/******************************************************************************* * 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 CONVOLUTION_PD_HPP #define CONVOLUTION_PD_HPP #include "mkldnn.h" #include "c_types_map.hpp" #include "primitive_desc.hpp" #include "utils.hpp" namespace mkldnn { namespace impl { status_t conv_desc_init(convolution_desc_t *conv_desc, prop_kind_t prop_kind, alg_kind_t alg_kind, const memory_desc_t *src_desc, const memory_desc_t *weights_desc, const memory_desc_t *bias_desc, const memory_desc_t *dst_desc, const dims_t strides, const dims_t dilates, const dims_t padding_l, const dims_t padding_r, padding_kind_t padding_kind); memory_desc_t *conv_prop_invariant_src_d(convolution_desc_t *desc); memory_desc_t *conv_prop_invariant_wei_d(convolution_desc_t *desc); memory_desc_t *conv_prop_invariant_bia_d(convolution_desc_t *desc); memory_desc_t *conv_prop_invariant_dst_d(convolution_desc_t *desc); const memory_desc_t *conv_prop_invariant_src_d(const convolution_desc_t *desc); const memory_desc_t *conv_prop_invariant_wei_d(const convolution_desc_t *desc); const memory_desc_t *conv_prop_invariant_bia_d(const convolution_desc_t *desc); const memory_desc_t *conv_prop_invariant_dst_d(const convolution_desc_t *desc); struct convolution_fwd_pd_t; struct convolution_pd_t: public primitive_desc_t { static constexpr auto base_pkind = primitive_kind::convolution; convolution_pd_t(engine_t *engine, const convolution_desc_t *adesc, const primitive_attr_t *attr, const convolution_fwd_pd_t *hint_fwd_pd) : primitive_desc_t(engine, attr, base_pkind) , desc_(*adesc) , hint_fwd_pd_(hint_fwd_pd) {} const convolution_desc_t *desc() const { return &desc_; } virtual const op_desc_t *op_desc() const override { return reinterpret_cast(this->desc()); } virtual void init_info() override { impl::init_info(this, this->info_); } virtual status_t query(query_t what, int idx, void *result) const override { switch (what) { case pkind_traits::query_d: *(const convolution_desc_t**)result = desc(); break; default: return primitive_desc_t::query(what, idx, result); } return status::success; } /* common conv aux functions */ dim_t MB() const { return _src_md()->dims[0]; } dim_t IC() const { return _src_md()->dims[1]; } dim_t OC() const { return _dst_md()->dims[1]; } dim_t G() const { return with_groups() ? _wei_md()->dims[0] : 1; } dim_t ID() const { return ndims() >= 5 ? _src_md()->dims[ndims() - 3] : 1; } dim_t IH() const { return ndims() >= 4 ? _src_md()->dims[ndims() - 2] : 1; } dim_t IW() const { return _src_md()->dims[ndims() - 1]; } dim_t OD() const { return ndims() >= 5 ? _dst_md()->dims[ndims() - 3] : 1; } dim_t OH() const { return ndims() >= 4 ? _dst_md()->dims[ndims() - 2] : 1; } dim_t OW() const { return _dst_md()->dims[ndims() - 1]; } dim_t KD() const { return ndims() >= 5 ? _wei_md()->dims[ndims() + with_groups() - 3] : 1; } dim_t KH() const { return ndims() >= 4 ? _wei_md()->dims[ndims() + with_groups() - 2] : 1; } dim_t KW() const { return _wei_md()->dims[ndims() + with_groups() - 1]; } dim_t KSD() const { return ndims() >= 5 ? desc_.strides[ndims() - 5] : 1; } dim_t KSH() const { return ndims() >= 4 ? desc_.strides[ndims() - 4] : 1; } dim_t KSW() const { return desc_.strides[ndims() - 3]; } dim_t KDD() const { return ndims() >= 5 ? desc_.dilates[ndims() - 5] : 0; } dim_t KDH() const { return ndims() >= 4 ? desc_.dilates[ndims() - 4] : 1; } dim_t KDW() const { return desc_.dilates[ndims() - 3]; } dim_t padFront() const { return ndims() >= 5 ? desc_.padding[0][ndims() - 5] : 0; } dim_t padBack() const { return ndims() >= 5 ? desc_.padding[1][ndims() - 5] : 0; } dim_t padT() const { return ndims() >= 4 ? desc_.padding[0][ndims() - 4] : 0; } dim_t padB() const { return ndims() >= 4 ? desc_.padding[1][ndims() - 4] : 0; } dim_t padL() const { return desc_.padding[0][ndims() - 3]; } dim_t