def dev_test(self, dev_x, dev_y, word2id, tag2id):
batches_x, batches_y, batches_seq_len = get_batches(
dev_x, dev_y, word2id, tag2id, self.bilstm.batch_size)
pred_lists = []
labels = []
id2tag = dict((id_, tag) for tag, id_ in tag2id.items())
for i in range(len(batches_x)):
pred_labels = self.pred_labels(batches_x[i], batches_y[i],
batches_seq_len[i])
for j in range(len(pred_labels)):
for k in range(batches_seq_len[i][j]):
pred_lists.append(id2tag[pred_labels[j][k]])
labels.append(id2tag[batches_y[i][j][k]])
metrics = Metrics(labels, pred_lists)
metrics.report_scores()
def main():
print('读取数据...')
train_word_lists, train_tag_lists, word2id, tag2id = build_corpus('train')
dev_word_lists, dev_tag_lists = build_corpus('dev', maek_vocab = False)
test_word_lists, test_tag_lists = build_corpus('test', maek_vocab = False)
print('训练HMM模型...')
hmm_model = HMMModel(len(tag2id), len(word2id))
hmm_model.train(train_word_lists, train_tag_lists, word2id, tag2id)
pred_tag_lists = hmm_model.test(test_word_lists, word2id, tag2id)
metrics = Metrics(test_tag_lists, pred_tag_lists)
metrics.report_scores()
print('训练CRF模型...')
crf_model = CRFModel(max_iterations = 90)
crf_model.train(train_word_lists, train_tag_lists)
pred_tag_lists = crf_model.test(test_word_lists)
metrics = Metrics(test_tag_lists, pred_tag_lists)
metrics.report_scores()
print('训练BiLSTM模型...')
word2id, tag2id = extend_maps(word2id, tag2id)
bilstm = BiLSTM(len(word2id), len(tag2id))
bilstm.train(train_word_lists, train_tag_lists, dev_word_lists, dev_tag_lists, word2id, tag2id, 0.8)
bilstm.dev_test(test_word_lists, test_tag_lists, word2id, tag2id)
bilstm.close_sess()
print('训练BiLSTM-CRF模型...')
bilstm_crf = BiLSTM_CRF(len(word2id), len(tag2id))
bilstm_crf.train(train_word_lists, train_tag_lists, dev_word_lists, dev_tag_lists, word2id, tag2id, 0.8)
bilstm_crf.dev_test(test_word_lists, test_tag_lists, word2id, tag2id)
bilstm_crf.close_sess()