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

   1 /*******************************************************************************
   2 * Copyright 2019 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_BINARY_CONVOLUTION_HPP
  18 #define CPU_JIT_UNI_BINARY_CONVOLUTION_HPP
  19
  20 #include "c_types_map.hpp"
  21 #include "cpu_binary_convolution_pd.hpp"
  22 #include "cpu_engine.hpp"
  23 #include "cpu_reducer.hpp"
  24 #include "jit_primitive_conf.hpp"
  25 #include "jit_uni_bin_conv_kernel.hpp"
  26 #include "mkldnn_thread.hpp"
  27
  28 namespace mkldnn {
  29 namespace impl {
  30 namespace cpu {
  31
  32 template <cpu_isa_t isa>
  33 struct jit_uni_binary_convolution_fwd_t: public cpu_primitive_t {
  34     struct pd_t: public _cpu_binary_convolution_fwd_pd_t {
  35         pd_t(engine_t *engine,
  36                 const binary_convolution_desc_t *adesc,
  37                 const primitive_attr_t *attr,
  38                 const typename pd_t::base_class *hint_fwd_pd)
  39             : _cpu_binary_convolution_fwd_pd_t(engine, adesc, attr, hint_fwd_pd)
  40             , jcp_(), jcp_dw_conv() {}
  41
  42         DECLARE_COMMON_PD_T(
  43                 JIT_IMPL_NAME_HELPER("jit:", isa, ""),
  44                 jit_uni_binary_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->cdesc_().prop_kind, forward_training, forward_inference)
  52                 && this->cdesc_().alg_kind == alg_kind::binary_convolution_direct
  53                 && utils::everyone_is(data_type::bin,
  54                         this->cdesc_().src_desc.data_type,
  55                         this->cdesc_().weights_desc.data_type)
  56                 && utils::one_of(this->cdesc_().dst_desc.data_type,
  57                         memory::data_type::f32,
  58                         memory::data_type::bin);
  59             if (!ok) return status::unimplemented;
  60
  61             status_t sts = jit_uni_bin_conv_fwd_kernel<isa>::init_conf(jcp_, *this->desc(),
  62                     *this->src_pd_.desc(), *this->weights_pd_.desc(),
  63                     *this->dst_pd_.desc(), *this->attr());
  64             if (sts != status::success) return sts;
  65
  66             if (jcp_.with_dw_conv) {
  67                 status_t sts_dw = jit_uni_dw_conv_row_f32<isa>::init_conf(jcp_, jcp_dw_conv, *this->attr());
  68                 if (sts_dw != status::success) return sts_dw;
  69             }
  70
  71             auto scratchpad = scratchpad_registry().registrar();
  72             jit_uni_bin_conv_fwd_kernel<isa>::init_scratchpad(scratchpad, jcp_, jcp_dw_conv);
  73
  74             return status::success;
  75         }
  76
  77         jit_bin_conv_conf_t jcp_;
  78         jit_conv_conf_t jcp_dw_conv;
  79
  80     protected:
  81         virtual status_t set_default_params() override {
  82             using namespace memory_format;
  83
  84             auto desired_weights_format = isa == avx512_common ? OhIw16o32i : OhIw8o32i;
  85
  86             if (this->src_pd_.desc()->format == any)
  87                 CHECK(this->src_pd_.set_format(nhwc));
  88             if (this->dst_pd_.desc()->format == any)
  89                 CHECK(this->dst_pd_.set_format(nhwc));
  90             if (this->weights_pd_.desc()->format == any)
  91                 CHECK(this->weights_pd_.set_format(desired_weights_format));
  92             return status::success;
  93         }
  94     };
  95
  96     jit_uni_binary_convolution_fwd_t(const pd_t *apd, const input_vector &inputs,
  97             const output_vector &outputs)
  98         : cpu_primitive_t(apd, inputs, outputs) {
  99         kernel_ = new jit_uni_bin_conv_fwd_kernel<isa>(pd()->jcp_, pd()->jcp_dw_conv, *pd()->attr());
 100
 101         if (pd()->jcp_.with_dw_conv) {
 102             dw_conv_kernel_ = new jit_uni_dw_conv_row_f32<isa>(pd()->jcp_dw_conv, *pd()->attr(), pd()->jcp_dw_conv.oc);
 103         }
 104     }
 105
 106     ~jit_uni_binary_convolution_fwd_t() {
 107         delete kernel_;
 108
 109         if (pd()->jcp_.with_dw_conv) {
 110             delete dw_conv_kernel_;
 111         }
 112     };
 113
 114     virtual void execute(event_t *e) const {
 115         if (pd()->jcp_.with_dw_conv)
 116             execute_forward_with_dw_conv();
 117         else
 118             execute_forward();
 119
 120         e->set_state(event_t::ready);
 121     }
 122
 123 private:
 124     void execute_forward() const;
 125     void execute_forward_with_dw_conv() const;
 126
 127     const pd_t *pd() const { return (const pd_t *)primitive_t::pd(); }
 128
 129     jit_uni_bin_conv_fwd_kernel<isa> *kernel_;
 130     /* fuse with dw conv */
 131     jit_uni_dw_conv_row_f32<isa> *dw_conv_kernel_;
 132 };
 133
 134 }
 135 }
 136 }
 137
 138 #endif