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
CreatePooling2dTfLiteModel(tflite::BuiltinOperator poolingOperatorCode,tflite::TensorType tensorType,const std::vector<int32_t> & inputTensorShape,const std::vector<int32_t> & outputTensorShape,tflite::Padding padding=tflite::Padding_SAME,int32_t strideWidth=0,int32_t strideHeight=0,int32_t filterWidth=0,int32_t filterHeight=0,tflite::ActivationFunctionType fusedActivation=tflite::ActivationFunctionType_NONE,float quantScale=1.0f,int quantOffset=0)24 std::vector<char> CreatePooling2dTfLiteModel(
25 tflite::BuiltinOperator poolingOperatorCode,
26 tflite::TensorType tensorType,
27 const std::vector <int32_t>& inputTensorShape,
28 const std::vector <int32_t>& outputTensorShape,
29 tflite::Padding padding = tflite::Padding_SAME,
30 int32_t strideWidth = 0,
31 int32_t strideHeight = 0,
32 int32_t filterWidth = 0,
33 int32_t filterHeight = 0,
34 tflite::ActivationFunctionType fusedActivation = tflite::ActivationFunctionType_NONE,
35 float quantScale = 1.0f,
36 int quantOffset = 0)
37 {
38 using namespace tflite;
39 flatbuffers::FlatBufferBuilder flatBufferBuilder;
40
41 flatbuffers::Offset<tflite::Buffer> buffers[3] = {CreateBuffer(flatBufferBuilder),
42 CreateBuffer(flatBufferBuilder),
43 CreateBuffer(flatBufferBuilder)};
44
45 auto quantizationParameters =
46 CreateQuantizationParameters(flatBufferBuilder,
47 0,
48 0,
49 flatBufferBuilder.CreateVector<float>({ quantScale }),
50 flatBufferBuilder.CreateVector<int64_t>({ quantOffset }));
51
52 flatbuffers::Offset<Tensor> tensors[2] {
53 CreateTensor(flatBufferBuilder,
54 flatBufferBuilder.CreateVector<int32_t>(inputTensorShape),
55 tensorType,
56 1,
57 flatBufferBuilder.CreateString("input"),
58 quantizationParameters),
59
60 CreateTensor(flatBufferBuilder,
61 flatBufferBuilder.CreateVector<int32_t>(outputTensorShape),
62 tensorType,
63 2,
64 flatBufferBuilder.CreateString("output"),
65 quantizationParameters)
66 };
67
68 // create operator
69 tflite::BuiltinOptions operatorBuiltinOptionsType = BuiltinOptions_Pool2DOptions;
70 flatbuffers::Offset<void> operatorBuiltinOptions = CreatePool2DOptions(flatBufferBuilder,
71 padding,
72 strideWidth,
73 strideHeight,
74 filterWidth,
75 filterHeight,
76 fusedActivation).Union();
77
78 const std::vector<int32_t> operatorInputs{0};
79 const std::vector<int32_t> operatorOutputs{1};
80 flatbuffers::Offset <Operator> poolingOperator =
81 CreateOperator(flatBufferBuilder,
82 0,
83 flatBufferBuilder.CreateVector<int32_t>(operatorInputs),
84 flatBufferBuilder.CreateVector<int32_t>(operatorOutputs),
85 operatorBuiltinOptionsType,
86 operatorBuiltinOptions);
87
88 const int subgraphInputs[1] = {0};
89 const int subgraphOutputs[1] = {1};
90 flatbuffers::Offset <SubGraph> subgraph =
91 CreateSubGraph(flatBufferBuilder,
92 flatBufferBuilder.CreateVector(tensors, 2),
93 flatBufferBuilder.CreateVector<int32_t>(subgraphInputs, 1),
94 flatBufferBuilder.CreateVector<int32_t>(subgraphOutputs, 1),
95 flatBufferBuilder.CreateVector(&poolingOperator, 1));
96
97 flatbuffers::Offset <flatbuffers::String> modelDescription =
