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提交 b1401fb7 编写于 作者: Y Yiqun Liu 提交者： 石晓伟
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Remove subgraph_detector from inference/analysis to the common framework/ir directory. (#22094) 

test=develop
上级 50bee83f
隐藏空白更改
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Showing with 660 addition and 673 deletion
paddle/fluid/framework/ir/CMakeLists.txt
浏览文件 @ b1401fb7
......@@ -39,6 +39,7 @@ cc_library(graph_helper SRCS graph_helper.cc DEPS graph)
cc_library(pass SRCS pass.cc DEPS graph node graph_helper)
cc_library(graph_traits SRCS graph_traits.cc DEPS graph)
cc_library(graph_pattern_detector SRCS graph_pattern_detector.cc DEPS graph graph_helper graph_traits)
cc_library(subgraph_detector SRCS subgraph_detector.cc DEPS graph_pattern_detector executor)
cc_library(fuse_pass_base SRCS fuse_pass_base.cc DEPS pass)
cc_library(placement_pass_base SRCS placement_pass_base.cc DEPS pass)
......@@ -99,7 +100,7 @@ endif()
if(WITH_NGRAPH)
cc_library(ngraph_subgraph_pass SRCS ngraph_subgraph_pass.cc DEPS ngraph_bridge
analysis_helper subgraph_detector graph_pattern_detector pass fuse_pass_base ${op_library_DEPS})
subgraph_detector fuse_pass_base ${op_library_DEPS})
set(pass_file ${PADDLE_BINARY_DIR}/paddle/fluid/inference/api/paddle_inference_pass.h)
file(APPEND ${pass_file} "USE_PASS(ngraph_subgraph_pass);\n")
set(INFER_IR_PASSES ${INFER_IR_PASSES} ngraph_subgraph_pass CACHE INTERNAL "")
......
paddle/fluid/framework/ir/ngraph_subgraph_pass.cc
浏览文件 @ b1401fb7
......@@ -20,8 +20,7 @@
#include "paddle/fluid/framework/ir/graph_helper.h"
#include "paddle/fluid/framework/ir/graph_pattern_detector.h"
#include "paddle/fluid/framework/ir/ngraph_subgraph_pass.h"
#include "paddle/fluid/inference/analysis/helper.h"
#include "paddle/fluid/inference/analysis/ir_passes/subgraph_detector.h"
#include "paddle/fluid/framework/ir/subgraph_detector.h"
#include "paddle/fluid/operators/ngraph/ngraph_bridge.h"
#include "paddle/fluid/platform/enforce.h"
#include "paddle/fluid/string/pretty_log.h"
......@@ -30,8 +29,6 @@ namespace paddle {
namespace framework {
namespace ir {
namespace ANAT = paddle::inference::analysis;
std::string GenerateEngineKey(const std::set<std::string> &engine_inputs,
const std::set<std::string> &engine_outputs,
const std::string &size) {
......@@ -59,19 +56,18 @@ void NgraphSubgraphPass::ApplyImpl(Graph *graph) const {
return !paddle::operators::NgraphBridge::isRegister(op_type);
};
ANAT::SubGraphFuser fuser(graph, teller, 0, "ngraph_engine");
SubGraphFuser fuser(graph, teller, 0, "ngraph_engine");
fuser();
for (auto *node : graph->Nodes()) {
if (node->IsOp() && !ANAT::Agent(node).subgraph()->empty()) {
if (node->IsOp() && !Agent(node).subgraph()->empty()) {
OpDesc *op_desc = node->Op();
op_desc->SetType("ngraph_engine");
CreateNgraphEngineOp(node, graph);
std::unordered_set<const Node *> nodes2remove(
ANAT::Agent(node).subgraph()->begin(),
ANAT::Agent(node).subgraph()->end());
Agent(node).subgraph()->begin(), Agent(node).subgraph()->end());
GraphSafeRemoveNodes(graph, nodes2remove);
}
......@@ -79,7 +75,7 @@ void NgraphSubgraphPass::ApplyImpl(Graph *graph) const {
std::unordered_set<const Node *> nodes2remove;
for (auto *node : graph->Nodes()) {
if (node->IsOp() && ANAT::Agent(node).deleted()) {
if (node->IsOp() && Agent(node).deleted()) {
nodes2remove.insert(node);
}
}
......@@ -116,7 +112,7 @@ void UpdateNgraphIO(Node *node, Graph *graph,
return;
}
auto &subgraph = *ANAT::Agent(node).subgraph();
auto &subgraph = *Agent(node).subgraph();
std::unordered_set<std::string> inputs;
std::unordered_set<std::string> outputs;
for (auto *node : subgraph) {
......@@ -138,7 +134,7 @@ void UpdateNgraphIO(Node *node, Graph *graph,
}
void NgraphSubgraphPass::CreateNgraphEngineOp(Node *node, Graph *graph) const {
auto &subgraph = *ANAT::Agent(node).subgraph();
auto &subgraph = *Agent(node).subgraph();
PADDLE_ENFORCE_NE(subgraph.empty(), true, "subgraph cannot be empty");
framework::proto::BlockDesc block_proto;
......
paddle/fluid/inference/analysis/ir_passes/subgraph_detector.cc → paddle/fluid/framework/ir/subgraph_detector.cc
浏览文件 @ b1401fb7
/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
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. */
#include "paddle/fluid/inference/analysis/ir_passes/subgraph_detector.h"
#include <string>
#include <unordered_map>
#include <unordered_set>
#include <utility>
#include "paddle/fluid/framework/ir/graph_helper.h"
#include "paddle/fluid/framework/ir/graph_pattern_detector.h"
#include "paddle/fluid/framework/ir/node.h"
DECLARE_bool(use_ngraph);
namespace paddle {
namespace inference {
namespace analysis {
using framework::ir::Node;
std::pair<std::vector<Node *>, std::vector<Node *>>
ExtractInputAndOutputOfSubGraph(std::vector<Node *> &graph) { // NOLINT
std::unordered_set<Node *> nodes(graph.begin(), graph.end());
std::unordered_set<Node *> inputs;
std::unordered_set<Node *> outputs;
// Input a Value, check whether its inlink is in the subgraph.
auto inlink_in_subgraph = [&](Node *n) {
for (auto *in : n->inputs) {
if (nodes.count(in)) return true;
}
return false;
};
for (auto &node : graph) {
for (auto *in : node->inputs) {
// The Value that is written by nodes inside a sub-graph shouldn't be the
// input of the sub-graph.
if (!nodes.count(in) && in->IsVar() && !inlink_in_subgraph(in)) {
inputs.insert(in);
}
}
for (auto *out : node->outputs) {
if (!nodes.count(out) && out->IsVar()) {
outputs.insert(out);
}
}
}
return std::make_pair(std::vector<Node *>(inputs.begin(), inputs.end()),
std::vector<Node *>(outputs.begin(), outputs.end()));
}
// Filter the Intermediate results of the subgraph node.
