diff --git a/infer/modules/train/train.py b/infer/modules/train/train.py
index ad9a5b5..b03d572 100644
--- a/infer/modules/train/train.py
+++ b/infer/modules/train/train.py
@@ -23,16 +23,14 @@ try:
 
     if torch.xpu.is_available():
         from infer.modules.ipex import ipex_init
-
-        ipex_init()
-
-        from torch.xpu.amp import autocast
         from infer.modules.ipex.gradscaler import gradscaler_init
+        from torch.xpu.amp import autocast
 
         GradScaler = gradscaler_init()
+        ipex_init()
     else:
         from torch.cuda.amp import GradScaler, autocast
-except Exception:  # pylint: disable=broad-exception-caught
+except Exception:
     from torch.cuda.amp import GradScaler, autocast
 
 torch.backends.cudnn.deterministic = False
@@ -106,11 +104,10 @@ def main():
     os.environ["MASTER_ADDR"] = "localhost"
     os.environ["MASTER_PORT"] = str(randint(20000, 55555))
     children = []
-    logger = utils.get_logger(hps.model_dir)
     for i in range(n_gpus):
         subproc = mp.Process(
             target=run,
-            args=(i, n_gpus, hps, logger),
+            args=(i, n_gpus, hps),
         )
         children.append(subproc)
         subproc.start()
@@ -119,10 +116,10 @@ def main():
         children[i].join()
 
 
-def run(rank, n_gpus, hps, logger: logging.Logger):
+def run(rank, n_gpus, hps,):
     global global_step
     if rank == 0:
-        # logger = utils.get_logger(hps.model_dir)
+        logger = utils.get_logger(hps.model_dir)
         logger.info(hps)
         # utils.check_git_hash(hps.model_dir)
         writer = SummaryWriter(log_dir=hps.model_dir)