1 | /******************************************************************************* |
2 | * Copyright 2016-2018 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 CPU_JIT_AVX512_COMMON_CONVOLUTION_HPP |
18 | #define CPU_JIT_AVX512_COMMON_CONVOLUTION_HPP |
19 | |
20 | #include "c_types_map.hpp" |
21 | #include "memory_tracking.hpp" |
22 | #include "mkldnn_thread.hpp" |
23 | #include "utils.hpp" |
24 | |
25 | #include "cpu_barrier.hpp" |
26 | #include "cpu_convolution_pd.hpp" |
27 | #include "cpu_primitive.hpp" |
28 | #include "cpu_reducer.hpp" |
29 | |
30 | #include "jit_transpose_src_utils.hpp" |
31 | #include "jit_avx512_common_conv_kernel.hpp" |
32 | |
33 | namespace mkldnn { |
34 | namespace impl { |
35 | namespace cpu { |
36 | |
37 | template <impl::data_type_t src_type, |
38 | impl::data_type_t wei_type = src_type, |
39 | impl::data_type_t dst_type = src_type> |
40 | struct jit_avx512_common_convolution_fwd_t : public cpu_primitive_t { |
41 | struct pd_t : public cpu_convolution_fwd_pd_t { |
42 | pd_t(engine_t *engine, const convolution_desc_t *adesc, |
43 | const primitive_attr_t *attr, |
44 | const typename pd_t::base_class *hint_fwd_pd) |
45 | : cpu_convolution_fwd_pd_t(engine, adesc, attr, hint_fwd_pd) |
46 | , jcp_() |
47 | {} |
48 | |
49 | DECLARE_COMMON_PD_T( |
50 | JIT_IMPL_NAME_HELPER("jit:" , avx512_common, "" ), |
51 | jit_avx512_common_convolution_fwd_t); |
52 | |
53 | status_t init() { |
54 | bool ok = true |
55 | && is_fwd() |
56 | && set_default_alg_kind(alg_kind::convolution_direct) |
57 | && expect_data_types(src_type, wei_type, dst_type, dst_type, |
58 | data_type::undef) |
59 | && !has_zero_dim_memory(); |
60 | if (!ok) return status::unimplemented; |
61 | |
62 | status_t status = jit_avx512_common_conv_fwd_kernel::init_conf( |
63 | jcp_, *desc(), src_md_, weights_md_, dst_md_, bias_md_, |
64 | *attr(), mkldnn_get_max_threads()); |
65 | if (status != status::success) return status; |
66 | |
67 | auto scratchpad = scratchpad_registry().registrar(); |
68 | jit_avx512_common_conv_fwd_kernel::init_scratchpad(scratchpad, |
69 | jcp_); |
70 | |
71 | return status; |
72 | } |
73 | |
74 | jit_conv_conf_t jcp_; |
75 | }; |
76 | |
77 | jit_avx512_common_convolution_fwd_t(const pd_t *apd) |
78 | : cpu_primitive_t(apd) |
79 | { |
80 | kernel_ = new jit_avx512_common_conv_fwd_kernel(pd()->jcp_, |
81 | *pd()->attr()); |
82 | } |
83 | ~jit_avx512_common_convolution_fwd_t() { delete kernel_; } |
84 | |
85 | typedef typename prec_traits<src_type>::type src_data_t; |
86 | typedef typename prec_traits<wei_type>::type wei_data_t; |
87 | typedef typename prec_traits<dst_type>::type dst_data_t; |
88 | |
89 | virtual status_t execute(const exec_ctx_t &ctx) const override { |
90 | if (pd()->ndims() == 3) |
91 | execute_forward_1d(ctx); |
92 | else if (pd()->ndims() == 4) |
93 | execute_forward_2d(ctx); |
94 | else if (pd()->ndims() == 5) |
95 | execute_forward_3d(ctx); |
96 | else |
97 | assert(false); |
98 | |
99 | if (pd()->wants_zero_pad_dst()) |
100 | ctx.memory(MKLDNN_ARG_DST)->zero_pad(); |
101 | |
102 | return status::success; |
103 | } |
104 | |
105 | private: |
106 | void prepare_padded_bias(const dst_data_t *&bias, |
107 | const memory_tracking::grantor_t &scratchpad) const; |
108 | void execute_forward_1d(const exec_ctx_t &ctx) const; |
109 | void execute_forward_2d(const exec_ctx_t &ctx) const; |
110 | void execute_forward_3d(const exec_ctx_t &ctx) const; |
111 | const pd_t *pd() const { return (const pd_t *)primitive_t::pd(); } |
112 | |
113 | jit_avx512_common_conv_fwd_kernel *kernel_; |
114 | }; |
115 | |
116 | template <impl::data_type_t diff_dst_type, |