void FilterRedundantOutputOfSubGraph(Graph *graph) {
std::vector<Node *> op_nodes;
for (auto &node : TopologicalSort(*graph)) {
if (node.IsVar() || Agent(&node).deleted()) {
continue;
}
op_nodes.push_back(&node);
}
size_t op_num = op_nodes.size();
for (size_t i = 0; i < op_num; i++) {
if (op_nodes[i]->IsOp()) continue;
std::unordered_set<std::string> follow_up_input_names;
for (size_t j = i + 1; j < op_num; j++) {
for (auto *in : op_nodes[j]->inputs) {
follow_up_input_names.insert(in->Name());
}
}
std::vector<Node *> filtered_subgraph_outlinks;
for (auto *out : op_nodes[i]->outputs) {
if (follow_up_input_names.count(out->Name())) {
filtered_subgraph_outlinks.push_back(out);
} else {
Agent(out).set_deleted(true);
}
}
// The filtered_subgraph_outlinks may be empty.
op_nodes[i]->outputs = filtered_subgraph_outlinks;
}
}
std::vector<std::vector<Node *>> SubgraphDetector::operator()() {
MarkNodesInsideSubGraph();
return ExtractSubGraphs();
}
// Mark the output variables inside a subgraph with the func.
inline void MarkOutLinksInSubGraph(const Node *func) {
for (auto *var : func->outputs) {
Agent(var).set_marked(true);
}
}
void SubgraphDetector::MarkNodesInsideSubGraph() {
for (auto &node : framework::ir::GraphTraits::DFS(*graph_)) {
if (node_inside_subgraph_teller_(&node)) {
Agent(&node).set_marked(true);
if (node.IsOp()) {
// If a function is inside the sub-graph, mark all the output variables
// to be inside too, so that two marked functions will be inside a same
// sub-graph, lets take a example: A_function->var->B_function, if
// A_function is marked, var should also be marked, so that B_function
// will be in the same sub-graph with A_function if B_function is
// marked.
MarkOutLinksInSubGraph(&node);
}
}
}
}
// Use the Union Find(UF) algorithm to find fully connected sub-graphs, if node
// a's output is node b, that is a and b is in the same sub-graph. The UF
// algorithm will group them to the same cluster.
using node_map_t = std::unordered_map<int, Node *>;
// Find the ancestor id of a node.
int UnionFindGetAncestor(const node_map_t &node_map, size_t id) {
int tmp = id;
do {
tmp = Agent(node_map.at(tmp)).union_find_parent();
} while (Agent(node_map.at(tmp)).union_find_parent() != tmp);
return tmp;
}
// Make this two node share the same ancestor.
// TODO(Superjom) bad performance, make a balanced tree latter.
void UnionFindCombine(const node_map_t &node_map, size_t a, size_t b) {
int a_ancestor = UnionFindGetAncestor(node_map, a);
int b_ancestor = UnionFindGetAncestor(node_map, b);
Agent(node_map.at(b_ancestor)).set_union_find_parent(a_ancestor);
Agent(node_map.at(a)).set_union_find_parent(a_ancestor);
Agent(node_map.at(b)).set_union_find_parent(a_ancestor);
}
// This is a simple representation of a graph.
// The BriefNode hold the pointer of the Node.
// This is to avoid changing the original graph
// in the process of trt graph analysis.
struct BriefNode {
explicit BriefNode(Node *n) { node = n; }
Node *node;
std::vector<BriefNode *> inlinks;
std::vector<BriefNode *> outlinks;
};
// Union two adjacent BriefNode.
// Suppose we have two adjacent nodes src and dst.
// We will perform the following operations:
// 1. add all inputs(except src) of dst to src inlinks.
// 2. add all outputs of dst to src outlinks.
// 3. change all the dst's inputs and outputs
// corresponding inlinks and outlinks to src node.
// 4. delete all dst's inlinks and outlinks.
void UnionContractedNodes(const std::unordered_map<int, BriefNode *> &node_map,
int src_id, int dst_id) {
// merge the two adjacent nodes into one node.
BriefNode *src_node = node_map.at(src_id);
BriefNode *dst_node = node_map.at(dst_id);
std::unordered_set<BriefNode *> inputs(src_node->inlinks.begin(),
src_node->inlinks.end());
std::unordered_set<BriefNode *> outputs;
for (auto *n : src_node->outlinks) {
if (n != dst_node) outputs.insert(n);
}
// Add the inlinks and outlinks of dst node to src node.
std::vector<BriefNode *> dst_in_nodes = dst_node->inlinks;
for (BriefNode *node : dst_in_nodes) {
if (node != src_node) {
inputs.insert(node);
}
}
std::vector<BriefNode *> dst_out_nodes = dst_node->outlinks;
for (BriefNode *node : dst_out_nodes) {
outputs.insert(node);
}
// update the dst and src node's inlinks and outlinks.
#ifdef __clang__
src_node->inlinks = std::vector<BriefNode *>(inputs.begin(), inputs.end());
src_node->outlinks = std::vector<BriefNode *>(outputs.begin(), outputs.end());
dst_node->inlinks.clear();
dst_node->outlinks.clear();
#else
src_node->inlinks =
std::move(std::vector<BriefNode *>(inputs.begin(), inputs.end()));
src_node->outlinks =
std::move(std::vector<BriefNode *>(outputs.begin(), outputs.end()));
dst_node->inlinks.clear();
dst_node->outlinks.clear();
#endif
auto inlink_or_outlink_cleaner = [&](std::vector<BriefNode *> &nodes) {
for (auto *&n : nodes) {
if (n == src_node || n == dst_node) {
n = src_node;
}
}
};
// Change all the dst inputs and outputs corresponding inlink and
// outlink to the src node.
for (auto *node : src_node->inlinks) {
inlink_or_outlink_cleaner(node->outlinks);
}
for (auto *node : src_node->outlinks) {
inlink_or_outlink_cleaner(node->inlinks);
}
}
// FlexibleDFS
// If reverse is true, do reverse dfs.
// If enter func is not nullptr, calls enter(node) before visiting any children
// of node.
