Merge pull request #14376 from baojun-nervana/intel/ngraph_fusedop
Adding fused operator for ngraphpanyx0718-patch-1
Tao Luo
6 years ago
committed by
GitHub
commit
c7b3bfcdf1
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/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License. */
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#ifdef PADDLE_WITH_NGRAPH
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#include <algorithm>
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#include <functional>
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#include "paddle/fluid/framework/ngraph_bridge.h"
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#include "ngraph/ngraph.hpp"
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namespace paddle {
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namespace framework {
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std::map<std::string,
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std::function<void(const std::shared_ptr<OperatorBase>&,
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std::shared_ptr<std::unordered_map<
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std::string, std::shared_ptr<ngraph::Node>>>)>>
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NgraphBridge::NG_NODE_MAP = {};
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void NgraphBridge::build_graph(const std::shared_ptr<OperatorBase>& op) {
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auto& op_type = op->Type();
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NG_NODE_MAP[op_type](op, ngb_node_map);
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}
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} // namespace framework
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} // namespace paddle
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#endif
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/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License. */
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#pragma once
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#ifdef PADDLE_WITH_NGRAPH
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#include <algorithm>
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#include <map>
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#include <string>
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#include <unordered_map>
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#include <vector>
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#include "paddle/fluid/framework/operator.h"
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#include "paddle/fluid/platform/enforce.h"
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#include "ngraph/ngraph.hpp"
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namespace paddle {
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namespace framework {
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class NgraphBridge {
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public:
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static std::map<
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std::string,
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std::function<void(const std::shared_ptr<OperatorBase>&,
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std::shared_ptr<std::unordered_map<
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std::string, std::shared_ptr<ngraph::Node>>>)>>
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NG_NODE_MAP;
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explicit NgraphBridge(
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std::shared_ptr<
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std::unordered_map<std::string, std::shared_ptr<ngraph::Node>>>
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var_node_map)
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: ngb_node_map(var_node_map) {}
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void build_graph(const std::shared_ptr<OperatorBase>& op);
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private:
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std::shared_ptr<
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std::unordered_map<std::string, std::shared_ptr<ngraph::Node>>>
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ngb_node_map;
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};
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} // namespace framework
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} // namespace paddle
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#endif
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@ -0,0 +1,220 @@
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/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License. */
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#ifdef PADDLE_WITH_NGRAPH
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#include <glog/logging.h>
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#include <algorithm>
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#include <map>
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#include "paddle/fluid/framework/feed_fetch_type.h"
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#include "paddle/fluid/framework/ngraph_operator.h"
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#include "paddle/fluid/framework/shape_inference.h"
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#include "paddle/fluid/framework/var_desc.h"
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#include "paddle/fluid/framework/var_type.h"
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namespace paddle {
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namespace framework {
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static std::map<proto::VarType::Type, ngraph::element::Type> pd2ng_type_map = {
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{proto::VarType::FP32, ngraph::element::f32},
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{proto::VarType::FP64, ngraph::element::f64},
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{proto::VarType::INT32, ngraph::element::i32},
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{proto::VarType::INT64, ngraph::element::i64},
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{proto::VarType::BOOL, ngraph::element::boolean},
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};
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typedef enum { /* nGraph support state on ops */
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FULL_TRAIN, /* Support full ops for train */
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PARTIAL_TRAIN, /* Support partial ops for train */
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FULL_TEST, /* Support full list of ops for test */
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PARTIAL_TEST /* Support partial list of ops for test */
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} op_state;
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class NgraphOperator {
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public:
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explicit NgraphOperator(const Scope& scope, const platform::Place& place,
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const std::vector<std::shared_ptr<OperatorBase>>& ops,
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const std::unordered_map<
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std::string, ngraph::element::Type>& var_type_map,
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const std::unordered_set<std::string>& persist,
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const std::unordered_set<std::string>& fetches,
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const std::unordered_set<std::string>& post_op_inputs,
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op_state ng_op_state)
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: scope_(scope),
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place_(place),
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fused_ops_(ops),
