import pickle
file = open('./Data/T2_data_train.pt', 'rb')
df = pickle.load(file)[:120]
German_corpus = Corpus()
English_corpus = Corpus()
German_corpus.load_vocab('./Parameters/German_corpus1k.pt')
English_corpus.load_vocab('./Parameters/English_corpus1k.pt')
German_vectorizer = WordsToVec(German_corpus, 150)
English_vectorizer = WordsToVec(English_corpus, 150)
German_vectorizer.load_model_state('./Parameters/German_vectors_150d')
English_vectorizer.load_model_state('./Parameters/English_vectors_150d')
my_translator = Translator(German_corpus,
English_corpus,
German_vectorizer,
English_vectorizer,
dec_GRU_count=2,
enc_GRU_count=2,
hidden_size=128,
use_feedforward=True)
# my_translator.train(df, epochs=50, batch_size=32, lr=0.001, lr_reduce=0.1)
my_translator.load_model('./Parameters/translator_feedforwardatt_epoch50.pt')
my_translator.reinforce_train(df, epochs=50, batch_size=32)
#coding:utf-8
from Translator import Translator
# 英日翻訳のテスト
en_lines = open('en-test.txt').read().split('\n')
epoch_num = 100
for epoch in range(epoch_num):
model = Translator()
modelfile = "./model/en2ja-" + str(epoch) + ".model"
model.load_model(modelfile)
for i in range(len(en_lines) - 1):
en_words = en_lines[i].lower().split()
ja_words = model.test(en_words)
print("{0}: {1}".format(epoch, ' '.join(ja_words)))