// If leave func not nullptr, calls leave(node) after visiting all parents of
// node.
void FlexibleDFS(const std::vector<BriefNode *> &source, bool reverse,
const std::function<bool(const BriefNode *)> &enter,
const std::function<bool(const BriefNode *)> &leave) {
typedef struct {
const BriefNode *node;
bool leave;
} FNode;
std::vector<FNode> stack;
for (auto &node : source) {
stack.push_back(FNode{node, false});
}
std::unordered_set<const BriefNode *> visited;
while (!stack.empty()) {
auto fnode = stack.back();
stack.pop_back();
if (fnode.leave) {
if (leave && !leave(fnode.node)) return;
}
if (visited.count(fnode.node)) continue;
visited.insert(fnode.node);
if (enter && !enter(fnode.node)) return;
if (leave) stack.push_back(FNode{fnode.node, true});
const std::vector<BriefNode *> iter_nodes =
reverse == true ? fnode.node->inlinks : fnode.node->outlinks;
for (const BriefNode *node : iter_nodes) {
if (!visited.count(node)) {
stack.push_back(FNode{node, false});
}
}
}
}
std::vector<std::vector<Node *>> SubgraphDetector::ExtractSubGraphs() {
// Run the Extract algorithm to find all subgraphs.
std::vector<Node *> marked_nodes;
// We use brief_node_map to represent the original graph in order to avoid
// changing the original graph.
std::unordered_map<int, BriefNode *> brief_node_map;
std::unordered_set<int32_t> valid_node_ids;
for (auto *node : graph_->Nodes()) {
valid_node_ids.insert(node->id());
}
for (auto &node : framework::ir::GraphTraits::TS(*graph_)) {
brief_node_map[node.id()] = new BriefNode(&node);
if (Agent(&node).marked()) {
marked_nodes.push_back(&node);
}
}
// extract sub-graphs in the marked node set, use Union Find algorithm.
node_map_t node_map; // id to ptr
for (auto *n : marked_nodes) {
// n's parent == n.id means it is the ancestor
Agent(n).set_union_find_parent(n->id());
node_map[n->id()] = n;
}
// create breif node map
for (auto &itr : brief_node_map) {
for (Node *node : itr.second->node->inputs) {
if (!valid_node_ids.count(node->id())) {
LOG(INFO) << "invalid node id " << node->id();
continue;
}
itr.second->inlinks.push_back(brief_node_map.at(node->id()));
}
for (Node *node : itr.second->node->outputs) {
if (!valid_node_ids.count(node->id())) {
LOG(INFO) << "invalid node id " << node->id();
continue;
}
itr.second->outlinks.push_back(brief_node_map.at(node->id()));
}
}
for (auto &itr : brief_node_map) {
BriefNode *brief_node = itr.second;
if (!Agent(brief_node->node).marked()) {
VLOG(4) << brief_node->node->id() << " node not a trt candidate.";
continue;
}
// Our algorithm must guarantee that:
// 1. The graph is always directed acyclic graph（DAG）.
// 2. If there is a path in the subgraph from X to Y (X and Y are both
// nodes in the subgraph), then all paths from X to Y are in the
// subgraph.
//
// In order to achieve the above guarantee.
// For adjacent nodes src -> dst.
// 1. Get all dst input nodes except src.
// 2. Reverse DFS from those input nodes
// 3. If there is a path from input nodes to src,
// then the src and dst nodes can not be fused into one node,
// otherwise it can be done.
while (true) {
std::unordered_set<BriefNode *> contract_nodes;
for (auto *out : brief_node->outlinks) {
// must be an trt candidate
if (!Agent(out->node).marked()) continue;
// get all dst input nodes except src.
std::vector<BriefNode *> source_nodes;
for (auto *n : out->inlinks) {
if (n != brief_node) {
source_nodes.push_back(n);
}
}
// Reverse DFS from the source_nodes.
bool have_excess_path = false;
FlexibleDFS(source_nodes, true, nullptr,
[&have_excess_path, brief_node](const BriefNode *n) {
if (n == brief_node) {
have_excess_path = true;
return false;
}
return true;
});
if (have_excess_path) continue;
contract_nodes.insert(out);
}
if (contract_nodes.empty()) break;
for (auto dst_node : contract_nodes) {
UnionFindCombine(node_map, brief_node->node->id(),
dst_node->node->id());
UnionContractedNodes(brief_node_map, brief_node->node->id(),
dst_node->node->id());
}
}
}
std::unordered_map<int /*ancestor*/, std::vector<Node *>> clusters;
for (auto *n : marked_nodes) {
if (n->IsOp()) {
clusters[UnionFindGetAncestor(node_map, Agent(n).union_find_parent())]
.push_back(n);
}
}
std::vector<std::vector<Node *>> result;
std::for_each(clusters.begin(), clusters.end(),
[&](const decltype(clusters)::value_type &it) {
result.push_back(it.second);
});
return result;
}
void SubGraphFuser::operator()() { ReplaceNodesWithSubGraphs(); }
void RemoveIntermediateOutputInSubgraph(const std::vector<Node *> &subgraph,
Graph *graph,
std::vector<Node *> *outputs) {
std::unordered_set<Node *> subgraph_set(subgraph.begin(), subgraph.end());
std::unordered_set<Node *> valid_output;
for (auto *output : *outputs) {
int num_used = 0;
for (auto *node : output->outputs) {
if (!subgraph_set.count(node)) ++num_used;
if (num_used > 0) valid_output.insert(output);
}
}
// In use for ngraph subgraph pass for parallel executor,
// this will remove all nodes, bypass this and let ngraph
// subgraph pass to process outputs
if (FLAGS_use_ngraph && valid_output.size() == 0) return;
outputs->assign(valid_output.begin(), valid_output.end());
}
void DetachDeletedNodes(framework::ir::Graph *graph) {
std::unordered_set<const Node *> nodes;
for (auto *node : graph->Nodes()) {
if (Agent(node).deleted()) {
node->inputs.clear();
node->outputs.clear();
}
}
}
void SubGraphFuser::ReplaceNodesWithSubGraphs() {
auto subgraphs = SubgraphDetector(graph_, node_inside_subgraph_teller_)();
for (auto &subgraph : subgraphs) {
if (subgraph.size() <= (size_t)min_subgraph_size_) continue;
std::unordered_set<Node *> subgraph_uniq(subgraph.begin(), subgraph.end());
// replace this sub-graph with the first node. Two steps: 1. Create a Block
// Node that contains this subgraph 2. Mark the nodes inside the sub-graph
// as deleted. 3. Replace the deleted node with the new Block Node.
framework::OpDesc empty_desc;
empty_desc.SetType(name_);
auto *block_node = graph_->CreateOpNode(&empty_desc);
Agent(block_node).set_subgraph({});
auto io = ExtractInputAndOutputOfSubGraph(subgraph);
block_node->inputs = std::move(io.first);
block_node->outputs = std::move(io.second);
RemoveIntermediateOutputInSubgraph(subgraph, graph_, &block_node->outputs);
for (auto *node : subgraph) {
// TODO(Superjomn) need a unified mechanism to treat deleted node in each
// pass.
