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使用swig_paddle进行多线程预估,在初始化时指定trainer_count=4:
swig_paddle.initPaddle("--trainer_count=4")
随后,构造长度为N的输入序列,对这个序列进行预测,返回一个结果序列。 但是,输入序列的长度不等于返回结果的序列长度,也就是说数据有丢失的问题。
将trainer_count改为1,则不会出现上面的问题。
The text was updated successfully, but these errors were encountered:
前一段时间修复了一个MultiGradientMachine的bug。你可以先更新代码,看看问题是否仍然复现。
Sorry, something went wrong.
建议简化场景,如果希望问题得到解决,尽量提供可以复现的例子。否则从这样的描述中,根本无从查起。
I close this issue due to inactivity. please feel free to reopen it if more information is available.
QiJune
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使用swig_paddle进行多线程预估,在初始化时指定trainer_count=4:
随后,构造长度为N的输入序列,对这个序列进行预测,返回一个结果序列。
但是,输入序列的长度不等于返回结果的序列长度,也就是说数据有丢失的问题。
将trainer_count改为1,则不会出现上面的问题。
The text was updated successfully, but these errors were encountered: