Revert run_model

generator.py

@@ -34,34 +34,29 @@ import streamlit as st
 # hfmodel = pickle.load(open('models/hfmodel.sav', 'rb'))
 
 def load_model():
-  hfm = pickle.load(open('t5_model.sav','rb'))
+  hfm = pickle.load(open('hfmodel.sav','rb'))
   hft = T5TokenizerFast.from_pretrained("t5-base")
   model = pickle.load(open('electra_model.sav','rb'))
   tok = et.from_pretrained("mrm8488/electra-small-finetuned-squadv2")
   # return hfm, hft,tok, model
   return hfm, hft,tok, model
 
-hfmodel, hftokenizer,tok, model = load_model()
+hfmodel, hftokenizer, tok, model = load_model()
 
 def run_model(input_string, **generator_args):
   generator_args = {
   "max_length": 256,
   "num_beams": 4,
   "length_penalty": 1.5,
-  "no_repeat_ngram_size": 2,
-  "early_stopping": False,
+  "no_repeat_ngram_size": 3,
+  "early_stopping": True,
   }
   # tokenizer = att.from_pretrained("ThomasSimonini/t5-end2end-question-generation")
-  # output = nlp(input_string)
-    
   input_string = "generate questions: " + input_string + " </s>"
-    
-  inputs = tokenize([input_string])
-    
-  res = hfmodel.generate(input_ids=inputs['input_ids'], attention_mask=inputs['attention_mask'], **generator_args)
-  output = hftokenizer.decode(res[0], skip_special_tokens=True)
-  # output = output.split('</sep>')
-  # output = [o.strip() for o in output[:-1]]
+  input_ids = hftokenizer.encode(input_string, return_tensors="pt")
+  res = hfmodel.generate(input_ids, **generator_args)
+  output = hftokenizer.batch_decode(res, skip_special_tokens=True)
+  output = [item.split("<sep>") for item in output]
   return output
 
 
@@ -126,18 +121,13 @@ def read_file(filepath_name):
 
 def create_string_for_generator(context):
     gen_list = gen_question(context)
-    return gen_list
+    return (gen_list[0][0]).split('? ')
 
 def creator(context):
   questions = create_string_for_generator(context)
-  questions = questions.split('?')
+  # questions = questions.split('?')
   pairs = []
   for ques in questions:
-    l = len(ques)
-    if(l == 0):
-        continue
-    if ques[l-1] != '?':
-        ques = ques + '?'
     pair = QA(ques,context)
     print(pair)
     pairs.append(pair)