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Diffstat (limited to 'thirdparty/oidn/mkl-dnn/src/cpu/jit_avx2_convolution.hpp')
| -rw-r--r-- | thirdparty/oidn/mkl-dnn/src/cpu/jit_avx2_convolution.hpp | 302 |
1 files changed, 302 insertions, 0 deletions
diff --git a/thirdparty/oidn/mkl-dnn/src/cpu/jit_avx2_convolution.hpp b/thirdparty/oidn/mkl-dnn/src/cpu/jit_avx2_convolution.hpp new file mode 100644 index 0000000000..bb65bce79c --- /dev/null +++ b/thirdparty/oidn/mkl-dnn/src/cpu/jit_avx2_convolution.hpp @@ -0,0 +1,302 @@ +/******************************************************************************* +* 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_AVX2_CONVOLUTION_HPP +#define CPU_JIT_AVX2_CONVOLUTION_HPP + +#include "c_types_map.hpp" +#include "memory_tracking.hpp" +#include "mkldnn_thread.hpp" +#include "utils.hpp" + +#include "cpu_convolution_pd.hpp" +#include "cpu_reducer.hpp" + +#include "jit_avx2_conv_kernel_f32.hpp" + +namespace mkldnn { +namespace impl { +namespace cpu { + +struct jit_avx2_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( + JIT_IMPL_NAME_HELPER("jit:", avx2, ""), + jit_avx2_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(); + if (!ok) return status::unimplemented; + + status_t status = jit_avx2_conv_fwd_kernel_f32::init_conf(jcp_, + *desc(), src_md(), weights_md(), dst_md(), *attr()); + if (status != status::success) return status; + + auto scratchpad = scratchpad_registry().registrar(); + jit_avx2_conv_fwd_kernel_f32::init_scratchpad(scratchpad, jcp_); + + return status::success; + } + + jit_conv_conf_t jcp_; + + protected: + bool set_default_formats() { + using namespace format_tag; + + const bool flat = IC() < 8; + auto src_tag = flat + ? utils::pick(ndims() - 3, ncw, nchw, ncdhw) + : utils::pick(ndims() - 3, nCw8c, nChw8c, nCdhw8c); + auto dst_tag = + utils::pick(ndims() - 3, nCw8c, nChw8c, nCdhw8c); + auto wei_tag = with_groups() + ? utils::pick(2 * ndims() - 6 + flat, gOIw8i8o, gOwi8o, + gOIhw8i8o, gOhwi8o, gOIdhw8i8o, gOdhwi8o) + : utils::pick(2 * ndims() - 6 + flat, OIw8i8o, Owi8o, + OIhw8i8o, Ohwi8o, OIdhw8i8o, Odhwi8o); + + return set_default_formats_common(src_tag, wei_tag, dst_tag); + } + }; + + jit_avx2_convolution_fwd_t(const pd_t *apd): cpu_primitive_t(apd) + { kernel_ = new jit_avx2_conv_fwd_kernel_f32(pd()->jcp_, *pd()->attr()); } + ~jit_avx2_convolution_fwd_t() { delete kernel_; } + + 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(); } + + jit_avx2_conv_fwd_kernel_f32 *kernel_; +}; + +struct jit_avx2_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( + JIT_IMPL_NAME_HELPER("jit:", avx2, ""), + jit_avx2_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(); + if (!ok) return status::unimplemented; + + status_t status = jit_avx2_conv_bwd_data_kernel_f32::init_conf( + jcp_, *desc(), *diff_src_md(), *weights_md(), + *diff_dst_md()); + if (status != status::success) return status; + + auto scratchpad = scratchpad_registry().registrar(); + jit_avx2_conv_bwd_data_kernel_f32::init_scratchpad(scratchpad, + jcp_); + + return status::success; + } + + jit_conv_conf_t jcp_; + + protected: + bool set_default_formats() { + using namespace format_tag; + + auto dat_tag = utils::pick(ndims() - 3, nCw8c, nChw8c, nCdhw8c); + auto wei_tag = with_groups() + ? utils::pick(ndims() - 3, gOIw8o8i, gOIhw8o8i, gOIdhw8o8i) + : utils::pick(ndims() - 3, OIw8o8i, OIhw8o8i, OIdhw8o8i); + + return