Update app.py

app.py

@@ -15,7 +15,7 @@ def preprocess(temp):
     temp = re.sub(u",", "，", temp)
     temp = re.sub(u"\?", "？", temp)
     temp = re.sub(u"!", "！", temp)
-    temp = re.sub(u".", "。", temp)
+    temp = re.sub(u"\.", "。", temp)
     temp = re.sub('[^\u4e00-\u9fa5，。？！\n]+', '', temp)
     temp = re.sub(u"\n", "，", temp)
     for _ in range(int(len(temp) / 2)):
@@ -28,21 +28,27 @@ def preprocess(temp):
     return temp
 
 def classify_text(inp):
+    print(inp)
     inp = preprocess(inp)
+    print(inp)
     inp = tokenizer(inp, padding=True, max_length=512, truncation=True, return_tensors="pt")
     print(inp)
     with torch.no_grad():
         logits = model(**inp).logits
     print(logits)
+    print(logits.argmax().item())
     # logits = torch.nn.Softmax(dim=0)(logits)
     # print(logits)
     # return {labels[i]: float(logits[i].item()) for i in range(len(labels))}
     return {logits.argmax().item() : labels[logits.argmax().item()]}
 
+input = '明天又是好日子\n千金的光阴不能等\n明天又是好日子\n赶上了盛世咱享太平\n今天是个好日子\n心想的事儿都能成\n明天又是好日子\n千金的光阴不能等\n今天明天都是好日子\n赶上了盛世咱享太平'
+
+
 gr.Interface(
     classify_text,
     # gr.inputs.Image(),
-    gr.inputs.Textbox(lines=5,default=""),
+    gr.inputs.Textbox(lines=5,default=input),
     outputs = 'label'
     # inputs='image',
     # outputs='label',