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var_type_map_(var_type_map),
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persistables_(persist),
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fetches_(fetches),
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post_op_inputs_(post_op_inputs),
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ng_op_state_(ng_op_state) {}
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void Run(const Scope& scope, const platform::Place& place) const;
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private:
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static std::unordered_map<std::string, std::shared_ptr<ngraph::Function>>
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func_cache;
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const Scope& scope_;
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const platform::Place& place_;
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std::vector<std::shared_ptr<OperatorBase>> fused_ops_;
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std::unordered_map<std::string, ngraph::element::Type> var_type_map_;
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std::unordered_set<std::string> persistables_;
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std::unordered_set<std::string> fetches_;
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std::unordered_set<std::string> post_op_inputs_;
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op_state ng_op_state_;
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};
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std::vector<std::vector<std::vector<std::unique_ptr<OperatorBase>>::iterator>>
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FusedOperator::FusedOpIntervals(
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std::vector<std::unique_ptr<paddle::framework::OperatorBase>>* ops) {
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std::vector<std::vector<std::vector<std::unique_ptr<OperatorBase>>::iterator>>
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intervals;
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if (ops->empty()) {
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return intervals;
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}
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size_t size = ops->size();
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size_t left = 0;
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while (left < size && ops.at(left)->Type() != kFeedOpType) {
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++left;
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}
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if (left == size) {
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return intervals;
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}
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while (left < size && ops->at(left)->Type() == kFeedOpType) {
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++left;
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}
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size_t right = left;
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while (right < size && ops->at(right)->Type() != kFetchOpType) {
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++right;
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}
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if (right == size) {
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return intervals;
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}
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if (left >= right) return intervals;
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// (left, right - 1) represents indices between feed and fetch
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size_t pivot = left;
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while (pivot < right) {
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auto op_type = ops->at(pivot)->Type();
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if (paddle::framework::NgraphBridge::NG_NODE_MAP.find(op_type) ==
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paddle::framework::NgraphBridge::NG_NODE_MAP.end()) {
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++pivot;
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} else {
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size_t start = pivot, end = start;
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while (pivot < right &&
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(paddle::framework::NgraphBridge::NG_NODE_MAP.find(
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ops.at(pivot)->Type()) !=
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paddle::framework::NgraphBridge::NG_NODE_MAP.end())) {
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++pivot;
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++end;
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}
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std::vector<std::vector<std::unique_ptr<OperatorBase>>::iterator>
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interval = {ops->begin() + start, ops->begin() + end};
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intervals.push_back(interval);
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}
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} // end while
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return intervals;
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}
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FusedOperator::FusedOperator(
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const ProgramDesc& prog, size_t block_id,
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std::vector<std::unique_ptr<OperatorBase>>::iterator start,
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std::vector<std::unique_ptr<OperatorBase>>::iterator end,
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const std::string& type, const VariableNameMap& inputs,
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const VariableNameMap& outputs, const AttributeMap& attrs)
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: OperatorBase(type, inputs, outputs, attrs), pdesc(prog), block(block_id) {
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for (std::vector<std::unique_ptr<OperatorBase>>::iterator it = start;
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it != end; ++it) {
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fused_ops_.push_back(std::move(*it));
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}
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for (std::vector<std::unique_ptr<OperatorBase>>::iterator it = end;
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(*it)->Type() != kFetchOpType; ++it) {
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for (auto& var_name_item : (*it)->Inputs()) {
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for (auto& var_name : var_name_item.second) {
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post_op_inputs_.insert(var_name);
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}
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}
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}
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if ((*(start - 1))->Type() == kFeedOpType && (*end)->Type() == kFetchOpType) {
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is_complete = true;
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}
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Process();
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}
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void FusedOperator::Process() {
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auto& bdesc = pdesc_.Block(block_);
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for (auto& var : bdesc.AllVars()) {
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if (!(var->GetType() == proto::VarType::SELECTED_ROWS ||
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var->GetType() == proto::VarType::LOD_TENSOR ||
