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
CreateReduceTfLiteModel(tflite::BuiltinOperator reduceOperatorCode,tflite::TensorType tensorType,std::vector<int32_t> & input0TensorShape,std::vector<int32_t> & input1TensorShape,const std::vector<int32_t> & outputTensorShape,std::vector<int32_t> & axisData,const bool keepDims,float quantScale=1.0f,int quantOffset=0,bool kTfLiteNoQuantizationForQuantized=false)24 std::vector<char> CreateReduceTfLiteModel(tflite::BuiltinOperator reduceOperatorCode,
25 tflite::TensorType tensorType,
26 std::vector<int32_t>& input0TensorShape,
27 std::vector<int32_t>& input1TensorShape,
28 const std::vector <int32_t>& outputTensorShape,
29 std::vector<int32_t>& axisData,
30 const bool keepDims,
31 float quantScale = 1.0f,
32 int quantOffset = 0,
33 bool kTfLiteNoQuantizationForQuantized = false)
34 {
35 using namespace tflite;
36 flatbuffers::FlatBufferBuilder flatBufferBuilder;
37
38 flatbuffers::Offset<tflite::Buffer> buffers[4] = {
39 CreateBuffer(flatBufferBuilder),
40 CreateBuffer(flatBufferBuilder),
41 CreateBuffer(flatBufferBuilder,
42 flatBufferBuilder.CreateVector(reinterpret_cast<const uint8_t*>(axisData.data()),
43 sizeof(int32_t) * axisData.size())),
44 CreateBuffer(flatBufferBuilder)
45 };
46
47 flatbuffers::Offset<tflite::QuantizationParameters> quantizationParametersAxis
48 = CreateQuantizationParameters(flatBufferBuilder);
49
50 flatbuffers::Offset<tflite::QuantizationParameters> quantizationParameters;
51
52 if (kTfLiteNoQuantizationForQuantized)
53 {
54 if ((quantScale == 1 || quantScale == 0) && quantOffset == 0)
55 {
56 // Creates quantization parameter with quantization.type = kTfLiteNoQuantization
57 quantizationParameters = CreateQuantizationParameters(flatBufferBuilder);
58 }
59 else
60 {
61 // Creates quantization parameter with quantization.type != kTfLiteNoQuantization
62 quantizationParameters = CreateQuantizationParameters(
63 flatBufferBuilder,
64 0,
65 0,
66 flatBufferBuilder.CreateVector<float>({quantScale}),
67 flatBufferBuilder.CreateVector<int64_t>({quantOffset}));
68 }
69 }
70 else
71 {
72 quantizationParameters = CreateQuantizationParameters(
73 flatBufferBuilder,
74 0,
75 0,
76 flatBufferBuilder.CreateVector<float>({quantScale}),
77 flatBufferBuilder.CreateVector<int64_t>({quantOffset}));
78 }
79
80 std::array<flatbuffers::Offset<Tensor>, 3> tensors;
81 tensors[0] = CreateTensor(flatBufferBuilder,
82 flatBufferBuilder.CreateVector<int32_t>(input0TensorShape.data(),
83 input0TensorShape.size()),
84 tensorType,
85 1,
86 flatBufferBuilder.CreateString("input"),
87 quantizationParameters);
88
89 tensors[1] = CreateTensor(flatBufferBuilder,
90 flatBufferBuilder.CreateVector<int32_t>(input1TensorShape.data(),
91 input1TensorShape.size()),
92 ::tflite::TensorType_INT32,
93 2,
94 flatBufferBuilder.CreateString("axis"),
95 quantizationParametersAxis);
96
97 // Create output tensor
98 tensors[2] = CreateTensor(flatBufferBuilder,
99 flatBufferBuilder.CreateVector<int32_t>(outputTensorShape.data(),
100 outputTensorShape.size()),
101 tensorType,
102 3,
103 flatBufferBuilder.CreateString("output"),
104 quantizationParameters);
105
106 // Create operator. Reduce operations MIN, MAX, SUM, MEAN, PROD uses ReducerOptions.
