def call_inference(self):
input_rawdata_filename = self.config['input_rawdata']
input_file = os.path.join(self.config['data_filepath'],
input_rawdata_filename)
with open(input_file, 'rt', encoding='utf-8') as f:
input_data = [line.strip() for line in f.readlines()]
model = load(self.config['model_filepath'])
self._inference(model, input_data)
def _evaluation(self, corpus_test):
model = load(self.config['model_filepath'])
text_list = [''.join(sample.text) for sample in corpus_test]
id_list = [sample.id for sample in corpus_test]
corpus_infer = MtModelEvaluation_Deliverable.inference_process(
model, text_list, id_list)
# symantic_corpus = corpus_test.intersection(corpus_infer)
differ_corpus_tuples = MtModelEvaluation_Deliverable.whats_different(
corpus_test, corpus_infer)
scores = MtModelEvaluation_Deliverable.calc_acc(
differ_corpus_tuples, len(corpus_test))
return scores, differ_corpus_tuples
import deliverable_model as dm import sys model_dir = sys.argv[1] model = dm.load(model_dir) request = dm.make_request(query=["明天天气如何", "上海明天天气"]) result = model.inference(request) print(result.data)
import deliverable_model as dm
import sys
model_dir = sys.argv[1]
endpoint_config = dm.make_endpoint_config(target="127.0.0.1:8500",
model_name="ner")
model = dm.load(model_dir, endpoint_config)
request = dm.make_request(query=["明天天气如何", "上海明天天气"])
result = model.inference(request)
print(result.data)
import deliverable_model as dm
model = dm.load("./res/deliverable_model")
request = dm.make_request(
query=["帮我看看上海26号会下雨吗", "青岛今天天气怎么样", "你以后就叫奥特曼", "打开NFC界面。", "附近哪里有KFC"])
result = model.inference(request)
for i in result.data:
print(i)
print('\n')