修复resume epoch数识别错，每次resume都要都训一轮的问题

修复resume epoch数识别错，每次resume都要都训一轮的问题

GPT_SoVITS/s2_train_v3_lora.py

@@ -161,6 +161,7 @@ def run(rank, n_gpus, hps):
             net_g,
             optim_g,
         )
+        epoch_str+=1
         global_step = (epoch_str - 1) * len(train_loader)
     except:  # 如果首次不能加载，加载pretrain
         # traceback.print_exc()
@@ -170,7 +171,7 @@ def run(rank, n_gpus, hps):
         if hps.train.pretrained_s2G != ""and hps.train.pretrained_s2G != None and os.path.exists(hps.train.pretrained_s2G):
             if rank == 0:
                 logger.info("loaded pretrained %s" % hps.train.pretrained_s2G)
-            print(
+            print("loaded pretrained %s" % hps.train.pretrained_s2G,
                 net_g.load_state_dict(
                     torch.load(hps.train.pretrained_s2G, map_location="cpu")["weight"],
                     strict=False,
@@ -198,6 +199,7 @@ def run(rank, n_gpus, hps):
 
     net_d=optim_d=scheduler_d=None
     for epoch in range(epoch_str, hps.train.epochs + 1):
+        print("start training from epoch %s"%epoch)
         if rank == 0:
             train_and_evaluate(
                 rank,
@@ -226,6 +228,7 @@ def run(rank, n_gpus, hps):
                 None,
             )
         scheduler_g.step()
+        print("training done")
 
 def train_and_evaluate(
     rank, epoch, hps, nets, optims, schedulers, scaler, loaders, logger, writers