diff --git a/infer/modules/train/train.py b/infer/modules/train/train.py
index a9c590f..38a5678 100644
--- a/infer/modules/train/train.py
+++ b/infer/modules/train/train.py
@@ -104,10 +104,11 @@ 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),
+            args=(i, n_gpus, hps, logger),
         )
         children.append(subproc)
         subproc.start()
@@ -116,14 +117,10 @@ def main():
         children[i].join()
 
 
-def run(
-    rank,
-    n_gpus,
-    hps,
-):
+def run(rank, n_gpus, hps, logger: logging.Logger):
     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)
@@ -229,13 +226,13 @@ def run(
             if rank == 0:
                 logger.info("loaded pretrained %s" % (hps.pretrainG))
             if hasattr(net_g, "module"):
-                print(
+                logger.info(
                     net_g.module.load_state_dict(
                         torch.load(hps.pretrainG, map_location="cpu")["model"]
                     )
                 )  ##测试不加载优化器
             else:
-                print(
+                logger.info(
                     net_g.load_state_dict(
                         torch.load(hps.pretrainG, map_location="cpu")["model"]
                     )
@@ -244,13 +241,13 @@ def run(
             if rank == 0:
                 logger.info("loaded pretrained %s" % (hps.pretrainD))
             if hasattr(net_d, "module"):
-                print(
+                logger.info(
                     net_d.module.load_state_dict(
                         torch.load(hps.pretrainD, map_location="cpu")["model"]
                     )
                 )
             else:
-                print(
+                logger.info(
                     net_d.load_state_dict(
                         torch.load(hps.pretrainD, map_location="cpu")["model"]
                     )