Agent(node).set_deleted(true);
Agent(block_node).subgraph()->push_back(node);
}
// Change all the sub-graph's inputs and outputs corresponding inlink and
// outlink to this sub-graph node.
auto inlink_or_outlink_cleaner = [&](std::vector<Node *> &nodes) {
for (auto *&n : nodes) {
if (subgraph_uniq.count(n)) {
n = block_node;
}
}
std::unordered_set<Node *> uniq(nodes.begin(), nodes.end());
nodes.assign(uniq.begin(), uniq.end());
};
for (auto *i : block_node->inputs) {
inlink_or_outlink_cleaner(i->outputs);
}
for (auto *&o : block_node->outputs) {
inlink_or_outlink_cleaner(o->inputs);
}
}
// DetachDeletedNodes(graph_);
FilterRedundantOutputOfSubGraph(graph_);
}
inline bool CheckNodeIndegreeEquals(const Node &node, size_t n) {
return node.inputs.size() == n;
}
} // namespace analysis
} // namespace inference
} // namespace paddle
/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
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. */
#include "paddle/fluid/framework/ir/subgraph_detector.h"
#include <string>
#include <unordered_map>
#include <unordered_set>
#include <utility>
#include "paddle/fluid/framework/ir/graph_helper.h"
#include "paddle/fluid/framework/ir/graph_pattern_detector.h"
#include "paddle/fluid/framework/ir/node.h"
DECLARE_bool(use_ngraph);
namespace paddle {
namespace framework {
namespace ir {
std::pair<std::vector<Node *>, std::vector<Node *>>
ExtractInputAndOutputOfSubGraph(std::vector<Node *> &graph) { // NOLINT
std::unordered_set<Node *> nodes(graph.begin(), graph.end());
std::unordered_set<Node *> inputs;
std::unordered_set<Node *> outputs;
// Input a Value, check whether its inlink is in the subgraph.
auto inlink_in_subgraph = [&](Node *n) {
for (auto *in : n->inputs) {
if (nodes.count(in)) return true;
}
return false;
};
for (auto &node : graph) {
for (auto *in : node->inputs) {
// The Value that is written by nodes inside a sub-graph shouldn't be the
// input of the sub-graph.
if (!nodes.count(in) && in->IsVar() && !inlink_in_subgraph(in)) {
inputs.insert(in);
}
}
for (auto *out : node->outputs) {
if (!nodes.count(out) && out->IsVar()) {
outputs.insert(out);
}
}
}
return std::make_pair(std::vector<Node *>(inputs.begin(), inputs.end()),
std::vector<Node *>(outputs.begin(), outputs.end()));
}
// Filter the Intermediate results of the subgraph node.
void FilterRedundantOutputOfSubGraph(Graph *graph) {
std::vector<Node *> op_nodes;
for (auto &node : TopologicalSort(*graph)) {
if (node.IsVar() || Agent(&node).deleted()) {
continue;
}
op_nodes.push_back(&node);
}
size_t op_num = op_nodes.size();
for (size_t i = 0; i < op_num; i++) {
if (op_nodes[i]->IsOp()) continue;
std::unordered_set<std::string> follow_up_input_names;
for (size_t j = i + 1; j < op_num; j++) {
for (auto *in : op_nodes[j]->inputs) {
follow_up_input_names.insert(in->Name());
}
}
std::vector<Node *> filtered_subgraph_outlinks;
for (auto *out : op_nodes[i]->outputs) {
if (follow_up_input_names.count(out->Name())) {
filtered_subgraph_outlinks.push_back(out);
} else {
Agent(out).set_deleted(true);
}
}
// The filtered_subgraph_outlinks may be empty.
op_nodes[i]->outputs = filtered_subgraph_outlinks;
}
}
std::vector<std::vector<Node *>> SubgraphDetector::operator()() {
MarkNodesInsideSubGraph();
return ExtractSubGraphs();
}
// Mark the output variables inside a subgraph with the func.
inline void MarkOutLinksInSubGraph(const Node *func) {
for (auto *var : func->outputs) {
Agent(var).set_marked(true);
}
}
void SubgraphDetector::MarkNodesInsideSubGraph() {
for (auto &node : framework::ir::GraphTraits::DFS(*graph_)) {
if (node_inside_subgraph_teller_(&node)) {
Agent(&node).set_marked(true);
if (node.IsOp()) {
// If a function is inside the sub-graph, mark all the output variables
// to be inside too, so that two marked functions will be inside a same
// sub-graph, lets take a example: A_function->var->B_function, if
// A_function is marked, var should also be marked, so that B_function
// will be in the same sub-graph with A_function if B_function is
// marked.
MarkOutLinksInSubGraph(&node);
}
}
}
}
// Use the Union Find(UF) algorithm to find fully connected sub-graphs, if node
// a's output is node b, that is a and b is in the same sub-graph. The UF
// algorithm will group them to the same cluster.
using node_map_t = std::unordered_map<int, Node *>;
// Find the ancestor id of a node.
int UnionFindGetAncestor(const node_map_t &node_map, size_t id) {
int tmp = id;
do {
tmp = Agent(node_map.at(tmp)).union_find_parent();
} while (Agent(node_map.at(tmp)).union_find_parent() != tmp);
return tmp;
}
// Make this two node share the same ancestor.
// TODO(Superjom) bad performance, make a balanced tree latter.
void UnionFindCombine(const node_map_t &node_map, size_t a, size_t b) {
int a_ancestor = UnionFindGetAncestor(node_map, a);
int b_ancestor = UnionFindGetAncestor(node_map, b);
Agent(node_map.at(b_ancestor)).set_union_find_parent(a_ancestor);
Agent(node_map.at(a)).set_union_find_parent(a_ancestor);
Agent(node_map.at(b)).set_union_find_parent(a_ancestor);
}
// This is a simple representation of a graph.
// The BriefNode hold the pointer of the Node.
// This is to avoid changing the original graph
// in the process of trt graph analysis.
struct BriefNode {
explicit BriefNode(Node *n) { node = n; }
Node *node;
std::vector<BriefNode *> inlinks;
std::vector<BriefNode *> outlinks;
};
// Union two adjacent BriefNode.
// Suppose we have two adjacent nodes src and dst.
// We will perform the following operations:
// 1. add all inputs(except src) of dst to src inlinks.
// 2. add all outputs of dst to src outlinks.
// 3. change all the dst's inputs and outputs
// corresponding inlinks and outlinks to src node.
// 4. delete all dst's inlinks and outlinks.
void UnionContractedNodes(const std::unordered_map<int, BriefNode *> &node_map,
int src_id, int dst_id) {
// merge the two adjacent nodes into one node.
BriefNode *src_node = node_map.at(src_id);
BriefNode *dst_node = node_map.at(dst_id);
std::unordered_set<BriefNode *> inputs(src_node->inlinks.begin(),
src_node->inlinks.end());
std::unordered_set<BriefNode *> outputs;
for (auto *n : src_node->outlinks) {
if (n != dst_node) outputs.insert(n);
}
// Add the inlinks and outlinks of dst node to src node.
std::vector<BriefNode *> dst_in_nodes = dst_node->inlinks;
for (BriefNode *node : dst_in_nodes) {
if (node != src_node) {
inputs.insert(node);
}
}
std::vector<BriefNode *> dst_out_nodes = dst_node->outlinks;
for (BriefNode *node : dst_out_nodes) {
outputs.insert(node);
}
// update the dst and src node's inlinks and outlinks.
