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
CreateGatherTfLiteModel(tflite::TensorType tensorType,std::vector<int32_t> & paramsShape,std::vector<int32_t> & indicesShape,const std::vector<int32_t> & expectedOutputShape,int32_t axis,float quantScale=1.0f,int quantOffset=0)24 std::vector<char> CreateGatherTfLiteModel(tflite::TensorType tensorType,
25 std::vector<int32_t>& paramsShape,
26 std::vector<int32_t>& indicesShape,
27 const std::vector<int32_t>& expectedOutputShape,
28 int32_t axis,
29 float quantScale = 1.0f,
30 int quantOffset = 0)
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));
39 buffers.push_back(CreateBuffer(flatBufferBuilder));
40
41 auto quantizationParameters =
42 CreateQuantizationParameters(flatBufferBuilder,
43 0,
44 0,
45 flatBufferBuilder.CreateVector<float>({quantScale}),
46 flatBufferBuilder.CreateVector<int64_t>({quantOffset}));
47
48 std::array<flatbuffers::Offset<Tensor>, 3> tensors;
49 tensors[0] = CreateTensor(flatBufferBuilder,
50 flatBufferBuilder.CreateVector<int32_t>(paramsShape.data(),
51 paramsShape.size()),
52 tensorType,
53 1,
54 flatBufferBuilder.CreateString("params"),
55 quantizationParameters);
56 tensors[1] = CreateTensor(flatBufferBuilder,
57 flatBufferBuilder.CreateVector<int32_t>(indicesShape.data(),
58 indicesShape.size()),
59 ::tflite::TensorType_INT32,
60 2,
61 flatBufferBuilder.CreateString("indices"),
62 quantizationParameters);
63 tensors[2] = CreateTensor(flatBufferBuilder,
64 flatBufferBuilder.CreateVector<int32_t>(expectedOutputShape.data(),
65 expectedOutputShape.size()),
66 tensorType,
67 3,
68 flatBufferBuilder.CreateString("output"),
69 quantizationParameters);
70
71
72 // create operator
73 tflite::BuiltinOptions operatorBuiltinOptionsType = tflite::BuiltinOptions_GatherOptions;
74 flatbuffers::Offset<void> operatorBuiltinOptions = CreateGatherOptions(flatBufferBuilder).Union();
75
76 const std::vector<int> operatorInputs{{0, 1}};
77 const std::vector<int> operatorOutputs{2};
78 flatbuffers::Offset<Operator> controlOperator =
79 CreateOperator(flatBufferBuilder,
80 0,
81 flatBufferBuilder.CreateVector<int32_t>(operatorInputs.data(),
82 operatorInputs.size()),
83 flatBufferBuilder.CreateVector<int32_t>(operatorOutputs.data(),
84 operatorOutputs.size()),
85 operatorBuiltinOptionsType,
86 operatorBuiltinOptions);
87
88 const std::vector<int> subgraphInputs{{0, 1}};
89 const std::vector<int> subgraphOutputs{2};
90 flatbuffers::Offset<SubGraph> subgraph =
91 CreateSubGraph(flatBufferBuilder,
92 flatBufferBuilder.CreateVector(tensors.data(), tensors.size()),
93 flatBufferBuilder.CreateVector<int32_t>(subgraphInputs.data(),
94 subgraphInputs.size()),
95 flatBufferBuilder.CreateVector<int32_t>(subgraphOutputs.data(),
96 subgraphOutputs.size()),
97 flatBufferBuilder.CreateVector(&controlOperator, 1));
98
99 flatbuffers::Offset<flatbuffers::String> modelDescription =
100 flatBufferBuilder.CreateString("ArmnnDelegate: GATHER Operator Model");
101 flatbuffers::Offset<OperatorCode> operatorCode = CreateOperatorCode(flatBufferBuilder,
