inference-engine/thirdparty/mkl-dnn/src/cpu/jit_uni_dw_convolution.hpp

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   2 * Copyright 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_UNI_DW_CONVOLUTION_HPP
  18 #define CPU_JIT_UNI_DW_CONVOLUTION_HPP
  19
  20 #include "c_types_map.hpp"
  21 #include "memory_tracking.hpp"
  22
  23 #include "cpu_barrier.hpp"
  24 #include "cpu_convolution_pd.hpp"
  25 #include "cpu_reducer.hpp"
  26
  27 #include "jit_uni_dw_conv_kernel_f32.hpp"
  28
  29 namespace mkldnn {
  30 namespace impl {
  31 namespace cpu {
  32
  33 template <cpu_isa_t isa>
  34 struct _jit_uni_dw_convolution_fwd_t: public cpu_primitive_t {
  35     struct pd_t: public cpu_convolution_fwd_pd_t {
  36         pd_t(engine_t *engine, const convolution_desc_t *adesc,
  37                 const primitive_attr_t *attr,
  38                 const typename pd_t::base_class *hint_fwd_pd)
  39             : cpu_convolution_fwd_pd_t(engine, adesc, attr, hint_fwd_pd)
  40             , jcp_() {}
  41
  42         DECLARE_COMMON_PD_T(
  43                 JIT_IMPL_NAME_HELPER("jit_dw:", isa, ""),
  44                 _jit_uni_dw_convolution_fwd_t<isa>);
  45
  46         virtual status_t init() override {
  47             using namespace prop_kind;
  48             assert(this->engine()->kind() == engine_kind::cpu);
  49             bool ok = true
  50                 && this->set_default_params() == status::success
  51                 && utils::one_of(this->desc()->prop_kind, forward_training,
  52                         forward_inference)
  53                 && utils::one_of(this->desc()->alg_kind,
  54                            alg_kind::convolution_auto,
  55                            alg_kind::convolution_direct)
  56                 && !this->has_zero_dim_memory()
  57                 && utils::everyone_is(data_type::f32,
  58                         this->desc()->src_desc.data_type,
  59                         this->desc()->weights_desc.data_type,
  60                         this->desc()->dst_desc.data_type)
  61                 && IMPLICATION(this->with_bias(),
  62                         data_type::f32 == this->desc()->bias_desc.data_type);
  63
  64             if (!ok) return status::unimplemented;
  65
  66             status_t status = jit_uni_dw_conv_fwd_kernel_f32<isa>::init_conf(
  67                     jcp_, *this->desc(), this->src_pd_.desc(),
  68                     *this->weights_pd_.desc(), *this->dst_pd_.desc(),
  69                     *this->attr());
  70             if (status != status::success) return status;
  71
  72             auto scratchpad = scratchpad_registry().registrar();
  73             jit_uni_dw_conv_fwd_kernel_f32<isa>::init_scratchpad(scratchpad,
  74                     jcp_);
  75
  76             return status::success;
  77         }
  78
  79         jit_conv_conf_t jcp_;
  80
  81     protected:
  82         virtual status_t set_default_params() override {
  83             using namespace memory_format;
  84             auto desired_act_fmt = isa == avx512_common ? nChw16c : nChw8c;
  85             auto desired_wei_fmt = isa == avx512_common ? Goihw16g : Goihw8g;
  86
  87             if (this->src_pd_.desc()->format == any)
  88                 CHECK(this->src_pd_.set_format(desired_act_fmt));
  89             if (this->dst_pd_.desc()->format == any)
  90                 CHECK(this->dst_pd_.set_format(desired_act_fmt));
  91             if (this->weights_pd_.desc()->format == any)
  92                 CHECK(this->weights_pd_.set_format(desired_wei_fmt));
  93             if (this->bias_pd_.desc()->format == any)
  94                 CHECK(this->bias_pd_.set_format(x));
  95             if (this->desc()->alg_kind == alg_kind::convolution_auto)
  96                 CHECK(this->set_alg_kind(alg_kind::convolution_direct));
  97             return status::success;
  98         }
  99     };
 100
 101     _jit_uni_dw_convolution_fwd_t(const pd_t *apd, const input_vector &inputs,
 102             const output_vector &outputs)
 103         : cpu_primitive_t(apd, inputs, outputs), kernel_(nullptr)
 104     { kernel_ = new jit_uni_dw_conv_fwd_kernel_f32<isa>(pd()->jcp_, *pd()->attr()); }
 105
 106     ~_jit_uni_dw_convolution_fwd_t() { delete kernel_; }
 107
 108     typedef typename prec_traits<data_type::f32>::type data_t;
 109
 110     virtual void execute(event_t *e) const {
 111         execute_forward();
 112         e->set_state(event_t::ready);
 113     }
 114
 115 private:
 116     void execute_forward() const;
 117     const pd_t *pd() const { return (const pd_t *)primitive_t::pd(); }
 118
 119     jit_uni_dw_conv_fwd_kernel_f32<isa> *kernel_;
