inference-engine/thirdparty/mkl-dnn/src/cpu/gemm_x8s8s32x_convolution.hpp

   1 /*******************************************************************************
   2 * Copyright 2017-2018 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 GEMM_X8S8S32X_CONVOLUTION_HPP
  18 #define GEMM_X8S8S32X_CONVOLUTION_HPP
  19
  20 #include "c_types_map.hpp"
  21 #include "memory_tracking.hpp"
  22
  23 #include "cpu_convolution_pd.hpp"
  24 #include "cpu_engine.hpp"
  25 #include "jit_primitive_conf.hpp"
  26 #include "jit_generator.hpp"
  27 #include "gemm_convolution_utils.hpp"
  28
  29 #include "gemm/gemm.hpp"
  30
  31 namespace mkldnn {
  32 namespace impl {
  33 namespace cpu {
  34
  35 template <data_type_t src_type, data_type_t dst_type>
  36 struct _gemm_x8s8s32x_convolution_fwd_t: public cpu_primitive_t {
  37     struct pd_t: public cpu_convolution_fwd_pd_t {
  38         pd_t(engine_t *engine, const convolution_desc_t *adesc,
  39                 const primitive_attr_t *attr,
  40                 const typename pd_t::base_class *hint_fwd_pd)
  41             : cpu_convolution_fwd_pd_t(engine, adesc, attr, hint_fwd_pd)
  42             , jcp_() {}
  43
  44         DECLARE_COMMON_PD_T(IGEMM_S8U8S32_IMPL_STR,
  45                 _gemm_x8s8s32x_convolution_fwd_t<src_type, dst_type>);
  46
  47         virtual status_t init() override {
  48             using namespace data_type;
  49             using namespace memory_format;
  50
  51             assert(this->engine()->kind() == engine_kind::cpu);
  52
  53             bool ok = true
  54                 && this->set_default_params() == status::success
  55                 && utils::one_of(this->desc()->prop_kind,
  56                         prop_kind::forward_training,
  57                         prop_kind::forward_inference)
  58                 && utils::one_of(this->desc()->alg_kind,
  59                         alg_kind::convolution_auto,
  60                         alg_kind::convolution_direct)
  61                 && !this->has_zero_dim_memory()
  62                 && this->desc()->src_desc.data_type == src_type
  63                 && this->desc()->dst_desc.data_type == dst_type
  64                 && this->desc()->weights_desc.data_type == s8
  65                 && IMPLICATION(this->with_bias(), utils::one_of(
  66                             this->desc()->bias_desc.data_type, f32, s32, s8,
  67                             u8))
  68                 && this->desc()->accum_data_type == data_type::s32
  69                 && utils::everyone_is(nhwc, this->src_pd_.desc()->format,
  70                         this->dst_pd_.desc()->format)
  71                 && this->weights_pd_.desc()->format == (this->with_groups()
  72                         ? ((src_type == data_type::s8) ? hwigo_s8s8 : hwigo)
  73                         : ((src_type == data_type::s8) ? hwio_s8s8 : hwio))
  74                 && this->is_gemm_conv_format();
  75             if (!ok) return status::unimplemented;
  76
  77             auto scratchpad = scratchpad_registry().registrar();
  78             return jit_gemm_convolution_utils::init_conf(jcp_, scratchpad,
  79                     *this->desc(), this->src_pd(), this->weights_pd(0),
  80                     this->dst_pd(), mkldnn_get_max_threads());
  81         }
  82
  83         jit_gemm_conv_conf_t jcp_;
  84
  85     protected:
  86         virtual status_t set_default_params() override {
  87             using namespace memory_format;
  88             const bool is_sign_input =
  89                 this->desc()->src_desc.data_type == data_type::s8;
  90
  91             if (this->src_pd_.desc()->format == any)
  92                 CHECK(this->src_pd_.set_format(nhwc));
  93             if (this->dst_pd_.desc()->format == any)
  94                 CHECK(this->dst_pd_.set_format(nhwc));
  95             if (this->weights_pd_.desc()->format == any)
  96                 CHECK(this->weights_pd_.set_format(this->with_groups()
  97                             ? (is_sign_input ? hwigo_s8s8 : hwigo)
  98                             : (is_sign_input ? hwio_s8s8 : hwio)));
  99             if (this->bias_pd_.desc()->format == any)
