1/*******************************************************************************
2* Copyright 2018-2022 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#ifndef COMMON_DECONVOLUTION_PD_HPP
18#define COMMON_DECONVOLUTION_PD_HPP
19
20#include "oneapi/dnnl/dnnl.h"
21
22#include "c_types_map.hpp"
23#include "convolution_pd.hpp"
24#include "primitive_desc.hpp"
25#include "utils.hpp"
26
27namespace dnnl {
28namespace impl {
29
30struct deconvolution_fwd_pd_t;
31
32struct deconvolution_pd_t : public primitive_desc_t {
33 static constexpr auto base_pkind = primitive_kind::deconvolution;
34
35 const deconvolution_desc_t *desc() const { return &desc_; }
36 const op_desc_t *op_desc() const override {
37 return reinterpret_cast<const op_desc_t *>(this->desc());
38 }
39
40 status_t query(query_t what, int idx, void *result) const override {
41 switch (what) {
42 case query::prop_kind:
43 *(prop_kind_t *)result = desc()->prop_kind;
44 break;
45 case query::alg_kind:
46 *(alg_kind_t *)result = desc()->alg_kind;
47 break;
48 case query::strides:
49 *(const dims_t **)result = &desc()->strides;
50 break;
51 case query::dilations:
52 *(const dims_t **)result = &desc()->dilates;
53 break;
54 case query::padding_l:
55 *(const dims_t **)result = &desc()->padding[0];
56 break;
57 case query::padding_r:
58 *(const dims_t **)result = &desc()->padding[1];
59 break;
60 default: return primitive_desc_t::query(what, idx, result);
61 }
62 return status::success;
63 }
64
65 /* common deconv aux functions (note that conv_desc_t == deconv_desc_t) */
66
67 dim_t MB() const { return invariant_src_md()->dims[0]; }
68
69 dim_t IC() const { return invariant_src_md()->dims[1]; }
70 dim_t OC() const { return invariant_dst_md()->dims[1]; }
71 dim_t G() const { return with_groups() ? invariant_wei_md()->dims[0] : 1; }
72
73 dim_t ID() const {
74 return ndims() >= 5 ? invariant_src_md()->dims[ndims() - 3] : 1;
75 }
76 dim_t IH() const {
77 return ndims() >= 4 ? invariant_src_md()->dims[ndims() - 2] : 1;
78 }
79 dim_t IW() const { return invariant_src_md()->dims[ndims() - 1]; }
80
81 dim_t OD() const {
82 return ndims() >= 5 ? invariant_dst_md()->dims[ndims() - 3] : 1;
83 }
84 dim_t OH() const {
85 return ndims() >= 4 ? invariant_dst_md()->dims[ndims() - 2] : 1;
86 }
87 dim_t OW() const { return invariant_dst_md()->dims[ndims() - 1]; }
88
89 dim_t KD() const {
90 const int w_ndims = ndims() + with_groups();
91 return ndims() >= 5 ? invariant_wei_md()->dims[w_ndims - 3] : 1;
92 }
93 dim_t KH() const {
94 const int w_ndims = ndims() + with_groups();
95 return ndims() >= 4 ? invariant_wei_md()->dims[w_ndims - 2] : 1;
96 }
97 dim_t KW() const {
98 const int w_ndims = ndims() + with_groups();
99 return invariant_wei_md()->dims[w_ndims - 1];
100 }
101
102 dim_t KSD() const { return ndims() >= 5 ? desc_.strides[ndims() - 5] : 1; }
103 dim_t KSH() const { return ndims() >= 4 ? desc_.strides[ndims() - 4] : 1; }
104 dim_t KSW() const { return desc_.strides[ndims() - 3]; }
105
106 dim_t KDD() const { return ndims() >= 5 ? desc_.dilates[ndims() - 5] : 0; }
107 dim_t KDH() const { return ndims() >= 4 ? desc_.dilates[ndims() - 4] : 1; }
108 dim_t KDW() const { return desc_.dilates[ndims() - 3]; }
109
110 dim_t padFront() const {
111 return ndims() >= 5 ? desc_.padding[0][ndims() - 5] : 0;
112 }
113 dim_t padBack() const {
114 return ndims() >= 5 ? desc_.padding[1][ndims() - 5] : 0;
115 }
116 dim_t padT() const {
117 return ndims() >= 4 ? desc_.padding[0][ndims() - 4] : 0;
118 }
119 dim_t padB() const {
120 return ndims() >= 4 ? desc_.padding[1][ndims() - 4] : 0;
121 }
122 dim_t padL() const { return desc_.padding[0][ndims() - 3]; }
123 dim_t padR() const { return desc_.padding[1][ndims() - 3]; }
124
