我在需求实例上使用0-256 m3.medium的计算环境.我的Job定义需要1个CPU和3 GB的Ram,m3.medium有.
AWS Batch Jobs陷入状态的可能原因是RUNNABLE什么？
AWS说:
A job that resides in the queue, has no outstanding dependencies, and is therefore ready to be scheduled to a host. Jobs in this state are started as soon as sufficient resources are available in one of the compute environments that are mapped to the job’s queue. However, jobs can remain in this state indefinitely when sufficient resources are unavailable.
但这不能回答我的问题
据我所知，静态 IPv4 地址对于 AWS 来说会更昂贵，因此每次重新启动实例时它都会发生变化。但公共 DNS 可以是静态的，因此在重新启动实例后，我不必更改所有应用程序中的地址。
我可以将实例公共 DNS 静态设置为“MyChoosenName.eu-west-1-compute.amazonaws.com”之类的内容吗？
我想将投票分类器应用于多个管道分类器并在网格搜索中调整参数。以下最小示例给了我一个错误。我必须以不同的方式做这件事吗？
from sklearn.ensemble import RandomForestClassifier
from sklearn.ensemble import AdaBoostClassifier
from sklearn.ensemble import VotingClassifier
p1 = Pipeline([['clf1', RandomForestClassifier()]])
p2 = Pipeline([['clf2', AdaBoostClassifier()]])
p3 = Pipeline([['clf3', VotingClassifier(estimators=(p1, p2))]])
p3.get_params()
错误：
TypeError: cannot convert dictionary update sequence element #0 to a sequence