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I mean datasets were used for training and testing, ie mnist_train.data, mnist_test.data, mnist_valid.data and mnist_train.solution I tried to download from https://competitions.codalab.org/competitions/4061#participate , but the link is broken. Pada Senin, 16 Januari 2017 14.56.35 UTC+7, krenova Math menulis: > > Hi, it should be working, i just accessed it. > > You may want to try this link to directly access the zip file: > > https://sites.google.com/a/chalearn.org/automl/general-mnist---cnn-example/MNISTrelease2.zip?attredirects=0&d=1 > > On Thursday, January 12, 2017 at 4:19:46 PM UTC+8, Desy rona wrote: >> >> Thanks for the solution .. >> but I had a little trouble downloading the dataset, the link is broken, is >> there any other links? >> >> Pada Selasa, 10 Januari 2017 12.47.20 UTC+7, krenova Math menulis: >>> >>> Hi Desy, >>> >>> I faced this issue before. >>> >>> One way to do this is to save and pickle all the weights. A good >>> reference would be to download and study the codes from the following: >>> >>> https://sites.google.com/a/chalearn.org/automl/general-mnist---cnn-example >>> >>> On Tuesday, January 10, 2017 at 1:22:22 PM UTC+8, Desy rona wrote: >>>> >>>> >>>> >>>> I am using the cnn text classification written by Yoo Kim >>>> <https://github.com/yoonkim/CNN_sentence> for sentiment analysis. This >>>> code applies cross validation to check the quality of learned model. >>>> However, I want to save the learned weights and biases, so I can apply the >>>> learned model on new instances one by one for the prediction purpose. I >>>> appreciate if someone provides an example of how I can do that. I know >>>> that >>>> I should use pickle load and dumb to do that, but I am not sure exactly >>>> which part of the code I should use them I want to have a separate test.py >>>> file so I can only test the trained model on a test sample without >>>> training >>>> the model again. how I should save and then predict based on saved model? >>>> I am new to both python and theano. So I appreciate it if someone can >>>> provide an example. >>>> >>> -- --- You received this message because you are subscribed to the Google Groups "theano-users" group. To unsubscribe from this group and stop receiving emails from it, send an email to theano-users+unsubscr...@googlegroups.com. For more options, visit https://groups.google.com/d/optout.
