提交 9f05a0f8 编写于 作者: Q qiaolongfei

use GradientMachine::start and finish

上级 55684af2
7 合并请求!11636[IMPORTANT] MKLDNN layout: Support for sum operator,!8482Release/0.11.0,!8190Release/0.11.0,!8189Release/0.11.0,!6633给线性回归的get-started代码加上了预测的示例~~,!4615Feature/tensor array add python binding,!2595fix MultiGradientMachine train and infer
......@@ -166,12 +166,16 @@ MultiGradientMachine::MultiGradientMachine(const ModelConfig& config,
outArgStream_ = HPPL_STREAM_1;
start();
}
void MultiGradientMachine::start() {
for (auto& thread : threads_) {
thread->start();
}
}
MultiGradientMachine::~MultiGradientMachine() {
void MultiGradientMachine::finish() {
for (auto& thread : threads_) {
thread->stop();
}
......@@ -445,7 +449,7 @@ TrainerThread::TrainerThread(const ModelConfig& config,
gradStream_ = HPPL_STREAM_2;
valueStream_ = HPPL_STREAM_3;
stopping_ = false;
stopping_ = true;
updateCounter_ = 0;
parameterUpdated_ = false;
}
......@@ -453,6 +457,10 @@ TrainerThread::TrainerThread(const ModelConfig& config,
TrainerThread::~TrainerThread() { stop(); }
void TrainerThread::start() {
if (!stopping_) return;
stopping_ = false;
gradientMachine_->start();
computeThread_.reset(new std::thread([this]() { computeThread(); }));
......
......@@ -176,7 +176,9 @@ public:
explicit MultiGradientMachine(const ModelConfig& config, bool useGpu);
virtual ~MultiGradientMachine();
virtual void start();
virtual void finish();
virtual void prefetch(const std::vector<Argument>& inArgs);
......
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