diff --git a/flask_macbert.py b/flask_macbert.py
index 818afb4..a3f0bf9 100644
--- a/flask_macbert.py
+++ b/flask_macbert.py
@@ -4,7 +4,8 @@ from flask import request
 import operator
 import torch
 from transformers import BertTokenizerFast, BertForMaskedLM
-device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+# device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+device = "cpu"
 import uuid
 import json
 from threading import Thread
@@ -121,20 +122,53 @@ def get_errors(corrected_text, origin_text):
 
 
 def main(texts):
+    batch_size_sentent_class = []
+
+    for text in texts:
+        batch_size_sentent_class.append(SentenceUlit(text))
+
+    batch_pre = []
+    batch_nums = []
+    for sentent_class in batch_size_sentent_class:
+        sentents = sentent_class.sentence_batch
+        batch_pre.extend(sentents)
+        batch_nums.append(len(sentents))
+
     with torch.no_grad():
-        outputs = model(**tokenizer(texts, padding=True, return_tensors='pt').to(device))
+        # input_pre = tokenizer(batch_pre, padding=True, return_tensors='pt').to(device)
+        # input_ids = input_pre['input_ids'].to(device)
+        # token_type_ids = input_pre["token_type_ids"].to(device)
+        # attention_mask = input_pre['attention_mask'].to(device)
+        # outputs = model(input_ids, token_type_ids, attention_mask)
+        outputs = model(**tokenizer(batch_pre, padding=True, return_tensors='pt').to(device))
 
-    result = []
-    print(outputs.logits)
-    for ids, text in zip(outputs.logits, texts):
+    batch_res = []
 
+    for ids,data_dan in zip(outputs.logits,batch_pre):
         _text = tokenizer.decode(torch.argmax(ids, dim=-1), skip_special_tokens=True).replace(' ', '')
-        corrected_text = _text[:len(text)]
-        print(corrected_text)
+        corrected_text = _text[:len(data_dan)]
+        batch_res.append(corrected_text)
+    print(batch_pre)
+    print(batch_res)
+    batch_new = []
+    index = 0
+    for i in batch_nums:
+        index_new = index + i
+        batch_new.append(batch_res[index:index_new])
+        index = index_new
+
+    batch_pre_data = []
+    for dan, sentent_class in zip(batch_new, batch_size_sentent_class):
+        sentent_class.inf_ulit(dan)
+        batch_pre_data.append("".join(sentent_class.sentence_list))
+
+    result = []
+    for text, corrected_text in zip(texts,batch_pre_data):
         corrected_text, details = get_errors(corrected_text, text)
         result.append({"old": text,
                        "new": corrected_text,
                        "re_pos": details})
+
     return result
 
 
@@ -156,4 +190,4 @@ if __name__ == "__main__":
                         '%(asctime)s - %(pathname)s[line:%(lineno)d] - %(levelname)s: %(message)s'
                         # 日志格式
                         )
-    app.run(host="0.0.0.0", port=16000, threaded=True, debug=False)
+    app.run(host="0.0.0.0", port=16001, threaded=True, debug=False)