125 bool with_bias() const {
126 auto *bia_d = desc()->prop_kind == prop_kind::backward_weights
127 ? &desc()->diff_bias_desc
128 : &desc()->bias_desc;
129 return !memory_desc_wrapper(bia_d).is_zero();
130 }
131
132 bool with_groups() const {
133 return invariant_wei_md()->ndims == ndims() + 1;
134 }
135
136 int ndims() const { return invariant_src_md()->ndims; }
137
138 bool is_fwd() const {
139 return utils::one_of(desc_.prop_kind, prop_kind::forward_training,
140 prop_kind::forward_inference);
141 }
142
143 bool has_zero_dim_memory() const {
144 const auto s_d = memory_desc_wrapper(*invariant_src_md());
145 const auto d_d = memory_desc_wrapper(*invariant_dst_md());
146 return s_d.has_zero_dim() || d_d.has_zero_dim();
147 }
148
149 const memory_desc_t *invariant_src_md() const {
150 return desc()->prop_kind == prop_kind::backward_data ? diff_src_md()
151 : src_md();
152 }
153 const memory_desc_t *invariant_wei_md(int index = 0) const {
154 return desc()->prop_kind == prop_kind::backward_weights
155 ? diff_weights_md(index)
156 : weights_md(index);
157 }
158 const memory_desc_t *invariant_bia_md() const {
159 return invariant_wei_md(1);
160 }
161 const memory_desc_t *invariant_dst_md() const {
162 return utils::one_of(desc()->prop_kind, prop_kind::forward_inference,
163 prop_kind::forward_training)
164 ? dst_md()
165 : diff_dst_md();
166 }
167
168protected:
169 deconvolution_desc_t desc_;
170 const deconvolution_fwd_pd_t *hint_fwd_pd_;
171
172 deconvolution_pd_t(const deconvolution_desc_t *adesc,
173 const primitive_attr_t *attr,
174 const deconvolution_fwd_pd_t *hint_fwd_pd)
175 : primitive_desc_t(attr, base_pkind)
176 , desc_(*adesc)
177 , hint_fwd_pd_(hint_fwd_pd) {}
178};
179
180struct deconvolution_fwd_pd_t : public deconvolution_pd_t {
181 typedef deconvolution_fwd_pd_t base_class;
182 typedef deconvolution_fwd_pd_t hint_class;
183
184 arg_usage_t arg_usage(int arg) const override {
185 if (utils::one_of(arg, DNNL_ARG_SRC, DNNL_ARG_WEIGHTS))
186 return arg_usage_t::input;
187
188 if (arg == DNNL_ARG_BIAS && with_bias()) return arg_usage_t::input;
189
190 if (arg == DNNL_ARG_DST) return arg_usage_t::output;
191
192 return primitive_desc_t::arg_usage(arg);
193 }
194
195 const memory_desc_t *arg_md(int arg) const override {
196 switch (arg) {
197 case DNNL_ARG_SRC: return src_md(0);
198 case DNNL_ARG_WEIGHTS: return weights_md(0);
199 case DNNL_ARG_BIAS: return weights_md(1);
200 case DNNL_ARG_DST: return dst_md(0);
201 default: return deconvolution_pd_t::arg_md(arg);
202 }
203 }
204
205 const memory_desc_t *src_md(int index = 0) const override {
206 return index == 0 ? &src_md_ : &glob_zero_md;
207 }
208 const memory_desc_t *dst_md(int index = 0) const override {
209 return index == 0 ? &dst_md_ : &glob_zero_md;
210 }
211 const memory_desc_t *weights_md(int index = 0) const override {
212 if (index == 0) return &weights_md_;
213 if (index == 1 && with_bias()) return &bias_md_;
214 return &glob_zero_md;
215 }
216
217 int n_inputs() const override {
218 return 2 + with_bias() + n_prelu_po_inputs() + n_binary_po_inputs();
219 }
220 int n_outputs() const override { return 1; }
221
222protected:
223 memory_desc_t src_md_;
224 memory_desc_t weights_md_;
225 memory_desc_t bias_md_;
226 memory_desc_t dst_md_;
227
228 deconvolution_fwd_pd_t(const deconvolution_desc_t *adesc,
229 const primitive_attr_t *attr,
230 const deconvolution_fwd_pd_t *hint_fwd_pd)
231 : deconvolution_pd_t(adesc, attr, hint_fwd_pd)
232 , src_md_(desc_.src_desc)
233 , weights_md_(desc_.weights_desc)
234 , bias_md_(desc_.bias_desc)
235 , dst_md_(desc_.dst_desc) {}
236};
237
238struct deconvolution_bwd_data_pd_t : public deconvolution_pd_t {
239 typedef deconvolution_bwd_data_pd_t base_class;
240 typedef deconvolution_fwd_pd_t hint_class;
241
242 arg_usage_t arg_usage(int arg) const override {
243 if (utils::one_of(arg, DNNL_ARG_WEIGHTS, DNNL_ARG_DIFF_DST))
244 return arg_usage_t::input;
245
246 if (arg == DNNL_ARG_DIFF_SRC) return arg_usage_t::output;
247
248 return primitive_desc_t::arg_usage(arg);
249 }
250
251 const memory_desc_t *arg_md(int arg) const override {
252 switch (arg) {
253 case DNNL_ARG_DIFF_SRC: return diff_src_md(0);
254 case DNNL_ARG_WEIGHTS: return weights_md(0);
255 case DNNL_ARG_BIAS: return weights_md(1);
256 case DNNL_ARG_DIFF_DST: return diff_dst_md(0);
257 default: return deconvolution_pd_t::arg_md(arg);
258 }
259 }
260
261 const memory_desc_t *diff_src_md(int index = 0) const override {
262 return index == 0 ? &diff_src_md_ : &glob_zero_md;
263 }
264 const memory_desc_t *diff_dst_md(int index = 0) const override {
265 return index == 0 ? &diff_dst_md_ : &glob_zero_md;
266 }
267 const memory_desc_t *weights_md(int index = 0) const override {
268 return index == 0 ? &weights_md_ : &glob_zero_md;
269 }
270
271 int n_inputs() const override { return 2; }
272 int n_outputs() const override { return 1; }
273
274protected:
275 memory_desc_t diff_src_md_;
276 memory_desc_t weights_md_;
277 memory_desc_t diff_dst_md_;
278
279 deconvolution_bwd_data_pd_t(const deconvolution_desc_t *adesc,
280 const primitive_attr_t *attr,
281 const deconvolution_fwd_pd_t *hint_fwd_pd)
282 : deconvolution_pd_t(adesc, attr, hint_fwd_pd)
283 , diff_src_md_(desc_.diff_src_desc)
284 , weights_md_(desc_.weights_desc)
285 , diff_dst_md_(desc_.diff_dst_desc) {}
286};
287
288struct deconvolution_bwd_weights_pd_t : public deconvolution_pd_t {
289 typedef deconvolution_bwd_weights_pd_t base_class;
290 typedef deconvolution_fwd_pd_t hint_class;
291
292 arg_usage_t arg_usage(int arg) const override {
293 if (utils::one_of(arg, DNNL_ARG_SRC, DNNL_ARG_DIFF_DST))
294 return arg_usage_t::input;
295
296 if (arg == DNNL_ARG_DIFF_WEIGHTS) return arg_usage_t::output;
297
298 if (arg == DNNL_ARG_DIFF_BIAS && with_bias())
299 return arg_usage_t::output;
300
301 return primitive_desc_t::arg_usage(arg);
302 }
303
304 const memory_desc_t *arg_md(int arg) const override {
305 switch (arg) {
306 case DNNL_ARG_SRC: return src_md(0);
307 case DNNL_ARG_DIFF_WEIGHTS: return diff_weights_md(0);
308 case DNNL_ARG_DIFF_BIAS: return diff_weights_md(1);
309 case DNNL_ARG_DIFF_DST: return diff_dst_md(0);
310 default: return deconvolution_pd_t::arg_md(arg);
311 }
312 }
313
314 const memory_desc_t *src_md(int index = 0) const override {
315 return index == 0 ? &src_md_ : &glob_zero_md;
316 }
317 const memory_desc_t *diff_dst_md(int index = 0) const override {
318 return index == 0 ? &diff_dst_md_ : &glob_zero_md;
319 }
320 const memory_desc_t *diff_weights_md(int index = 0) const override {
321 if (index == 0) return &diff_weights_md_;
322 if (index == 1 && with_bias()) return &diff_bias_md_;
323 return &glob_zero_md;
324 }
325
326 int n_inputs() const override { return 2; }
327 int n_outputs() const override { return 1 + with_bias(); }
328
329protected:
330 memory_desc_t src_md_;
331 memory_desc_t diff_weights_md_;
332 memory_desc_t diff_bias_md_;
333 memory_desc_t diff_dst_md_;
334
335 deconvolution_bwd_weights_pd_t(const deconvolution_desc_t *adesc,
336 const primitive_attr_t *attr,
337 const deconvolution_fwd_pd_t *hint_fwd_pd)
338 : deconvolution_pd_t(adesc, attr, hint_fwd_pd)
339 , src_md_(desc_.src_desc)
340 , diff_weights_md_(desc_.diff_weights_desc)
341 , diff_bias_md_(desc_.diff_bias_desc)
342 , diff_dst_md_(desc_.diff_dst_desc) {}
343};
344
345} // namespace impl
346} // namespace dnnl
347
348#endif
349
350// vim: et ts=4 sw=4 cindent cino+=l0,\:4,N-s
351