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Diffstat (limited to 'thirdparty/oidn/mkl-dnn/src/cpu/gemm_convolution.hpp')
| -rw-r--r-- | thirdparty/oidn/mkl-dnn/src/cpu/gemm_convolution.hpp | 250 |
1 files changed, 250 insertions, 0 deletions
diff --git a/thirdparty/oidn/mkl-dnn/src/cpu/gemm_convolution.hpp b/thirdparty/oidn/mkl-dnn/src/cpu/gemm_convolution.hpp new file mode 100644 index 0000000000..302e46369a --- /dev/null +++ b/thirdparty/oidn/mkl-dnn/src/cpu/gemm_convolution.hpp @@ -0,0 +1,250 @@ +/******************************************************************************* +* Copyright 2016-2018 Intel Corporation +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*******************************************************************************/ + +#ifndef CPU_JIT_GEMM_CONVOLUTION_HPP +#define CPU_JIT_GEMM_CONVOLUTION_HPP + +#include "c_types_map.hpp" +#include "memory_tracking.hpp" + +#include "gemm_convolution_utils.hpp" +#include "gemm/gemm.hpp" +#include "ref_eltwise.hpp" + +#include "cpu_convolution_pd.hpp" + +namespace mkldnn { +namespace impl { +namespace cpu { + +struct gemm_convolution_fwd_t: public cpu_primitive_t { + struct pd_t: public cpu_convolution_fwd_pd_t { + pd_t(engine_t *engine, + const convolution_desc_t *adesc, const primitive_attr_t *attr, + const typename pd_t::base_class *hint_fwd_pd) + : cpu_convolution_fwd_pd_t(engine, adesc, attr, hint_fwd_pd) + , jcp_() {} + + DECLARE_COMMON_PD_T(GEMM_IMPL_STR, gemm_convolution_fwd_t); + + status_t init() { + bool ok = true + && is_fwd() + && set_default_alg_kind(alg_kind::convolution_direct) + && expect_data_types(data_type::f32, data_type::f32, + data_type::f32, data_type::f32, data_type::f32) + && !has_zero_dim_memory() + && set_default_formats_common(dat_tag(), wei_tag(), dat_tag()) + && post_ops_ok() + && memory_desc_matches_tag(*src_md(), dat_tag()) + && memory_desc_matches_tag(*dst_md(), dat_tag()) + && memory_desc_matches_tag(*weights_md(), wei_tag()); + if (!ok) return status::unimplemented; + + auto scratchpad = scratchpad_registry().registrar(); + return jit_gemm_convolution_utils::init_conf(jcp_, scratchpad, + *desc(), src_md(), weights_md(0), dst_md(), + mkldnn_get_max_threads()); + } + + jit_gemm_conv_conf_t jcp_; + + protected: + format_tag_t dat_tag() const { + using namespace format_tag; + return utils::pick(ndims() - 3, ncw, nchw, ncdhw); + } + + format_tag_t wei_tag() const { + using namespace format_tag; + return with_groups() + ? utils::pick(ndims() - 3, goiw, goihw, goidhw) + : utils::pick(ndims() - 3, oiw, oihw, oidhw); + } + + bool post_ops_ok() const { + auto const &po = attr()->post_ops_; + auto is_eltwise = [&](int idx) + { return po.entry_[idx].is_eltwise(); }; + auto is_sum = [&](int idx) { return po.entry_[idx].is_sum(); }; + + switch (po.len_) { + case 0: return true; // no post_ops + case 1: return is_eltwise(0) || is_sum(0); // sum OR eltwise + case 2: return is_sum(0) && is_eltwise(1); // sum -> eltwise + default: return false; + } + return false; + } + }; + + gemm_convolution_fwd_t(const pd_t *apd) + : cpu_primitive_t(apd, true) + , eltwise_(nullptr) + { + const auto &post_ops = pd()->attr()->post_ops_; + const data_t one = 1.0, zero = 0.0; + beta_ = post_ops.find(primitive_kind::sum) >= 0 ? one : zero; + + const int entry_idx = post_ops.find(primitive_kind::eltwise); + if (entry_idx != -1) eltwise_ = new ref_eltwise_scalar_fwd_t( + post_ops.entry_[entry_idx].eltwise); + } + + ~gemm_convolution_fwd_t() { delete eltwise_; } + + typedef typename prec_traits<data_type::f32>::type data_t; + + virtual status_t execute(const exec_ctx_t &ctx) const override { + execute_forward(ctx); + return status::success; + } + +private: + void execute_forward(const exec_ctx_t &ctx) const; + const pd_t *pd() const { return (const pd_t *)primitive_t::pd(); } + + data_t beta_; + + ref_eltwise_scalar_fwd_t* eltwise_; +}; + +struct gemm_convolution_bwd_data_t: