Don't log anything before logging is setup in examples (#12121)

* Don't log anything before logging is setup in examples

* Last example

examples/pytorch/summarization/run_summarization.py

@@ -251,6 +251,24 @@ def main():
     else:
         model_args, data_args, training_args = parser.parse_args_into_dataclasses()
 
+    # Setup logging
+    logging.basicConfig(
+        format="%(asctime)s - %(levelname)s - %(name)s -   %(message)s",
+        datefmt="%m/%d/%Y %H:%M:%S",
+        handlers=[logging.StreamHandler(sys.stdout)],
+    )
+    logger.setLevel(logging.INFO if training_args.should_log else logging.WARN)
+
+    # Log on each process the small summary:
+    logger.warning(
+        f"Process rank: {training_args.local_rank}, device: {training_args.device}, n_gpu: {training_args.n_gpu}"
+        + f"distributed training: {bool(training_args.local_rank != -1)}, 16-bits training: {training_args.fp16}"
+    )
+    # Set the verbosity to info of the Transformers logger (on main process only):
+    if training_args.should_log:
+        transformers.utils.logging.set_verbosity_info()
+    logger.info(f"Training/evaluation parameters {training_args}")
+
     if data_args.source_prefix is None and model_args.model_name_or_path in [
         "t5-small",
         "t5-base",
@@ -278,24 +296,6 @@ def main():
                 "the `--output_dir` or add `--overwrite_output_dir` to train from scratch."
             )
 
-    # Setup logging
-    logging.basicConfig(
-        format="%(asctime)s - %(levelname)s - %(name)s -   %(message)s",
-        datefmt="%m/%d/%Y %H:%M:%S",
-        handlers=[logging.StreamHandler(sys.stdout)],
-    )
-    logger.setLevel(logging.INFO if training_args.should_log else logging.WARN)
-
-    # Log on each process the small summary:
-    logger.warning(
-        f"Process rank: {training_args.local_rank}, device: {training_args.device}, n_gpu: {training_args.n_gpu}"
-        + f"distributed training: {bool(training_args.local_rank != -1)}, 16-bits training: {training_args.fp16}"
-    )
-    # Set the verbosity to info of the Transformers logger (on main process only):
-    if training_args.should_log:
-        transformers.utils.logging.set_verbosity_info()
-    logger.info(f"Training/evaluation parameters {training_args}")
-
     # Set seed before initializing model.
     set_seed(training_args.seed)