/******************************************************************************* * 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 BATCH_NORMALIZATION_PD_HPP #define BATCH_NORMALIZATION_PD_HPP #include "mkldnn.h" #include "c_types_map.hpp" #include "primitive_desc.hpp" #include "utils.hpp" namespace mkldnn { namespace impl { struct batch_normalization_fwd_pd_t; struct batch_normalization_pd_t: public primitive_desc_t { static constexpr auto base_pkind = primitive_kind::batch_normalization; batch_normalization_pd_t(engine_t *engine, const batch_normalization_desc_t *adesc, const primitive_attr_t *attr, const batch_normalization_fwd_pd_t *hint_fwd_pd) : primitive_desc_t(engine, attr, base_pkind) , desc_(*adesc) , hint_fwd_pd_(hint_fwd_pd) , data_md_(desc_.data_desc) , stat_md_(desc_.mean_desc) , scaleshift_md_(desc_.data_scaleshift_desc) , ws_md_() {} const batch_normalization_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 query::batch_normalization_d: *(const batch_normalization_desc_t**)result = desc(); break; default: return primitive_desc_t::query(what, idx, result); } return status::success; } /* common batch_normalization aux functions */ dim_t MB() const { return data_desc().dims[0]; } dim_t C() const { return data_desc().dims[1]; } dim_t D() const { return ndims() >= 5 ? data_desc().dims[ndims() - 3] : 1; } dim_t H() const { return ndims() >= 4 ? data_desc().dims[ndims() - 2] : 1; } dim_t W() const { return ndims() >= 3 ? data_desc().dims[ndims() - 1] : 1; } int ndims() const { return desc_.data_desc.ndims; } bool stats_is_src() const { return desc_.flags & mkldnn_use_global_stats; } bool use_scaleshift() const { return desc_.flags & mkldnn_use_scaleshift; } bool use_global_stats() const { return desc_.flags & mkldnn_use_global_stats; } bool fuse_bn_relu() const { return desc_.flags & mkldnn_fuse_bn_relu; } bool with_relu_post_op() const { const auto &p = this->attr()->post_ops_; return p.len_ == 1 && p.entry_[0].is_relu(true, true); } bool is_fwd() const { return utils::one_of(desc_.prop_kind, prop_kind::forward_training, prop_kind::forward_inference); } bool is_bwd() const { return !this->is_fwd(); } bool is_training() const { return desc_.prop_kind == prop_kind::forward_training; } bool has_zero_dim_memory() const { return memory_desc_wrapper(desc_.data_desc).has_zero_dim(); } protected: batch_normalization_desc_t desc_; const batch_normalization_fwd_pd_t *hint_fwd_pd_; memory_desc_t data_md_; memory_desc_t stat_md_; memory_desc_t scaleshift_md_; memory_desc_t ws_md_; void init_default_ws(size_t bits_per_element) { const auto data_mdw = memory_desc_wrapper(data_md_); const dim_t data_nelems = data_mdw.nelems(true); const dim_t bits_per_byte = 8; const dims_t ws_sz = { (dim_t)utils::div_up( data_nelems * bits_per_element, bits_per_byte) }; mkldnn_memory_desc_init_by_tag(&ws_md_, 1, ws_sz, impl::data_type::u8, format_tag::x); } private: const memory_desc_t &data_desc() const { return desc_.data_desc; } }; struct batch_normalization_fwd_pd_t: public batch_normalization_pd_t { typedef batch_normalization_fwd_pd_t base_class; typedef batch_normalization_fwd_pd_t hint_class; batch_normalization_fwd_pd_t(engine_t *engine, const batch_normalization_desc_t *adesc, const primitive_attr_t *attr, const batch_normalization_fwd_pd_t *hint_fwd_pd) : batch_normalization_pd_t(engine, adesc, attr, hint_fwd_pd) {} virtual arg_usage_t arg_usage(primitive_arg_index_t arg) const override { if (arg == MKLDNN_ARG_SRC) return arg_usage_t::input; if (arg == MKLDNN_ARG_DST) return arg_usage_t::output; if (utils::one_of(arg, MKLDNN_ARG_MEAN, MKLDNN_ARG_VARIANCE)) { if (stats_is_src()) return arg_usage_t::input; if (!stats_is_src() && is_training()) return arg_usage_t::output; return arg_usage_t::unused; } if (arg == MKLDNN_ARG_SCALE_SHIFT && use_scaleshift()) return arg_usage_t::input; if (arg == MKLDNN_ARG_WORKSPACE && is_training() && fuse_bn_relu()) return arg_usage_t::output; return primitive_desc_t::arg_usage(arg); } virtual const memory_desc_t *src_md(int index = 0) const override { if (index == 0) return &data_md_; if (stats_is_src() && (index == 1 || index == 2)) return &stat_md_; return nullptr; } virtual const memory_desc_t *dst_md(int index = 0) const override { if (index == 0) return &data_md_; if (!stats_is_src() && is_training() && (index == 1 || index == 2)) return &stat_md_; return nullptr; } virtual const memory_desc_t *weights_md(int index = 0) const override { return index == 0 ? &scaleshift_md_ : nullptr; } virtual const memory_desc_t *workspace_md(int index = 0) const override { return index == 0 && is_training() && fuse_bn_relu() ? &ws_md_ : nullptr; } const memory_desc_t *stat_md() const { return stats_is_src() ? src_md(1) : dst_md(1); } virtual int n_inputs() const override { return 1 + 2 * stats_is_src() + use_scaleshift(); } virtual int n_outputs() const override { return 1 + (fuse_bn_relu() + 2 * (!stats_is_src())) * is_training(); } }; struct batch_normalization_bwd_pd_t: public batch_normalization_pd_t { typedef batch_normalization_bwd_pd_t base_class; typedef batch_normalization_fwd_pd_t hint_class; batch_normalization_bwd_pd_t(engine_t *engine, const batch_normalization_desc_t *adesc, const primitive_attr_t *attr, const batch_normalization_fwd_pd_t *hint_fwd_pd) : batch_normalization_pd_t(engine, adesc, attr, hint_fwd_pd) , diff_data_md_(desc_.diff_data_desc) , diff_scaleshift_md_(desc_.diff_data_scaleshift_desc) {} virtual arg_usage_t arg_usage(primitive_arg_index_t arg) const override { if (utils::one_of(arg, MKLDNN_ARG_SRC, MKLDNN_ARG_MEAN, MKLDNN_ARG_VARIANCE, MKLDNN_ARG_DIFF_DST)) return arg_usage_t::input; if (arg == MKLDNN_ARG_SCALE_SHIFT && use_scaleshift()) return arg_usage_t::input; if (arg == MKLDNN_ARG_WORKSPACE && fuse_bn_relu()) return arg_usage_t::input; if (arg == MKLDNN_ARG_DIFF_SRC) return arg_usage_t::output; if (arg == MKLDNN_ARG_DIFF_SCALE_SHIFT && use_scaleshift()) 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 ? &data_md_ : index <= 2 ? &stat_md_ : nullptr; } virtual const memory_desc_t *diff_dst_md(int index = 0) const override { return index == 0 ? &diff_data_md_ : nullptr; } virtual const memory_desc_t *diff_src_md(int index = 0) const override { return index == 0 ? &diff_data_md_ : nullptr; } virtual const memory_desc_t *weights_md(int index = 0) const override { return index == 0 ? &scaleshift_md_ : nullptr; } virtual const memory_desc_t *diff_weights_md(int index = 0) const override { return index == 0 ? &diff_scaleshift_md_ : nullptr; } virtual const memory_desc_t *workspace_md(int index = 0) const override { return index == 0 && fuse_bn_relu() ? &ws_md_ : nullptr; } const memory_desc_t *stat_md() const { return src_md(1); } virtual int n_inputs() const override { return 4 + use_scaleshift() + fuse_bn_relu(); } virtual int n_outputs() const override { return 1 + (desc_.prop_kind == prop_kind::backward); } protected: memory_desc_t diff_data_md_; memory_desc_t diff_scaleshift_md_; }; } } #endif // vim: et ts=4 sw=4 cindent cino^=l0,\:0,N-s