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

   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_REF_ELTWISE_HPP
  18 #define CPU_REF_ELTWISE_HPP
  19
  20 #include <assert.h>
  21
  22 #include "c_types_map.hpp"
  23 #include "cpu_eltwise_pd.hpp"
  24 #include "cpu_engine.hpp"
  25 #include "type_helpers.hpp"
  26 #include "utils.hpp"
  27
  28 namespace mkldnn {
  29 namespace impl {
  30 namespace cpu {
  31
  32 struct ref_eltwise_scalar_fwd_t {
  33 public:
  34     ref_eltwise_scalar_fwd_t(alg_kind_t alg, float alpha, float beta);
  35
  36     // note that eltwise.scale is ignored
  37     ref_eltwise_scalar_fwd_t(const post_ops_t::entry_t::eltwise_t &eltwise);
  38
  39     float compute_scalar(float s);
  40
  41     const alg_kind_t alg_;
  42     const float alpha_;
  43     const float beta_;
  44 };
  45
  46 template <impl::data_type_t data_type>
  47 struct ref_eltwise_fwd_t: public cpu_primitive_t {
  48     struct pd_t: public cpu_eltwise_fwd_pd_t {
  49         pd_t(engine_t *engine, const eltwise_desc_t *adesc,
  50                 const primitive_attr_t *attr,
  51                 const eltwise_fwd_pd_t *hint_fwd_pd)
  52             : cpu_eltwise_fwd_pd_t(engine, adesc, attr, hint_fwd_pd) {}
  53
  54         DECLARE_COMMON_PD_T("ref:any", ref_eltwise_fwd_t);
  55
  56         virtual status_t init() override {
  57             using namespace prop_kind;
  58             using namespace memory_format;
  59             using namespace utils;
  60             assert(engine()->kind() == engine_kind::cpu);
  61
  62             auto src_d = memory_desc_wrapper(src_pd());
  63
  64             use_dense_ = false
  65                 || src_d.is_dense()
  66                 || (src_d.is_dense(true) && is_zero_preserved());
  67
  68             use_nCspBc_padded_ = !use_dense_
  69                 && one_of(desc()->data_desc.format, nChw8c, nChw16c,
  70                     nCdhw8c, nCdhw16c)
  71                 && src_d.only_padded_dim(1)
  72                 && src_d.is_dense(true);
  73
  74             if (has_zero_dim_memory())
  75                 use_dense_ = use_nCspBc_padded_ = false;
  76
  77             const bool use_generic = !use_dense_ && !use_nCspBc_padded_;
  78
  79             bool ok = true
  80                 && one_of(desc()->prop_kind, forward_training,
  81                         forward_inference)
  82                 && everyone_is(data_type, desc()->data_desc.data_type)
  83                 && IMPLICATION(use_generic, one_of(src_d.ndims(), 4, 5))
  84                 && attr()->has_default_values();
  85             if (!ok) return status::unimplemented;
  86
  87             return status::success;
  88         }
  89
  90         bool use_dense_, use_nCspBc_padded_;
  91     };
  92
  93     ref_eltwise_fwd_t(const pd_t *apd, const input_vector &inputs,
  94             const output_vector &outputs)
  95         : cpu_primitive_t(apd, inputs, outputs) {}
  96     typedef typename prec_traits<data_type>::type data_t;
  97
  98     virtual void execute(event_t *e) const {
  99         if (pd()->use_dense_)
 100             execute_forward_dense();
 101         else if (pd()->use_nCspBc_padded_)
 102             execute_forward_nCspBc_padded();
 103         else
 104             execute_forward_generic();
 105         e->set_state(event_t::ready);
 106     }
 107
 108 private:
 109     void execute_forward_nCspBc_padded() const;
 110     void execute_forward_dense() const;
 111     void execute_forward_generic() const;
 112     const pd_t *pd() const { return (const pd_t *)primitive_t::pd(); }
 113 };
 114
 115 template <impl::data_type_t data_type>
 116 struct ref_eltwise_bwd_t: public cpu_primitive_t {
 117     struct pd_t: public cpu_eltwise_bwd_pd_t {
 118         pd_t(engine_t *engine, const eltwise_desc_t *adesc,
 119                 const primitive_attr_t *attr,
 120                 const eltwise_fwd_pd_t *hint_fwd_pd)
 121             : cpu_eltwise_bwd_pd_t(engine, adesc, attr, hint_fwd_pd) {}
 122
 123         DECLARE_COMMON_PD_T("ref:any", ref_eltwise_bwd_t);
 124
 125         virtual status_t init() override {
 126             using namespace prop_kind;
 127             using namespace utils;
 128             assert(engine()->kind() == engine_kind::cpu);
 129             bool ok = true && desc()->prop_kind == backward_data
 130                     && everyone_is(data_type, desc()->data_desc.data_type,
 131                             desc()->diff_data_desc.data_type)
 132                     && attr()->has_default_values();
 133             if (!ok) return status::unimplemented;
 134
 135             auto diff_dst_d = memory_desc_wrapper(diff_dst_pd());
 136             const bool same_fmt_ = diff_dst_d == memory_desc_wrapper(src_pd());
 137
 138             use_dense_ = true
 139                 && same_fmt_
 140                 && diff_dst_d.is_dense(true)
 141                 && is_zero_preserved()
 142                 && !has_zero_dim_memory();
 143             const bool use_generic = !use_dense_;
 144
 145             if (use_generic && !one_of(diff_dst_d.ndims(), 4, 5))
 146                 return status::unimplemented;
 147
 148             if (desc()->alg_kind == mkldnn_eltwise_not)
 149                 return status::unimplemented;
 150
 151             return status::success;
 152         }
 153
 154         bool use_dense_;
 155     };
 156
 157     ref_eltwise_bwd_t(const pd_t *apd, const input_vector &inputs,
 158             const output_vector &outputs)
 159         : cpu_primitive_t(apd, inputs, outputs) {}
 160     typedef typename prec_traits<data_type>::type data_t;
 161
 162     virtual void execute(event_t *e) const {
 163         if (pd()->use_dense_) execute_backward_dense();
 164         else execute_backward_generic();
 165         e->set_state(event_t::ready);
 166     }
 167
 168 private:
 169     void execute_backward_dense() const;
 170     void execute_backward_generic() const;
 171     const pd_t *pd() const { return (const pd_t *)primitive_t::pd(); }
 172 };
 173
 174 }
 175 }
 176 }
 177
 178 #endif
 179
 180 // vim: et ts=4 sw=4 cindent cino^=l0,\:0,N-s