Running distributed tensorflow on machines with different versions of Tensorflow -


in particular i'm interested in happens if tensorflow installed on parameter server different tensorflow installed on worker. (e.g: different versions of tensorflow). how distributed tensorflow reconcile potential differences in execution code between workers , parameter servers?

i'd it's highly discouraged. depending on how many versions differ, in cases, errors. in base cases, things seemingly run e.g. nothing trains , you'll have hard time figuring out why....


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