1 //
2 // Copyright © 2022-2023 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
CreateSliceTfLiteModel(tflite::TensorType tensorType,const std::vector<int32_t> & inputTensorShape,const std::vector<int32_t> & beginTensorData,const std::vector<int32_t> & sizeTensorData,const std::vector<int32_t> & beginTensorShape,const std::vector<int32_t> & sizeTensorShape,const std::vector<int32_t> & outputTensorShape)24 std::vector<char> CreateSliceTfLiteModel(tflite::TensorType tensorType,
25 const std::vector<int32_t>& inputTensorShape,
26 const std::vector<int32_t>& beginTensorData,
27 const std::vector<int32_t>& sizeTensorData,
28 const std::vector<int32_t>& beginTensorShape,
29 const std::vector<int32_t>& sizeTensorShape,
30 const std::vector<int32_t>& outputTensorShape)
31 {
32 using namespace tflite;
33 flatbuffers::FlatBufferBuilder flatBufferBuilder;
34
35 flatbuffers::Offset<tflite::Buffer> buffers[5] = {
36 CreateBuffer(flatBufferBuilder),
37 CreateBuffer(flatBufferBuilder),
38 CreateBuffer(flatBufferBuilder,
39 flatBufferBuilder.CreateVector(reinterpret_cast<const uint8_t*>(beginTensorData.data()),
40 sizeof(int32_t) * beginTensorData.size())),
41 CreateBuffer(flatBufferBuilder,
42 flatBufferBuilder.CreateVector(reinterpret_cast<const uint8_t*>(sizeTensorData.data()),
43 sizeof(int32_t) * sizeTensorData.size())),
44 CreateBuffer(flatBufferBuilder)
45 };
46
47 std::array<flatbuffers::Offset<Tensor>, 4> tensors;
48 tensors[0] = CreateTensor(flatBufferBuilder,
49 flatBufferBuilder.CreateVector<int32_t>(inputTensorShape.data(),
50 inputTensorShape.size()),
51 tensorType,
52 1,
53 flatBufferBuilder.CreateString("input"));
54 tensors[1] = CreateTensor(flatBufferBuilder,
55 flatBufferBuilder.CreateVector<int32_t>(beginTensorShape.data(),
56 beginTensorShape.size()),
57 ::tflite::TensorType_INT32,
58 2,
59 flatBufferBuilder.CreateString("begin_tensor"));
60 tensors[2] = CreateTensor(flatBufferBuilder,
61 flatBufferBuilder.CreateVector<int32_t>(sizeTensorShape.data(),
62 sizeTensorShape.size()),
63 ::tflite::TensorType_INT32,
64 3,
65 flatBufferBuilder.CreateString("size_tensor"));
66 tensors[3] = CreateTensor(flatBufferBuilder,
67 flatBufferBuilder.CreateVector<int32_t>(outputTensorShape.data(),
68 outputTensorShape.size()),
69 tensorType,
70 4,
71 flatBufferBuilder.CreateString("output"));
72
73
74 // create operator
75 tflite::BuiltinOptions operatorBuiltinOptionsType = tflite::BuiltinOptions_SliceOptions;
76 flatbuffers::Offset<void> operatorBuiltinOptions = CreateSliceOptions(flatBufferBuilder).Union();
77
78 const std::vector<int> operatorInputs{ 0, 1, 2 };
79 const std::vector<int> operatorOutputs{ 3 };
80 flatbuffers::Offset <Operator> sliceOperator =
81 CreateOperator(flatBufferBuilder,
82 0,
83 flatBufferBuilder.CreateVector<int32_t>(operatorInputs.data(), operatorInputs.size()),
84 flatBufferBuilder.CreateVector<int32_t>(operatorOutputs.data(), operatorOutputs.size()),
85 operatorBuiltinOptionsType,
86 operatorBuiltinOptions);
87
88 const std::vector<int> subgraphInputs{ 0, 1, 2 };
89 const std::vector<int> subgraphOutputs{ 3 };
90 flatbuffers::Offset <SubGraph> subgraph =
91 CreateSubGraph(flatBufferBuilder,
92 flatBufferBuilder.CreateVector(tensors.data(), tensors.size()),
93 flatBufferBuilder.CreateVector<int32_t>(subgraphInputs.data(), subgraphInputs.size()),
