Merge branch 'develop' of https://github.com/PaddlePaddle/Paddle into multiclass_nms_op
dangqingqing
7 years ago
commit
73b66540b6
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/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
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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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#include <stddef.h> // for size_t
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namespace paddle {
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namespace framework {
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// Channel is the abstract class of buffered and un-buffered channels.
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template <typename T>
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class Channel {
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public:
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virtual void Send(T*) = 0;
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virtual void Receive(T*) = 0;
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virtual size_t Cap() = 0;
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// Don't delete channels; instead, call Channel::Close.
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protected:
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virtual ~Channel() {}
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};
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// Forward declaration of channel implementations.
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namespace details {
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template <typename T>
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class Buffered;
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template <typename T>
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class UnBuffered;
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} // namespace details
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template <typename T>
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Channel<T>* MakeChannel(size_t buffer_size) {
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if (buffer_size > 0) {
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return new details::Buffered<T>(buffer_size);
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}
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return new details::UnBuffered<T>();
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}
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template <typename T>
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void CloseChannel(Channel<T>* ch) {
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if (ch->Cap() > 0) {
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delete dynamic_cast<details::Buffered<T>*>(ch);
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} else {
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delete dynamic_cast<details::UnBuffered<T>*>(ch);
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}
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}
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} // namespace framework
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} // namespace paddle
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#include "paddle/framework/details/buffered_channel.h"
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#include "paddle/framework/details/unbuffered_channel.h"
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/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
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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/framework/channel.h"
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#include "gtest/gtest.h"
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TEST(Channel, MakeAndClose) {
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using paddle::framework::Channel;
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using paddle::framework::MakeChannel;
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using paddle::framework::CloseChannel;
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Channel<int>* ch = MakeChannel<int>(10);
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CloseChannel(ch);
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}
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/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
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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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#include <condition_variable>
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#include <deque>
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#include <mutex>
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#include "paddle/framework/channel.h"
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namespace paddle {
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namespace framework {
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namespace details {
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template <typename T>
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class Buffered : public paddle::framework::Channel<T> {
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friend Channel<T>* paddle::framework::MakeChannel<T>(size_t);
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friend void paddle::framework::CloseChannel<T>(Channel<T>*);
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public:
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virtual void Send(T*);
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virtual void Receive(T*);
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virtual size_t Cap() { return cap_; }
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private:
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size_t cap_;
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std::mutex mu_;
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std::condition_variable empty_cond_var_;
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std::condition_variable full_cond_var_;
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std::deque<T> channel_;
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Buffered(size_t cap) : cap_(cap) {}
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virtual ~Buffered();
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void NotifyAllSenders(std::unique_lock<std::mutex>*);
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};
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template <typename T>
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void Buffered<T>::Send(T* item) {
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std::unique_lock<std::mutex> lock(mu_);
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full_cond_var_.wait(lock, [this]() { return channel_.size() < cap_; });
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channel_.push_back(std::move(*item));
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lock.unlock();
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empty_cond_var_.notify_one();
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}
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template <typename T>
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void Buffered<T>::Receive(T* item) {
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std::unique_lock<std::mutex> lock(mu_);
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empty_cond_var_.wait(lock, [this]() { return !channel_.empty(); });
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*item = std::move(channel_.front());
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channel_.pop_front();
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NotifyAllSenders(&lock);
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}
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template <typename T>
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Buffered<T>::~Buffered() {
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std::unique_lock<std::mutex> lock(mu_);
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channel_.clear();
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NotifyAllSenders(&lock);
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}
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template <typename T>
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void Buffered<T>::NotifyAllSenders(std::unique_lock<std::mutex>* lock) {
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lock->unlock();
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full_cond_var_.notify_one();
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}
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} // namespace details
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} // namespace framework
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} // namespace paddle
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@ -0,0 +1,52 @@
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/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
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|
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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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#include <condition_variable>
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#include <deque>
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#include <mutex>
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#include "paddle/framework/channel.h"
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namespace paddle {
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namespace framework {
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namespace details {
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template <typename T>
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class UnBuffered : public paddle::framework::Channel<T> {
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friend Channel<T>* paddle::framework::MakeChannel<T>(size_t);
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friend void paddle::framework::CloseChannel<T>(Channel<T>*);
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public:
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virtual void Send(T*);
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virtual void Receive(T*);
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virtual size_t Cap() { return 0; }
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private:
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UnBuffered() {}
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virtual ~UnBuffered();
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};
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template <typename T>
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void UnBuffered<T>::Send(T* channel_element) {}
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template <typename T>
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void UnBuffered<T>::Receive(T*) {}
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template <typename T>
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UnBuffered<T>::~UnBuffered() {}
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} // namespace details
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} // namespace framework
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} // namespace paddle
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/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
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|
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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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|
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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,
|
||||
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. */
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#include "paddle/framework/feed_fetch_method.h"
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#include "glog/logging.h"
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#include "paddle/framework/variable.h"
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namespace paddle {
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namespace framework {
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void SetFeedVariable(Scope* scope, const LoDTensor& input,
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const std::string& var_name, size_t index) {
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// If var_name Variable is not found in GlobalScope, a new variable will
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// be created.
