model = BetterRnnlmGen()
model.load_params('../ch6/BetterRnnlm.pkl')
start_word = 'you'
start_id = word_to_id[start_word]
skip_words = ['N', '<unk>', '$']
skip_ids = [word_to_id[w] for w in skip_words]
word_ids = model.generate(start_id, skip_ids)
txt = ' '.join([id_to_word[i] for i in word_ids])
txt = txt.replace(' <eos>', '.\n')
print(txt)
model.reset_state()
start_words = 'the meaning of life is'
start_ids = [word_to_id[w] for w in start_words.split(' ')]
for x in start_ids[:-1]:
x = np.array(x).reshape(1, 1)
model.predict(x)
word_ids = model.generate(start_ids[-1], skip_ids)
word_ids = start_ids[:-1] + word_ids
txt = ' '.join([id_to_word[i] for i in word_ids])
txt = txt.replace(' <eos>', '.\n')
print('-' * 50)
print(txt)
model = BetterRnnlmGen()
model.load_params('../ch06_게이트가_추가된_RNN/BetterRnnlm.pkl') # 미리 학습된 가중치 불러와 성능 높임
# 시작 (start) 문자와 건너뛸 (skip) 문자 설정
start_word = 'you'
start_id = word_to_id[start_word]
skip_words = ['N', '<unk>', '$']
skip_ids = [word_to_id[w] for w in skip_words]
# 문장 생성
word_ids = model.generate(start_id, skip_ids)
txt = ' '.join([id_to_word[i] for i in word_ids])
txt = txt.replace('<eos>', '.\n')
print(txt)
model.reset_state() # not continue the previous sequences anymore, now you will start feeding new sequences.
start_words = 'the meaning of life is'
start_ids = [word_to_id[w] for w in start_words.split(' ')]
for x in start_ids[:-1]:
x = np.array(x).reshape(1, 1)
model.predict(x) # shape = (1, 1, 10000)
word_ids = model.generate(start_ids[-1], skip_ids)
word_ids = start_ids[:-1] + word_ids
txt = ' '.join([id_to_word[i] for i in word_ids])
txt = txt.replace(' <eos>', '.\n')
print('-' * 50)
print(txt)