padR() const { return desc_.padding[1][ndims() - 3]; } int ndims() const { return _src_md()->ndims; } bool with_bias() const { return !memory_desc_wrapper(*_bia_md()).is_zero(); } bool with_groups() const { return _wei_md()->ndims == ndims() + 1; } bool is_fwd() const { return utils::one_of(desc_.prop_kind, prop_kind::forward_training, prop_kind::forward_inference); } bool has_zero_dim_memory() const { const auto s_d = memory_desc_wrapper(*_src_md()); const auto d_d = memory_desc_wrapper(*_dst_md()); return s_d.has_zero_dim() || d_d.has_zero_dim(); } protected: convolution_desc_t desc_; const convolution_fwd_pd_t *hint_fwd_pd_; bool set_default_formats_common_template( memory_desc_t &src_md, format_tag_t src_tag, memory_desc_t &wei_md, format_tag_t wei_tag, memory_desc_t &dst_md, format_tag_t dst_tag, memory_desc_t &bia_md) { using namespace format_tag; # define IS_OK(f) \ do { if ((f) != status::success) return false; } while(0) if (src_md.format_kind == format_kind::any && !utils::one_of(src_tag, any, undef)) IS_OK(memory_desc_init_by_tag(src_md, src_tag)); if (dst_md.format_kind == format_kind::any && !utils::one_of(dst_tag, any, undef)) IS_OK(memory_desc_init_by_tag(dst_md, dst_tag)); if (wei_md.format_kind == format_kind::any && !utils::one_of(wei_tag, any, undef)) IS_OK(memory_desc_init_by_tag(wei_md, wei_tag)); if (with_bias() && bia_md.format_kind == format_kind::any) IS_OK(memory_desc_init_by_tag(bia_md, x)); # undef IS_OK return true; } bool set_default_alg_kind(alg_kind_t alg_kind) { assert(utils::one_of(alg_kind, alg_kind::convolution_direct, alg_kind::convolution_winograd)); if (desc_.alg_kind == alg_kind::convolution_auto) desc_.alg_kind = alg_kind; return desc_.alg_kind == alg_kind; } bool expect_data_types(data_type_t src_dt, data_type_t wei_dt, data_type_t bia_dt, data_type_t dst_dt, data_type_t acc_dt) const { bool ok = true && (src_dt == data_type::undef || _src_md()->data_type == src_dt) && (wei_dt == data_type::undef || _wei_md()->data_type == wei_dt) && (dst_dt == data_type::undef || _dst_md()->data_type == dst_dt) && (acc_dt == data_type::undef || desc_.accum_data_type == acc_dt); if (with_bias() && bia_dt != data_type::undef) ok = ok && _bia_md()->data_type == bia_dt; return ok; } private: const memory_desc_t *_src_md() const { return conv_prop_invariant_src_d(&desc_); } const memory_desc_t *_wei_md() const { return conv_prop_invariant_wei_d(&desc_); } const memory_desc_t *_bia_md() const { return conv_prop_invariant_bia_d(&desc_); } const memory_desc_t *_dst_md() const { return conv_prop_invariant_dst_d(&desc_); } }; struct convolution_fwd_pd_t: public convolution_pd_t { typedef convolution_fwd_pd_t base_class; typedef convolution_fwd_pd_t hint_class; convolution_fwd_pd_t(engine_t *engine, const convolution_desc_t *adesc, const primitive_attr_t *attr, const convolution_fwd_pd_t *hint_fwd_pd) : convolution_pd_t(engine, adesc, attr, hint_fwd_pd) , src_md_(desc_.src_desc) , weights_md_(desc_.weights_desc) , bias_md_(desc_.bias_desc) , dst_md_(desc_.dst_desc) {} virtual arg_usage_t arg_usage(primitive_arg_index_t arg) const override { if (utils::one_of(arg, MKLDNN_ARG_SRC, MKLDNN_ARG_WEIGHTS)) return arg_usage_t::input; if (arg == MKLDNN_ARG_BIAS && with_bias()) return arg_usage_t::input; if (arg == MKLDNN_ARG_DST) return arg_usage_t::output; return primitive_desc_t::arg_usage(arg); } virtual const memory_desc_t *src_md(int index = 0) const override { return index == 0 ? &src_md_ : nullptr; } virtual const memory_desc_t *dst_md(int index = 0) const override { return index == 0 ? &dst_md_ : nullptr; } virtual const memory_desc_t *weights_md(int index = 0) const override { if (index == 0) return &weights_md_; if (index == 1 && with_bias()) return &bias_md_; return nullptr; } virtual int n_inputs() const override { return 2 + with_bias(); } virtual int n_outputs() const override { return 1; } protected: memory_desc_t src_md_; memory_desc_t weights_md_; memory_desc_t bias_md_; memory_desc_t dst_md_; bool set_default_formats_common(format_tag_t src_tag, format_tag_t wei_tag, format_tag_t dst_tag) { return set_default_formats_common_template(src_md_, src_tag, weights_md_, wei_tag, dst_md_, dst_tag, bias_md_); } }; struct convolution_bwd_data_pd_t: public convolution_pd_t { typedef convolution_bwd_data_pd_t base_class; typedef convolution_fwd_pd_t hint_class; convolution_bwd_data_pd_t(engine_t *engine, const convolution_desc_t *adesc, const primitive_attr_t *attr, const convolution_fwd_pd_t *hint_fwd_pd) : convolution_pd_t(engine, adesc, attr, hint_fwd_pd) , diff_src_md_(desc_.diff_src_desc) , weights_md_(desc_.weights_desc) , bias_md_(desc_.bias_desc) , diff_dst_md_(desc_.diff_dst_desc) {} virtual arg_usage_t arg_usage(primitive_arg_index_t arg) const override { if (utils::one_of(arg, MKLDNN_ARG_WEIGHTS, MKLDNN_ARG_DIFF_DST)) return arg_usage_t::input; if (arg == MKLDNN_ARG_DIFF_SRC) return arg_usage_t::output; return primitive_desc_t::arg_usage(arg); } virtual const memory_desc_t *diff_src_md(int index = 0) const override { return index == 0 ? &diff_src_md_ : nullptr; } virtual const memory_desc_t *diff_dst_md(int index = 0) const override { return index == 0 ? &diff_dst_md_ : nullptr; } virtual const memory_desc_t *weights_md(int index = 0) const override { if (index == 0) return &weights_md_; if (index == 1 && with_bias()) return &bias_md_; return nullptr; } virtual int n_inputs() const override { return 2 + with_bias(); } virtual int n_outputs() const override { return 1; } virtual bool support_bias() const { return false; } protected: memory_desc_t diff_src_md_; memory_desc_t weights_md_; memory_desc_t bias_md_; memory_desc_t diff_dst_md_; bool set_default_formats_common(format_tag_t diff_src_tag, format_tag_t wei_tag, format_tag_t diff_dst_tag) { return set_default_formats_common_template(diff_src_md_, diff_src_tag, weights_md_, wei_tag, diff_dst_md_, diff_dst_tag, bias_md_); } }; struct convolution_bwd_weights_pd_t: public convolution_pd_t { typedef convolution_bwd_weights_pd_t base_class; typedef convolution_fwd_pd_t hint_class; convolution_bwd_weights_pd_t(engine_t *engine, const convolution_desc_t *adesc, const primitive_attr_t *attr, const convolution_fwd_pd_t *hint_fwd_pd) : convolution_pd_t(engine, adesc, attr, hint_fwd_pd) , src_md_(desc_.src_desc) , diff_weights_md_(desc_.diff_weights_desc) , diff_bias_md_(desc_.diff_bias_desc) , diff_dst_md_(desc_.diff_dst_desc) {} virtual arg_usage_t arg_usage(primitive_arg_index_t arg) const override { if (utils::one_of(arg, MKLDNN_ARG_SRC, MKLDNN_ARG_DIFF_DST)) return arg_usage_t::input; if (arg == MKLDNN_ARG_DIFF_WEIGHTS) return arg_usage_t::output; if (arg == MKLDNN_ARG_DIFF_BIAS && with_bias()) return arg_usage_t::output; return primitive_desc_t::arg_usage(arg); } virtual const memory_desc_t *src_md(int index = 0) const override { return index == 0 ? &src_md_ : nullptr; } virtual const memory_desc_t *diff_dst_md(int index = 0) const override { return index == 0 ? &diff_dst_md_ : nullptr; } virtual const memory_desc_t *diff_weights_md(int index = 0) const override { if (index == 0) return &diff_weights_md_; if (index == 1 && with_bias()) return &diff_bias_md_; return nullptr; } virtual int n_inputs() const override { return 2; } virtual int n_outputs() const override { return 1 + with_bias(); } protected: memory_desc_t src_md_; memory_desc_t diff_weights_md_; memory_desc_t diff_bias_md_; memory_desc_t diff_dst_md_; bool set_default_formats_common(format_tag_t src_tag, format_tag_t diff_wei_tag, format_tag_t diff_dst_tag) { return set_default_formats_common_template(src_md_, src_tag, diff_weights_md_, diff_wei_tag, diff_dst_md_, diff_dst_tag, diff_bias_md_); } }; } } #endif // vim: et ts=4 sw=4 cindent cino^=l0,\:0,N-s