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VLOG(3) << "SetFeedVariable name=" << var_name << " index=" << index;
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Variable* g_feed_value = scope->Var(var_name);
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auto& feed_inputs =
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*(g_feed_value->GetMutable<std::vector<paddle::framework::LoDTensor>>());
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if (index >= feed_inputs.size()) {
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feed_inputs.resize(index + 1);
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}
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// shared data with input tensor
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feed_inputs[index].ShareDataWith(input);
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// set lod
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feed_inputs[index].set_lod(input.lod());
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}
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LoDTensor& GetFetchVariable(const Scope& scope, const std::string& var_name,
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size_t index) {
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// Since we want to fetch LodTensor from a variable, the variable must
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// be created alreadly.
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Variable* g_fetch_value = scope.FindVar(var_name);
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PADDLE_ENFORCE(g_fetch_value->IsType<FeedFetchList>(),
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"Only %s can be invoked by GetFetchVariable",
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typeid(FeedFetchList).name());
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auto& fetch_outputs = *g_fetch_value->GetMutable<FeedFetchList>();
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auto& tensor = fetch_outputs[index];
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VLOG(3) << "Fetch " << var_name << " with index " << index
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<< " shape= " << tensor.dims();
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PADDLE_ENFORCE_LT(index, fetch_outputs.size());
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return tensor;
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}
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} // namespace framework
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} // namespace paddle
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@ -1,24 +1,93 @@
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/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
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|
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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
|
||||
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
|
||||
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,
|
||||
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. */
|
||||
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/framework/threadpool.h"
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namespace paddle {
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namespace framework {
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std::unique_ptr<ThreadPool> ThreadPool::threadpool(nullptr);
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std::once_flag ThreadPool::init_flag;
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std::unique_ptr<ThreadPool> ThreadPool::threadpool_(nullptr);
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std::once_flag ThreadPool::init_flag_;
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ThreadPool* ThreadPool::GetInstance() {
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std::call_once(init_flag_, &ThreadPool::Init);
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return threadpool_.get();
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}
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void ThreadPool::Init() {
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if (threadpool_.get() == nullptr) {
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// TODO(Yancey1989): specify the max threads number
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int num_threads = std::thread::hardware_concurrency();
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PADDLE_ENFORCE_GT(num_threads, 0);
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threadpool_.reset(new ThreadPool(num_threads));
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}
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}
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ThreadPool::ThreadPool(int num_threads)
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: total_threads_(num_threads), idle_threads_(num_threads), running_(true) {
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threads_.resize(num_threads);
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for (auto& thread : threads_) {
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// TODO(Yancey1989): binding the thread on the specify CPU number
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thread.reset(new std::thread(std::bind(&ThreadPool::TaskLoop, this)));
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}
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}
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ThreadPool::~ThreadPool() {
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{
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// notify all threads to stop running
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running_ = false;
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scheduled_.notify_all();
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}
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for (auto& t : threads_) {
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t->join();
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t.reset(nullptr);
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}
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}
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void ThreadPool::Wait() {
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std::unique_lock<std::mutex> lock(mutex_);
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completed_.wait(lock, [=] { return Done() == true; });
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}
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void ThreadPool::TaskLoop() {
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while (running_) {
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std::unique_lock<std::mutex> lock(mutex_);
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scheduled_.wait(lock, [=] { return !tasks_.empty() || !running_; });
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if (!running_) {
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break;
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}
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// pop a task from the task queue
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auto task = std::move(tasks_.front());
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tasks_.pop();
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--idle_threads_;
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lock.unlock();
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// run the task
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task();
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{
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std::unique_lock<std::mutex> lock(mutex_);
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++idle_threads_;
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if (Done()) {
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completed_.notify_all();
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}
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}
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}
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}
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} // namespace framework
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} // namespace paddle
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