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

   1 /*******************************************************************************
   2 * Copyright 2017 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_SOFTMAX_HPP
  18 #define CPU_JIT_UNI_SOFTMAX_HPP
  19
  20 #include <assert.h>
  21
  22 #include "c_types_map.hpp"
  23 #include "cpu_softmax_pd.hpp"
  24 #include "cpu_engine.hpp"
  25 #include "type_helpers.hpp"
  26 #include "utils.hpp"
  27 #include "jit_primitive_conf.hpp"
  28 #include "jit_uni_softmax_kernel_f32.hpp"
  29 #include "mkldnn_types.h"
  30
  31
  32 namespace mkldnn {
  33 namespace impl {
  34 namespace cpu {
  35
  36 template <cpu_isa_t isa>
  37 struct jit_uni_softmax_fwd_t : public cpu_primitive_t {
  38     struct pd_t : public cpu_softmax_fwd_pd_t {
  39         pd_t(engine_t *engine, const softmax_desc_t *adesc,
  40              const primitive_attr_t *attr,
  41              const softmax_fwd_pd_t *hint_fwd_pd)
  42             : cpu_softmax_fwd_pd_t(engine, adesc, attr, hint_fwd_pd) {}
  43
  44         DECLARE_COMMON_PD_T(
  45                 JIT_IMPL_NAME_HELPER("jit:", isa, ""),
  46                 jit_uni_softmax_fwd_t<isa>);
  47
  48         virtual status_t init() override {
  49             using namespace prop_kind;
  50
  51             auto desired_fmt = memory_format::nchw;
  52
  53             assert(engine()->kind() == engine_kind::cpu);
  54
  55             auto ndims = desc_.data_desc.ndims;
  56             auto dims = desc_.data_desc.dims;
  57             auto axis = desc_.softmax_axis;
  58
  59             size_t inner_size = utils::array_product(dims + axis + 1, ndims - axis - 1);
  60
  61             bool ok = mayiuse(isa)
  62                       && utils::one_of(desc()->prop_kind, forward_training,
  63                                        forward_inference)
  64                       && utils::everyone_is(data_type::f32, desc()->data_desc.data_type)
  65                       && memory_desc_wrapper(src_pd()).is_dense(true)
  66                       && utils::everyone_is(desired_fmt, src_pd()->desc()->format,
  67                                             dst_pd()->desc()->format)
  68                       && inner_size > 1;
  69
  70             if (!ok) return status::unimplemented;
  71
  72
  73             return jit_uni_softmax_kernel_f32<isa>::init_conf(jpp_, desc_,
  74                                                               src_pd()->desc(), dst_pd()->desc());
  75         }
  76         jit_softmax_conf_t jpp_;
  77     };
  78
  79     jit_uni_softmax_fwd_t(const pd_t *apd, const input_vector &inputs,
  80                        const output_vector &outputs);
  81     ~jit_uni_softmax_fwd_t();
  82
  83     using data_t = prec_traits<data_type::f32>::type;
  84
  85     virtual void execute(event_t *e) const override {
  86         execute_forward();
  87         e->set_state(event_t::ready);
  88     }
  89
  90 private:
  91     void execute_forward() const;
  92     const pd_t *pd() const { return (const pd_t *)primitive_t::pd(); }
  93     jit_uni_softmax_kernel_f32<isa> *kernel_;
  94 };
  95
  96 }
  97 }
  98 }
  99
 100 #endif