#ifdef __clang__
src_node->inlinks = std::vector<BriefNode *>(inputs.begin(), inputs.end());
src_node->outlinks = std::vector<BriefNode *>(outputs.begin(), outputs.end());
dst_node->inlinks.clear();
dst_node->outlinks.clear();
#else
src_node->inlinks =
std::move(std::vector<BriefNode *>(inputs.begin(), inputs.end()));
src_node->outlinks =
std::move(std::vector<BriefNode *>(outputs.begin(), outputs.end()));
dst_node->inlinks.clear();
dst_node->outlinks.clear();
#endif
auto inlink_or_outlink_cleaner = [&](std::vector<BriefNode *> &nodes) {
for (auto *&n : nodes) {
if (n == src_node || n == dst_node) {
n = src_node;
}
}
};
// Change all the dst inputs and outputs corresponding inlink and
// outlink to the src node.
for (auto *node : src_node->inlinks) {
inlink_or_outlink_cleaner(node->outlinks);
}
for (auto *node : src_node->outlinks) {
inlink_or_outlink_cleaner(node->inlinks);
}
}
// FlexibleDFS
// If reverse is true, do reverse dfs.
// If enter func is not nullptr, calls enter(node) before visiting any children
// of node.
// If leave func not nullptr, calls leave(node) after visiting all parents of
// node.
void FlexibleDFS(const std::vector<BriefNode *> &source, bool reverse,
const std::function<bool(const BriefNode *)> &enter,
const std::function<bool(const BriefNode *)> &leave) {
typedef struct {
const BriefNode *node;
bool leave;
} FNode;
std::vector<FNode> stack;
for (auto &node : source) {
stack.push_back(FNode{node, false});
}
std::unordered_set<const BriefNode *> visited;
while (!stack.empty()) {
auto fnode = stack.back();
stack.pop_back();
if (fnode.leave) {
if (leave && !leave(fnode.node)) return;
}
if (visited.count(fnode.node)) continue;
visited.insert(fnode.node);
if (enter && !enter(fnode.node)) return;
if (leave) stack.push_back(FNode{fnode.node, true});
const std::vector<BriefNode *> iter_nodes =
reverse == true ? fnode.node->inlinks : fnode.node->outlinks;
for (const BriefNode *node : iter_nodes) {
if (!visited.count(node)) {
stack.push_back(FNode{node, false});
}
}
}
}
std::vector<std::vector<Node *>> SubgraphDetector::ExtractSubGraphs() {
// Run the Extract algorithm to find all subgraphs.
std::vector<Node *> marked_nodes;
// We use brief_node_map to represent the original graph in order to avoid
// changing the original graph.
std::unordered_map<int, BriefNode *> brief_node_map;
std::unordered_set<int32_t> valid_node_ids;
for (auto *node : graph_->Nodes()) {
valid_node_ids.insert(node->id());
}
for (auto &node : framework::ir::GraphTraits::TS(*graph_)) {
brief_node_map[node.id()] = new BriefNode(&node);
if (Agent(&node).marked()) {
marked_nodes.push_back(&node);
}
}
// extract sub-graphs in the marked node set, use Union Find algorithm.
node_map_t node_map; // id to ptr
for (auto *n : marked_nodes) {
// n's parent == n.id means it is the ancestor
Agent(n).set_union_find_parent(n->id());
node_map[n->id()] = n;
}
// create breif node map
for (auto &itr : brief_node_map) {
for (Node *node : itr.second->node->inputs) {
if (!valid_node_ids.count(node->id())) {
LOG(INFO) << "invalid node id " << node->id();
continue;
}
itr.second->inlinks.push_back(brief_node_map.at(node->id()));
}
for (Node *node : itr.second->node->outputs) {
if (!valid_node_ids.count(node->id())) {
LOG(INFO) << "invalid node id " << node->id();
continue;
}
itr.second->outlinks.push_back(brief_node_map.at(node->id()));
}
}
for (auto &itr : brief_node_map) {
BriefNode *brief_node = itr.second;
if (!Agent(brief_node->node).marked()) {
VLOG(4) << brief_node->node->id() << " node not a trt candidate.";
continue;
}
// Our algorithm must guarantee that:
// 1. The graph is always directed acyclic graph（DAG）.
// 2. If there is a path in the subgraph from X to Y (X and Y are both
// nodes in the subgraph), then all paths from X to Y are in the
// subgraph.
//
// In order to achieve the above guarantee.
// For adjacent nodes src -> dst.
// 1. Get all dst input nodes except src.
// 2. Reverse DFS from those input nodes
// 3. If there is a path from input nodes to src,
// then the src and dst nodes can not be fused into one node,
// otherwise it can be done.
while (true) {
std::unordered_set<BriefNode *> contract_nodes;
for (auto *out : brief_node->outlinks) {
// must be an trt candidate
if (!Agent(out->node).marked()) continue;
// get all dst input nodes except src.
std::vector<BriefNode *> source_nodes;
for (auto *n : out->inlinks) {
if (n != brief_node) {
source_nodes.push_back(n);
}
}
// Reverse DFS from the source_nodes.
bool have_excess_path = false;
FlexibleDFS(source_nodes, true, nullptr,
[&have_excess_path, brief_node](const BriefNode *n) {
if (n == brief_node) {
have_excess_path = true;
return false;
}
return true;
});
if (have_excess_path) continue;
contract_nodes.insert(out);
}
if (contract_nodes.empty()) break;
for (auto dst_node : contract_nodes) {
UnionFindCombine(node_map, brief_node->node->id(),
dst_node->node->id());
UnionContractedNodes(brief_node_map, brief_node->node->id(),
dst_node->node->id());
}
}
}
std::unordered_map<int /*ancestor*/, std::vector<Node *>> clusters;
for (auto *n : marked_nodes) {
if (n->IsOp()) {
clusters[UnionFindGetAncestor(node_map, Agent(n).union_find_parent())]
.push_back(n);
}
}
std::vector<std::vector<Node *>> result;
std::for_each(clusters.begin(), clusters.end(),
[&](const decltype(clusters)::value_type &it) {
result.push_back(it.second);
});
return result;
}
void SubGraphFuser::operator()() { ReplaceNodesWithSubGraphs(); }
void RemoveIntermediateOutputInSubgraph(const std::vector<Node *> &subgraph,
Graph *graph,
std::vector<Node *> *outputs) {
std::unordered_set<Node *> subgraph_set(subgraph.begin(), subgraph.end());
std::unordered_set<Node *> valid_output;
for (auto *output : *outputs) {
int num_used = 0;
for (auto *node : output->outputs) {
if (!subgraph_set.count(node)) ++num_used;
if (num_used > 0) valid_output.insert(output);
}
}
// In use for ngraph subgraph pass for parallel executor,
// this will remove all nodes, bypass this and let ngraph
// subgraph pass to process outputs
if (FLAGS_use_ngraph && valid_output.size() == 0) return;
outputs->assign(valid_output.begin(), valid_output.end());
}
void DetachDeletedNodes(framework::ir::Graph *graph) {
std::unordered_set<const Node *> nodes;
for (auto *node : graph->Nodes()) {
if (Agent(node).deleted()) {
node->inputs.clear();
node->outputs.clear();
}
}
}
void SubGraphFuser::ReplaceNodesWithSubGraphs() {
auto subgraphs = SubgraphDetector(graph_, node_inside_subgraph_teller_)();
for (auto &subgraph : subgraphs) {
if (subgraph.size() <= (size_t)min_subgraph_size_) continue;
std::unordered_set<Node *> subgraph_uniq(subgraph.begin(), subgraph.end());
// replace this sub-graph with the first node. Two steps: 1. Create a Block
// Node that contains this subgraph 2. Mark the nodes inside the sub-graph
// as deleted. 3. Replace the deleted node with the new Block Node.