94 flatBufferBuilder.CreateVector<int32_t>(subgraphOutputs.data(), subgraphOutputs.size()),
95 flatBufferBuilder.CreateVector(&sliceOperator, 1));
96
97 flatbuffers::Offset <flatbuffers::String> modelDescription =
98 flatBufferBuilder.CreateString("ArmnnDelegate: Slice Operator Model");
99 flatbuffers::Offset <OperatorCode> operatorCode = CreateOperatorCode(flatBufferBuilder,
100 BuiltinOperator_SLICE);
101
102 flatbuffers::Offset <Model> flatbufferModel =
103 CreateModel(flatBufferBuilder,
104 TFLITE_SCHEMA_VERSION,
105 flatBufferBuilder.CreateVector(&operatorCode, 1),
106 flatBufferBuilder.CreateVector(&subgraph, 1),
107 modelDescription,
108 flatBufferBuilder.CreateVector(buffers, 5));
109
110 flatBufferBuilder.Finish(flatbufferModel, armnnDelegate::FILE_IDENTIFIER);
111
112 return std::vector<char>(flatBufferBuilder.GetBufferPointer(),
113 flatBufferBuilder.GetBufferPointer() + flatBufferBuilder.GetSize());
114 }
115
116 template <typename T>
SliceTestImpl(std::vector<armnn::BackendId> & backends,std::vector<T> & inputValues,std::vector<T> & expectedOutputValues,std::vector<int32_t> & beginTensorData,std::vector<int32_t> & sizeTensorData,std::vector<int32_t> & inputTensorShape,std::vector<int32_t> & beginTensorShape,std::vector<int32_t> & sizeTensorShape,std::vector<int32_t> & outputTensorShape)117 void SliceTestImpl(std::vector<armnn::BackendId>& backends,
118 std::vector<T>& inputValues,
119 std::vector<T>& expectedOutputValues,
120 std::vector<int32_t>& beginTensorData,
121 std::vector<int32_t>& sizeTensorData,
122 std::vector<int32_t>& inputTensorShape,
123 std::vector<int32_t>& beginTensorShape,
124 std::vector<int32_t>& sizeTensorShape,
125 std::vector<int32_t>& outputTensorShape)
126 {
127 using namespace delegateTestInterpreter;
128 std::vector<char> modelBuffer = CreateSliceTfLiteModel(
129 ::tflite::TensorType_FLOAT32,
130 inputTensorShape,
131 beginTensorData,
132 sizeTensorData,
133 beginTensorShape,
134 sizeTensorShape,
135 outputTensorShape);
136
137 // Setup interpreter with just TFLite Runtime.
138 auto tfLiteInterpreter = DelegateTestInterpreter(modelBuffer);
139 CHECK(tfLiteInterpreter.AllocateTensors() == kTfLiteOk);
140 CHECK(tfLiteInterpreter.FillInputTensor<T>(inputValues, 0) == kTfLiteOk);
141 CHECK(tfLiteInterpreter.Invoke() == kTfLiteOk);
142 std::vector<T> tfLiteOutputValues = tfLiteInterpreter.GetOutputResult<T>(0);
143 std::vector<int32_t> tfLiteOutputShape = tfLiteInterpreter.GetOutputShape(0);
144
145 // Setup interpreter with Arm NN Delegate applied.
146 auto armnnInterpreter = DelegateTestInterpreter(modelBuffer, backends);
147 CHECK(armnnInterpreter.AllocateTensors() == kTfLiteOk);
148 CHECK(armnnInterpreter.FillInputTensor<T>(inputValues, 0) == kTfLiteOk);
149 CHECK(armnnInterpreter.Invoke() == kTfLiteOk);
150 std::vector<T> armnnOutputValues = armnnInterpreter.GetOutputResult<T>(0);
151 std::vector<int32_t> armnnOutputShape = armnnInterpreter.GetOutputShape(0);
152
153 armnnDelegate::CompareOutputData<T>(tfLiteOutputValues, armnnOutputValues, expectedOutputValues);
154 armnnDelegate::CompareOutputShape(tfLiteOutputShape, armnnOutputShape, outputTensorShape);
155
156 tfLiteInterpreter.Cleanup();
157 armnnInterpreter.Cleanup();
158 } // End of Slice Test
159
160 } // anonymous namespace