 120 };
 121
 122 using jit_avx512_common_dw_convolution_fwd_t =
 123     _jit_uni_dw_convolution_fwd_t<avx512_common>;
 124 using jit_avx2_dw_convolution_fwd_t = _jit_uni_dw_convolution_fwd_t<avx2>;
 125 using jit_sse42_dw_convolution_fwd_t = _jit_uni_dw_convolution_fwd_t<sse42>;
 126
 127 template <cpu_isa_t isa>
 128 struct _jit_uni_dw_convolution_bwd_data_t: public cpu_primitive_t {
 129     struct pd_t: public cpu_convolution_bwd_data_pd_t {
 130         pd_t(engine_t *engine,
 131                 const convolution_desc_t *adesc,
 132                 const primitive_attr_t *attr,
 133                 const convolution_fwd_pd_t *hint_fwd_pd)
 134             : cpu_convolution_bwd_data_pd_t(engine, adesc, attr, hint_fwd_pd)
 135             , jcp_()
 136         {}
 137
 138         DECLARE_COMMON_PD_T(
 139                 JIT_IMPL_NAME_HELPER("jit_dw:", isa, ""),
 140                 _jit_uni_dw_convolution_bwd_data_t);
 141
 142         virtual status_t init() override {
 143             using namespace prop_kind;
 144
 145             assert(this->engine()->kind() == engine_kind::cpu);
 146             bool ok = true
 147                 && this->set_default_params() == status::success
 148                 && utils::one_of(this->desc()->prop_kind, backward,
 149                         backward_data)
 150                 && utils::one_of(this->desc()->alg_kind,
 151                            alg_kind::convolution_auto,
 152                            alg_kind::convolution_direct)
 153                 && !this->has_zero_dim_memory()
 154                 && utils::everyone_is(data_type::f32,
 155                         this->desc()->diff_src_desc.data_type,
 156                         this->desc()->weights_desc.data_type,
 157                         this->desc()->diff_dst_desc.data_type);
 158
 159             if (!ok) return status::unimplemented;
 160
 161             status_t status =
 162                 jit_uni_dw_conv_bwd_data_kernel_f32<isa>::init_conf(jcp_,
 163                         *this->desc(), *this->diff_src_pd_.desc(),
 164                         *this->weights_pd_.desc(), *this->diff_dst_pd_.desc());
 165             if (status != status::success) return status;
 166
 167             auto scratchpad = scratchpad_registry().registrar();
 168             jit_uni_dw_conv_bwd_data_kernel_f32<isa>::init_scratchpad(
 169                     scratchpad, jcp_);
 170
 171             return status::success;
 172         }
 173
 174         jit_conv_conf_t jcp_;
 175
 176     protected:
 177         virtual status_t set_default_params() override {
 178             using namespace memory_format;
 179             auto desired_act_fmt = isa == avx512_common ? nChw16c : nChw8c;
 180             auto desired_wei_fmt = isa == avx512_common ? Goihw16g : Goihw8g;
 181
 182             if (this->diff_src_pd_.desc()->format == any)
 183                 CHECK(this->diff_src_pd_.set_format(desired_act_fmt));
 184             if (this->diff_dst_pd_.desc()->format == any)
 185                 CHECK(this->diff_dst_pd_.set_format(desired_act_fmt));
 186             if (this->weights_pd_.desc()->format == any)
 187                 CHECK(this->weights_pd_.set_format(desired_wei_fmt));
 188             if (this->desc()->alg_kind == alg_kind::convolution_auto)
 189                 CHECK(this->set_alg_kind(alg_kind::convolution_direct));
 190
 191             return status::success;
 192         }
 193     };
 194
 195     _jit_uni_dw_convolution_bwd_data_t(const pd_t *apd,
 196             const input_vector &inputs, const output_vector &outputs)
 197         : cpu_primitive_t(apd, inputs, outputs)
 198     { kernel_ = new jit_uni_dw_conv_bwd_data_kernel_f32<isa>(pd()->jcp_); }
 199     ~_jit_uni_dw_convolution_bwd_data_t() { delete kernel_; };
 200
 201     typedef typename prec_traits<data_type::f32>::type data_t;
 202
 203     virtual void execute(event_t *e) const {
 204         switch (pd()->desc()->prop_kind) {
 205         case prop_kind::backward_data:
 206             execute_backward_data();
 207             break;
 208         default:
 209             assert(!"invalid prop_kind");
 210         }
 211         e->set_state(event_t::ready);
 212     }
 213
 214 private:
 215     void execute_backward_data() const;
 216     const pd_t *pd() const { return (const pd_t *)primitive_t::pd(); }
 217
 218     jit_uni_dw_conv_bwd_data_kernel_f32<isa> *kernel_;
 219 };
 220
 221 using jit_avx512_common_dw_convolution_bwd_data_t =
 222     _jit_uni_dw_convolution_bwd_data_t<avx512_common>;
 223 using jit_avx2_dw_convolution_bwd_data_t =
 224     _jit_uni_dw_convolution_bwd_data_t<avx2>;