framework::OpDesc empty_desc;
empty_desc.SetType(name_);
auto *block_node = graph_->CreateOpNode(&empty_desc);
Agent(block_node).set_subgraph({});
auto io = ExtractInputAndOutputOfSubGraph(subgraph);
block_node->inputs = std::move(io.first);
block_node->outputs = std::move(io.second);
RemoveIntermediateOutputInSubgraph(subgraph, graph_, &block_node->outputs);
for (auto *node : subgraph) {
// TODO(Superjomn) need a unified mechanism to treat deleted node in each
// pass.
Agent(node).set_deleted(true);
Agent(block_node).subgraph()->push_back(node);
}
// Change all the sub-graph's inputs and outputs corresponding inlink and
// outlink to this sub-graph node.
auto inlink_or_outlink_cleaner = [&](std::vector<Node *> &nodes) {
for (auto *&n : nodes) {
if (subgraph_uniq.count(n)) {
n = block_node;
}
}
std::unordered_set<Node *> uniq(nodes.begin(), nodes.end());
nodes.assign(uniq.begin(), uniq.end());
};
for (auto *i : block_node->inputs) {
inlink_or_outlink_cleaner(i->outputs);
}
for (auto *&o : block_node->outputs) {
inlink_or_outlink_cleaner(o->inputs);
}
}
// DetachDeletedNodes(graph_);
FilterRedundantOutputOfSubGraph(graph_);
}
inline bool CheckNodeIndegreeEquals(const Node &node, size_t n) {
return node.inputs.size() == n;
}
} // namespace ir
} // namespace framework
} // namespace paddle
paddle/fluid/inference/analysis/ir_passes/subgraph_detector.h → paddle/fluid/framework/ir/subgraph_detector.h
浏览文件 @ b1401fb7
/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
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. */
/*
* This file defines the the class to partition a graph.
*/
#pragma once
#include <string>
#include <vector>
#include "paddle/fluid/framework/ir/graph.h"
#include "paddle/fluid/framework/ir/graph_traits.h"
#include "paddle/fluid/framework/ir/node.h"
#include "paddle/fluid/inference/analysis/argument.h"
#include "paddle/fluid/inference/analysis/helper.h"
namespace paddle {
namespace inference {
namespace analysis {
using framework::ir::Graph;
using framework::ir::NodesTSIterator;
const char kIsFunctionNode[] = "__is_function_node__";
const char kFunctionNodeSubGraph[] = "__function_node_sub_graph__";
const char kSubgraphSplitterMarkerAttrName[] =
"_sub_graph_splitter_inside_sub_graph";
/*
* Detect the nodes in a sub-graph that meet some conditions. This class doesn't
* modify the graph.
*/
class SubgraphDetector {
public:
// Tell whether a node is inside a sub-graph.
using NodeInsideSubgraphTeller =
std::function<bool(const framework::ir::Node *)>;
SubgraphDetector(Graph *graph, const NodeInsideSubgraphTeller &teller)
: graph_(graph), node_inside_subgraph_teller_(teller) {}
std::vector<std::vector<framework::ir::Node *>> operator()();
protected:
// Mark the nodes inside the accepted sub-graph using
// node_inside_subgraph_teller.
void MarkNodesInsideSubGraph();
// Merge the marked nodes into sub-graphs and return the sub-graphs.
std::vector<std::vector<framework::ir::Node *>> ExtractSubGraphs();
private:
Graph *graph_;
NodeInsideSubgraphTeller node_inside_subgraph_teller_;
};
/*
* SubGraphFuser - Replace some nodes with the sub-graph node they are inside.
* To some extent, the TensorRT engine is just a fusion op for a model.
*/
class SubGraphFuser {
public:
using NodeInsideSubgraphTeller = SubgraphDetector::NodeInsideSubgraphTeller;
SubGraphFuser(Graph *graph, const NodeInsideSubgraphTeller &teller,
int min_subgraph_size, std::string name = "anakin_engine")
: graph_(graph),
node_inside_subgraph_teller_(teller),
min_subgraph_size_{min_subgraph_size},
name_{name} {}
// The main method which run all the logic.
void operator()();
protected:
// Remove the nodes inside sub-graphs and replace with the SubGraphNode.
void ReplaceNodesWithSubGraphs();
private:
Graph *graph_;
NodeInsideSubgraphTeller node_inside_subgraph_teller_;
int min_subgraph_size_;
const std::string name_;
};
struct NodeWrapper {
bool deleted{false};
bool marked{false};
int union_find_parent{-1};
std::vector<framework::ir::Node *> subgraph;
};
/*
* ir::Node agent for subgraph detector.
*/
struct Agent {
explicit Agent(framework::ir::Node *x) : x_(x) {}
NodeWrapper &wrapper() {
if (!x_->IsWrappedBy<NodeWrapper>()) {
x_->WrappedBy<NodeWrapper>(new NodeWrapper);
}
return x_->template Wrapper<NodeWrapper>();
}
bool deleted() { return wrapper().deleted; }
void set_deleted(bool x) { wrapper().deleted = x; }
bool marked() { return wrapper().marked; }
void set_marked(bool x) { wrapper().marked = x; }
void set_subgraph(const std::vector<framework::ir::Node *> &x) {
wrapper().subgraph = x;
}
int union_find_parent() { return wrapper().union_find_parent; }
void set_union_find_parent(int v) { wrapper().union_find_parent = v; }
std::vector<framework::ir::Node *> *subgraph() { return &wrapper().subgraph; }
std::vector<framework::ir::Node *> &inputs() { return x_->inputs; }
std::vector<framework::ir::Node *> &outputs() { return x_->outputs; }
private:
framework::ir::Node *x_;
};
// The nodes those have no input will be treated as start points.
