xref: /aosp_15_r20/external/ComputeLibrary/tests/datasets/dynamic_fusion/PoolingLayerDataset.h (revision c217d954acce2dbc11938adb493fc0abd69584f3)
1 /*
2  * Copyright (c) 2023 Arm Limited.
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4  * SPDX-License-Identifier: MIT
5  *
6  * Permission is hereby granted, free of charge, to any person obtaining a copy
7  * of this software and associated documentation files (the "Software"), to
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10  * sell copies of the Software, and to permit persons to whom the Software is
11  * furnished to do so, subject to the following conditions:
12  *
13  * The above copyright notice and this permission notice shall be included in all
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15  *
16  * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
17  * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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22  * SOFTWARE.
23  */
24 #include "arm_compute/core/TensorShape.h"
25 #include "arm_compute/core/Types.h"
26 #include "utils/TypePrinter.h"
27 #include "arm_compute/dynamic_fusion/sketch/attributes/Pool2dAttributes.h"
28 
29 
30 using Pool2dAttributes = arm_compute::experimental::dynamic_fusion::Pool2dAttributes;
31 
32 namespace arm_compute
33 {
34 namespace test
35 {
36 namespace datasets
37 {
38 
39 class DynamicFusionPoolingLayerDataset
40 {
41 public:
42     using type = std::tuple<TensorShape, Pool2dAttributes>;
43 
44     struct iterator
45     {
iteratoriterator46         iterator(std::vector<TensorShape>::const_iterator      src_it,
47                  std::vector<Pool2dAttributes>::const_iterator infos_it)
48             : _src_it{ std::move(src_it) },
49               _infos_it{ std::move(infos_it) }
50         {
51         }
52 
descriptioniterator53         std::string description() const
54         {
55             std::stringstream description;
56             description << "In=" << *_src_it << ":";
57             description << "Info=" << *_infos_it << ":";
58             return description.str();
59         }
60 
61         DynamicFusionPoolingLayerDataset::type operator*() const
62         {
63             return std::make_tuple(*_src_it, *_infos_it);
64         }
65 
66         iterator &operator++()
67         {
68             ++_src_it;
69             ++_infos_it;
70 
71             return *this;
72         }
73 
74     private:
75         std::vector<TensorShape>::const_iterator      _src_it;
76         std::vector<Pool2dAttributes>::const_iterator _infos_it;
77     };
78 
begin()79     iterator begin() const
80     {
81         return iterator(_src_shapes.begin(), _infos.begin());
82     }
83 
size()84     int size() const
85     {
86         return std::min(_src_shapes.size(), _infos.size());
87     }
88 
add_config(TensorShape src,Pool2dAttributes info)89     void add_config(TensorShape src, Pool2dAttributes info)
90     {
91         _src_shapes.emplace_back(std::move(src));
92         _infos.emplace_back(std::move(info));
93     }
94 
95 protected:
96     DynamicFusionPoolingLayerDataset()                       = default;
97     DynamicFusionPoolingLayerDataset(DynamicFusionPoolingLayerDataset &&) = default;
98 
99 private:
100     std::vector<TensorShape>      _src_shapes{};
101     std::vector<Pool2dAttributes> _infos{};
102 };
103 
104 // Special pooling dataset
105 class PoolingLayerDatasetSpecialDynamicFusion final : public DynamicFusionPoolingLayerDataset
106 {
107 public:
PoolingLayerDatasetSpecialDynamicFusion()108     PoolingLayerDatasetSpecialDynamicFusion()
109     {
110         // NCHW DataLayout
111         // Special cases
112         add_config(TensorShape(2U, 3U, 4U, 1U), Pool2dAttributes().pool_type(PoolingType::AVG).pool_size(Size2D(2,2)).stride(Size2D(3,3)));
113         add_config(TensorShape(60U, 52U, 3U, 2U), Pool2dAttributes().pool_type(PoolingType::AVG).pool_size(Size2D(100,100)).stride(Size2D(5,5)).pad(Padding2D(50,50,50,50)));
114         // Asymmetric padding
115         add_config(TensorShape(112U, 112U, 32U), Pool2dAttributes().pool_type(PoolingType::MAX).pool_size(Size2D(3,3)).pad(Padding2D(0,1,0,1)).stride(Size2D(2,2)));
116         add_config(TensorShape(14U, 14U, 832U), Pool2dAttributes().pool_type(PoolingType::MAX).pool_size(Size2D(2,2)).stride(Size2D(1,1)).pad(Padding2D(0,0,0,0)));
117 
118     }
119 };
120 } // namespace datasets
121 } // namespace test
122 } // namespace arm_compute