2012/5/9 Yaroslav Halchenko <[email protected]>: > > > so if it fails for some specific seed, I could check if it gets > replicated by running the same test again with the same seed. > > if it doesn't -- I know **for sure** that it is not related to having > random data but smth more fun, worth valgrinding for decisions based on > uninitialized memory etc. e.g. now it halted (burns cpu, doesn't return) with > seed 1072 (before actually it just crashed in the same > sklearn.svm.tests.test_sparse.test_sparse_svc_clone_with_callable_kernel and > didn't reproduce).
I am not sure I understand. You are saying that this test sklearn.svm.tests.test_sparse.test_sparse_svc_clone_with_callable_kernel crashes deterministically with seed 1072 for numpy.random while passing most of the time otherwise? -- Olivier http://twitter.com/ogrisel - http://github.com/ogrisel ------------------------------------------------------------------------------ Live Security Virtual Conference Exclusive live event will cover all the ways today's security and threat landscape has changed and how IT managers can respond. Discussions will include endpoint security, mobile security and the latest in malware threats. http://www.accelacomm.com/jaw/sfrnl04242012/114/50122263/ _______________________________________________ Scikit-learn-general mailing list [email protected] https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
