machine learning - Keras Text Preprocessing - Saving Tokenizer object to file for scoring

Question

I've trained a sentiment classifier model using Keras library by following the below steps(broadly).

1. Convert Text corpus into sequences using Tokenizer object/class
2. Build a model using the model.fit() method
3. Evaluate this model

Now for scoring using this model, I was able to save the model to a file and load from a file. However I've not found a way to save the Tokenizer object to file. Without this I'll have to process the corpus every time I need to score even a single sentence. Is there a way around this?

Answer 1

The most common way is to use either pickle or joblib. Here you have an example on how to use pickle in order to save Tokenizer:

import pickle

# saving
with open('tokenizer.pickle', 'wb') as handle:
    pickle.dump(tokenizer, handle, protocol=pickle.HIGHEST_PROTOCOL)

# loading
with open('tokenizer.pickle', 'rb') as handle:
    tokenizer = pickle.load(handle)