# coding: utf-8
import sys
sys.path.append('..')
from common.np import *
from rnnlm_gen import BetterRnnlmGen
from dataset import ptb
corpus, word_to_id, id_to_word = ptb.load_data('train')
vocab_size = len(word_to_id)
corpus_size = len(corpus)
model = BetterRnnlmGen()
model.load_params('../ch6/BetterRnnlm.pkl')
start_word = 'you'
start_id = word_to_id[start_word]
skip_words = ['N', '<unk>', '$']
skip_ids = [word_to_id[w] for w in skip_words]
word_ids = model.generate(start_id, skip_ids)
txt = ' '.join([id_to_word[i] for i in word_ids])
txt = txt.replace(' <eos>', '.\n')
print(txt)
model.reset_state()
start_words = 'the meaning of life is'
start_ids = [word_to_id[w] for w in start_words.split(' ')]
import sys
sys.path.append("..")
from rnnlm_gen import BetterRnnlmGen
from dataset import ptb
corpus, word_to_id, id_to_word = ptb.load_data('train')
vocab_size = len(word_to_id)
corpus_size = len(corpus)
model = BetterRnnlmGen()
model.load_params('../ch06_게이트가_추가된_RNN/BetterRnnlm.pkl') # 미리 학습된 가중치 불러와 성능 높임
# 시작 (start) 문자와 건너뛸 (skip) 문자 설정
start_word = 'you'
start_id = word_to_id[start_word]
skip_words = ['N', '<unk>', '$']
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)
# coding: utf-8
import sys
sys.path.append(
'/Users/ahjeong_park/Study/WegraLee/deep-learning-from-scratch-2')
from common.np import *
from rnnlm_gen import BetterRnnlmGen
from dataset import ptb
corpus, word_to_id, id_to_word = ptb.load_data('train')
vocab_size = len(word_to_id)
corpus_size = len(corpus)
model = BetterRnnlmGen()
model.load_params(
'/Users/ahjeong_park/Study/Deep-Learning-from-Scratch-2/ch06/BetterRnnlm.pkl'
)
# start 문자와 skip 문자 설정
start_word = 'you'
start_id = word_to_id[start_word]
skip_words = ['N', '<unk>', '$']
skip_ids = [word_to_id[w] for w in skip_words]
# 문장 생성
word_ids = model.generate(start_id, skip_ids)
txt = ' '.join([id_to_word[i] for i in word_ids])
txt = txt.replace(' <eos>', '.\n')
print(txt)
model.reset_state()
import numpy as np
from rnnlm_gen import RnnlmGen as BetterRnnlmGen
from dataset import ptb
def get_perplexity(model):
from common.util import eval_perplexity
corpus_val, _, _ = ptb.load_data('val')
ppl = eval_perplexity(model, corpus_val)
return ppl
corpus, word_to_id, id_to_word = ptb.load_data('train')
vocab_size = len(word_to_id)
corpus_size = len(corpus)
model = BetterRnnlmGen()
model.load_params('../chapter6/BetterRnnlm.pkl')
# print(get_perplexity(model))
# start文字とskip文字の設定
start_word = 'you'
start_id = word_to_id[start_word]
skip_words = ['N', '<unk>', '$']
skip_ids = [word_to_id[w] for w in skip_words]
# 文章生成
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)
import sys
sys.path.append('..')
from rnnlm_gen import BetterRnnlmGen
from dataset import ptb
corpus, word_to_id, id_to_word = ptb.load_data('train')
vocab_size = len(word_to_id)
corpus_size = len(corpus)
model = BetterRnnlmGen()
model.load_params('../ch06/BetterRnnlm.pkl')
# start文字とskip文字の設定
start_word = 'you'
start_id = word_to_id[start_word]
skip_words =['N', '<unk>', '$']
skip_ids = [word_to_id[w] for w in skip_words]
# 文章生成
word_ids = model.generate(start_id, skip_ids)
txt = ' '.join([id_to_word[i] for i in word_ids])
txt = txt.replace(' <eos>', '\n')
print(txt)
# coding: utf-8
import sys
sys.path.append('/home/hiromasa/deep-learning-from-scratch-2')
from common.np import *
from rnnlm_gen import BetterRnnlmGen
from dataset import ptb
corpus, word_to_id, id_to_word = ptb.load_data('train')
vocab_size = len(word_to_id)
corpus_size = len(corpus)
model = BetterRnnlmGen()
model.load_params(
'/home/hiromasa/deep-learning-from-scratch-2/ch06/BetterRnnlm.pkl')
# start文字とskip文字の設定
start_word = 'you'
start_id = word_to_id[start_word]
skip_words = ['N', '<unk>', '$']
skip_ids = [word_to_id[w] for w in skip_words]
# 文章生成
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(' ')]
