/* Copyright 2016 The TensorFlow 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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==============================================================================*/
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// Class method definitions for HostStream, the Stream implementation for
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// the HostExecutor implementation.
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#include "tensorflow/stream_executor/host/host_stream.h"
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namespace stream_executor {
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namespace host {
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HostStream::HostStream()
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: host_executor_(new port::ThreadPool(port::Env::Default(),
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port::ThreadOptions(),
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"host_executor", kExecutorThreads)) {}
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HostStream::~HostStream() {}
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bool HostStream::EnqueueTask(std::function<void()> task) {
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struct NotifiedTask {
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HostStream* stream;
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std::function<void()> task;
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void operator()() {
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task();
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// Destroy the task before unblocking its waiters, as BlockHostUntilDone()
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// should guarantee that all tasks are destroyed.
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task = std::function<void()>();
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{
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mutex_lock lock(stream->mu_);
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--stream->pending_tasks_;
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}
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stream->completion_condition_.notify_all();
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}
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};
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{
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mutex_lock lock(mu_);
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++pending_tasks_;
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}
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host_executor_->Schedule(NotifiedTask{this, std::move(task)});
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return true;
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}
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void HostStream::BlockUntilDone() {
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mutex_lock lock(mu_);
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while (pending_tasks_ != 0) {
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completion_condition_.wait(lock);
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}
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}
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} // namespace host
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} // namespace stream_executor
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