logging

app.py

@@ -1,15 +1,10 @@
 from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
-from transformers.utils import logging
 from datetime import datetime
 import gradio as gr
 import spaces
 import torch
 
 
-logging.set_verbosity_info()
-logger = logging.get_logger("transformers")
-logger.info("INFO")
-
 DEVICE = 'cuda' if torch.cuda.is_available() else 'cpu'
 DEBUG_UI = False
 LANGS = {
@@ -59,9 +54,9 @@ else:
         output = '\n'.join(result)
 
         end = datetime.now()
-        time = (end - start).microseconds / 1_000_000
-        max_text = max([len(line) for line in lines] + [0])
-        logger.info(f'time: {time:5.1f}\tvolume: {max_text:5}x{len(lines)}')
+        input_shape = tuple(inputs.input_ids.shape)
+        output_shape = tuple(translated_tokens.shape)
+        print(f'[{end}] {DEVICE}_time - {end-start}; input {input_shape} / output {output_shape};')
         return output