117 | impl::data_type_t wei_type = diff_dst_type, |
118 | impl::data_type_t diff_src_type = diff_dst_type> |
119 | struct jit_avx512_common_convolution_bwd_data_t: public cpu_primitive_t { |
120 | struct pd_t: public cpu_convolution_bwd_data_pd_t { |
121 | pd_t(engine_t *engine, |
122 | const convolution_desc_t *adesc, |
123 | const primitive_attr_t *attr, |
124 | const convolution_fwd_pd_t *hint_fwd_pd) |
125 | : cpu_convolution_bwd_data_pd_t(engine, adesc, attr, hint_fwd_pd) |
126 | , jcp_() |
127 | {} |
128 | |
129 | DECLARE_COMMON_PD_T( |
130 | JIT_IMPL_NAME_HELPER("jit:" , avx512_common, "" ), |
131 | jit_avx512_common_convolution_bwd_data_t); |
132 | |
133 | status_t init() { |
134 | bool ok = true |
135 | && desc()->prop_kind == prop_kind::backward_data |
136 | && set_default_alg_kind(alg_kind::convolution_direct) |
137 | && expect_data_types(diff_src_type, wei_type, |
138 | data_type::undef, diff_dst_type, data_type::undef) |
139 | && !has_zero_dim_memory() |
140 | && set_default_formats(); |
141 | if (!ok) return status::unimplemented; |
142 | |
143 | status_t status = |
144 | jit_avx512_common_conv_bwd_data_kernel_f32::init_conf(jcp_, |
145 | *desc(), *diff_src_md(), *weights_md(), *diff_dst_md()); |
146 | if (status != status::success) return status; |
147 | |
148 | auto scratchpad = scratchpad_registry().registrar(); |
149 | jit_avx512_common_conv_bwd_data_kernel_f32::init_scratchpad( |
150 | scratchpad, jcp_); |
151 | |
152 | return status::success; |
153 | } |
154 | |
155 | jit_conv_conf_t jcp_; |
156 | |
157 | protected: |
158 | bool set_default_formats() { |
159 | using namespace format_tag; |
160 | |
161 | auto dat_tag = utils::pick(ndims() - 3, nCw16c, nChw16c, nCdhw16c); |
162 | auto wei_tag = utils::pick(2 * ndims() - 6 + with_groups(), |
163 | OIw16o16i, gOIw16o16i, OIhw16o16i, gOIhw16o16i, |
164 | OIdhw16o16i, gOIdhw16o16i); |
165 | |
166 | return set_default_formats_common(dat_tag, wei_tag, dat_tag); |
167 | } |
168 | }; |
169 | |
170 | jit_avx512_common_convolution_bwd_data_t(const pd_t *apd) |
171 | : cpu_primitive_t(apd) |
172 | { kernel_ = new jit_avx512_common_conv_bwd_data_kernel_f32(pd()->jcp_); } |
173 | ~jit_avx512_common_convolution_bwd_data_t() { delete kernel_; }; |
174 | |
175 | typedef typename prec_traits<diff_dst_type>::type diff_dst_data_t; |
176 | typedef typename prec_traits<wei_type>::type wei_data_t; |
177 | typedef typename prec_traits<diff_src_type>::type diff_src_data_t; |
178 | |
179 | virtual status_t execute(const exec_ctx_t &ctx) const override { |
180 | if (pd()->ndims() == 3) |
181 | execute_backward_data_1d(ctx); |
182 | else if (pd()->ndims() == 4) |
183 | execute_backward_data_2d(ctx); |
184 | else if (pd()->ndims() == 5) |
185 | execute_backward_data_3d(ctx); |
186 | else |
187 | assert(false); |
188 | return status::success; |
189 | } |
190 | |
191 | private: |
192 | void execute_backward_data_1d(const exec_ctx_t &ctx) const; |
193 | void execute_backward_data_2d(const exec_ctx_t &ctx) const; |
194 | void execute_backward_data_3d(const exec_ctx_t &ctx) const; |
195 | const pd_t *pd() const { return (const pd_t *)primitive_t::pd(); } |
196 | |
197 | jit_avx512_common_conv_bwd_data_kernel_f32 *kernel_; |
198 | }; |
199 | |
200 | template <impl::data_type_t src_type, |
201 | impl::data_type_t diff_dst_type = src_type, |
202 | impl::data_type_t diff_weights_type = src_type> |
203 | struct jit_avx512_common_convolution_bwd_weights_t: public cpu_primitive_t { |
204 | struct pd_t: public cpu_convolution_bwd_weights_pd_t { |
205 | pd_t(engine_t *engine, const convolution_desc_t *adesc, |
