def runExperiment(opt, visualize_steps, visualize_learning, visualize_performance, q):
# Experiment要在子进程中创建，不能直接传创建好的对象（会影响logger的正常工作）
exp = Experiment(**opt)
# 给logger加handler
# 子进程的log->MemoryHandler->OutputHandler-> queue <-ExpOutputDialog.receive->QTextEdit
# log通过queue在进程间传递，主线程通过thread接收queue中的新消息
from logging.handlers import MemoryHandler
handler = MemoryHandler(capacity=1024, flushLevel=logging.INFO, target=OutputHandler(q))
exp.logger.addHandler(handler)
exp.run(visualize_steps=visualize_steps, # should each learning step be shown?
visualize_learning=visualize_learning, # show policy / value function?
visualize_performance=visualize_performance) # show performance runs?
exp.plot()
def runExperiment(opt, visualize_steps, visualize_learning,
visualize_performance, q):
# Experiment要在子进程中创建，不能直接传创建好的对象（会影响logger的正常工作）
exp = Experiment(**opt)
# 给logger加handler
# 子进程的log->MemoryHandler->OutputHandler-> queue <-ExpOutputDialog.receive->QTextEdit
# log通过queue在进程间传递，主线程通过thread接收queue中的新消息
from logging.handlers import MemoryHandler
handler = MemoryHandler(capacity=1024,
flushLevel=logging.INFO,
target=OutputHandler(q))
exp.logger.addHandler(handler)
exp.run(
visualize_steps=visualize_steps, # should each learning step be shown?
visualize_learning=visualize_learning, # show policy / value function?
visualize_performance=visualize_performance) # show performance runs?
exp.plot()
