增加infer的pipeline

reproduction/chinese_word_segment/train_context.py

@@ -209,9 +209,10 @@ torch.save(test_context_dict, 'models/test_context.pkl')
 # 4. 组装需要存下的内容
 
 from fastNLP.api.processor import ModelProcessor
+from reproduction.chinese_word_segment.process.cws_processor import SegApp2OutputProcessor
 
 model_proc = ModelProcessor(cws_model)
-index2word_proc =
+output_proc = SegApp2OutputProcessor()
 
 pp = Pipeline()
 pp.add_processor(fs2hs_proc)
@@ -222,27 +223,15 @@ pp.add_processor(char_index_proc)
 pp.add_processor(bigram_index_proc)
 pp.add_processor(seq_len_proc)
 
+pp.add_processor(model_proc)
+pp.add_processor(output_proc)
 
-pp.add_processor()
-
-
-
-te_filename = '/hdd/fudanNLP/CWS/Multi_Criterion/all_data/{}/middle_files/{}_test.txt'.format(ds_name, ds_name)
-te_dataset = reader.load(te_filename)
-pp(te_dataset)
-
-batch_size = 64
-te_batcher = Batch(te_dataset, batch_size, SequentialSampler(), use_cuda=False)
-pre, rec, f1 = calculate_pre_rec_f1(cws_model, te_batcher)
-print("f1:{:.2f}, pre:{:.2f}, rec:{:.2f}".format(f1 * 100,
-                                                 pre * 100,
-                                                 rec * 100))
 
 # TODO 这里貌似需要区分test pipeline与infer pipeline
 
-test_context_dict = {'pipeline': pp,
+infer_context_dict = {'pipeline': pp,
                      'model': cws_model}
-torch.save(test_context_dict, 'models/test_context.pkl')
+torch.save(infer_context_dict, 'models/infer_context.pkl')
 
 
 # TODO 还需要考虑如何替换回原文的问题？