Closed dionman closed 6 years ago
No there is not. A lot of the code is in cython and there are no sparse matrices for that.
-- Flavio
On Thu, Sep 14, 2017 at 2:03 PM, dionman notifications@github.com wrote:
Running the script for reciprocal rank computation on the predictions of the model for the brightkite dataset, I am getting MemoryError upon the creation of predictions array
`
PYTHONPATH=. python scripts/mrr.py data/output_brightkite.h5 rss.dat data/predictions_brightkite.dat &
matrix shape : (10000, 3) (10000, 1) (525267, 10) Traceback (most recent call last): File "scripts/mrr.py", line 86, in plac.call(main) File "/usr/local/lib/python2.7/dist-packages/plac_core.py", line 328, in call cmd, result = parser.consume(arglist) File "/usr/local/lib/python2.7/dist-packages/plac_core.py", line 207, in consume return cmd, self.func(*(args + varargs + extraopts), **kwargs) File "scripts/mrr.py", line 77, in main HSDs, previous_stamps, Theta_zh, Psi_sz, count_z, kernel, True) File "tribeflow/_eval.pyx", line 97, in tribeflow._eval.reciprocal_rank (tribeflow/_eval.c:2525) np.zeros(shape=(HOs.shape[0], ns), dtype='d') MemoryError `
Is there a scipy.sparse based workaround for large datasets?
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Running the script for reciprocal rank computation on the predictions of the model for the brightkite dataset, I am getting MemoryError upon the creation of predictions array
Is there a scipy.sparse based workaround for large datasets?