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.