static std::vector<framework::ir::Node *> ExtractStartPoints(const Graph &g) {
std::vector<framework::ir::Node *> result;
for (auto *node : g.Nodes()) {
if (node->inputs.empty()) {
result.push_back(node);
}
}
return result;
}
static iterator_range<NodesTSIterator> TopologicalSort(const Graph &g) {
auto start_points = ExtractStartPoints(g);
PADDLE_ENFORCE(!start_points.empty());
NodesTSIterator x(start_points);
return iterator_range<NodesTSIterator>(NodesTSIterator(start_points),
NodesTSIterator());
}
} // namespace analysis
} // namespace inference
} // namespace paddle
/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
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. */
#pragma once
#include <string>
#include <vector>
#include "paddle/fluid/framework/ir/graph.h"
#include "paddle/fluid/framework/ir/graph_traits.h"
#include "paddle/fluid/framework/ir/node.h"
namespace paddle {
namespace framework {
namespace ir {
const char kIsFunctionNode[] = "__is_function_node__";
const char kFunctionNodeSubGraph[] = "__function_node_sub_graph__";
const char kSubgraphSplitterMarkerAttrName[] =
"_sub_graph_splitter_inside_sub_graph";
/*
* Detect the nodes in a sub-graph that meet some conditions. This class doesn't
* modify the graph.
*/
class SubgraphDetector {
public:
// Tell whether a node is inside a sub-graph.
using NodeInsideSubgraphTeller = std::function<bool(const Node *)>;
SubgraphDetector(Graph *graph, const NodeInsideSubgraphTeller &teller)
: graph_(graph), node_inside_subgraph_teller_(teller) {}
std::vector<std::vector<Node *>> operator()();
protected:
// Mark the nodes inside the accepted sub-graph using
// node_inside_subgraph_teller.
void MarkNodesInsideSubGraph();
// Merge the marked nodes into sub-graphs and return the sub-graphs.
std::vector<std::vector<Node *>> ExtractSubGraphs();
private:
Graph *graph_;
NodeInsideSubgraphTeller node_inside_subgraph_teller_;
};
/*
* SubGraphFuser - Replace some nodes with the sub-graph node they are inside.
* To some extent, the TensorRT engine is just a fusion op for a model.
*/
class SubGraphFuser {
public:
using NodeInsideSubgraphTeller = SubgraphDetector::NodeInsideSubgraphTeller;
SubGraphFuser(Graph *graph, const NodeInsideSubgraphTeller &teller,
int min_subgraph_size, std::string name = "anakin_engine")
: graph_(graph),
node_inside_subgraph_teller_(teller),
min_subgraph_size_{min_subgraph_size},
name_{name} {}
// The main method which run all the logic.
void operator()();
protected:
// Remove the nodes inside sub-graphs and replace with the SubGraphNode.
void ReplaceNodesWithSubGraphs();
private:
Graph *graph_;
NodeInsideSubgraphTeller node_inside_subgraph_teller_;
int min_subgraph_size_;
const std::string name_;
};
struct NodeWrapper {
bool deleted{false};
bool marked{false};
int union_find_parent{-1};
std::vector<Node *> subgraph;
};
/*
* ir::Node agent for subgraph detector.
*/
struct Agent {
explicit Agent(Node *x) : x_(x) {}
NodeWrapper &wrapper() {
if (!x_->IsWrappedBy<NodeWrapper>()) {
x_->WrappedBy<NodeWrapper>(new NodeWrapper);
}
return x_->template Wrapper<NodeWrapper>();
}
bool deleted() { return wrapper().deleted; }
void set_deleted(bool x) { wrapper().deleted = x; }
bool marked() { return wrapper().marked; }
void set_marked(bool x) { wrapper().marked = x; }
void set_subgraph(const std::vector<framework::ir::Node *> &x) {
wrapper().subgraph = x;
}
int union_find_parent() { return wrapper().union_find_parent; }
void set_union_find_parent(int v) { wrapper().union_find_parent = v; }
std::vector<Node *> *subgraph() { return &wrapper().subgraph; }
std::vector<Node *> &inputs() { return x_->inputs; }
std::vector<Node *> &outputs() { return x_->outputs; }
private:
Node *x_;
};
// The nodes those have no input will be treated as start points.
static std::vector<Node *> ExtractStartPoints(const Graph &g) {
std::vector<Node *> result;
for (auto *node : g.Nodes()) {
if (node->inputs.empty()) {
result.push_back(node);
}
}
return result;
}
static iterator_range<NodesTSIterator> TopologicalSort(const Graph &g) {
auto start_points = ExtractStartPoints(g);
PADDLE_ENFORCE_GT(
start_points.size(), 0U,
platform::errors::InvalidArgument(
"Expected the number of graph's start points >= 1. Expected %d.",
start_points.size()));
NodesTSIterator x(start_points);
return iterator_range<NodesTSIterator>(NodesTSIterator(start_points),
NodesTSIterator());
}
} // namespace ir
} // namespace framework
} // namespace paddle
paddle/fluid/inference/analysis/ir_pass_manager.cc
浏览文件 @ b1401fb7
......@@ -24,7 +24,6 @@
#include "paddle/fluid/framework/ir/graph.h"
#include "paddle/fluid/framework/scope.h"
#include "paddle/fluid/inference/analysis/argument.h"
#include "paddle/fluid/inference/analysis/ir_passes/subgraph_detector.h"
#include "paddle/fluid/string/pretty_log.h"
namespace paddle {
......
paddle/fluid/inference/analysis/ir_passes/CMakeLists.txt
浏览文件 @ b1401fb7
cc_library(subgraph_detector SRCS subgraph_detector.cc subgraph_util.cc DEPS proto_desc)
if(WITH_TESTING)
add_dependencies(subgraph_detector gtest)
endif()
cc_library(subgraph_util SRCS subgraph_util.cc DEPS subgraph_detector)
if (WITH_GPU AND TENSORRT_FOUND)
cc_library(tensorrt_subgraph_pass SRCS tensorrt_subgraph_pass.cc DEPS subgraph_detector tensorrt_op_teller)
cc_library(tensorrt_subgraph_pass SRCS tensorrt_subgraph_pass.cc DEPS subgraph_util tensorrt_op_teller)
set(analysis_deps ${analysis_deps}
subgraph_detector tensorrt_subgraph_pass
subgraph_util tensorrt_subgraph_pass
CACHE INTERNAL "")
set(pass_file ${PADDLE_BINARY_DIR}/paddle/fluid/inference/api/paddle_inference_pass.h)
......@@ -16,10 +13,10 @@ if (WITH_GPU AND TENSORRT_FOUND)
endif()
if (ANAKIN_SUBGRAPH)
cc_library(anakin_subgraph_pass SRCS anakin_subgraph_pass.cc DEPS subgraph_detector anakin_op_teller)
cc_library(anakin_subgraph_pass SRCS anakin_subgraph_pass.cc DEPS subgraph_util anakin_op_teller)
set(analysis_deps ${analysis_deps}
subgraph_detector anakin_subgraph_pass
subgraph_util anakin_subgraph_pass
CACHE INTERNAL "")
set(pass_file ${PADDLE_BINARY_DIR}/paddle/fluid/inference/api/paddle_inference_pass.h)
......
