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
CreateResizeTfLiteModel(tflite::BuiltinOperator operatorCode,tflite::TensorType inputTensorType,const std::vector<int32_t> & inputTensorShape,const std::vector<int32_t> & sizeTensorData,const std::vector<int32_t> & sizeTensorShape,const std::vector<int32_t> & outputTensorShape)24 std::vector<char> CreateResizeTfLiteModel(tflite::BuiltinOperator operatorCode,
25 tflite::TensorType inputTensorType,
26 const std::vector <int32_t>& inputTensorShape,
27 const std::vector <int32_t>& sizeTensorData,
28 const std::vector <int32_t>& sizeTensorShape,
29 const std::vector <int32_t>& outputTensorShape)
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(CreateBuffer(flatBufferBuilder));
37 buffers.push_back(CreateBuffer(flatBufferBuilder,
38 flatBufferBuilder.CreateVector(
39 reinterpret_cast<const uint8_t*>(sizeTensorData.data()),
40 sizeof(int32_t) * sizeTensorData.size())));
41 buffers.push_back(CreateBuffer(flatBufferBuilder));
42
43 std::array<flatbuffers::Offset<Tensor>, 3> tensors;
44 tensors[0] = CreateTensor(flatBufferBuilder,
45 flatBufferBuilder.CreateVector<int32_t>(inputTensorShape.data(), inputTensorShape.size()),
46 inputTensorType,
47 1,
48 flatBufferBuilder.CreateString("input_tensor"));
49
50 tensors[1] = CreateTensor(flatBufferBuilder,
51 flatBufferBuilder.CreateVector<int32_t>(sizeTensorShape.data(),
52 sizeTensorShape.size()),
53 TensorType_INT32,
54 2,
55 flatBufferBuilder.CreateString("size_input_tensor"));
56
57 tensors[2] = CreateTensor(flatBufferBuilder,
58 flatBufferBuilder.CreateVector<int32_t>(outputTensorShape.data(),
59 outputTensorShape.size()),
60 inputTensorType,
61 3,
62 flatBufferBuilder.CreateString("output_tensor"));
63
64 // Create Operator
65 tflite::BuiltinOptions operatorBuiltinOptionsType = tflite::BuiltinOptions_NONE;
66 flatbuffers::Offset<void> operatorBuiltinOption = 0;
67 switch (operatorCode)
68 {
69 case BuiltinOperator_RESIZE_BILINEAR:
70 {
71 operatorBuiltinOption = CreateResizeBilinearOptions(flatBufferBuilder, false, false).Union();
72 operatorBuiltinOptionsType = tflite::BuiltinOptions_ResizeBilinearOptions;
73 break;
74 }
75 case BuiltinOperator_RESIZE_NEAREST_NEIGHBOR:
76 {
77 operatorBuiltinOption = CreateResizeNearestNeighborOptions(flatBufferBuilder, false, false).Union();
78 operatorBuiltinOptionsType = tflite::BuiltinOptions_ResizeNearestNeighborOptions;
79 break;
80 }
81 default:
82 break;
83 }
84
85 const std::vector<int> operatorInputs{0, 1};
86 const std::vector<int> operatorOutputs{2};
87 flatbuffers::Offset <Operator> resizeOperator =
88 CreateOperator(flatBufferBuilder,
89 0,
90 flatBufferBuilder.CreateVector<int32_t>(operatorInputs.data(), operatorInputs.size()),
91 flatBufferBuilder.CreateVector<int32_t>(operatorOutputs.data(), operatorOutputs.size()),
92 operatorBuiltinOptionsType,
93 operatorBuiltinOption);
94
95 const std::vector<int> subgraphInputs{0, 1};
96 const std::vector<int> subgraphOutputs{2};
97 flatbuffers::Offset <SubGraph> subgraph =
98 CreateSubGraph(flatBufferBuilder,
99 flatBufferBuilder.CreateVector(tensors.data(), tensors.size()),
100 flatBufferBuilder.CreateVector<int32_t>(subgraphInputs.data(), subgraphInputs.size()),
101 flatBufferBuilder.CreateVector<int32_t>(subgraphOutputs.data(), subgraphOutputs.size()),
