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authorJuan Linietsky <reduzio@gmail.com>2020-05-01 09:34:23 -0300
committerJuan Linietsky <reduzio@gmail.com>2020-05-10 15:59:09 -0300
commit1bea8e1eacc68bcedbd3f207395bccf11011dae2 (patch)
treeb75303a69491978c1e13360a3e6f355c5234dfe0 /thirdparty/oidn/mkl-dnn/src/common/rnn_pd.hpp
parent6a0473bcc23c096ef9ee929632a209761c2668f6 (diff)
New lightmapper
-Added LocalVector (needed it) -Added stb_rect_pack (It's pretty cool, we could probably use it for other stuff too) -Fixes and changes all around the place -Added library for 128 bits fixed point (required for Delaunay3D)
Diffstat (limited to 'thirdparty/oidn/mkl-dnn/src/common/rnn_pd.hpp')
-rw-r--r--thirdparty/oidn/mkl-dnn/src/common/rnn_pd.hpp280
1 files changed, 280 insertions, 0 deletions
diff --git a/thirdparty/oidn/mkl-dnn/src/common/rnn_pd.hpp b/thirdparty/oidn/mkl-dnn/src/common/rnn_pd.hpp
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+++ b/thirdparty/oidn/mkl-dnn/src/common/rnn_pd.hpp
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+/*******************************************************************************
+* 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 "primitive_desc.hpp"
+#include "type_helpers.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(engine_t *engine,
+ const rnn_desc_t *adesc,
+ const primitive_attr_t *attr,
+ const rnn_fwd_pd_t *hint_fwd_pd)
+ : primitive_desc_t(engine, attr, base_pkind)
+ , desc_(*adesc)
+ , hint_fwd_pd_(hint_fwd_pd)
+ , src_layer_md_(desc_.src_layer_desc)
+ , src_iter_md_(desc_.src_iter_desc)
+ , weights_layer_md_(desc_.weights_layer_desc)
+ , weights_iter_md_(desc_.weights_iter_desc)
+ , bias_md_(desc_.bias_desc)
+ , dst_layer_md_(desc_.dst_layer_desc)
+ , dst_iter_md_(desc_.dst_iter_desc)
+ , ws_md_()
+ {}
+
+ const rnn_desc_t *desc() const { return &desc_; }
+ virtual const op_desc_t *op_desc() const override
+ { return reinterpret_cast<const op_desc_t *>(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::rnn_d: *(const rnn_desc_t **)result = desc(); break;
+ default: return primitive_desc_t::query(what, idx, result);
+ }
+ return status::success;
+ }
+
+ virtual const memory_desc_t *src_md(int index = 0) const override {
+ if (index == 0) return &src_layer_md_;
+ if (index == 1 && with_src_iter()) return &src_iter_md_;
+ return nullptr;
+ }
+ virtual const memory_desc_t *weights_md(int index = 0) const override {
+ if (index == 0) return &weights_layer_md_;
+ if (index == 1) return &weights_iter_md_;
+ if (index == 2 && with_bias()) return &bias_md_;
+ return nullptr;
+ }
+ virtual const memory_desc_t *dst_md(int index = 0) const override {
+ if (index == 0) return &dst_layer_md_;
+ if (index == 1 && with_dst_iter()) return &dst_iter_md_;
+ return nullptr;
+ }
+ virtual const memory_desc_t *workspace_md(int index = 0) const override
+ { return index == 0 && !types::is_zero_md(&ws_md_) ? &ws_md_ : nullptr; }
+
+ /* common pooling aux functions */
+
+ bool is_training() const {
+ return utils::one_of(desc_.prop_kind, prop_kind::forward_training,
+ prop_kind::backward);
+ }
+
+ bool is_fwd() const {
+ return utils::one_of(desc_.prop_kind, prop_kind::forward_training,
+ prop_kind::forward_inference);
+ }
+
+ dim_t T() const { return desc_.src_layer_desc.dims[0]; }
+ dim_t MB() const { return desc_.src_layer_desc.dims[1]; }
+
+ dim_t L() const { return desc_.weights_layer_desc.dims[0]; }
+ dim_t D() const { return desc_.weights_layer_desc.dims[1]; }
+
+ dim_t SIC() const { return desc_.weights_iter_desc.dims[2]; }
+
+ dim_t SLC() const { return desc_.weights_layer_desc.dims[2]; }
+ dim_t G() const { return desc_.weights_layer_desc.dims[3]; }
+ dim_t DIC() const { return desc_.weights_layer_desc.dims[4]; }
+
+ dim_t DLC() const { return desc_.dst_layer_desc.dims[2]; }
+
