blob: fcacf04134a820e277b84e5a50f4bc94f73bb241 [file] [log] [blame]
Teresa Charlin98427a12020-11-25 18:22:57 +00001//
2// Copyright © 2020 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
12#include <flatbuffers/flatbuffers.h>
13#include <tensorflow/lite/interpreter.h>
14#include <tensorflow/lite/kernels/register.h>
15#include <tensorflow/lite/model.h>
16#include <tensorflow/lite/schema/schema_generated.h>
17#include <tensorflow/lite/version.h>
18
19#include <doctest/doctest.h>
20
21namespace
22{
23
24std::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, flatBufferBuilder.CreateVector({})));
37
38 auto quantizationParameters =
39 CreateQuantizationParameters(flatBufferBuilder,
40 0,
41 0,
42 flatBufferBuilder.CreateVector<float>({quantScale}),
43 flatBufferBuilder.CreateVector<int64_t>({quantOffset}));
44
45 std::array<flatbuffers::Offset<Tensor>, 3> tensors;
46 tensors[0] = CreateTensor(flatBufferBuilder,
47 flatBufferBuilder.CreateVector<int32_t>(paramsShape.data(),
48 paramsShape.size()),
49 tensorType,
50 0,
51 flatBufferBuilder.CreateString("params"),
52 quantizationParameters);
53 tensors[1] = CreateTensor(flatBufferBuilder,
54 flatBufferBuilder.CreateVector<int32_t>(indicesShape.data(),
55 indicesShape.size()),
56 ::tflite::TensorType_INT32,
57 0,
58 flatBufferBuilder.CreateString("indices"),
59 quantizationParameters);
60 tensors[2] = CreateTensor(flatBufferBuilder,
61 flatBufferBuilder.CreateVector<int32_t>(expectedOutputShape.data(),
62 expectedOutputShape.size()),
63 tensorType,
64 0,
65 flatBufferBuilder.CreateString("output"),
66 quantizationParameters);
67
68
69 // create operator
70 tflite::BuiltinOptions operatorBuiltinOptionsType = tflite::BuiltinOptions_GatherOptions;
71 flatbuffers::Offset<void> operatorBuiltinOptions = CreateGatherOptions(flatBufferBuilder).Union();
72
73 const std::vector<int> operatorInputs{{0, 1}};
Finn Williams019840d2020-11-30 17:43:28 +000074 const std::vector<int> operatorOutputs{2};
Teresa Charlin98427a12020-11-25 18:22:57 +000075 flatbuffers::Offset<Operator> controlOperator =
76 CreateOperator(flatBufferBuilder,
77 0,
78 flatBufferBuilder.CreateVector<int32_t>(operatorInputs.data(),
79 operatorInputs.size()),
80 flatBufferBuilder.CreateVector<int32_t>(operatorOutputs.data(),
81 operatorOutputs.size()),
82 operatorBuiltinOptionsType,
83 operatorBuiltinOptions);
84
85 const std::vector<int> subgraphInputs{{0, 1}};
Finn Williams019840d2020-11-30 17:43:28 +000086 const std::vector<int> subgraphOutputs{2};
Teresa Charlin98427a12020-11-25 18:22:57 +000087 flatbuffers::Offset<SubGraph> subgraph =
88 CreateSubGraph(flatBufferBuilder,
89 flatBufferBuilder.CreateVector(tensors.data(), tensors.size()),
90 flatBufferBuilder.CreateVector<int32_t>(subgraphInputs.data(),
91 subgraphInputs.size()),
92 flatBufferBuilder.CreateVector<int32_t>(subgraphOutputs.data(),
93 subgraphOutputs.size()),
94 flatBufferBuilder.CreateVector(&controlOperator, 1));
95
96 flatbuffers::Offset<flatbuffers::String> modelDescription =
97 flatBufferBuilder.CreateString("ArmnnDelegate: GATHER Operator Model");