98 flatBufferBuilder.CreateString("ArmnnDelegate: Pooling2d Operator Model");
99 flatbuffers::Offset <OperatorCode> operatorCode = CreateOperatorCode(flatBufferBuilder, poolingOperatorCode);
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, 3));
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>
Pooling2dTest(tflite::BuiltinOperator poolingOperatorCode,tflite::TensorType tensorType,std::vector<armnn::BackendId> & backends,std::vector<int32_t> & inputShape,std::vector<int32_t> & outputShape,std::vector<T> & inputValues,std::vector<T> & expectedOutputValues,tflite::Padding padding=tflite::Padding_SAME,int32_t strideWidth=0,int32_t strideHeight=0,int32_t filterWidth=0,int32_t filterHeight=0,tflite::ActivationFunctionType fusedActivation=tflite::ActivationFunctionType_NONE,float quantScale=1.0f,int quantOffset=0)116 void Pooling2dTest(tflite::BuiltinOperator poolingOperatorCode,
117 tflite::TensorType tensorType,
118 std::vector<armnn::BackendId>& backends,
119 std::vector<int32_t>& inputShape,
120 std::vector<int32_t>& outputShape,
121 std::vector<T>& inputValues,
122 std::vector<T>& expectedOutputValues,
123 tflite::Padding padding = tflite::Padding_SAME,
124 int32_t strideWidth = 0,
125 int32_t strideHeight = 0,
126 int32_t filterWidth = 0,
127 int32_t filterHeight = 0,
128 tflite::ActivationFunctionType fusedActivation = tflite::ActivationFunctionType_NONE,
129 float quantScale = 1.0f,
130 int quantOffset = 0)
131 {
132 using namespace delegateTestInterpreter;
133 std::vector<char> modelBuffer = CreatePooling2dTfLiteModel(poolingOperatorCode,
134 tensorType,
135 inputShape,
136 outputShape,
137 padding,
138 strideWidth,
139 strideHeight,
140 filterWidth,
141 filterHeight,
142 fusedActivation,
143 quantScale,
144 quantOffset);
145
146 // Setup interpreter with just TFLite Runtime.
147 auto tfLiteInterpreter = DelegateTestInterpreter(modelBuffer);
148 CHECK(tfLiteInterpreter.AllocateTensors() == kTfLiteOk);
149 CHECK(tfLiteInterpreter.FillInputTensor<T>(inputValues, 0) == kTfLiteOk);
150 CHECK(tfLiteInterpreter.Invoke() == kTfLiteOk);
151 std::vector<T> tfLiteOutputValues = tfLiteInterpreter.GetOutputResult<T>(0);
152 std::vector<int32_t> tfLiteOutputShape = tfLiteInterpreter.GetOutputShape(0);
153
154 // Setup interpreter with Arm NN Delegate applied.
155 auto armnnInterpreter = DelegateTestInterpreter(modelBuffer, backends);
156 CHECK(armnnInterpreter.AllocateTensors() == kTfLiteOk);
157 CHECK(armnnInterpreter.FillInputTensor<T>(inputValues, 0) == kTfLiteOk);
158 CHECK(armnnInterpreter.Invoke() == kTfLiteOk);
159 std::vector<T> armnnOutputValues = armnnInterpreter.GetOutputResult<T>(0);
160 std::vector<int32_t> armnnOutputShape = armnnInterpreter.GetOutputShape(0);
161
162 armnnDelegate::CompareOutputData<T>(tfLiteOutputValues, armnnOutputValues, expectedOutputValues);
163 armnnDelegate::CompareOutputShape(tfLiteOutputShape, armnnOutputShape, outputShape);
164
165 tfLiteInterpreter.Cleanup();
166 armnnInterpreter.Cleanup();
167 }
168
169 } // anonymous namespace
170
171
172
173
174