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214 lines
6.8 KiB
214 lines
6.8 KiB
/* 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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#include "paddle/fluid/inference/analysis/data_flow_graph.h"
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#include "paddle/fluid/inference/analysis/dot.h"
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#include "paddle/fluid/inference/analysis/node.h"
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namespace paddle {
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namespace inference {
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namespace analysis {
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// It is a better idea that the inputs and outputs of this graph is set manually
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// before, but there must be a Pass that helps to prune the unnecessary ops that
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// do not contribute to the given targets, so in this pass, analysis and get the
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// inputs and outputs is OK.
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void DataFlowGraph::Build() {
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inputs.clear();
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outputs.clear();
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std::unordered_set<Node *> ins;
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std::unordered_set<Node *> outs;
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for (auto &node : nodes.nodes()) {
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for (auto *in : node->inlinks) {
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ins.insert(in);
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}
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for (auto *out : node->outlinks) {
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outs.insert(out);
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}
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}
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// The nodes that in ins but not in outs is the graph's inputs
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// similarly, the nodes that in outs but not in ins is the graphs' outputs
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for (auto *in : ins) {
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if (!outs.count(in)) {
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inputs.push_back(in);
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}
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}
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for (auto *out : outs) {
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if (!outs.count(out)) {
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outputs.push_back(out);
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}
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}
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Clean();
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}
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void DataFlowGraph::Clean() {
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for (auto &node : nodes.nodes()) {
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std::unordered_set<Node *> inlinks_set(node->inlinks.begin(),
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node->inlinks.end());
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std::unordered_set<Node *> outlinks_set(node->outlinks.begin(),
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node->outlinks.end());
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if (inlinks_set.size() < node->inlinks.size()) {
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LOG(INFO) << "Clean: node " << node->repr() << " prune duplicate inputs";
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node->inlinks.assign(inlinks_set.begin(), inlinks_set.end());
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}
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if (outlinks_set.size() < node->outlinks.size()) {
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LOG(INFO) << "Clean: node " << node->repr() << " prune duplicate inputs";
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node->outlinks.assign(outlinks_set.begin(), outlinks_set.end());
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}
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}
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}
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std::string DataFlowGraph::DotString() const {
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Dot dot;
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// Add nodes
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for (size_t i = 0; i < nodes.size(); i++) {
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const Node &node = nodes.Get(i);
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dot.AddNode(node.repr(), node.dot_attrs());
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}
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// Add edges
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for (size_t i = 0; i < nodes.size(); i++) {
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const Node &node = nodes.Get(i);
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for (auto &in : node.inlinks) {
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dot.AddEdge(in->repr(), node.repr(), {});
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}
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}
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return dot.Build();
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}
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//
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// NodesBFSIterator
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//
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GraphTraits<DataFlowGraph>::NodesBFSIterator::NodesBFSIterator(
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const std::vector<Node *> &source)
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: queue_(source.begin(), source.end()) {}
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// GraphTraits<DataFlowGraph>::NodesBFSIterator::NodesBFSIterator(
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// GraphTraits<DataFlowGraph>::NodesBFSIterator &&other) noexcept
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// : queue_(std::move(other.queue_)),
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// visited_(std::move(other.visited_)) {}
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GraphTraits<DataFlowGraph>::NodesBFSIterator::NodesBFSIterator(
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const GraphTraits<DataFlowGraph>::NodesBFSIterator &other)
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: queue_(other.queue_), visited_(other.visited_) {}
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Node &GraphTraits<DataFlowGraph>::NodesBFSIterator::operator*() {
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PADDLE_ENFORCE(!queue_.empty());
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return *queue_.front();
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}
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Node *GraphTraits<DataFlowGraph>::NodesBFSIterator::operator->() {
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PADDLE_ENFORCE(!queue_.empty());
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return queue_.front();
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}
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GraphTraits<DataFlowGraph>::NodesBFSIterator &
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GraphTraits<DataFlowGraph>::NodesBFSIterator::operator=(
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const GraphTraits<DataFlowGraph>::NodesBFSIterator &other) {
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queue_ = other.queue_;
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visited_ = other.visited_;
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return *this;
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}
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GraphTraits<DataFlowGraph>::NodesBFSIterator
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&GraphTraits<DataFlowGraph>::NodesBFSIterator::operator++() {
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PADDLE_ENFORCE(!queue_.empty());
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auto *cur = queue_.front();
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visited_.insert(cur);
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queue_.pop_front();
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for (auto *output : cur->outlinks) {
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if (!visited_.count(output)) {
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queue_.push_back(output);
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visited_.insert(output);
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}
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}
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return *this;
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}
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bool GraphTraits<DataFlowGraph>::NodesBFSIterator::operator==(
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const GraphTraits<DataFlowGraph>::NodesBFSIterator &other) {
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if (queue_.empty()) return other.queue_.empty();
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if ((!queue_.empty()) && (!other.queue_.empty())) {
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return queue_.front() == other.queue_.front() &&
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visited_.size() == other.visited_.size(); // here need to check the
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// equality of queue and
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// visited. Just a light but week implementation.
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}
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return false;
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}
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//
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// NodesDFSIterator
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//
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GraphTraits<DataFlowGraph>::NodesDFSIterator::NodesDFSIterator(
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const std::vector<Node *> &source) {
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for (auto *x : source) stack_.push(x);
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}
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// GraphTraits<DataFlowGraph>::NodesDFSIterator::NodesDFSIterator(
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// GraphTraits<DataFlowGraph>::NodesDFSIterator &&other) noexcept
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// : stack_(std::move(other.stack_)),
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// visited_(std::move(other.visited_)) {}
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GraphTraits<DataFlowGraph>::NodesDFSIterator::NodesDFSIterator(
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const GraphTraits<DataFlowGraph>::NodesDFSIterator &other)
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: stack_(other.stack_), visited_(other.visited_) {}
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Node &GraphTraits<DataFlowGraph>::NodesDFSIterator::operator*() {
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PADDLE_ENFORCE(!stack_.empty());
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return *stack_.top();
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}
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GraphTraits<DataFlowGraph>::NodesDFSIterator
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&GraphTraits<DataFlowGraph>::NodesDFSIterator::operator++() {
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if (stack_.empty()) return *this;
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visited_.insert(stack_.top());
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auto *cur = stack_.top();
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stack_.pop();
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for (auto *x : cur->outlinks) {
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if (!visited_.count(x)) {
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stack_.push(x);
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visited_.insert(x);
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}
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}
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return *this;
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}
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bool GraphTraits<DataFlowGraph>::NodesDFSIterator::operator==(
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const GraphTraits<DataFlowGraph>::NodesDFSIterator &other) {
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if (stack_.empty()) return other.stack_.empty();
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if ((!stack_.empty()) && (!other.stack_.empty())) {
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return stack_.top() == other.stack_.top();
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}
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return false;
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}
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GraphTraits<DataFlowGraph>::NodesDFSIterator &
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GraphTraits<DataFlowGraph>::NodesDFSIterator::operator=(
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const GraphTraits<DataFlowGraph>::NodesDFSIterator &other) {
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stack_ = other.stack_;
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visited_ = other.visited_;
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return *this;
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}
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Node *GraphTraits<DataFlowGraph>::NodesDFSIterator::operator->() {
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return stack_.top();
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}
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} // namespace analysis
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} // namespace inference
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} // namespace paddle
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