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max_words = 10000
# Generate split training and testing data (80% training, 20% testing)
x_train, x_test, y_train, y_test = load_encoded_data(data_split=0.8)
# Vectorizing the input data into a Keras readable format (sequence matrix)
tokenizer = Tokenizer(num_words=max_words)
x_train = tokenizer.sequences_to_matrix(x_train, mode='binary')
x_test = tokenizer.sequences_to_matrix(x_test, mode='binary')
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