Your code is perfectly fine. You are training 10 networks in parallel (since you have n_jobs=10), so each network started training in its own, and outputing its progress independently.
Given enough amount of time, you will see that all 10 networks will eventually get to epoch number 2, and 10 messages of epoch #2 will be printed out. -- Julio > El 16 mar 2017, a las 17:59, Carlton Banks <[email protected]> escribió: > > I haven’t a verbosity level in the code?… but set it to 3 as suggested by > Julio… It did not seem to work.. > > https://www.dropbox.com/s/nr5rattzts0wuvd/Screenshot%20from%202017-03-16%2017%3A56%3A26.png?dl=0 > >> Den 16. mar. 2017 kl. 17.51 skrev Carlton Banks <[email protected]>: >> >> Ohh.. actually the data size cannot be wrong.. >> input_train and output_train are both lists… which i then only take a part >> of … and then make then to a np.array… >> >> So that should not be incorrect. >> >>> Den 16. mar. 2017 kl. 17.33 skrev Carlton Banks <[email protected]>: >>> >>> I am running this on a super computer, so yes I am running a few training >>> sessions. >>> I guess i will look at the verbose, and the adjust the training data size. >>> >>>> Den 16. mar. 2017 kl. 17.30 skrev Julio Antonio Soto de Vicente >>>> <[email protected]>: >>>> >>>> IMO this has nothing to do with GridSearchCV itself... >>>> >>>> It rather looks like different (verbose) keras models are being trained >>>> simultaneously, and therefore "collapsing" your stdout. >>>> >>>> I recommend setting Keras verbosity level to 3, in order to avoid printing >>>> the progress bars during GridSearchCV (which can be misleading). >>>> >>>> -- >>>> Julio >>>> >>>>> El 16 mar 2017, a las 16:50, Carlton Banks <[email protected]> escribió: >>>>> >>>>> I am currently using grid search to optimize my keras model… >>>>> >>>>> Something seemed a bit off during the training? >>>>> >>>>> https://www.dropbox.com/s/da0ztv2kqtkrfpu/Screenshot%20from%202017-03-16%2016%3A43%3A42.png?dl=0 >>>>> >>>>> For some reason is the training for each epoch not done for all >>>>> datapoints?… >>>>> >>>>> What could be wrong? >>>>> >>>>> Here is the code: >>>>> >>>>> http://pastebin.com/raw/itJFm5a6 >>>>> >>>>> Anything that seems off? >>>>> _______________________________________________ >>>>> 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
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