 100                 CHECK(this->bias_pd_.set_format(x));
 101             if (this->desc()->alg_kind == alg_kind::convolution_auto)
 102                 CHECK(this->set_alg_kind(alg_kind::convolution_direct));
 103             return status::success;
 104         }
 105
 106         virtual bool is_gemm_conv_format() const {
 107             using namespace mkldnn::impl::primitive_kind;
 108             auto const &po = this->attr()->post_ops_;
 109             auto is_relu = [&](int idx) {
 110                 return po.entry_[idx].is_relu(true, false); };
 111
 112             switch (po.len_) {
 113             case 0: return true;
 114             case 1: return is_relu(0) || po.contain(sum, 0);
 115             case 2: return po.contain(sum, 0) && is_relu(1);
 116             default: return false;
 117             }
 118             return false;
 119         }
 120     };
 121
 122     _gemm_x8s8s32x_convolution_fwd_t(const pd_t *apd, const input_vector &inputs,
 123            const output_vector &outputs)
 124         : cpu_primitive_t(apd, inputs, outputs, true) {
 125         pp_ker_ = new pp_ker_t(apd);
 126     }
 127     ~_gemm_x8s8s32x_convolution_fwd_t() {
 128         delete pp_ker_;
 129     }
 130
 131     typedef typename prec_traits<src_type>::type src_data_t;
 132     typedef typename prec_traits<data_type::s8>::type wei_data_t;
 133     typedef typename prec_traits<dst_type>::type dst_data_t;
 134     typedef typename prec_traits<data_type::s32>::type acc_data_t;
 135
 136     virtual void execute(event_t *e) const {
 137         execute_forward();
 138         e->set_state(event_t::ready);
 139     }
 140
 141 private:
 142     const pd_t *pd() const { return (const pd_t *)primitive_t::pd(); }
 143     void execute_forward() const;
 144     // XXX: this is throwaway code that will become unnecessary when we have a
 145     // sufficiently advanced igemm jit generator that supports quantization,
 146     // relu, and whatnot
 147     class pp_ker_t : jit_generator {
 148     public:
 149         DECLARE_CPU_JIT_AUX_FUNCTIONS(
 150         _gemm_x8s8s32x_convolution_fwd_t::pp_kernel);
 151         pp_ker_t(const pd_t *pd);
 152
 153         void operator()(dst_data_t *dst, const acc_data_t *acc,
 154             const char *bias, const float *scales,
 155             float nslope, float sum_scale, float signed_scale,
 156             int g, size_t start, size_t end);
 157     private:
 158         void generate();
 159
 160         struct ker_args {
 161             dst_data_t *dst;
 162             const acc_data_t *acc;
 163             const char *bias;
 164             const float *scales;
 165             float nslope;
 166             float sum_scale;
 167             float signed_scale;
 168             size_t len;
 169             size_t oc_offset;
 170         };
 171         void(*ker_)(const ker_args *args);
 172
 173         const jit_gemm_conv_conf_t jcp_;
 174         size_t OC_;
 175         size_t OS_;
 176         data_type_t bias_data_type_;
 177         size_t bias_data_type_size_;
 178         size_t scale_idx_mult_;
 179         round_mode_t rmode_;
 180         bool do_bias_;
 181         bool do_relu_;
 182         bool do_sum_;
 183         bool do_signed_scaling_;
 184         size_t dst_os_stride_;
 185         size_t vlen_;
 186     };
 187
 188
 189     void execute_forward_thr(const int ithr, const int nthr,
 190             const src_data_t *src_base, const wei_data_t *wei_base,
 191             const char *bia_base, dst_data_t *dst_base,
 192             const memory_tracking::grantor_t &scratchpad) const;
 193
 194     int nthr_;
 195     pp_ker_t *pp_ker_;
 196
 197 };
 198
 199 template <data_type_t dst_type>
 200 struct _gemm_u8s8s32x_convolution_bwd_data_t: public cpu_primitive_t {
 201     struct pd_t: public cpu_convolution_bwd_data_pd_t{
 202         pd_t(engine_t *engine,
 203                 const convolution_desc_t *adesc, const primitive_attr_t *attr,
 204                 const convolution_fwd_pd_t *hint_fwd_pd)
 205             : cpu_convolution_bwd_data_pd_t(engine, adesc, attr, hint_fwd_pd)
