1 //
2 // Copyright © 2017,2022 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 <Graph.hpp>
11 #include <ResolveType.hpp>
12 #include <SubgraphViewSelector.hpp>
13
14 #include <armnn/BackendRegistry.hpp>
15 #include <armnn/Types.hpp>
16 #include <armnn/backends/SubgraphView.hpp>
17 #include <armnn/backends/TensorHandle.hpp>
18
19 #include <algorithm>
20 #include <random>
21 #include <vector>
22
23 // Checks that two collections have the exact same contents (in any order)
24 // The given collections do not have to contain duplicates
25 // Cannot use std::sort here because std lists have their own std::list::sort method
26 template <typename CollectionType>
AreEqual(const CollectionType & lhs,const CollectionType & rhs)27 bool AreEqual(const CollectionType& lhs, const CollectionType& rhs)
28 {
29 if (lhs.size() != rhs.size())
30 {
31 return false;
32 }
33
34 auto lhs_it = std::find_if(lhs.begin(), lhs.end(), [&rhs](auto& item)
35 {
36 return std::find(rhs.begin(), rhs.end(), item) == rhs.end();
37 });
38
39 return lhs_it == lhs.end();
40 }
41
42 // Checks that the given collection contains the specified item
43 template <typename CollectionType>
Contains(const CollectionType & collection,const typename CollectionType::value_type & item)44 bool Contains(const CollectionType& collection, const typename CollectionType::value_type& item)
45 {
46 return std::find(collection.begin(), collection.end(), item) != collection.end();
47 }
48
49 // Checks that the given map contains the specified key
50 template <typename MapType>
Contains(const MapType & map,const typename MapType::key_type & key)51 bool Contains(const MapType& map, const typename MapType::key_type& key)
52 {
53 return map.find(key) != map.end();
54 }
55
56 // Utility template for comparing tensor elements
57 template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
Compare(T a,T b,float tolerance=0.000001f)58 inline bool Compare(T a, T b, float tolerance = 0.000001f)
59 {
60 if (ArmnnType == armnn::DataType::Boolean)
61 {
62 // NOTE: Boolean is represented as uint8_t (with zero equals
63 // false and everything else equals true), therefore values
64 // need to be casted to bool before comparing them
65 return static_cast<bool>(a) == static_cast<bool>(b);
66 }
67
68 // NOTE: All other types can be cast to float and compared with
69 // a certain level of tolerance
70 return std::fabs(static_cast<float>(a) - static_cast<float>(b)) <= tolerance;
71 }
72
73 armnn::SubgraphView::InputSlots CreateInputsFrom(armnn::Layer* layer,
74 std::vector<unsigned int> ignoreSlots = {});
75
76 armnn::SubgraphView::InputSlots CreateInputsFrom(const std::vector<armnn::Layer*>& layers,
77 std::vector<unsigned int> ignoreSlots = {});
78
79 armnn::SubgraphView::OutputSlots CreateOutputsFrom(const std::vector<armnn::Layer*>& layers);
80
81 armnn::SubgraphView::SubgraphViewPtr CreateSubgraphViewFrom(armnn::SubgraphView::InputSlots&& inputs,
82 armnn::SubgraphView::OutputSlots&& outputs,
83 armnn::SubgraphView::Layers&& layers);
84
85 armnn::IBackendInternalUniquePtr CreateBackendObject(const armnn::BackendId& backendId);
86
87 armnn::TensorShape MakeTensorShape(unsigned int batches,
88 unsigned int channels,
89 unsigned int height,
90 unsigned int width,
91 armnn::DataLayout layout);
92
93 template<typename DataType>
GenerateRandomData(size_t size)94 static std::vector<DataType> GenerateRandomData(size_t size)
95 {
96 constexpr bool isIntegerType = std::is_integral<DataType>::value;
97 using Distribution =
98 typename std::conditional<isIntegerType,
99 std::uniform_int_distribution<DataType>,
100 std::uniform_real_distribution<DataType>>::type;
101
102 static constexpr DataType lowerLimit = std::numeric_limits<DataType>::min();
103 static constexpr DataType upperLimit = std::numeric_limits<DataType>::max();
104
105 static Distribution distribution(lowerLimit, upperLimit);
106 static std::default_random_engine generator;
107
108 std::vector<DataType> randomData(size);
109 generate(randomData.begin(), randomData.end(), []() { return distribution(generator); });
110
111 return randomData;
112 }
113