102 flatBufferBuilder.CreateVector(&resizeOperator, 1));
103
104 flatbuffers::Offset <flatbuffers::String> modelDescription =
105 flatBufferBuilder.CreateString("ArmnnDelegate: Resize Biliniar Operator Model");
106 flatbuffers::Offset <OperatorCode> opCode = CreateOperatorCode(flatBufferBuilder, operatorCode);
107
108 flatbuffers::Offset <Model> flatbufferModel =
109 CreateModel(flatBufferBuilder,
110 TFLITE_SCHEMA_VERSION,
111 flatBufferBuilder.CreateVector(&opCode, 1),
112 flatBufferBuilder.CreateVector(&subgraph, 1),
113 modelDescription,
114 flatBufferBuilder.CreateVector(buffers.data(), buffers.size()));
115
116 flatBufferBuilder.Finish(flatbufferModel, armnnDelegate::FILE_IDENTIFIER);
117
118 return std::vector<char>(flatBufferBuilder.GetBufferPointer(),
119 flatBufferBuilder.GetBufferPointer() + flatBufferBuilder.GetSize());
120 }
121
ResizeFP32TestImpl(tflite::BuiltinOperator operatorCode,std::vector<armnn::BackendId> & backends,std::vector<float> & input1Values,std::vector<int32_t> input1Shape,std::vector<int32_t> input2NewShape,std::vector<int32_t> input2Shape,std::vector<float> & expectedOutputValues,std::vector<int32_t> expectedOutputShape)122 void ResizeFP32TestImpl(tflite::BuiltinOperator operatorCode,
123 std::vector<armnn::BackendId>& backends,
124 std::vector<float>& input1Values,
125 std::vector<int32_t> input1Shape,
126 std::vector<int32_t> input2NewShape,
127 std::vector<int32_t> input2Shape,
128 std::vector<float>& expectedOutputValues,
129 std::vector<int32_t> expectedOutputShape)
130 {
131 using namespace delegateTestInterpreter;
132
133 std::vector<char> modelBuffer = CreateResizeTfLiteModel(operatorCode,
134 ::tflite::TensorType_FLOAT32,
135 input1Shape,
136 input2NewShape,
137 input2Shape,
138 expectedOutputShape);
139
140 // Setup interpreter with just TFLite Runtime.
141 auto tfLiteInterpreter = DelegateTestInterpreter(modelBuffer);
142 CHECK(tfLiteInterpreter.AllocateTensors() == kTfLiteOk);
143 CHECK(tfLiteInterpreter.FillInputTensor<float>(input1Values, 0) == kTfLiteOk);
144 CHECK(tfLiteInterpreter.FillInputTensor<int32_t>(input2NewShape, 1) == kTfLiteOk);
145 CHECK(tfLiteInterpreter.Invoke() == kTfLiteOk);
146 std::vector<float> tfLiteOutputValues = tfLiteInterpreter.GetOutputResult<float>(0);
147 std::vector<int32_t> tfLiteOutputShape = tfLiteInterpreter.GetOutputShape(0);
148
149 // Setup interpreter with Arm NN Delegate applied.
150 auto armnnInterpreter = DelegateTestInterpreter(modelBuffer, backends);
151 CHECK(armnnInterpreter.AllocateTensors() == kTfLiteOk);
152 CHECK(armnnInterpreter.FillInputTensor<float>(input1Values, 0) == kTfLiteOk);
153 CHECK(armnnInterpreter.FillInputTensor<int32_t>(input2NewShape, 1) == kTfLiteOk);
154 CHECK(armnnInterpreter.Invoke() == kTfLiteOk);
155 std::vector<float> armnnOutputValues = armnnInterpreter.GetOutputResult<float>(0);
156 std::vector<int32_t> armnnOutputShape = armnnInterpreter.GetOutputShape(0);
157
158 armnnDelegate::CompareOutputData<float>(tfLiteOutputValues, armnnOutputValues, expectedOutputValues);
159 armnnDelegate::CompareOutputShape(tfLiteOutputShape, armnnOutputShape, expectedOutputShape);
160
161 tfLiteInterpreter.Cleanup();
162 armnnInterpreter.Cleanup();
163 }
164
165 } // anonymous namespace