102 BuiltinOperator_GATHER);
103
104 flatbuffers::Offset<Model> flatbufferModel =
105 CreateModel(flatBufferBuilder,
106 TFLITE_SCHEMA_VERSION,
107 flatBufferBuilder.CreateVector(&operatorCode, 1),
108 flatBufferBuilder.CreateVector(&subgraph, 1),
109 modelDescription,
110 flatBufferBuilder.CreateVector(buffers.data(), buffers.size()));
111
112 flatBufferBuilder.Finish(flatbufferModel, armnnDelegate::FILE_IDENTIFIER);
113
114 return std::vector<char>(flatBufferBuilder.GetBufferPointer(),
115 flatBufferBuilder.GetBufferPointer() + flatBufferBuilder.GetSize());
116 }
117
118 template<typename T>
GatherTest(tflite::TensorType tensorType,std::vector<armnn::BackendId> & backends,std::vector<int32_t> & paramsShape,std::vector<int32_t> & indicesShape,std::vector<int32_t> & expectedOutputShape,int32_t axis,std::vector<T> & paramsValues,std::vector<int32_t> & indicesValues,std::vector<T> & expectedOutputValues,float quantScale=1.0f,int quantOffset=0)119 void GatherTest(tflite::TensorType tensorType,
120 std::vector<armnn::BackendId>& backends,
121 std::vector<int32_t>& paramsShape,
122 std::vector<int32_t>& indicesShape,
123 std::vector<int32_t>& expectedOutputShape,
124 int32_t axis,
125 std::vector<T>& paramsValues,
126 std::vector<int32_t>& indicesValues,
127 std::vector<T>& expectedOutputValues,
128 float quantScale = 1.0f,
129 int quantOffset = 0)
130 {
131 using namespace delegateTestInterpreter;
132 std::vector<char> modelBuffer = CreateGatherTfLiteModel(tensorType,
133 paramsShape,
134 indicesShape,
135 expectedOutputShape,
136 axis,
137 quantScale,
138 quantOffset);
139 // Setup interpreter with just TFLite Runtime.
140 auto tfLiteInterpreter = DelegateTestInterpreter(modelBuffer);
141 CHECK(tfLiteInterpreter.AllocateTensors() == kTfLiteOk);
142 CHECK(tfLiteInterpreter.FillInputTensor<T>(paramsValues, 0) == kTfLiteOk);
143 CHECK(tfLiteInterpreter.FillInputTensor<int32_t>(indicesValues, 1) == kTfLiteOk);
144 CHECK(tfLiteInterpreter.Invoke() == kTfLiteOk);
145 std::vector<T> tfLiteOutputValues = tfLiteInterpreter.GetOutputResult<T>(0);
146 std::vector<int32_t> tfLiteOutputShape = tfLiteInterpreter.GetOutputShape(0);
147
148 // Setup interpreter with Arm NN Delegate applied.
149 auto armnnInterpreter = DelegateTestInterpreter(modelBuffer, backends);
150 CHECK(armnnInterpreter.AllocateTensors() == kTfLiteOk);
151 CHECK(armnnInterpreter.FillInputTensor<T>(paramsValues, 0) == kTfLiteOk);
152 CHECK(armnnInterpreter.FillInputTensor<int32_t>(indicesValues, 1) == kTfLiteOk);
153 CHECK(armnnInterpreter.Invoke() == kTfLiteOk);
154 std::vector<T> armnnOutputValues = armnnInterpreter.GetOutputResult<T>(0);
155 std::vector<int32_t> armnnOutputShape = armnnInterpreter.GetOutputShape(0);
156
157 armnnDelegate::CompareOutputData<T>(tfLiteOutputValues, armnnOutputValues, expectedOutputValues);
158 armnnDelegate::CompareOutputShape(tfLiteOutputShape, armnnOutputShape, expectedOutputShape);
159
160 tfLiteInterpreter.Cleanup();
161 armnnInterpreter.Cleanup();
162 }
163 } // anonymous namespace