 206             , jcp_() {}
 207
 208         DECLARE_COMMON_PD_T(IGEMM_S8U8S32_IMPL_STR,
 209                 _gemm_u8s8s32x_convolution_bwd_data_t<dst_type>);
 210
 211         virtual status_t init() override {
 212             using namespace data_type;
 213             using namespace memory_format;
 214
 215             assert(this->engine()->kind() == engine_kind::cpu);
 216
 217             bool ok = true
 218                 && this->set_default_params() == status::success
 219                 && this->desc()->prop_kind == prop_kind::backward_data
 220                 && utils::one_of(this->desc()->alg_kind, alg_kind::convolution_auto,
 221                            alg_kind::convolution_direct)
 222                 && !this->has_zero_dim_memory()
 223                 && this->desc()->diff_src_desc.data_type == dst_type
 224                 && this->desc()->diff_dst_desc.data_type == u8
 225                 && this->desc()->weights_desc.data_type == s8
 226                 && IMPLICATION(this->with_bias(), utils::one_of(
 227                             this->desc()->bias_desc.data_type, f32, s32, s8,
 228                             u8))
 229                 && this->desc()->accum_data_type == data_type::s32
 230                 && utils::everyone_is(nhwc, this->diff_src_pd_.desc()->format,
 231                         this->diff_dst_pd_.desc()->format)
 232                 && this->weights_pd_.desc()->format == (this->with_groups()
 233                         ? hwigo : hwio)
 234                 && attr()->post_ops_.has_default_values();
 235             if (!ok) return status::unimplemented;
 236
 237             auto scratchpad = scratchpad_registry().registrar();
 238             return jit_gemm_convolution_utils::init_conf(jcp_, scratchpad,
 239                     *this->desc(), this->diff_src_pd(), this->weights_pd(0),
 240                     this->diff_dst_pd(), mkldnn_get_max_threads());
 241         }
 242
 243         virtual bool support_bias() const override { return true; }
 244
 245         jit_gemm_conv_conf_t jcp_;
 246
 247     protected:
 248         virtual status_t set_default_params() override {
 249             using namespace memory_format;
 250
 251             if (this->diff_src_pd_.desc()->format == any)
 252                 CHECK(this->diff_src_pd_.set_format(nhwc));
 253             if (this->diff_dst_pd_.desc()->format == any)
 254                 CHECK(this->diff_dst_pd_.set_format(nhwc));
 255             if (this->weights_pd_.desc()->format == any)
 256                 CHECK(this->weights_pd_.set_format(
 257                             this->with_groups() ? hwigo : hwio));
 258             if (bias_pd_.desc()->format == any)
 259                 CHECK(bias_pd_.set_format(x));
 260             if (this->desc()->alg_kind == alg_kind::convolution_auto)
 261                 CHECK(this->set_alg_kind(alg_kind::convolution_direct));
 262              return status::success;
 263         }
 264     };
 265
 266     _gemm_u8s8s32x_convolution_bwd_data_t(const pd_t *apd, const input_vector &inputs,
 267            const output_vector &outputs)
 268         : cpu_primitive_t(apd, inputs, outputs, true) {}
 269     ~_gemm_u8s8s32x_convolution_bwd_data_t() {}
 270
 271     typedef typename prec_traits<data_type::u8>::type diff_dst_data_t;
 272     typedef typename prec_traits<data_type::s8>::type wei_data_t;
 273     typedef typename prec_traits<dst_type>::type diff_src_data_t;
 274     typedef typename prec_traits<data_type::s32>::type acc_data_t;
 275
 276     virtual void execute(event_t *e) const {
 277         execute_backward_data();
 278         e->set_state(event_t::ready);
 279     }
 280
 281 private:
 282     void execute_backward_data() const;
 283     void execute_backward_data_thr(const int ithr, const int nthr,
 284             const diff_dst_data_t *diff_dst_base, const wei_data_t *wei_base,
 285             const char *bia_base, diff_src_data_t *diff_src_base,
 286             const memory_tracking::grantor_t &scratchpad) const;
 287     const pd_t *pd() const { return (const pd_t *)primitive_t::pd(); }
 288 };
 289
 290 }
 291 }
 292 }
 293
 294 #endif