def __init__(self, inputer: Inputer, modelTrainer: object) -> object:
self.config = inputer.config
self.inputer = inputer
self.modelTrainer = modelTrainer
config = self.config
if not os.path.exists(config.model_file_path):
vector = inputer.getSentenceVectorFromFile(config.corpus_file_path)
print("句子向量矩阵的shape" + str(vector.sentence_vec.shape)) #(346, 100)
print("位置向量矩阵的shape" + str(vector.position_vec.shape)) # (346, 100, 40)
print("词性向量矩阵的shape" + str(vector.pos_vec.shape)) # (346, 100, 84)
print("关系分类矩阵的shape" + str(vector.classifications_vec.shape)) # (346, 21)
self.model = self.train(vector)
self.model.save(config.model_file_path)
self.model = load_model(config.model_file_path)
def __init__(self, inputer: Inputer, modelTrainer: object) -> object:
self.config = inputer.config
self.inputer = inputer
self.modelTrainer = modelTrainer
config = self.config
if not os.path.exists(config.model_file_path):
vector = inputer.getSentenceVectorFromFile(config.corpus_file_path)
print(vector.sentence_vec.shape)
print(vector.position_vec.shape)
print(vector.pos_vec.shape)
print(vector.classifications_vec.shape)
self.model = self.train(vector)
self.model.save(config.model_file_path)
self.model = load_model(config.model_file_path)
def predict(self, sentence_vector: SentencesVector):
classVector = np.ones(sentence_vector.classifications_vec.shape)
prop = self.model.predict({
'sequence_input': sentence_vector.embedded_sequences,
"posi_input": sentence_vector.position_vec,
"typeInput": classVector
})
return sentence_vector.prop2index(prop)
if __name__ == '__main__':
config = Configuration(
position_matrix_file_path="../data/posi_matrix.npy",
word2vec_file_path="../data/needed_zh_word2vec.bin",
POS_list_file_path="../data/military/pos_list.txt",
types_file_path="../data/military/relations_zh.txt",
corpus_file_path="../data/military/train_zh.txt",
model_file_path="../data/model/re_military_zh_model.bilstm.hdf5",
)
inputer = Inputer(config)
trainer = Trainer(inputer, BiLstmTrainer())
outputer = Outputer(trainer)
predict_texts = [
"<loc>美国</loc>目前共有2级11艘航空母舰，包括企业级核动力航母1艘，尼米兹级核动力航母10<loc>艘，</loc>全部采用核动力发动机",
"<loc>美国</loc>经过多年航空母舰的发<loc>展，</loc>一直以来都是全球拥有最多、排水量和体积最大、舰载机搭载数量最多、作战效率最强大、而且全部使用核动力航空母舰的国家"
]
import json
print(
json.dumps(outputer.getDescription(predict_texts), ensure_ascii=False))