1 | /******************************************************************************* |
2 | * Copyright 2016-2022 Intel Corporation |
3 | * |
4 | * Licensed under the Apache License, Version 2.0 (the "License"); |
5 | * you may not use this file except in compliance with the License. |
6 | * You may obtain a copy of the License at |
7 | * |
8 | * http://www.apache.org/licenses/LICENSE-2.0 |
9 | * |
10 | * Unless required by applicable law or agreed to in writing, software |
11 | * distributed under the License is distributed on an "AS IS" BASIS, |
12 | * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. |
13 | * See the License for the specific language governing permissions and |
14 | * limitations under the License. |
15 | *******************************************************************************/ |
16 | |
17 | #include <assert.h> |
18 | #include "oneapi/dnnl/dnnl.h" |
19 | |
20 | #include "c_types_map.hpp" |
21 | #include "opdesc.hpp" |
22 | #include "primitive_desc_iface.hpp" |
23 | #include "type_helpers.hpp" |
24 | #include "utils.hpp" |
25 | |
26 | using namespace dnnl::impl; |
27 | using namespace dnnl::impl::utils; |
28 | using namespace dnnl::impl::status; |
29 | using namespace dnnl::impl::prop_kind; |
30 | using namespace dnnl::impl::alg_kind; |
31 | using namespace dnnl::impl::types; |
32 | |
33 | namespace { |
34 | status_t pooling_desc_init(pooling_desc_t *pool_desc, prop_kind_t prop_kind, |
35 | alg_kind_t alg_kind, const memory_desc_t *src_desc, |
36 | const memory_desc_t *dst_desc, const dims_t strides, |
37 | const dims_t kernel, const dims_t dilation, const dims_t padding_l, |
38 | const dims_t padding_r) { |
39 | bool args_ok = !any_null(pool_desc, src_desc, dst_desc, strides, kernel, |
40 | padding_l) |
41 | && one_of(alg_kind, pooling_max, pooling_avg_include_padding, |
42 | pooling_avg_exclude_padding) |
43 | && IMPLICATION( |
44 | one_of(prop_kind, forward_training, forward_inference), |
45 | !memory_desc_wrapper(src_desc).format_any()); |
46 | if (!args_ok) return invalid_arguments; |
47 | |
48 | if (padding_r == nullptr) padding_r = padding_l; |
49 | |
50 | auto pd = pooling_desc_t(); |
51 | pd.primitive_kind = primitive_kind::pooling; |
52 | pd.prop_kind = prop_kind; |
53 | pd.alg_kind = alg_kind; |
54 | pd.src_desc.ndims = src_desc->ndims; |
55 | |
56 | const bool is_fwd = one_of(prop_kind, forward_training, forward_inference); |
57 | |
58 | bool runtime_dims_or_strides |
59 | = memory_desc_wrapper(src_desc).has_runtime_dims_or_strides() |
60 | || memory_desc_wrapper(dst_desc).has_runtime_dims_or_strides(); |
61 | if (runtime_dims_or_strides) return unimplemented; |
62 | |
63 | pd.diff_src_desc = pd.src_desc = zero_md(); |
64 | pd.diff_dst_desc = pd.dst_desc = zero_md(); |
65 | |
66 | (is_fwd ? pd.src_desc : pd.diff_src_desc) = *src_desc; |
67 | (is_fwd ? pd.dst_desc : pd.diff_dst_desc) = *dst_desc; |
68 | |
69 | int sp_dims = src_desc->ndims - 2; |
70 | utils::array_copy(pd.strides, strides, sp_dims); |
71 | utils::array_copy(pd.kernel, kernel, sp_dims); |
72 | utils::array_copy(pd.padding[0], padding_l, sp_dims); |
73 | utils::array_copy(pd.padding[1], padding_r, sp_dims); |
74 | utils::array_copy(pd.dilation, dilation, sp_dims); |
75 | |
76 | if (one_of(alg_kind, pooling_max, pooling_avg_include_padding, |
77 | pooling_avg_exclude_padding)) { |