public cpu_primitive_t { + struct pd_t: public cpu_convolution_bwd_data_pd_t { + pd_t(engine_t *engine, + const convolution_desc_t *adesc, const primitive_attr_t *attr, + const convolution_fwd_pd_t *hint_fwd_pd) + : cpu_convolution_bwd_data_pd_t(engine, adesc, attr, hint_fwd_pd) + , jcp_() {} + + DECLARE_COMMON_PD_T(GEMM_IMPL_STR, gemm_convolution_bwd_data_t); + + status_t init() { + bool ok = true + && desc()->prop_kind == prop_kind::backward_data + && set_default_alg_kind(alg_kind::convolution_direct) + && expect_data_types(data_type::f32, data_type::f32, + data_type::undef, data_type::f32, data_type::f32) + && !has_zero_dim_memory() + && set_default_formats_common(dat_tag(), wei_tag(), dat_tag()) + && memory_desc_matches_tag(*diff_src_md(), dat_tag()) + && memory_desc_matches_tag(*diff_dst_md(), dat_tag()) + && memory_desc_matches_tag(*weights_md(), wei_tag()); + if (!ok) return status::unimplemented; + + auto scratchpad = scratchpad_registry().registrar(); + return jit_gemm_convolution_utils::init_conf(jcp_, scratchpad, + *desc(), diff_src_md(), weights_md(0), diff_dst_md(), + mkldnn_get_max_threads()); + } + + jit_gemm_conv_conf_t jcp_; + + protected: + format_tag_t dat_tag() const { + using namespace format_tag; + return utils::pick(ndims() - 3, ncw, nchw, ncdhw); + } + + format_tag_t wei_tag() const { + using namespace format_tag; + return with_groups() + ? utils::pick(ndims() - 3, goiw, goihw, goidhw) + : utils::pick(ndims() - 3, oiw, oihw, oidhw); + } + }; + + gemm_convolution_bwd_data_t(const pd_t *apd) + : cpu_primitive_t(apd, true) {} + + typedef typename prec_traits<data_type::f32>::type data_t; + + virtual status_t execute(const exec_ctx_t &ctx) const override { + execute_backward_data(ctx); + return status::success; + } + +private: + void execute_backward_data(const exec_ctx_t &ctx) const; + const pd_t *pd() const { return (const pd_t *)primitive_t::pd(); } +}; + +struct gemm_convolution_bwd_weights_t: public cpu_primitive_t { + struct pd_t: public cpu_convolution_bwd_weights_pd_t { + pd_t(engine_t *engine, + const convolution_desc_t *adesc, + const primitive_attr_t *attr, + const convolution_fwd_pd_t *hint_fwd_pd) + : cpu_convolution_bwd_weights_pd_t(engine, adesc, attr, hint_fwd_pd) + , jcp_() {} + + DECLARE_COMMON_PD_T(GEMM_IMPL_STR, gemm_convolution_bwd_weights_t); + + status_t init() { + bool ok = true + && desc()->prop_kind == prop_kind::backward_weights + && set_default_alg_kind(alg_kind::convolution_direct) + && expect_data_types(data_type::f32, data_type::f32, + data_type::f32, data_type::f32, data_type::f32) + && !has_zero_dim_memory() + && set_default_formats_common(dat_tag(), wei_tag(), dat_tag()) + && memory_desc_matches_tag(*src_md(), dat_tag()) + && memory_desc_matches_tag(*diff_dst_md(), dat_tag()) + && memory_desc_matches_tag(*diff_weights_md(), wei_tag()); + if (!ok) return status::unimplemented; + + auto scratchpad = scratchpad_registry().registrar(); + return jit_gemm_convolution_utils::init_conf(jcp_, scratchpad, + *desc(), src_md(), diff_weights_md(0), diff_dst_md(), + mkldnn_get_max_threads()); + } + + jit_gemm_conv_conf_t jcp_; + + protected: + format_tag_t dat_tag() const { + using namespace format_tag; + return utils::pick(ndims() - 3, ncw, nchw, ncdhw); + } + + format_tag_t wei_tag() const { + using namespace format_tag; + return with_groups() + ? utils::pick(ndims() - 3, goiw, goihw, goidhw) + : utils::pick(ndims() - 3, oiw, oihw, oidhw); + } + }; + + gemm_convolution_bwd_weights_t(const pd_t *apd) + : cpu_primitive_t(apd, true) {} + + typedef typename prec_traits<data_type::f32>::type data_t; + + virtual status_t execute(const exec_ctx_t &ctx) const override { + execute_backward_weights(ctx); + return status::success; + } + +private: + void execute_backward_weights(const exec_ctx_t &ctx) const; + const pd_t *pd() const { return (const pd_t *)primitive_t::pd(); } +}; + +} +} +} + +#endif |