1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
|
/* Copyright 2017 The TensorFlow Authors. All Rights Reserved.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
==============================================================================*/
#ifndef TENSORFLOW_CONTRIB_NEAREST_NEIGHBOR_KERNELS_HEAP_H_
#define TENSORFLOW_CONTRIB_NEAREST_NEIGHBOR_KERNELS_HEAP_H_
#include <cassert>
#include <cstdint>
#include <cstdlib>
#include <vector>
namespace tensorflow {
namespace nearest_neighbor {
// A simple binary heap. We use our own implementation because multiprobe for
// the cross-polytope hash interacts with the heap in a way so that about half
// of the insertion operations are guaranteed to be on top of the heap. We make
// use of this fact in the AugmentedHeap below.
// HeapBase is a base class for both the SimpleHeap and AugmentedHeap below.
template <typename KeyType, typename DataType>
class HeapBase {
public:
class Item {
public:
KeyType key;
DataType data;
Item() {}
Item(const KeyType& k, const DataType& d) : key(k), data(d) {}
bool operator<(const Item& i2) const { return key < i2.key; }
};
void ExtractMin(KeyType* key, DataType* data) {
*key = v_[0].key;
*data = v_[0].data;
num_elements_ -= 1;
v_[0] = v_[num_elements_];
HeapDown(0);
}
bool IsEmpty() { return num_elements_ == 0; }
// This method adds an element at the end of the internal array without
// "heapifying" the array afterwards. This is useful for setting up a heap
// where a single call to heapify at the end of the initial insertion
// operations suffices.
void InsertUnsorted(const KeyType& key, const DataType& data) {
if (v_.size() == static_cast<size_t>(num_elements_)) {
v_.push_back(Item(key, data));
} else {
v_[num_elements_].key = key;
v_[num_elements_].data = data;
}
num_elements_ += 1;
}
void Insert(const KeyType& key, const DataType& data) {
if (v_.size() == static_cast<size_t>(num_elements_)) {
v_.push_back(Item(key, data));
} else {
v_[num_elements_].key = key;
v_[num_elements_].data = data;
}
num_elements_ += 1;
HeapUp(num_elements_ - 1);
}
void Heapify() {
int_fast32_t rightmost = parent(num_elements_ - 1);
for (int_fast32_t cur_loc = rightmost; cur_loc >= 0; --cur_loc) {
HeapDown(cur_loc);
}
}
void Reset() { num_elements_ = 0; }
void Resize(size_t new_size) { v_.resize(new_size); }
protected:
int_fast32_t lchild(int_fast32_t x) { return 2 * x + 1; }
int_fast32_t rchild(int_fast32_t x) { return 2 * x + 2; }
int_fast32_t parent(int_fast32_t x) { return (x - 1) / 2; }
void SwapEntries(int_fast32_t a, int_fast32_t b) {
Item tmp = v_[a];
v_[a] = v_[b];
v_[b] = tmp;
}
void HeapUp(int_fast32_t cur_loc) {
int_fast32_t p = parent(cur_loc);
while (cur_loc > 0 && v_[p].key > v_[cur_loc].key) {
SwapEntries(p, cur_loc);
cur_loc = p;
p = parent(cur_loc);
}
}
void HeapDown(int_fast32_t cur_loc) {
while (true) {
int_fast32_t lc = lchild(cur_loc);
int_fast32_t rc = rchild(cur_loc);
if (lc >= num_elements_) {
return;
}
if (v_[cur_loc].key <= v_[lc].key) {
if (rc >= num_elements_ || v_[cur_loc].key <= v_[rc].key) {
return;
} else {
SwapEntries(cur_loc, rc);
cur_loc = rc;
}
} else {
if (rc >= num_elements_ || v_[lc].key <= v_[rc].key) {
SwapEntries(cur_loc, lc);
cur_loc = lc;
} else {
SwapEntries(cur_loc, rc);
cur_loc = rc;
}
}
}
}
std::vector<Item> v_;
int_fast32_t num_elements_ = 0;
};
// A "simple" binary heap.
template <typename KeyType, typename DataType>
class SimpleHeap : public HeapBase<KeyType, DataType> {
public:
void ReplaceTop(const KeyType& key, const DataType& data) {
this->v_[0].key = key;
this->v_[0].data = data;
this->HeapDown(0);
}
KeyType MinKey() { return this->v_[0].key; }
std::vector<typename HeapBase<KeyType, DataType>::Item>& GetData() {
return this->v_;
}
};
// An "augmented" heap that can hold an extra element that is guaranteed to
// be at the top of the heap. This is useful if a significant fraction of the
// insertion operations are guaranteed insertions at the top. However, the heap
// only stores at most one such special top element, i.e., the heap assumes
// that extract_min() is called at least once between successive calls to
// insert_guaranteed_top().
template <typename KeyType, typename DataType>
class AugmentedHeap : public HeapBase<KeyType, DataType> {
public:
void ExtractMin(KeyType* key, DataType* data) {
if (has_guaranteed_top_) {
has_guaranteed_top_ = false;
*key = guaranteed_top_.key;
*data = guaranteed_top_.data;
} else {
*key = this->v_[0].key;
*data = this->v_[0].data;
this->num_elements_ -= 1;
this->v_[0] = this->v_[this->num_elements_];
this->HeapDown(0);
}
}
bool IsEmpty() { return this->num_elements_ == 0 && !has_guaranteed_top_; }
void InsertGuaranteedTop(const KeyType& key, const DataType& data) {
assert(!has_guaranteed_top_);
has_guaranteed_top_ = true;
guaranteed_top_.key = key;
guaranteed_top_.data = data;
}
void Reset() {
this->num_elements_ = 0;
has_guaranteed_top_ = false;
}
protected:
typename HeapBase<KeyType, DataType>::Item guaranteed_top_;
bool has_guaranteed_top_ = false;
};
} // namespace nearest_neighbor
} // namespace tensorflow
#endif // TENSORFLOW_CONTRIB_NEAREST_NEIGHBOR_KERNELS_HEAP_H_
|