set_default_formats_common(dat_tag, wei_tag, dat_tag); + } + }; + + jit_avx2_convolution_bwd_data_t(const pd_t *apd): cpu_primitive_t(apd) + { kernel_ = new jit_avx2_conv_bwd_data_kernel_f32(pd()->jcp_); } + ~jit_avx2_convolution_bwd_data_t() { delete kernel_; } + + 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(); } + + jit_avx2_conv_bwd_data_kernel_f32 *kernel_; +}; + +struct jit_avx2_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( + JIT_IMPL_NAME_HELPER("jit:", avx2, ""), + jit_avx2_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(); + if (!ok) return status::unimplemented; + + status_t status = jit_avx2_conv_bwd_weights_kernel_f32::init_conf( + jcp_, *desc(), *src_md(), *diff_weights_md(), + *diff_dst_md()); + if (status != status::success) return status; + + init_balancers(); + + auto scratchpad = scratchpad_registry().registrar(); + jit_avx2_conv_bwd_weights_kernel_f32::init_scratchpad(scratchpad, + jcp_); + + auto reducer_bia_scratchpad = memory_tracking::registrar_t( + scratchpad, memory_tracking::names::prefix_reducer_bia); + reducer_bia_conf_.init_scratchpad(reducer_bia_scratchpad); + + auto reducer_wei_scratchpad = memory_tracking::registrar_t( + scratchpad, memory_tracking::names::prefix_reducer_wei); + reducer_wei_conf_.init_scratchpad(reducer_wei_scratchpad); + + return status::success; + } + + jit_conv_conf_t jcp_; + cpu_reducer_t<data_type::f32>::conf_t reducer_bia_conf_; + cpu_reducer_t<data_type::f32>::conf_t reducer_wei_conf_; + + protected: + bool set_default_formats() { + using namespace format_tag; + const bool flat = IC() == 3; + + auto src_tag = flat + ? utils::pick(ndims() - 3, ncw, nchw, ncdhw) + : utils::pick(ndims() - 3, nCw8c, nChw8c, nCdhw8c); + auto dst_tag = + utils::pick(ndims() - 3, nCw8c, nChw8c, nCdhw8c); + auto wei_tag = with_groups() + ? utils::pick(2 * ndims() - 6 + flat, gOIw8i8o, gOwi8o, + gOIhw8i8o, gOhwi8o, gOIdhw8i8o, gOdhwi8o) + : utils::pick(2 * ndims() - 6 + flat, OIw8i8o, Owi8o, + OIhw8i8o, Ohwi8o, OIdhw8i8o, Odhwi8o); + + return set_default_formats_common(src_tag, wei_tag, dst_tag); + } + + private: + void init_balancers() { + const int max_threads = mkldnn_get_max_threads(); + const size_t max_buffer_size = 1<<21; /* just a heuristic */ + + if(with_bias()) { + reducer_bia_conf_.init(reduce_balancer_t(max_threads, + jcp_.oc_block, jcp_.ngroups * jcp_.nb_oc, jcp_.mb, + max_buffer_size)); + } + + reducer_wei_conf_.init(reduce_balancer_t(max_threads, + jcp_.kd * jcp_.kh * jcp_.kw + * jcp_.ic_block * jcp_.oc_block, + jcp_.ngroups * jcp_.nb_ic * jcp_.nb_oc, + jcp_.mb * jcp_.od, max_buffer_size)); + } + }; + + jit_avx2_convolution_bwd_weights_t(const pd_t *apd) + : cpu_primitive_t(apd) + , kernel_(nullptr) + , reducer_weights_(nullptr) + , reducer_bias_(nullptr) + { + kernel_ = new jit_avx2_conv_bwd_weights_kernel_f32(pd()->jcp_); + reducer_bias_ = + new cpu_reducer_t<data_type::f32>(pd()->reducer_bia_conf_); + reducer_weights_ = + new cpu_reducer_t<data_type::f32>(pd()->reducer_wei_conf_); + } + + ~jit_avx2_convolution_bwd_weights_t() { + delete kernel_; + delete reducer_weights_; + delete reducer_bias_; + } + + 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(); } + + jit_avx2_conv_bwd_weights_kernel_f32 *kernel_; + cpu_reducer_t<data_type::f32> *reducer_weights_, *reducer_bias_; +}; + +} +} +} + +#endif + +// vim: et ts=4 sw=4 cindent cino^=l0,\:0,N-s |