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
CreateGatherNdTfLiteModel(tflite::TensorType tensorType,std::vector<int32_t> & paramsShape,std::vector<int32_t> & indicesShape,const std::vector<int32_t> & expectedOutputShape,float quantScale=1.0f,int quantOffset=0)24 std::vector<char> CreateGatherNdTfLiteModel(tflite::TensorType tensorType,
25 std::vector<int32_t>& paramsShape,
26 std::vector<int32_t>& indicesShape,
27 const std::vector<int32_t>& expectedOutputShape,
28 float quantScale = 1.0f,
29 int quantOffset = 0)
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 buffers.push_back(CreateBuffer(flatBufferBuilder));
39
40 auto quantizationParameters =
41 CreateQuantizationParameters(flatBufferBuilder,
42 0,
43 0,
44 flatBufferBuilder.CreateVector<float>({quantScale}),
45 flatBufferBuilder.CreateVector<int64_t>({quantOffset}));
46
47 std::array<flatbuffers::Offset<Tensor>, 3> tensors;
48 tensors[0] = CreateTensor(flatBufferBuilder,
49 flatBufferBuilder.CreateVector<int32_t>(paramsShape.data(),
50 paramsShape.size()),
51 tensorType,
52 1,
53 flatBufferBuilder.CreateString("params"),
54 quantizationParameters);
55 tensors[1] = CreateTensor(flatBufferBuilder,
56 flatBufferBuilder.CreateVector<int32_t>(indicesShape.data(),
57 indicesShape.size()),
58 ::tflite::TensorType_INT32,
59 2,
60 flatBufferBuilder.CreateString("indices"),
61 quantizationParameters);
62 tensors[2] = CreateTensor(flatBufferBuilder,
63 flatBufferBuilder.CreateVector<int32_t>(expectedOutputShape.data(),
64 expectedOutputShape.size()),
65 tensorType,
66 3,
67 flatBufferBuilder.CreateString("output"),
68 quantizationParameters);
69
70
71 // create operator
72 tflite::BuiltinOptions operatorBuiltinOptionsType = tflite::BuiltinOptions_GatherNdOptions;
73 flatbuffers::Offset<void> operatorBuiltinOptions = CreateGatherNdOptions(flatBufferBuilder).Union();
74
75 const std::vector<int> operatorInputs{{0, 1}};
76 const std::vector<int> operatorOutputs{2};
77 flatbuffers::Offset<Operator> controlOperator =
78 CreateOperator(flatBufferBuilder,
79 0,
80 flatBufferBuilder.CreateVector<int32_t>(operatorInputs.data(),
81 operatorInputs.size()),
82 flatBufferBuilder.CreateVector<int32_t>(operatorOutputs.data(),
83 operatorOutputs.size()),
84 operatorBuiltinOptionsType,
85 operatorBuiltinOptions);
86
87 const std::vector<int> subgraphInputs{{0, 1}};
88 const std::vector<int> subgraphOutputs{2};
89 flatbuffers::Offset<SubGraph> subgraph =
90 CreateSubGraph(flatBufferBuilder,
91 flatBufferBuilder.CreateVector(tensors.data(), tensors.size()),
92 flatBufferBuilder.CreateVector<int32_t>(subgraphInputs.data(),
93 subgraphInputs.size()),
94 flatBufferBuilder.CreateVector<int32_t>(subgraphOutputs.data(),
95 subgraphOutputs.size()),
96 flatBufferBuilder.CreateVector(&controlOperator, 1));
97
98 flatbuffers::Offset<flatbuffers::String> modelDescription =
99 flatBufferBuilder.CreateString("ArmnnDelegate: GATHER_ND Operator Model");
100 flatbuffers::Offset<OperatorCode> operatorCode = CreateOperatorCode(flatBufferBuilder,
101 BuiltinOperator_GATHER_ND);
102
103 flatbuffers::Offset<Model> flatbufferModel =
104 CreateModel(flatBufferBuilder,
105 TFLITE_SCHEMA_VERSION,
106 flatBufferBuilder.CreateVector(&operatorCode, 1),
107 flatBufferBuilder.CreateVector(&subgraph, 1),
108 modelDescription,
109 flatBufferBuilder.CreateVector(buffers.data(), buffers.size()));
110
111 flatBufferBuilder.Finish(flatbufferModel, armnnDelegate::FILE_IDENTIFIER);
112
113 return std::vector<char>(flatBufferBuilder.GetBufferPointer(),
114 flatBufferBuilder.GetBufferPointer() + flatBufferBuilder.GetSize());
115 }
116
117 template<typename T>
GatherNdTest(tflite::TensorType tensorType,std::vector<armnn::BackendId> & backends,std::vector<int32_t> & paramsShape,std::vector<int32_t> & indicesShape,std::vector<int32_t> & expectedOutputShape,std::vector<T> & paramsValues,std::vector<int32_t> & indicesValues,std::vector<T> & expectedOutputValues,float quantScale=1.0f,int quantOffset=0)118 void GatherNdTest(tflite::TensorType tensorType,
119 std::vector<armnn::BackendId>& backends,
120 std::vector<int32_t>& paramsShape,
121 std::vector<int32_t>& indicesShape,
122 std::vector<int32_t>& expectedOutputShape,
123 std::vector<T>& paramsValues,
124 std::vector<int32_t>& indicesValues,
125 std::vector<T>& expectedOutputValues,
126 float quantScale = 1.0f,
127 int quantOffset = 0)
128 {
129 using namespace delegateTestInterpreter;
130 std::vector<char> modelBuffer = CreateGatherNdTfLiteModel(tensorType,
131 paramsShape,
132 indicesShape,
133 expectedOutputShape,
134 quantScale,
135 quantOffset);
136 // Setup interpreter with just TFLite Runtime.
137 auto tfLiteInterpreter = DelegateTestInterpreter(modelBuffer);
138 CHECK(tfLiteInterpreter.AllocateTensors() == kTfLiteOk);
139 CHECK(tfLiteInterpreter.FillInputTensor<T>(paramsValues, 0) == kTfLiteOk);
140 CHECK(tfLiteInterpreter.FillInputTensor<int32_t>(indicesValues, 1) == 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>(paramsValues, 0) == kTfLiteOk);
149 CHECK(armnnInterpreter.FillInputTensor<int32_t>(indicesValues, 1) == kTfLiteOk);
150 CHECK(armnnInterpreter.Invoke() == kTfLiteOk);
151 std::vector<T> armnnOutputValues = armnnInterpreter.GetOutputResult<T>(0);
152 std::vector<int32_t> armnnOutputShape = armnnInterpreter.GetOutputShape(0);
153
154 armnnDelegate::CompareOutputData<T>(tfLiteOutputValues, armnnOutputValues, expectedOutputValues);
155 armnnDelegate::CompareOutputShape(tfLiteOutputShape, armnnOutputShape, expectedOutputShape);
156
157 tfLiteInterpreter.Cleanup();
158 armnnInterpreter.Cleanup();
159 }
160 } // anonymous namespace