Update app.py

app.py

@@ -70,17 +70,17 @@ class Translators:
         model.half() # recommended
         model.eval()
         # Translating from one or several sentences to a sole language
-        src_tokens = tokenizer.encode_source_tokens_to_input_ids([self.input_text, ], target_language=self.tl)
+        src_tokens = tokenizer.encode_source_tokens_to_input_ids(self.input_text, target_language=self.tl)
         # src_tokens = src_tokens.to(self.device)
-        generated_tokens = model.generate(src_tokens)
-        return tokenizer.batch_decode(generated_tokens, skip_special_tokens=True)        
+        # generated_tokens = model.generate(src_tokens)
+        # return tokenizer.batch_decode(generated_tokens, skip_special_tokens=True)[0] 
         # Translating from one or several sentences to corresponding languages
         # src_tokens = tokenizer.encode_source_tokens_to_input_ids_with_different_tags([english_text, english_text, ], target_languages_list=["de", "zh", ])      
         # generated_tokens = model.generate(src_tokens.to(self.device))
         # results = tokenizer.batch_decode(generated_tokens, skip_special_tokens=True)
-        # with torch.no_grad():
-        #     generated_tokens = model.generate(src_tokens)
-        # return tokenizer.batch_decode(generated_tokens, skip_special_tokens=True)
+        with torch.no_grad():
+            generated_tokens = model.generate(src_tokens)
+        return tokenizer.batch_decode(generated_tokens, skip_special_tokens=True)
     
     def hplt(self, opus = False):
         # langs = ['ar', 'bs', 'ca', 'en', 'et', 'eu', 'fi', 'ga', 'gl', 'hi', 'hr', 'is', 'mt', 'nn', 'sq', 'sw', 'zh_hant']