def rewrite(self, batch):
unk = self.vocab.word2id['<unk>']
model = self.model
h_ori, h_tsf = self.sess.run(
[model.h_ori, model.h_tsf],
feed_dict={
model.dropout: 1,
model.batch_size: batch['size'],
model.enc_inputs: batch['enc_inputs'],
model.labels: batch['labels']
})
ori = self.decode(h_ori)
ori = [[self.vocab.id2word[i] for i in sent] for sent in ori[0].sent]
ori = strip_eos(ori)
tsf_beam = self.decode(h_tsf)
tsf = []
for idx1, sent in enumerate(tsf_beam[0].sent):
t = []
for idx2, i in enumerate(sent):
if i == unk:
for j in range(self.beam_width):
if tsf_beam[j].sent[idx1][idx2] != unk:
t.append(self.vocab.id2word[tsf_beam[j].sent[idx1]
[idx2]])
break
else:
t.append(self.vocab.id2word[i])
tsf.append(t)
tsf = strip_eos(tsf)
return ori, tsf
def rewrite(self, batch):
model = self.model
h_ori, h_tsf= self.sess.run([model.h_ori, model.h_tsf],
feed_dict={model.dropout: 1,
model.batch_size: batch['size'],
model.enc_inputs: batch['enc_inputs'],
model.labels: batch['labels']})
ori = self.decode(h_ori)
ori = [[self.vocab.id2word[i] for i in sent] for sent in ori]
ori = strip_eos(ori)
tsf = self.decode(h_tsf)
tsf = [[self.vocab.id2word[i] for i in sent] for sent in tsf]
tsf = strip_eos(tsf)
return ori, tsf
def rewrite(self, batch):
model = self.model
logits_ori, logits_tsf = self.sess.run(
[model.hard_logits_ori, model.hard_logits_tsf],
feed_dict={model.dropout: 1,
model.batch_size: batch['size'],
model.enc_inputs: batch['enc_inputs'],
model.dec_inputs: batch['dec_inputs'],
model.labels: batch['labels']})
ori = np.argmax(logits_ori, axis=2).tolist()
ori = [[self.vocab.id2word[i] for i in sent] for sent in ori]
ori = strip_eos(ori)
tsf = np.argmax(logits_tsf, axis=2).tolist()
tsf = [[self.vocab.id2word[i] for i in sent] for sent in tsf]
tsf = strip_eos(tsf)
return ori, tsf