/******************************************************************************* * Copyright 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 RNN_PD_HPP #define RNN_PD_HPP #include "mkldnn.h" #include "c_types_map.hpp" #include "memory_pd.hpp" #include "primitive_desc.hpp" namespace mkldnn { namespace impl { // struct rnn_fwd_pd_t; struct rnn_pd_t : public primitive_desc_t { static constexpr auto base_pkind = primitive_kind::rnn; rnn_pd_t(mkldnn::impl::engine_t *engine, const rnn_desc_t *adesc, const primitive_attr_t *attr, const rnn_pd_t *hint_pd) : primitive_desc_t(engine, attr, primitive_kind::rnn) , desc_(*adesc) , hint_pd_(hint_pd) {} virtual ~rnn_pd_t() {} const rnn_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 { init_info_rnn(this, this->info_); } virtual status_t query(query_t what, int idx, void *result) const override { switch (what) { case query::rnn_d: *(const rnn_desc_t **)result = desc(); break; default: return primitive_desc_t::query(what, idx, result); } return status::success; } inline bool is_training() const { return utils::one_of(desc_.prop_kind, prop_kind::forward_training, prop_kind::backward); } inline size_t ws_states_size() { int wic = nstl::max(SLC(), nstl::max(SIC(), DIC())); return (size_t)(L() + 1) * D() * (T() + 1) * S() * MB() * wic; } inline size_t ws_diff_states_size() { int wic = nstl::max(SLC(), nstl::max(SIC(), DIC())); return (size_t)(L() + 1) * D() * (T() + 1) * (S() + 1) * MB() * wic; } inline size_t ws_gates_size() { int n_layer = L(); int n_direction = D(); int n_iter = T(); int n_gates = G(); int batch = MB(); int s_size = DIC(); return (size_t)n_layer * n_direction * n_iter * batch * n_gates * s_size; } inline size_t ws_cell_comp_size() { int n_gates = G(); int batch = MB(); int s_size = DIC(); return (size_t)is_lbr() * n_gates * batch * s_size; } inline size_t ws_grid_comp_size() { int n_layer = L(); int n_direction = D(); int n_iter = T(); int batch = MB(); int s_size = DIC(); return (size_t)is_lbr() * is_training() * n_layer * n_direction * n_iter * batch * s_size; } inline int ws_per_cell() { int batch = MB(); int s_size = DIC(); return is_lbr() * is_training() * batch * s_size; } inline void set_offsets(size_t &ws_gates_offset, size_t &ws_states_offset, size_t &ws_diff_states_offset, size_t &ws_grid_comp_offset, size_t &ws_cell_comp_offset) { const size_t page_size = 4096; // 2097152; ws_gates_offset = 0; // assumes the workspace base pointer is page aligned ws_states_offset = utils::rnd_up(ws_gates_size(), page_size); ws_diff_states_offset = utils::rnd_up(ws_states_offset + ws_states_size(), page_size); ws_grid_comp_offset = utils::rnd_up(ws_diff_states_offset + ws_diff_states_size(), page_size); ws_cell_comp_offset = utils::rnd_up(ws_grid_comp_offset + ws_grid_comp_size(), page_size); } inline size_t get_ws_size() { size_t ws_gates_offset, ws_states_offset, ws_diff_states_offset, ws_grid_comp_offset, ws_cell_comp_offset; set_offsets( ws_gates_offset, ws_states_offset, ws_diff_states_offset, ws_grid_comp_offset, ws_cell_comp_offset); return ws_grid_comp_offset + ws_grid_comp_size(); } inline size_t get_scratchpad_size() { size_t ws_gates_offset, ws_states_offset, ws_diff_states_offset, ws_grid_comp_offset, ws_cell_comp_offset; set_offsets( ws_gates_offset, ws_states_offset, ws_diff_states_offset, ws_grid_comp_offset, ws_cell_comp_offset); if (desc_.prop_kind == prop_kind::forward_inference) return ws_cell_comp_offset + ws_cell_comp_size(); else return ws_cell_comp_size(); } int T() const { return desc_.src_layer_desc.dims[0]; } int MB() const { return desc_.src_layer_desc.dims[1]; } int L() const { return desc_.weights_layer_desc.dims[0]; } int D() const { return desc_.weights_layer_desc.dims[1]; } int SIC() const { return desc_.weights_iter_desc.dims[2]; } int SLC() const { return desc_.weights_layer_desc.dims[2]; } int G() const { return desc_.weights_layer_desc.dims[3]; } int DIC() const { return desc_.weights_layer_desc.dims[4]; } int DLC() const { return desc_.dst_layer_desc.dims[2]; } int S() const { return mkldnn_rnn_cell_get_states_count(&desc_.cell_desc); } bool with_bias() const { return !memory_desc_wrapper(desc_.bias_desc).is_zero(); } bool with_src_iter() const { return !(memory_desc_wrapper(desc_.src_iter_desc).is_zero()); } bool with_dst_iter() const { return !memory_desc_wrapper(desc_.dst_iter_desc).is_zero(); } mkldnn::impl::alg_kind_t cell_kind() const { return desc_.cell_desc.cell_kind; } mkldnn::impl::alg_kind_t activation_kind() const { return desc_.cell_desc.activation_kind; } bool is_lbr() const { return cell_kind() == mkldnn_gru_linear_before_reset; } mkldnn_rnn_direction_t direction() const { return desc_.direction; } protected: rnn_desc_t desc_; const rnn_pd_t *hint_pd_; }; struct rnn_fwd_pd_t : public rnn_pd_t { typedef rnn_fwd_pd_t base_class; typedef rnn_fwd_pd_t hint_class; using rnn_pd_t::rnn_pd_t; virtual ~rnn_fwd_pd_t() {} virtual const memory_pd_t *input_pd(int index = 0) const override { switch (index) { case 0: return src_pd(0); case 1: return src_pd(1); case 2: return weights_pd(0); case 3: return weights_pd(1); case 4: return weights_pd(2); default: return nullptr; } } virtual const memory_pd_t *output_pd(int index = 0) const override { switch (index) { case 0: return dst_pd(0); case 1: return dst_pd(1); case 2: return workspace_pd(); default: return nullptr; } } virtual int n_inputs() const override { return 3 + with_bias() + with_src_iter(); } virtual int n_outputs() const override { return 1 + with_dst_iter() + is_training(); } int ws_idx() const { return 1 + with_dst_iter(); } }; struct rnn_bwd_pd_t : public rnn_pd_t { typedef rnn_bwd_pd_t base_class; typedef rnn_bwd_pd_t hint_class; using rnn_pd_t::rnn_pd_t; virtual ~rnn_bwd_pd_t() {} virtual const memory_pd_t *input_pd(int index = 0) const override { switch (index) { case 0: return src_pd(0); case 1: return src_pd(1); case 2: return weights_pd(0); case 3: return weights_pd(1); case 4: return weights_pd(2); case 5: return dst_pd(0); case 6: return dst_pd(1); case 7: return diff_dst_pd(0); case 8: return diff_dst_pd(1); case 9: return workspace_pd(); default: return nullptr; } } virtual const memory_pd_t *output_pd(int index = 0) const override { switch (index) { case 0: return diff_src_pd(0); case 1: return diff_src_pd(1); case 2: return diff_weights_pd(0); case 3: return diff_weights_pd(1); case 4: return diff_weights_pd(2); default: return nullptr; } } virtual int n_inputs() const override { return 6 + with_src_iter() + with_bias() + 2 * with_dst_iter(); } virtual int n_outputs() const override { return 3 + with_src_iter() + with_bias(); } int ws_idx() const { return 5 + with_src_iter() + with_bias() + 2 * with_dst_iter(); } }; } } #endif