paddle/fluid/inference/analysis/ir_passes/anakin_subgraph_pass.cc
浏览文件 @ b1401fb7
......@@ -22,11 +22,11 @@
#include <vector>
#include "paddle/fluid/framework/ir/graph_pattern_detector.h"
#include "paddle/fluid/framework/ir/subgraph_detector.h"
#include "paddle/fluid/inference/anakin/convert/op_converter.h"
#include "paddle/fluid/inference/anakin/op_teller.h"
#include "paddle/fluid/inference/analysis/helper.h"
#include "paddle/fluid/inference/analysis/ir_passes/anakin_subgraph_pass.h"
#include "paddle/fluid/inference/analysis/ir_passes/subgraph_detector.h"
#include "paddle/fluid/string/pretty_log.h"
namespace paddle {
......@@ -50,7 +50,7 @@ void analysis::AnakinSubgraphPass::ApplyImpl(
return anakin::OpTeller::Global().Tell(node->Op()->Type(), *node->Op());
};
SubGraphFuser fuser(graph, teller, 6 /* min_subgraph_size */);
framework::ir::SubGraphFuser fuser(graph, teller, 6 /* min_subgraph_size */);
fuser();
std::vector<std::string> graph_param_names =
......@@ -61,17 +61,18 @@ void analysis::AnakinSubgraphPass::ApplyImpl(
std::vector<std::string> repetitive_params;
for (auto *node : graph->Nodes()) {
if (node->IsOp() && !Agent(node).subgraph()->empty()) {
if (node->IsOp() && !framework::ir::Agent(node).subgraph()->empty()) {
CreateAnakinOp(node, graph, graph_param_names, &repetitive_params);
std::unordered_set<const Node *> nodes2remove(
Agent(node).subgraph()->begin(), Agent(node).subgraph()->end());
framework::ir::Agent(node).subgraph()->begin(),
framework::ir::Agent(node).subgraph()->end());
framework::ir::GraphSafeRemoveNodes(graph, nodes2remove);
}
}
std::unordered_set<const Node *> nodes2remove;
for (auto *node : graph->Nodes()) {
if (node->IsOp() && Agent(node).deleted()) {
if (node->IsOp() && framework::ir::Agent(node).deleted()) {
nodes2remove.insert(node);
}
}
......@@ -96,11 +97,11 @@ std::string GenerateAnakinEngineKey(const std::set<std::string> &engine_inputs,
}
void AnakinSubgraphPass::CreateAnakinOp(
framework::ir::Node *node, Graph *graph,
framework::ir::Node *node, framework::ir::Graph *graph,
const std::vector<std::string> &graph_params,
std::vector<std::string> *repetitive_params) const {
auto *op_desc = node->Op();
auto &subgraph = *Agent(node).subgraph();
auto &subgraph = *framework::ir::Agent(node).subgraph();
PADDLE_ENFORCE(!subgraph.empty());
framework::ProgramDesc *program_desc =
......@@ -164,7 +165,7 @@ void AnakinSubgraphPass::CreateAnakinOp(
graph_var_map[node->Name()] = node;
}
}
auto &subgraph_nodes = *Agent(node).subgraph();
auto &subgraph_nodes = *framework::ir::Agent(node).subgraph();
// The following procedure is used to rename all the intermediate
// variables and the output variables of the subgraph.
......
paddle/fluid/inference/analysis/ir_passes/tensorrt_subgraph_pass.cc
浏览文件 @ b1401fb7
......@@ -17,8 +17,8 @@
#include <set>
#include "paddle/fluid/framework/ir/graph_pattern_detector.h"
#include "paddle/fluid/framework/ir/subgraph_detector.h"
#include "paddle/fluid/inference/analysis/helper.h"
#include "paddle/fluid/inference/analysis/ir_passes/subgraph_detector.h"
#include "paddle/fluid/inference/analysis/ir_passes/tensorrt_subgraph_pass.h"
#include "paddle/fluid/inference/tensorrt/convert/op_converter.h"
#include "paddle/fluid/inference/tensorrt/engine.h"
......@@ -40,9 +40,9 @@ void analysis::TensorRtSubgraphPass::ApplyImpl(
return tensorrt::OpTeller::Global().Tell(node->Op()->Type(), *node->Op());
};
SubGraphFuser fuser(graph, teller,
Get<int>("min_subgraph_size") /*min subgraph size*/,
"tensorrt_engine");
framework::ir::SubGraphFuser fuser(
graph, teller, Get<int>("min_subgraph_size") /*min subgraph size*/,
"tensorrt_engine");
fuser();
std::vector<std::string> graph_param_names =
......@@ -52,18 +52,19 @@ void analysis::TensorRtSubgraphPass::ApplyImpl(
std::vector<std::string> repetitive_params;
for (auto *node : graph->Nodes()) {
if (node->IsOp() && !Agent(node).subgraph()->empty()) {
if (node->IsOp() && !framework::ir::Agent(node).subgraph()->empty()) {
CreateTensorRTOp(node, graph, graph_param_names, &repetitive_params);
std::unordered_set<const Node *> nodes2remove(
Agent(node).subgraph()->begin(), Agent(node).subgraph()->end());
framework::ir::Agent(node).subgraph()->begin(),
framework::ir::Agent(node).subgraph()->end());
framework::ir::GraphSafeRemoveNodes(graph, nodes2remove);
}
}
std::unordered_set<const Node *> nodes2remove;
for (auto *node : graph->Nodes()) {
if (node->IsOp() && Agent(node).deleted()) {
if (node->IsOp() && framework::ir::Agent(node).deleted()) {
nodes2remove.insert(node);
}
}
......@@ -88,11 +89,11 @@ std::string GenerateEngineKey(const std::set<std::string> &engine_inputs,
}
void TensorRtSubgraphPass::CreateTensorRTOp(
framework::ir::Node *node, Graph *graph,
framework::ir::Node *node, framework::ir::Graph *graph,
const std::vector<std::string> &graph_params,
std::vector<std::string> *repetitive_params) const {
auto *op_desc = node->Op();
auto &subgraph = *Agent(node).subgraph();
auto &subgraph = *framework::ir::Agent(node).subgraph();
PADDLE_ENFORCE(!subgraph.empty());
framework::ProgramDesc *program_desc =
......@@ -161,7 +162,7 @@ void TensorRtSubgraphPass::CreateTensorRTOp(
if (precision_mode == AnalysisConfig::Precision::kHalf) enable_fp16 = true;
auto enable_int8 = Get<bool>("enable_int8");
auto use_calib_mode = Get<bool>("use_calib_mode");
auto &subgraph_nodes = *Agent(node).subgraph();
auto &subgraph_nodes = *framework::ir::Agent(node).subgraph();
// The following procedure is used to rename all the intermediate
// variables and the output variables of the subgraph.
......
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