData<T>(tfLiteOutputValues, armnnOutputValues, expectedOutputValues[i]);
161 armnnDelegate::CompareOutputShape(tfLiteOutputShape, armnnOutputShape, expectedOutputShape);
162 }
163
164 tfLiteInterpreter.Cleanup();
165 armnnInterpreter.Cleanup();
166 }
167
168 } // anonymous namespace