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var->GetType() == proto::VarType::LOD_TENSOR_ARRAY)) {
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continue;
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}
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auto var_name = var->Name();
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if (var->Name() == framework::kEmptyVarName) {
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continue;
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}
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if (var_name != "fetch" && var_name != "feed") {
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auto pd_type = var->GetDataType();
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if (pd2ng_type_map.find(pd_type) == pd2ng_type_map.end()) {
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PADDLE_THROW("Data type of var %s not found in pd2ng_type_map",
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var_name);
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}
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var_type_map_[var_name] = pd2ng_type_map[pd_type];
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}
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if (var->Persistable()) {
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persistables_.insert(var->Name());
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}
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}
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for (auto* op : bdesc.AllOps()) {
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if (op->Type() == kFetchOpType) {
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std::string fetch_target_name = op->Input("X")[0];
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fetches_.insert(fetch_target_name);
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}
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}
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}
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void FusedOperator::RunImpl(const Scope& scope,
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const platform::Place& place) const {
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op_state ng_op_state = PARTIAL_TEST;
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auto& bdesc = pdesc_.Block(block_);
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for (auto* op : bdesc.AllOps()) {
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if (op->Type().find("_grad") != std::string::npos) {
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ng_op_state = PARTIAL_TRAIN;
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break;
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}
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}
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if (is_full) {
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ng_op_state = ng_op_state == PARTIAL_TEST ? FULL_TEST : FULL_TRAIN;
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}
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NgraphOperator ngraph_op(scope, place, fused_ops_, var_type_map_,
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persistables_, fetches_, post_op_inputs_,
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ng_op_state);
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ngraph_op.Run(scope, place);
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}
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} // namespace framework
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} // namespace paddle
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#endif
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@ -0,0 +1,72 @@
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/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License. */
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#pragma once
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#ifdef PADDLE_WITH_NGRAPH
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#include <algorithm>
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#include <atomic>
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#include <string>
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#include <unordered_map>
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#include <vector>
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#include "paddle/fluid/framework/attribute.h"
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#include "paddle/fluid/framework/framework.pb.h"
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#include "paddle/fluid/framework/lod_tensor.h"
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#include "paddle/fluid/framework/ngraph_bridge.h"
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#include "paddle/fluid/framework/op_info.h"
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#include "paddle/fluid/framework/op_kernel_type.h"
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#include "paddle/fluid/framework/operator.h"
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#include "paddle/fluid/framework/program_desc.h"
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#include "paddle/fluid/framework/scope.h"
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#include "paddle/fluid/framework/tensor.h"
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#include "paddle/fluid/platform/variant.h"
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#include "ngraph/ngraph.hpp"
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namespace paddle {
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namespace framework {
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class FusedOperator : public OperatorBase {
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public:
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static std::vector<
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std::vector<std::vector<std::unique_ptr<OperatorBase>>::iterator>>
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FusedOpIntervals(
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std::vector<std::unique_ptr<paddle::framework::OperatorBase>>* ops);
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explicit FusedOperator(
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const ProgramDesc& prog, size_t block_id,
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std::vector<std::unique_ptr<OperatorBase>>::iterator start,
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std::vector<std::unique_ptr<OperatorBase>>::iterator end,
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const std::string& type = "fused_op", const VariableNameMap& inputs = {},
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const VariableNameMap& outputs = {}, const AttributeMap& attrs = {});
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void RunImpl(const Scope& scope, const platform::Place& place) const final;
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private:
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const ProgramDesc pdesc_;
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size_t block_;
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std::vector<std::shared_ptr<OperatorBase>> fused_ops_;
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std::unordered_map<std::string, ngraph::element::Type> var_type_map_;
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std::unordered_set<std::string> persistables_;
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std::unordered_set<std::string> fetches_;
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std::unordered_set<std::string> post_op_inputs_;
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bool is_full_ = false;
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void Process();
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};
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} // namespace framework
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} // namespace paddle
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#endif
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