switch back transformer logger

app.py

@@ -24,10 +24,12 @@ from gradio.themes.utils import colors, fonts, sizes
 import argparse
 
 import langid
-from transformers import pipeline, AutoModelForSeq2SeqLM, AutoTokenizer
+from transformers import pipeline, AutoModelForSeq2SeqLM, AutoTokenizer, logging
 from easynmt import EasyNMT
 
-import logging
+# Initialize logging
+logging.set_verbosity_info()
+logger = logging.get_logger("transformers")
 
 # # Initialize nllb-200 models
 # tokenizer = AutoTokenizer.from_pretrained("facebook/nllb-200-distilled-600M")
@@ -36,11 +38,11 @@ import logging
 # Initialize mbart50 models
 mbart_m2en_model = EasyNMT("mbart50_m2en")
 mbart_en2m_model = EasyNMT("mbart50_en2m")
-logging.info("mbart50 models initialized")
+logger.info("mbart50 models initialized")
 
 # Initialize m2m_100 models
 m2m_model = EasyNMT("m2m_100_1.2B")
-logging.info("m2m_100 models initialized")
+logger.info("m2m_100 models initialized")
 
 
 class myTheme(Base):
@@ -106,7 +108,7 @@ def detect_lang(article):
     """
 
     result_lang = langid.classify(article)
-    logging.info(f"language detected as {result_lang}")
+    logger.info(f"language detected as {result_lang}")
     return result_lang[0]
 
 
@@ -176,21 +178,21 @@ def mbart_trans(article, target_language):
     elif target_language == "Chinese":
         target_lang = "zh"
 
-    logging.info(f"Article to translate : {article}")
-    logging.info(f"Chose which translation model: mbart model")
-    logging.info(f"Language selected: {target_language}")
+    logger.info(f"Article to translate : {article}")
+    logger.info(f"Chose which translation model: mbart model")
+    logger.info(f"Language selected: {target_language}")
 
     if result_lang != target_lang:
         if target_language == "English":
             translated = mbart_m2en_model.translate(article, target_lang="en")
-            logging.info(f"Translated Result: {translated}")
+            logger.info(f"Translated Result: {translated}")
             return translated
         else:
             translated = mbart_en2m_model.translate(article, target_lang="zh")
-            logging.info(f"Translated Result: {translated}")
+            logger.info(f"Translated Result: {translated}")
             return translated
     else:
-        logging.warning(
+        logger.warning(
             "Error: You chose the same language as the article detected language. Please reselect language and try again."
         )
         return "Error: You chose the same language as the article detected language. Please reselect language and try again."
@@ -203,16 +205,16 @@ def m2m_trans(article, target_language):
     elif target_language == "Chinese":
         target_lang = "zh"
 
-    logging.info(f"Article to translate : {article}")
-    logging.info(f"Chose which translation model: m2m model")
-    logging.info(f"Language selected: {target_language}")
+    logger.info(f"Article to translate : {article}")
+    logger.info(f"Chose which translation model: m2m model")
+    logger.info(f"Language selected: {target_language}")
 
     if result_lang != target_lang:
         translated = m2m_model.translate(article, target_lang)
-        logging.info(f"Translation Result: {translated}")
+        logger.info(f"Translation Result: {translated}")
         return translated
     else:
-        logging.warning(
+        logger.warning(
             f"Error: You chose the same language as the article detected language. Please reselect language and try again."
         )
         return "Error: You chose the same language as the article detected language. Please reselect language and try again."