Hi Ben, This actually sounds like a bug in this case! At a glance, the code should use the correct BLAS calls for the data type you provide. Can you reproduce this with a simple small example that gets different results if the data is 32 vs 64 bit? Would you mind filing an issue?
Thanks, Vlad On Tue, Feb 14, 2017 at 8:19 PM, Benjamin Merkt <[email protected]> wrote: > OK, the issue is resolved. My dictionary was still in 32bit float from > saving. When I convert it to 64float before calling fit it works fine. > > Sorry to bother. > > > > On 14.02.2017 11:00, Benjamin Merkt wrote: >> >> Hi, >> >> I tried that with no effect. The fit still breaks after two iterations. >> >> If I set precompute=True I get three coefficients instead of only two. >> My Dictionary is fairly large (currently 128x42000). Is it even feasible >> to use OMP with such a big Matrix (even with ~120GB ram)? >> >> -Ben >> >> >> >> On 13.02.2017 23:31, Vlad Niculae wrote: >>> >>> Hi, >>> >>> Are the columns of your matrix normalized? Try setting `normalized=True`. >>> >>> Yours, >>> Vlad >>> >>> On Mon, Feb 13, 2017 at 6:55 PM, Benjamin Merkt >>> <[email protected]> wrote: >>>> >>>> Hi everyone, >>>> >>>> I'm using OrthogonalMatchingPursuit to get a sparse coding of a >>>> signal using >>>> a dictionary learned by a KSVD algorithm (pyksvd). However, during >>>> the fit I >>>> get the following RuntimeWarning: >>>> >>>> /usr/local/lib/python2.7/dist-packages/sklearn/linear_model/omp.py:391: >>>> RuntimeWarning: Orthogonal matching pursuit ended prematurely due to >>>> linear >>>> dependence in the dictionary. The requested precision might not have >>>> been >>>> met. >>>> >>>> copy_X=copy_X, return_path=return_path) >>>> >>>> In those cases the results are indeed not satisfactory. I don't get the >>>> point of this warning as it is common in sparse coding to have an >>>> overcomplete dictionary an thus also linear dependency within it. That >>>> should not be an issue for OMP. In fact, the warning is also raised >>>> if the >>>> dictionary is a square matrix. >>>> >>>> Might this Warning also point to other issues in the application? >>>> >>>> >>>> Thanks, Ben >>>> >>>> _______________________________________________ >>>> scikit-learn mailing list >>>> [email protected] >>>> https://mail.python.org/mailman/listinfo/scikit-learn >>> >>> _______________________________________________ >>> scikit-learn mailing list >>> [email protected] >>> https://mail.python.org/mailman/listinfo/scikit-learn >>> >> _______________________________________________ >> scikit-learn mailing list >> [email protected] >> https://mail.python.org/mailman/listinfo/scikit-learn > > _______________________________________________ > scikit-learn mailing list > [email protected] > https://mail.python.org/mailman/listinfo/scikit-learn _______________________________________________ scikit-learn mailing list [email protected] https://mail.python.org/mailman/listinfo/scikit-learn