206 | const primitive_attr_t *attr, |
207 | const convolution_fwd_pd_t *hint_fwd_pd) |
208 | : cpu_convolution_bwd_weights_pd_t(engine, adesc, attr, hint_fwd_pd) |
209 | , jcp_() {} |
210 | |
211 | DECLARE_COMMON_PD_T( |
212 | JIT_IMPL_NAME_HELPER("jit:" , avx512_common, "" ), |
213 | jit_avx512_common_convolution_bwd_weights_t); |
214 | |
215 | status_t init() { |
216 | bool ok = true |
217 | && desc()->prop_kind == prop_kind::backward_weights |
218 | && set_default_alg_kind(alg_kind::convolution_direct) |
219 | && expect_data_types(src_type, diff_weights_type, |
220 | diff_weights_type, diff_dst_type, data_type::undef) |
221 | && !has_zero_dim_memory(); |
222 | if (!ok) return status::unimplemented; |
223 | |
224 | status_t status = jit_avx512_common_conv_bwd_weights_kernel_f32:: |
225 | init_conf(jcp_, *desc(), src_md_, diff_weights_md_, |
226 | diff_bias_md_, diff_dst_md_); |
227 | if (status != status::success) return status; |
228 | |
229 | init_balancers(); |
230 | |
231 | auto scratchpad = scratchpad_registry().registrar(); |
232 | jit_avx512_common_conv_bwd_weights_kernel_f32::init_scratchpad( |
233 | scratchpad, jcp_); |
234 | |
235 | auto reducer_bia_scratchpad = memory_tracking::registrar_t( |
236 | scratchpad, memory_tracking::names::prefix_reducer_bia); |
237 | reducer_bia_conf_.init_scratchpad(reducer_bia_scratchpad); |
238 | |
239 | return status; |
240 | } |
241 | |
242 | jit_conv_conf_t jcp_; |
243 | typename cpu_reducer_t<diff_weights_type>::conf_t reducer_bia_conf_; |
244 | |
245 | private: |
246 | void init_balancers() { |
247 | const size_t max_buffer_size = jcp_.nthr * 3 * 5 * 5 * 16 * 16; |
248 | if (with_bias()) { |
249 | reducer_bia_conf_.init(reduce_balancer_t(jcp_.nthr, |
250 | jcp_.oc_block, jcp_.ngroups * jcp_.nb_oc, jcp_.mb, |
251 | max_buffer_size)); |
252 | } |
253 | } |
254 | }; |
255 | |
256 | jit_avx512_common_convolution_bwd_weights_t(const pd_t *apd); |
257 | ~jit_avx512_common_convolution_bwd_weights_t() { |
258 | delete kernel_; |
259 | if (trans_kernel_) |
260 | delete trans_kernel_; |
261 | if (acc_ker_) |
262 | delete acc_ker_; |
263 | delete reducer_bias_; |
264 | } |
265 | |
266 | typedef typename prec_traits<src_type>::type src_data_t; |
267 | typedef typename prec_traits<diff_dst_type>::type diff_dst_data_t; |
268 | typedef typename prec_traits<diff_weights_type>::type diff_weights_data_t; |
269 | |
270 | virtual status_t execute(const exec_ctx_t &ctx) const override { |
271 | execute_backward_weights(ctx); |
272 | return status::success; |
273 | } |
274 | |
275 | private: |
276 | void execute_backward_weights(const exec_ctx_t &ctx) const; |
277 | void prepare_scratchpad_data(const exec_ctx_t &ctx) const; |
278 | struct thread_info_t; |
279 | void compute_diff_weights(const thread_info_t *) const; |
280 | void compute_diff_weights_3d(const thread_info_t *) const; |
281 | void reduce_diff_weights(const thread_info_t *) const; |
282 | void reduce_diff_weights_3d(const thread_info_t *) const; |
283 | void compute_diff_bias(const thread_info_t *) const; |
284 | void compute_diff_bias_3d(const thread_info_t *) const; |
285 | |
286 | const pd_t *pd() const { return (const pd_t *)primitive_t::pd(); } |
287 | |
288 | int nthr_, nthr_mb_, nthr_g_, nthr_oc_b_, nthr_ic_b_; |
289 | |
290 | jit_avx512_common_conv_bwd_weights_kernel_f32 *kernel_; |
291 | jit_trans_src_t *trans_kernel_; |
292 | cpu_accumulator_1d_t<diff_weights_type> *acc_ker_; |
293 | cpu_reducer_t<diff_weights_type> *reducer_bias_; |
294 | }; |
295 | |
296 | } |
297 | } |
298 | } |
299 | |
300 | #endif |
301 | |
302 | // vim: et ts=4 sw=4 cindent cino^=l0,\:0,N-s |
303 | |