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
CreatePreluTfLiteModel(tflite::BuiltinOperator preluOperatorCode,tflite::TensorType tensorType,const std::vector<int32_t> & inputShape,const std::vector<int32_t> & alphaShape,const std::vector<int32_t> & outputShape,std::vector<float> & alphaData,bool alphaIsConstant)24 std::vector<char> CreatePreluTfLiteModel(tflite::BuiltinOperator preluOperatorCode,
25 tflite::TensorType tensorType,
26 const std::vector<int32_t>& inputShape,
27 const std::vector<int32_t>& alphaShape,
28 const std::vector<int32_t>& outputShape,
29 std::vector<float>& alphaData,
30 bool alphaIsConstant)
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, flatBufferBuilder.CreateVector(
39 reinterpret_cast<const uint8_t *>(alphaData.data()), sizeof(float) * alphaData.size())));
40 buffers.push_back(CreateBuffer(flatBufferBuilder));
41
42
43 auto quantizationParameters =
44 CreateQuantizationParameters(flatBufferBuilder,
45 0,
46 0,
47 flatBufferBuilder.CreateVector<float>({ 1.0f }),
48 flatBufferBuilder.CreateVector<int64_t>({ 0 }));
49
50 auto inputTensor = CreateTensor(flatBufferBuilder,
51 flatBufferBuilder.CreateVector<int32_t>(inputShape.data(),
52 inputShape.size()),
53 tensorType,
54 1,
55 flatBufferBuilder.CreateString("input"),
56 quantizationParameters);
57
58 auto alphaTensor = CreateTensor(flatBufferBuilder,
59 flatBufferBuilder.CreateVector<int32_t>(alphaShape.data(),
60 alphaShape.size()),
61 tensorType,
62 2,
63 flatBufferBuilder.CreateString("alpha"),
64 quantizationParameters);
65
66 auto outputTensor = CreateTensor(flatBufferBuilder,
67 flatBufferBuilder.CreateVector<int32_t>(outputShape.data(),
68 outputShape.size()),
69 tensorType,
70 3,
71 flatBufferBuilder.CreateString("output"),
72 quantizationParameters);
73
74 std::vector<flatbuffers::Offset<Tensor>> tensors = { inputTensor, alphaTensor, outputTensor };
75
76 const std::vector<int> operatorInputs{0, 1};
77 const std::vector<int> operatorOutputs{2};
78 flatbuffers::Offset <Operator> preluOperator =
79 CreateOperator(flatBufferBuilder,
80 0,
81 flatBufferBuilder.CreateVector<int32_t>(operatorInputs.data(), operatorInputs.size()),
82 flatBufferBuilder.CreateVector<int32_t>(operatorOutputs.data(), operatorOutputs.size()));
83
84 std::vector<int> subgraphInputs{0};
85 if (!alphaIsConstant)
86 {
87 subgraphInputs.push_back(1);
88 }
89
90 const std::vector<int> subgraphOutputs{2};
91 flatbuffers::Offset <SubGraph> subgraph =
92 CreateSubGraph(flatBufferBuilder,
93 flatBufferBuilder.CreateVector(tensors.data(), tensors.size()),
94 flatBufferBuilder.CreateVector<int32_t>(subgraphInputs.data(), subgraphInputs.size()),
95 flatBufferBuilder.CreateVector<int32_t>(subgraphOutputs.data(), subgraphOutputs.size()),
96 flatBufferBuilder.CreateVector(&preluOperator, 1));
97
98 flatbuffers::Offset <flatbuffers::String> modelDescription =
99 flatBufferBuilder.CreateString("ArmnnDelegate: Prelu Operator Model");
100 flatbuffers::Offset <OperatorCode> opCode = CreateOperatorCode(flatBufferBuilder, preluOperatorCode);
101
102 flatbuffers::Offset <Model> flatbufferModel =
103 CreateModel(flatBufferBuilder,
