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
24 template <typename T>
CreateFillTfLiteModel(tflite::BuiltinOperator fillOperatorCode,tflite::TensorType tensorType,const std::vector<int32_t> & inputShape,const std::vector<int32_t> & tensorShape,const std::vector<T> fillValue)25 std::vector<char> CreateFillTfLiteModel(tflite::BuiltinOperator fillOperatorCode,
26 tflite::TensorType tensorType,
27 const std::vector<int32_t>& inputShape,
28 const std::vector <int32_t>& tensorShape,
29 const std::vector<T> fillValue)
30 {
31 using namespace tflite;
32 flatbuffers::FlatBufferBuilder flatBufferBuilder;
33
34 std::vector<flatbuffers::Offset<tflite::Buffer>> buffers;
35 buffers.push_back(CreateBuffer(flatBufferBuilder));
36 buffers.push_back(
37 CreateBuffer(flatBufferBuilder,
38 flatBufferBuilder.CreateVector(reinterpret_cast<const uint8_t*>(tensorShape.data()),
39 sizeof(int32_t) * tensorShape.size())));
40 buffers.push_back(
41 CreateBuffer(flatBufferBuilder,
42 flatBufferBuilder.CreateVector(reinterpret_cast<const uint8_t*>(fillValue.data()),
43 sizeof(T) * fillValue.size())));
44 buffers.push_back(CreateBuffer(flatBufferBuilder));
45
46 std::array<flatbuffers::Offset<Tensor>, 3> tensors;
47 tensors[0] = CreateTensor(flatBufferBuilder,
48 flatBufferBuilder.CreateVector<int32_t>(inputShape.data(),
49 inputShape.size()),
50 tflite::TensorType_INT32,
51 1,
52 flatBufferBuilder.CreateString("dims"));
53
54 std::vector<int32_t> fillShape = {};
55 tensors[1] = CreateTensor(flatBufferBuilder,
56 flatBufferBuilder.CreateVector<int32_t>(fillShape.data(),
57 fillShape.size()),
58 tensorType,
59 2,
60 flatBufferBuilder.CreateString("value"));
61
62 tensors[2] = CreateTensor(flatBufferBuilder,
63 flatBufferBuilder.CreateVector<int32_t>(tensorShape.data(),
64 tensorShape.size()),
65 tensorType,
66 3,
67 flatBufferBuilder.CreateString("output"));
68
69 tflite::BuiltinOptions operatorBuiltinOptionsType = BuiltinOptions_FillOptions;
70 flatbuffers::Offset<void> operatorBuiltinOptions = CreateFillOptions(flatBufferBuilder).Union();
71
72 // create operator
73 const std::vector<int> operatorInputs{ {0, 1} };
74 const std::vector<int> operatorOutputs{ 2 };
75 flatbuffers::Offset <Operator> fillOperator =
76 CreateOperator(flatBufferBuilder,
77 0,
78 flatBufferBuilder.CreateVector<int32_t>(operatorInputs.data(), operatorInputs.size()),
79 flatBufferBuilder.CreateVector<int32_t>(operatorOutputs.data(), operatorOutputs.size()),
80 operatorBuiltinOptionsType,
81 operatorBuiltinOptions);
82
83 const std::vector<int> subgraphInputs{ {0, 1} };
84 const std::vector<int> subgraphOutputs{ 2 };
85 flatbuffers::Offset <SubGraph> subgraph =
86 CreateSubGraph(flatBufferBuilder,
87 flatBufferBuilder.CreateVector(tensors.data(), tensors.size()),
88 flatBufferBuilder.CreateVector<int32_t>(subgraphInputs.data(), subgraphInputs.size()),
89 flatBufferBuilder.CreateVector<int32_t>(subgraphOutputs.data(), subgraphOutputs.size()),
90 flatBufferBuilder.CreateVector(&fillOperator, 1));
91
92 flatbuffers::Offset <flatbuffers::String> modelDescription =
93 flatBufferBuilder.CreateString("ArmnnDelegate: Fill Operator Model");
94 flatbuffers::Offset <OperatorCode> operatorCode = CreateOperatorCode(flatBufferBuilder,
95 fillOperatorCode);
96
97 flatbuffers::Offset <Model> flatbufferModel =
98 CreateModel(flatBufferBuilder,
99 TFLITE_SCHEMA_VERSION,
100 flatBufferBuilder.CreateVector(&operatorCode, 1),
101 flatBufferBuilder.CreateVector(&subgraph, 1),
102 modelDescription,
103 flatBufferBuilder.CreateVector(buffers.data(), buffers.size()));
104
105 flatBufferBuilder.Finish(flatbufferModel, armnnDelegate::FILE_IDENTIFIER);
106
107 return std::vector<char>(flatBufferBuilder.GetBufferPointer(),
108 flatBufferBuilder.GetBufferPointer() + flatBufferBuilder.GetSize());
109
110 }
111
112 template <typename T>
FillTest(tflite::BuiltinOperator fillOperatorCode,tflite::TensorType tensorType,const std::vector<armnn::BackendId> & backends,std::vector<int32_t> & inputShape,std::vector<int32_t> & tensorShape,std::vector<T> & expectedOutputValues,T fillValue)113 void FillTest(tflite::BuiltinOperator fillOperatorCode,
114 tflite::TensorType tensorType,
115 const std::vector<armnn::BackendId>& backends,
116 std::vector<int32_t >& inputShape,
117 std::vector<int32_t >& tensorShape,
118 std::vector<T>& expectedOutputValues,
119 T fillValue)
120 {
121 using namespace delegateTestInterpreter;
122 std::vector<char> modelBuffer = CreateFillTfLiteModel<T>(fillOperatorCode,
123 tensorType,
124 inputShape,
125 tensorShape,
126 {fillValue});
127
128 // Setup interpreter with just TFLite Runtime.
129 auto tfLiteInterpreter = DelegateTestInterpreter(modelBuffer);
130 CHECK(tfLiteInterpreter.AllocateTensors() == kTfLiteOk);
131 CHECK(tfLiteInterpreter.Invoke() == kTfLiteOk);
132 std::vector<T> tfLiteOutputValues = tfLiteInterpreter.GetOutputResult<T>(0);
133 std::vector<int32_t> tfLiteOutputShape = tfLiteInterpreter.GetOutputShape(0);
134
135 // Setup interpreter with Arm NN Delegate applied.
136 auto armnnInterpreter = DelegateTestInterpreter(modelBuffer, backends);
137 CHECK(armnnInterpreter.AllocateTensors() == kTfLiteOk);
138 CHECK(armnnInterpreter.Invoke() == kTfLiteOk);
139 std::vector<T> armnnOutputValues = armnnInterpreter.GetOutputResult<T>(0);
140 std::vector<int32_t> armnnOutputShape = armnnInterpreter.GetOutputShape(0);
141
142 armnnDelegate::CompareOutputData<T>(tfLiteOutputValues, armnnOutputValues, expectedOutputValues);
143 armnnDelegate::CompareOutputShape(tfLiteOutputShape, armnnOutputShape, tensorShape);
144
145 tfLiteInterpreter.Cleanup();
146 armnnInterpreter.Cleanup();
147 }
148
149 } // anonymous namespace
150