 225 using jit_sse42_dw_convolution_bwd_data_t =
 226     _jit_uni_dw_convolution_bwd_data_t<sse42>;
 227
 228 template <cpu_isa_t isa>
 229 struct _jit_uni_dw_convolution_bwd_weights_t: public cpu_primitive_t {
 230     struct pd_t: public cpu_convolution_bwd_weights_pd_t {
 231         pd_t(engine_t *engine,
 232                 const convolution_desc_t *adesc,
 233                 const primitive_attr_t *attr,
 234                 const convolution_fwd_pd_t *hint_fwd_pd)
 235             : cpu_convolution_bwd_weights_pd_t(engine, adesc, attr, hint_fwd_pd)
 236             , jcp_() {}
 237
 238         DECLARE_COMMON_PD_T(
 239                 JIT_IMPL_NAME_HELPER("jit_dw:", isa, ""),
 240                 _jit_uni_dw_convolution_bwd_weights_t<isa>);
 241
 242         virtual status_t init() override {
 243             using namespace prop_kind;
 244
 245             assert(this->engine()->kind() == engine_kind::cpu);
 246             bool ok = true
 247                 && this->set_default_params() == status::success
 248                 && this->desc()->prop_kind == prop_kind::backward_weights
 249                 && utils::one_of(this->desc()->alg_kind,
 250                            alg_kind::convolution_auto,
 251                            alg_kind::convolution_direct)
 252                 && utils::everyone_is(data_type::f32,
 253                         this->desc()->src_desc.data_type,
 254                         this->desc()->diff_weights_desc.data_type,
 255                         this->desc()->diff_dst_desc.data_type);
 256
 257             if (!ok) return status::unimplemented;
 258
 259             const int max_threads = mkldnn_in_parallel()
 260                 ? 1 : mkldnn_get_max_threads();
 261
 262             status_t status =
 263                 jit_uni_dw_conv_bwd_weights_kernel_f32<isa>::init_conf(jcp_,
 264                         *this->desc(), *this->src_pd_.desc(),
 265                         *this->diff_weights_pd_.desc(),
 266                         *this->diff_dst_pd_.desc(), max_threads);
 267             if (status != status::success) return status;
 268
 269             auto scratchpad = scratchpad_registry().registrar();
 270             jit_uni_dw_conv_bwd_weights_kernel_f32<isa>::init_scratchpad(
 271                     scratchpad, jcp_);
 272
 273             return status::success;
 274         }
 275
 276         jit_conv_conf_t jcp_;
 277
 278     protected:
 279         virtual status_t set_default_params() override {
 280             using namespace memory_format;
 281             auto desired_act_fmt = isa == avx512_common ? nChw16c : nChw8c;
 282             auto desired_wei_fmt = isa == avx512_common ? Goihw16g : Goihw8g;
 283
 284             if (this->src_pd_.desc()->format == any)
 285                 CHECK(this->src_pd_.set_format(desired_act_fmt));
 286             if (this->diff_dst_pd_.desc()->format == any)
 287                 CHECK(this->diff_dst_pd_.set_format(desired_act_fmt));
 288             if (this->diff_weights_pd_.desc()->format == any)
 289                 CHECK(this->diff_weights_pd_.set_format(desired_wei_fmt));
 290             if (this->diff_bias_pd_.desc()->format == any)
 291                 CHECK(this->diff_bias_pd_.set_format(x));
 292             if (this->desc()->alg_kind == alg_kind::convolution_auto)
 293                 CHECK(this->set_alg_kind(alg_kind::convolution_direct));
 294
 295             return status::success;
 296         }
 297     };
 298
 299     _jit_uni_dw_convolution_bwd_weights_t(const pd_t *apd,
 300             const input_vector &inputs, const output_vector &outputs);
 301
 302     ~_jit_uni_dw_convolution_bwd_weights_t() {
 303         delete kernel_;
 304         delete acc_ker_;
 305     };
 306
 307     typedef typename prec_traits<data_type::f32>::type data_t;
 308
 309     virtual void execute(event_t *e) const {
 310         execute_backward_weights();
 311         e->set_state(event_t::ready);
 312     }
 313
 314 private:
 315     void execute_backward_weights() const;
 316     bool do_parallel_reduction() const { return false; }
 317     const pd_t *pd() const { return (const pd_t *)primitive_t::pd(); }
 318
 319     jit_uni_dw_conv_bwd_weights_kernel_f32<isa> *kernel_;
 320     cpu_accumulator_1d_t<data_type::f32> *acc_ker_;
 321 };
 322
 323 using jit_avx512_common_dw_convolution_bwd_weights_t =
 324     _jit_uni_dw_convolution_bwd_weights_t<avx512_common>;
 325 using jit_avx2_dw_convolution_bwd_weights_t =
 326     _jit_uni_dw_convolution_bwd_weights_t<avx2>;
 327 using jit_sse42_dw_convolution_bwd_weights_t =
 328     _jit_uni_dw_convolution_bwd_weights_t<sse42>;
 329
 330 }
 331 }
 332 }
 333
 334 #endif