predict.py

import h5py
import yaoai

import numpy as np

from keras.models import Sequential
from keras.layers import Dense
from keras.layers import Dropout
from keras.layers import LSTM
from keras.layers import Masking


def main():
    sentence_length = 40
    dataX, dataY, story, word_to_int, int_to_word = yaoai.setup(sentence_length, './input.txt')

    model = Sequential([
        Masking(mask_value=0.0, input_shape=(dataX.shape[1:])),
        LSTM(256, return_sequences=True),
        Dropout(0.2),
        LSTM(256, return_sequences=True),
        Dropout(0.2),
        Dense(dataY.shape[2], activation='softmax'),
    ])
    model.load_weights('./model.hdf5')
    model.compile(loss='categorical_crossentropy', optimizer='adam')

    model_output = model.predict(dataX)
    file_path = './output.txt'
    file = open(file_path, 'w')
    for x in model_output:
        output_data = []
        for y in x:
            output_data.append(int_to_word[np.argmax(y)])
        output_data.append('\n\n')
        file.writelines(output_data)
    file.close()

if __name__ == '__main__':
    main()