78 | pd.accum_data_type = types::default_accum_data_type( |
79 | src_desc->data_type, dst_desc->data_type, false); |
80 | if (pd.accum_data_type == data_type::undef) return invalid_arguments; |
81 | } else { |
82 | pd.accum_data_type = dst_desc->data_type; |
83 | } |
84 | |
85 | if (!utils::one_of(src_desc->ndims, 3, 4, 5) |
86 | || !utils::one_of(dst_desc->ndims, 3, 4, 5) |
87 | || src_desc->dims[0] != dst_desc->dims[0] |
88 | || src_desc->dims[1] != dst_desc->dims[1]) |
89 | return invalid_arguments; |
90 | |
91 | for (int i = 2; i < src_desc->ndims; ++i) { |
92 | const int src = src_desc->dims[i]; |
93 | const int dst = dst_desc->dims[i]; |
94 | const int ker = kernel[i - 2]; |
95 | const int dil = dilation ? dilation[i - 2] : 0; |
96 | const int pad_l = padding_l[i - 2]; |
97 | const int pad_r = padding_r[i - 2]; |
98 | const int str = strides[i - 2]; |
99 | const int ker_range = 1 + (ker - 1) * (dil + 1); |
100 | |
101 | if (str < 1 || dil < 0 || pad_l < 0 || pad_r + str < 0) |
102 | return invalid_arguments; |
103 | |
104 | if ((src - ker_range + pad_l + pad_r) / str + 1 != dst) |
105 | return invalid_arguments; |
106 | |
107 | // It's not allowed for pooling window to be totally placed outside |
108 | // of real source domain for pooling_avg_exclude_padding algorithm |
109 | // due to 0 / 0 ambiguity |
110 | if (alg_kind == pooling_avg_exclude_padding |
111 | && !(pad_l < ker_range && pad_r < ker_range && dil < src)) |
112 | return invalid_arguments; |
113 | } |
114 | |
115 | *pool_desc = pd; |
116 | return success; |
117 | } |
118 | } // namespace |
119 | |
120 | dnnl_status_t dnnl_pooling_forward_primitive_desc_create( |
121 | primitive_desc_iface_t **primitive_desc_iface, engine_t *engine, |
122 | prop_kind_t prop_kind, alg_kind_t alg_kind, |
123 | const memory_desc_t *src_desc, const memory_desc_t *dst_desc, |
124 | const dims_t strides, const dims_t kernel, const dims_t dilation, |
125 | const dims_t padding_l, const dims_t padding_r, |
126 | const primitive_attr_t *attr) { |
127 | |
128 | if (!one_of(prop_kind, forward_training, forward_inference)) |
129 | return invalid_arguments; |
130 | |
131 | auto pool_desc = pooling_desc_t(); |
132 | CHECK(pooling_desc_init(&pool_desc, prop_kind, alg_kind, src_desc, dst_desc, |
133 | strides, kernel, dilation, padding_l, padding_r)); |
134 | return primitive_desc_create(primitive_desc_iface, engine, |
135 | (const op_desc_t *)&pool_desc, nullptr, attr); |
136 | } |
137 | |
138 | dnnl_status_t dnnl_pooling_backward_primitive_desc_create( |
139 | primitive_desc_iface_t **primitive_desc_iface, engine_t *engine, |
140 | alg_kind_t alg_kind, const memory_desc_t *diff_src_desc, |
141 | const memory_desc_t *diff_dst_desc, const dims_t strides, |
142 | const dims_t kernel, const dims_t dilation, const dims_t padding_l, |
143 | const dims_t padding_r, const primitive_desc_iface_t *hint_fwd_pd, |
144 | const primitive_attr_t *attr) { |
145 | |
146 | auto pool_desc = pooling_desc_t(); |
147 | CHECK(pooling_desc_init(&pool_desc, prop_kind::backward_data, alg_kind, |
148 | diff_src_desc, diff_dst_desc, strides, kernel, dilation, padding_l, |
149 | padding_r)); |
150 | return primitive_desc_create(primitive_desc_iface, engine, |
151 | (const op_desc_t *)&pool_desc, hint_fwd_pd, attr); |
152 | } |
153 | |
154 | // vim: et ts=4 sw=4 cindent cino+=l0,\:4,N-s |
155 | |