+ 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_fwd_pd_t *hint_fwd_pd_;
+
+ memory_desc_t src_layer_md_;
+ memory_desc_t src_iter_md_;
+ memory_desc_t weights_layer_md_;
+ memory_desc_t weights_iter_md_;
+ memory_desc_t bias_md_;
+ memory_desc_t dst_layer_md_;
+ memory_desc_t dst_iter_md_;
+
+ memory_desc_t ws_md_;
+};
+
+struct rnn_fwd_pd_t: public rnn_pd_t {
+ typedef rnn_fwd_pd_t base_class;
+ typedef rnn_fwd_pd_t hint_class;
+
+ rnn_fwd_pd_t(engine_t *engine,
+ const rnn_desc_t *adesc,
+ const primitive_attr_t *attr,
+ const rnn_fwd_pd_t *hint_fwd_pd)
+ : rnn_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_LAYER)
+ return arg_usage_t::input;
+
+ if (arg == MKLDNN_ARG_SRC_ITER && with_src_iter())
+ return arg_usage_t::input;
+
+ if (utils::one_of(arg, MKLDNN_ARG_WEIGHTS_LAYER,
+ MKLDNN_ARG_WEIGHTS_ITER))
+ return arg_usage_t::input;
+
+ if (arg == MKLDNN_ARG_BIAS && with_bias())
+ return arg_usage_t::input;
+
+ if (arg == MKLDNN_ARG_DST_LAYER)
+ return arg_usage_t::output;
+
+ if (arg == MKLDNN_ARG_DST_ITER && with_dst_iter())
+ return arg_usage_t::output;
+
+ if (arg == MKLDNN_ARG_WORKSPACE && is_training())
+ return arg_usage_t::output;
+
+ return primitive_desc_t::arg_usage(arg);
+ }
+
+ 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(); }
+};
+
+struct rnn_bwd_pd_t : public rnn_pd_t {
+ typedef rnn_bwd_pd_t base_class;
+ typedef rnn_fwd_pd_t hint_class;
+
+ rnn_bwd_pd_t(engine_t *engine,
+ const rnn_desc_t *adesc,
+ const primitive_attr_t *attr,
+ const rnn_fwd_pd_t *hint_fwd_pd)
+ : rnn_pd_t(engine, adesc, attr, hint_fwd_pd)
+ , diff_src_layer_md_(desc_.diff_src_layer_desc)
+ , diff_src_iter_md_(desc_.diff_src_iter_desc)
+ , diff_weights_layer_md_(desc_.diff_weights_layer_desc)
+ , diff_weights_iter_md_(desc_.diff_weights_iter_desc)
+ , diff_bias_md_(desc_.diff_bias_desc)
+ , diff_dst_layer_md_(desc_.diff_dst_layer_desc)
+ , diff_dst_iter_md_(desc_.diff_dst_iter_desc)
+ {}
+
+ virtual arg_usage_t arg_usage(primitive_arg_index_t arg) const override {
+ if (utils::one_of(arg, MKLDNN_ARG_SRC_LAYER, MKLDNN_ARG_DST_LAYER,
+ MKLDNN_ARG_DIFF_DST_LAYER))
+ return arg_usage_t::input;
+
+ if (with_src_iter()) {
+ if (arg == MKLDNN_ARG_SRC_ITER)
+ return arg_usage_t::input;
+
+ if (arg == MKLDNN_ARG_DIFF_SRC_ITER)
+ return arg_usage_t::output;
+ }
+
+ if (utils::one_of(arg, MKLDNN_ARG_WEIGHTS_LAYER,
+ MKLDNN_ARG_WEIGHTS_ITER))
+ return arg_usage_t::input;
+
+ if (with_bias()) {
+ if (arg == MKLDNN_ARG_BIAS)
+ return arg_usage_t::input;
+
+ if (arg == MKLDNN_ARG_DIFF_BIAS)
+ return arg_usage_t::output;
+ }
+
+ if (utils::one_of(arg, MKLDNN_ARG_DST_ITER, MKLDNN_ARG_DIFF_DST_ITER)
+ && with_dst_iter())
+ return arg_usage_t::input;
+
+ if (arg == MKLDNN_ARG_WORKSPACE)
+ return arg_usage_t::input;
+
+ if (utils::one_of(arg, MKLDNN_ARG_DIFF_SRC_LAYER,
+ MKLDNN_ARG_DIFF_WEIGHTS_LAYER,
+ MKLDNN_ARG_DIFF_WEIGHTS_ITER))
+ 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 {
+ if (index == 0) return &diff_src_layer_md_;
+ if (index == 1 && with_src_iter()) return &diff_src_iter_md_;
+ return nullptr;
+ }
+ virtual const memory_desc_t *diff_weights_md(
+ int index = 0) const override {
+ if (index == 0) return &diff_weights_layer_md_;
+ if (index == 1) return &diff_weights_iter_md_;
+ if (index == 2 && with_bias()) return &diff_bias_md_;
+ return nullptr;
+ }
+ virtual const memory_desc_t *diff_dst_md(int index = 0) const override {
+ if (index == 0) return &diff_dst_layer_md_;
+ if (index == 1 && with_dst_iter()) return &diff_dst_iter_md_;
+ 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(); }
+
+protected:
+ memory_desc_t diff_src_layer_md_;
+ memory_desc_t diff_src_iter_md_;
+ memory_desc_t diff_weights_layer_md_;
+ memory_desc_t diff_weights_iter_md_;
+ memory_desc_t diff_bias_md_;
+ memory_desc_t diff_dst_layer_md_;
+ memory_desc_t diff_dst_iter_md_;
+};
+
+}
+}
+
+#endif