def init_metric(self):
nll = Nll(data_loader=self.oracle_data_loader, rnn=self.oracle, sess=self.sess)
self.add_metric(nll)
inll = Nll(data_loader=self.gen_data_loader, rnn=self.generator, sess=self.sess)
inll.set_name('nll-test')
self.add_metric(inll)
def init_metric(self):
nll = Nll(data_loader=self.oracle_data_loader, rnn=self.oracle, sess=self.sess)
self.add_metric(nll)
inll = Nll(data_loader=self.gen_data_loader, rnn=self.generator, sess=self.sess)
inll.set_name('nll-test')
self.add_metric(inll)
def init_real_metric(self):
from utils.metrics.DocEmbSim import DocEmbSim
docsim = DocEmbSim(oracle_file=self.oracle_file, generator_file=self.generator_file, num_vocabulary=self.vocab_size)
self.add_metric(docsim)
inll = Nll(data_loader=self.gen_data_loader, rnn=self.generator, sess=self.sess)
inll.set_name('nll-test')
self.add_metric(inll)
def init_metric(self):
nll = Nll(data_loader=self.oracle_data_loader, rnn=self.oracle, sess=self.sess)
self.add_metric(nll)
inll = Nll(data_loader=self.gen_data_loader, rnn=self.generator, sess=self.sess)
inll.set_name('nll-test')
self.add_metric(inll)
from utils.metrics.DocEmbSim import DocEmbSim
docsim = DocEmbSim(oracle_file=self.oracle_file, generator_file=self.generator_file, num_vocabulary=self.vocab_size)
self.add_metric(docsim)
print("Metrics Applied: " + nll.get_name() + ", " + inll.get_name() + ", " + docsim.get_name())
def init_metric(self):
# nll-oracle: 用oracle去评判generator产生的数据
nll = Nll(data_loader=self.oracle_data_loader,
rnn=self.oracle,
sess=self.sess)
self.add_metric(nll)
# nll-test: 用generator去评判真实数据
inll = Nll(data_loader=self.gen_data_loader,
rnn=self.generator,
sess=self.sess)
inll.set_name('nll-test')
self.add_metric(inll)
def init_real_metric(self):
from utils.metrics.DocEmbSim import DocEmbSim
docsim = DocEmbSim(oracle_file=self.oracle_file,
generator_file=self.generator_file,
num_vocabulary=self.vocab_size)
self.add_metric(docsim)
inll = Nll(data_loader=self.gen_data_loader,
rnn=self.generator,
sess=self.sess)
inll.set_name('nll-test')
self.add_metric(inll)
bleu = Bleu(test_text=self.test_file,
real_text='data/image_coco.txt',
gram=2)
self.add_metric(bleu)
sbleu = SelfBleu(test_text=self.test_file, gram=2)
self.add_metric(sbleu)
def init_real_metric(self):
from utils.metrics.Nll import Nll
from utils.metrics.PPL import PPL
from utils.metrics.DocEmbSim import DocEmbSim
from utils.others.Bleu import Bleu
from utils.metrics.SelfBleu import SelfBleu
if self.valid_ppl:
valid_ppl = PPL(self.valid_data_loader, self.generator, self.sess)
valid_ppl.set_name('valid_ppl')
self.add_metric(valid_ppl)
if self.nll_gen:
nll_gen = Nll(self.gen_data_loader, self.generator, self.sess)
nll_gen.set_name('nll_gen')
self.add_metric(nll_gen)
if self.doc_embsim:
doc_embsim = DocEmbSim(self.oracle_file, self.generator_file,
self.vocab_size)
doc_embsim.set_name('doc_embsim')
self.add_metric(doc_embsim)
if self.bleu:
FLAGS = tf.app.flags.FLAGS
dataset = FLAGS.data
if dataset == "image_coco":
real_text = 'data/testdata/test_image_coco.txt'
elif dataset == "emnlp_news":
real_text = 'data/testdata/test_emnlp_news.txt'
else:
raise ValueError
for i in range(3, 4):
bleu = Bleu(test_text=self.text_file,
real_text=real_text,
gram=i)
bleu.set_name(f"Bleu{i}")
self.add_metric(bleu)
if self.selfbleu:
for i in range(2, 6):
selfbleu = SelfBleu(test_text=self.text_file, gram=i)
selfbleu.set_name(f"Selfbleu{i}")
self.add_metric(selfbleu)
def init_metric(self):
# docsim = DocEmbSim(oracle_file=self.truth_file, generator_file=self.generator_file,
# num_vocabulary=self.vocab_size)
# self.add_metric(docsim)
inll = Nll(data_loader=self.gen_data_loader,
rnn=self.generator,
sess=self.sess)
inll.set_name('nll-test')
self.add_metric(inll)
bleu1 = Bleu(test_text=self.test_file,
real_text=self.trunc_train_file,
gram=1)
bleu1.set_name('BLEU-1')
self.add_metric(bleu1)
bleu2 = Bleu(test_text=self.test_file,
real_text=self.trunc_train_file,
gram=2)
bleu2.set_name('BLEU-2')
self.add_metric(bleu2)