104 TFLITE_SCHEMA_VERSION,
105 flatBufferBuilder.CreateVector(&opCode, 1),
106 flatBufferBuilder.CreateVector(&subgraph, 1),
107 modelDescription,
108 flatBufferBuilder.CreateVector(buffers.data(), buffers.size()));
109
110 flatBufferBuilder.Finish(flatbufferModel, armnnDelegate::FILE_IDENTIFIER);
111
112 return std::vector<char>(flatBufferBuilder.GetBufferPointer(),
113 flatBufferBuilder.GetBufferPointer() + flatBufferBuilder.GetSize());
114 }
115
PreluTest(tflite::BuiltinOperator preluOperatorCode,tflite::TensorType tensorType,const std::vector<armnn::BackendId> & backends,const std::vector<int32_t> & inputShape,const std::vector<int32_t> & alphaShape,std::vector<int32_t> & outputShape,std::vector<float> & inputData,std::vector<float> & alphaData,std::vector<float> & expectedOutput,bool alphaIsConstant)116 void PreluTest(tflite::BuiltinOperator preluOperatorCode,
117 tflite::TensorType tensorType,
118 const std::vector<armnn::BackendId>& backends,
119 const std::vector<int32_t>& inputShape,
120 const std::vector<int32_t>& alphaShape,
121 std::vector<int32_t>& outputShape,
122 std::vector<float>& inputData,
123 std::vector<float>& alphaData,
124 std::vector<float>& expectedOutput,
125 bool alphaIsConstant)
126 {
127 using namespace delegateTestInterpreter;
128
129 std::vector<char> modelBuffer = CreatePreluTfLiteModel(preluOperatorCode,
130 tensorType,
131 inputShape,
132 alphaShape,
133 outputShape,
134 alphaData,
135 alphaIsConstant);
136
137
138 // Setup interpreter with just TFLite Runtime.
139 auto tfLiteInterpreter = DelegateTestInterpreter(modelBuffer);
140 CHECK(tfLiteInterpreter.AllocateTensors() == kTfLiteOk);
141
142 // Setup interpreter with Arm NN Delegate applied.
143 auto armnnInterpreter = DelegateTestInterpreter(modelBuffer, backends);
144 CHECK(armnnInterpreter.AllocateTensors() == kTfLiteOk);
145
146 CHECK(armnnInterpreter.FillInputTensor<float>(inputData, 0) == kTfLiteOk);
147 CHECK(tfLiteInterpreter.FillInputTensor<float>(inputData, 0) == kTfLiteOk);
148
149 // Set alpha data if not constant
150 if (!alphaIsConstant)
151 {
152 CHECK(tfLiteInterpreter.FillInputTensor<float>(alphaData, 1) == kTfLiteOk);
153 CHECK(armnnInterpreter.FillInputTensor<float>(alphaData, 1) == kTfLiteOk);
154 }
155
156 CHECK(tfLiteInterpreter.Invoke() == kTfLiteOk);
157 std::vector<float> tfLiteOutputValues = tfLiteInterpreter.GetOutputResult<float>(0);
158
159 CHECK(armnnInterpreter.Invoke() == kTfLiteOk);
160 std::vector<float> armnnOutputValues = armnnInterpreter.GetOutputResult<float>(0);
161
162 armnnDelegate::CompareOutputData<float>(tfLiteOutputValues, armnnOutputValues, expectedOutput);
163
164 // Don't compare shapes on dynamic output tests, as output shape gets cleared.
165 if(!outputShape.empty())
166 {
167 std::vector<int32_t> tfLiteOutputShape = tfLiteInterpreter.GetOutputShape(0);
168 std::vector<int32_t> armnnOutputShape = armnnInterpreter.GetOutputShape(0);
169 armnnDelegate::CompareOutputShape(tfLiteOutputShape, armnnOutputShape, outputShape);
170 }
171
172 tfLiteInterpreter.Cleanup();
173 armnnInterpreter.Cleanup();
174 }
175 } // anonymous namespace