107 tflite::BuiltinOptions operatorBuiltinOptionsType = tflite::BuiltinOptions_ReducerOptions;
108 flatbuffers::Offset<void> operatorBuiltinOptions = CreateReducerOptions(flatBufferBuilder, keepDims).Union();
109
110 const std::vector<int> operatorInputs{ {0, 1} };
111 const std::vector<int> operatorOutputs{ 2 };
112 flatbuffers::Offset <Operator> reduceOperator =
113 CreateOperator(flatBufferBuilder,
114 0,
115 flatBufferBuilder.CreateVector<int32_t>(operatorInputs.data(), operatorInputs.size()),
116 flatBufferBuilder.CreateVector<int32_t>(operatorOutputs.data(), operatorOutputs.size()),
117 operatorBuiltinOptionsType,
118 operatorBuiltinOptions);
119
120 const std::vector<int> subgraphInputs{ {0, 1} };
121 const std::vector<int> subgraphOutputs{ 2 };
122 flatbuffers::Offset <SubGraph> subgraph =
123 CreateSubGraph(flatBufferBuilder,
124 flatBufferBuilder.CreateVector(tensors.data(), tensors.size()),
125 flatBufferBuilder.CreateVector<int32_t>(subgraphInputs.data(), subgraphInputs.size()),
126 flatBufferBuilder.CreateVector<int32_t>(subgraphOutputs.data(), subgraphOutputs.size()),
127 flatBufferBuilder.CreateVector(&reduceOperator, 1));
128
129 flatbuffers::Offset <flatbuffers::String> modelDescription =
130 flatBufferBuilder.CreateString("ArmnnDelegate: Reduce Operator Model");
131 flatbuffers::Offset <OperatorCode> operatorCode = CreateOperatorCode(flatBufferBuilder, reduceOperatorCode);
132
133 flatbuffers::Offset <Model> flatbufferModel =
134 CreateModel(flatBufferBuilder,
135 TFLITE_SCHEMA_VERSION,
136 flatBufferBuilder.CreateVector(&operatorCode, 1),
137 flatBufferBuilder.CreateVector(&subgraph, 1),
138 modelDescription,
139 flatBufferBuilder.CreateVector(buffers, 4));
140
141 flatBufferBuilder.Finish(flatbufferModel, armnnDelegate::FILE_IDENTIFIER);
142
143 return std::vector<char>(flatBufferBuilder.GetBufferPointer(),
144 flatBufferBuilder.GetBufferPointer() + flatBufferBuilder.GetSize());
145 }
146
147 template <typename T>
ReduceTest(tflite::BuiltinOperator reduceOperatorCode,tflite::TensorType tensorType,std::vector<armnn::BackendId> & backends,std::vector<int32_t> & input0Shape,std::vector<int32_t> & input1Shape,std::vector<int32_t> & expectedOutputShape,std::vector<T> & input0Values,std::vector<int32_t> & input1Values,std::vector<T> & expectedOutputValues,const bool keepDims,float quantScale=1.0f,int quantOffset=0)148 void ReduceTest(tflite::BuiltinOperator reduceOperatorCode,
149 tflite::TensorType tensorType,
150 std::vector<armnn::BackendId>& backends,
151 std::vector<int32_t>& input0Shape,
152 std::vector<int32_t>& input1Shape,
153 std::vector<int32_t>& expectedOutputShape,
154 std::vector<T>& input0Values,
155 std::vector<int32_t>& input1Values,
156 std::vector<T>& expectedOutputValues,
157 const bool keepDims,
158 float quantScale = 1.0f,
159 int quantOffset = 0)
160 {
161 using namespace delegateTestInterpreter;
162 std::vector<char> modelBufferArmNN = CreateReduceTfLiteModel(reduceOperatorCode,
163 tensorType,
164 input0Shape,
165 input1Shape,
166 expectedOutputShape,
167 input1Values,
168 keepDims,
169 quantScale,
170 quantOffset,
171 false);
172 std::vector<char> modelBufferTFLite = CreateReduceTfLiteModel(reduceOperatorCode,
173 tensorType,
174 input0Shape,
175 input1Shape,
176 expectedOutputShape,
177 input1Values,
178 keepDims,
179 quantScale,
180 quantOffset,
181 true);
182
183 // Setup interpreter with just TFLite Runtime.
184 auto tfLiteInterpreter = DelegateTestInterpreter(modelBufferTFLite);
185 CHECK(tfLiteInterpreter.AllocateTensors() == kTfLiteOk);
186 CHECK(tfLiteInterpreter.FillInputTensor<T>(input0Values, 0) == kTfLiteOk);
187 CHECK(tfLiteInterpreter.Invoke() == kTfLiteOk);
188 std::vector<T> tfLiteOutputValues = tfLiteInterpreter.GetOutputResult<T>(0);
189 std::vector<int32_t> tfLiteOutputShape = tfLiteInterpreter.GetOutputShape(0);
190
191 // Setup interpreter with Arm NN Delegate applied.
192 auto armnnInterpreter = DelegateTestInterpreter(modelBufferArmNN, backends);
193 CHECK(armnnInterpreter.AllocateTensors() == kTfLiteOk);
194 CHECK(armnnInterpreter.FillInputTensor<T>(input0Values, 0) == kTfLiteOk);
195 CHECK(armnnInterpreter.Invoke() == kTfLiteOk);
196 std::vector<T> armnnOutputValues = armnnInterpreter.GetOutputResult<T>(0);
197 std::vector<int32_t> armnnOutputShape = armnnInterpreter.GetOutputShape(0);
198
199 armnnDelegate::CompareOutputData<T>(tfLiteOutputValues, armnnOutputValues, expectedOutputValues);
200 armnnDelegate::CompareOutputShape(tfLiteOutputShape, armnnOutputShape, expectedOutputShape);
201
202 tfLiteInterpreter.Cleanup();
203 armnnInterpreter.Cleanup();
204 }
205
206 } // anonymous namespace