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.
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