Repository navigation
Expand file tree
/
Copy pathpool_kernel.h
More file actions
147 lines (133 loc) · 6.22 KB
/
Copy pathpool_kernel.h
File metadata and controls
147 lines (133 loc) · 6.22 KB
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
// Copyright (c) 2022 PaddlePaddle 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.
#pragma once
#include <string>
#include <vector>
#include "paddle/phi/common/int_array.h"
#include "paddle/phi/core/dense_tensor.h"
namespace phi {
template <typename T, typename Context>
void Pool2dKernel(const Context& dev_ctx,
const DenseTensor& x,
const IntArray& kernel_size,
const std::vector<int64_t>& strides,
const std::vector<int64_t>& paddings,
bool ceil_mode,
bool exclusive,
const std::string& data_format,
const std::string& pooling_type,
bool global_pooling,
bool adaptive,
const std::string& padding_algorithm,
DenseTensor* out);
template <typename T, typename Context>
void LPPool2dKernel(const Context& dev_ctx,
const DenseTensor& x,
const IntArray& kernel_size,
const std::vector<int64_t>& strides,
const std::vector<int64_t>& paddings,
bool ceil_mode,
bool exclusive,
const std::string& data_format,
const std::string& pooling_type,
bool global_pooling,
bool adaptive,
const std::string& padding_algorithm,
const float norm_type,
DenseTensor* out);
template <typename T, typename Context>
void Pool2dGPUDNNKernel(const Context& dev_ctx,
const DenseTensor& x,
const IntArray& kernel_size,
const std::vector<int64_t>& strides,
const std::vector<int64_t>& paddings,
bool ceil_mode,
bool exclusive,
const std::string& data_format,
const std::string& pooling_type,
bool global_pooling,
bool adaptive,
const std::string& padding_algorithm,
DenseTensor* out);
template <typename T, typename Context>
void MaxPool2dWithIndexKernel(const Context& dev_ctx,
const DenseTensor& x,
const std::vector<int>& kernel_size,
const std::vector<int>& strides,
const std::vector<int>& paddings,
const std::vector<int>& dilations,
bool global_pooling,
bool adaptive,
bool ceil_mode,
DenseTensor* out,
DenseTensor* mask);
template <typename T, typename Context>
void Pool3dKernel(const Context& dev_ctx,
const DenseTensor& x,
const std::vector<int64_t>& kernel_size,
const std::vector<int64_t>& strides,
const std::vector<int64_t>& paddings,
bool ceil_mode,
bool exclusive,
const std::string& data_format,
const std::string& pooling_type,
bool global_pooling,
bool adaptive,
const std::string& padding_algorithm,
DenseTensor* out);
template <typename T, typename Context>
void Pool3dGPUDNNKernel(const Context& dev_ctx,
const DenseTensor& x,
const std::vector<int64_t>& kernel_size,
const std::vector<int64_t>& strides,
const std::vector<int64_t>& paddings,
bool ceil_mode,
bool exclusive,
const std::string& data_format,
const std::string& pooling_type,
bool global_pooling,
bool adaptive,
const std::string& padding_algorithm,
DenseTensor* out);
template <typename T, typename Context>
void MaxPool3dWithIndexKernel(const Context& dev_ctx,
const DenseTensor& x,
const std::vector<int>& kernel_size,
const std::vector<int>& strides,
const std::vector<int>& paddings,
const std::vector<int>& dilations,
bool global_pooling,
bool adaptive,
bool ceil_mode,
DenseTensor* out,
DenseTensor* mask);
template <typename T, typename Context>
void FractionalMaxPool2dKernel(const Context& dev_ctx,
const DenseTensor& x,
const std::vector<int>& output_size,
const std::vector<int>& kernel_size,
float random_u,
bool return_mask,
DenseTensor* out,
DenseTensor* mask);
template <typename T, typename Context>
void FractionalMaxPool3dKernel(const Context& dev_ctx,
const DenseTensor& x,
const std::vector<int>& output_size,
const std::vector<int>& kernel_size,
float random_u,
bool return_mask,
DenseTensor* out,
DenseTensor* mask);
} // namespace phi