Any point in adding data redundancy to joblib dumped objects?
On Tue, Jan 22, 2013 at 5:35 PM, Gael Varoquaux <
[email protected]> wrote:
> On Tue, Jan 22, 2013 at 10:30:01PM +0000, Ark wrote:
> > /home/n7/newenv/lib/python2.6/site-
> > packages/sklearn/externals/joblib/numpy_pickle.pyc in
> read_zfile(file_handle)
> > 69 assert len(data) == length, (
> > 70 "Incorrect data length while decompressing %s."
> > ---> 71 "The file could be corrupted." % file_handle)
> > 72 return data
> > 73
>
> > AssertionError: Incorrect data length while decompressing <open file
> > 'compressedclassifier.joblib_01.npy.z', mode 'rb' at 0x2d5b5d0>.The file
> could
> > be corrupted.
>
> Well, I can't tell for sure, but it really seems that the file is
> corrupted: the length of the data restored does not match the length of
> the data that was originaly given to compress.
>
> G
>
>
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