98 flatbuffers::Offset<OperatorCode> operatorCode = CreateOperatorCode(flatBufferBuilder,
99 BuiltinOperator_GATHER);
100
101 flatbuffers::Offset<Model> flatbufferModel =
102 CreateModel(flatBufferBuilder,
103 TFLITE_SCHEMA_VERSION,
104 flatBufferBuilder.CreateVector(&operatorCode, 1),
105 flatBufferBuilder.CreateVector(&subgraph, 1),
106 modelDescription,
107 flatBufferBuilder.CreateVector(buffers.data(), buffers.size()));
108
109 flatBufferBuilder.Finish(flatbufferModel);
110
111 return std::vector<char>(flatBufferBuilder.GetBufferPointer(),
112 flatBufferBuilder.GetBufferPointer() + flatBufferBuilder.GetSize());
113}
114
115template<typename T>
116void GatherTest(tflite::TensorType tensorType,
117 std::vector<armnn::BackendId>& backends,
118 std::vector<int32_t>& paramsShape,
119 std::vector<int32_t>& indicesShape,
120 std::vector<int32_t>& expectedOutputShape,
121 int32_t axis,
122 std::vector<T>& paramsValues,
123 std::vector<int32_t>& indicesValues,
124 std::vector<T>& expectedOutputValues,
125 float quantScale = 1.0f,
126 int quantOffset = 0)
127{
128 using namespace tflite;
129 std::vector<char> modelBuffer = CreateGatherTfLiteModel(tensorType,
130 paramsShape,
131 indicesShape,
132 expectedOutputShape,
133 axis,
134 quantScale,
135 quantOffset);
136 const Model* tfLiteModel = GetModel(modelBuffer.data());
137
138 // Create TfLite Interpreters
139 std::unique_ptr<Interpreter> armnnDelegate;
140 CHECK(InterpreterBuilder(tfLiteModel, ::tflite::ops::builtin::BuiltinOpResolver())
141 (&armnnDelegate) == kTfLiteOk);
142 CHECK(armnnDelegate != nullptr);
143 CHECK(armnnDelegate->AllocateTensors() == kTfLiteOk);
144
145 std::unique_ptr<Interpreter> tfLiteDelegate;
146 CHECK(InterpreterBuilder(tfLiteModel, ::tflite::ops::builtin::BuiltinOpResolver())
147 (&tfLiteDelegate) == kTfLiteOk);
148 CHECK(tfLiteDelegate != nullptr);
149 CHECK(tfLiteDelegate->AllocateTensors() == kTfLiteOk);
150
151 // Create the ArmNN Delegate
152 armnnDelegate::DelegateOptions delegateOptions(backends);
153 std::unique_ptr<TfLiteDelegate, decltype(&armnnDelegate::TfLiteArmnnDelegateDelete)>
154 theArmnnDelegate(armnnDelegate::TfLiteArmnnDelegateCreate(delegateOptions),
155 armnnDelegate::TfLiteArmnnDelegateDelete);
156 CHECK(theArmnnDelegate != nullptr);
157
158 // Modify armnnDelegateInterpreter to use armnnDelegate
159 CHECK(armnnDelegate->ModifyGraphWithDelegate(theArmnnDelegate.get()) == kTfLiteOk);
160
161 // Set input data
162 armnnDelegate::FillInput<T>(tfLiteDelegate, 0, paramsValues);
163 armnnDelegate::FillInput<T>(armnnDelegate, 0, paramsValues);
164 armnnDelegate::FillInput<int32_t>(tfLiteDelegate, 1, indicesValues);
165 armnnDelegate::FillInput<int32_t>(armnnDelegate, 1, indicesValues);
166
167 // Run EnqueWorkload
168 CHECK(tfLiteDelegate->Invoke() == kTfLiteOk);
169 CHECK(armnnDelegate->Invoke() == kTfLiteOk);
170
171 // Compare output data
172 armnnDelegate::CompareOutputData<T>(tfLiteDelegate,
173 armnnDelegate,
174 expectedOutputShape,
175 expectedOutputValues,
176 0);
177
178 tfLiteDelegate.reset(nullptr);
179 armnnDelegate.reset(nullptr);
180}
181} // anonymous namespace