def validate(self, sess, x_val, y_val, true_val):
# Calculate BLEU on validation data
hypotheses_val = []
references_val = []
symbol = []
if self.config['experiment'] == 'qgen':
symbol.append('?')
for batch_i, (input_batch, output_batch, source_sent_lengths,
tar_sent_lengths) in enumerate(
data_utils.get_batches(x_val, y_val,
self.batch_size)):
answer_logits = sess.run(self.inference_logits,
feed_dict={
self.input_data: input_batch,
self.source_sentence_length:
source_sent_lengths,
self.keep_prob: 1.0
})
for k, pred in enumerate(answer_logits):
hypotheses_val.append(
word_tokenize(" ".join([
self.decoder_idx_word[i]
for i in pred if i not in [self.pad, -1, self.eos]
])) + symbol)
references_val.append(
[word_tokenize(true_val[batch_i * self.batch_size + k])])
bleu_scores = eval_utils.calculate_bleu_scores(references_val,
hypotheses_val)
self.epoch_bleu_score_val['1'].append(bleu_scores[0])
self.epoch_bleu_score_val['2'].append(bleu_scores[1])
self.epoch_bleu_score_val['3'].append(bleu_scores[2])
self.epoch_bleu_score_val['4'].append(bleu_scores[3])
def predict(self, checkpoint, x_test, y_test, true_test):
pred_logits = []
hypotheses_test = []
references_test = []
symbol=[]
if self.config['experiment'] == 'qgen':
symbol.append('?')
with tf.Session() as sess:
sess.run(tf.global_variables_initializer())
saver = tf.train.Saver()
saver.restore(sess, checkpoint)
for batch_i, (input_batch, output_batch, source_sent_lengths, tar_sent_lengths) in enumerate(
data_utils.get_batches(x_test, y_test, self.batch_size)):
result = sess.run(self.inference_logits, feed_dict={self.input_data: input_batch,
self.source_sentence_length: source_sent_lengths,
self.keep_prob: 1.0})
pred_logits.extend(result)
for k, pred in enumerate(result):
hypotheses_test.append(
word_tokenize(" ".join(
[self.decoder_idx_word[i] for i in pred if i not in [self.pad, -1, self.eos]])) + symbol)
references_test.append([word_tokenize(true_test[batch_i * self.batch_size + k])])
bleu_scores = eval_utils.calculate_bleu_scores(references_test, hypotheses_test)
print('BLEU 1 to 4 : {}'.format(' | '.join(map(str, bleu_scores))))
return pred_logits