update

examples/mpnet_aishell/step_2_train_model.py

@@ -176,9 +176,6 @@ def main():
     optim_g = torch.optim.AdamW(generator.parameters(), config.learning_rate, betas=[config.adam_b1, config.adam_b2])
     optim_d = torch.optim.AdamW(discriminator.parameters(), config.learning_rate, betas=[config.adam_b1, config.adam_b2])
 
-    scheduler_g = torch.optim.lr_scheduler.ExponentialLR(optim_g, gamma=config.lr_decay, last_epoch=last_epoch)
-    scheduler_d = torch.optim.lr_scheduler.ExponentialLR(optim_d, gamma=config.lr_decay, last_epoch=last_epoch)
-
     # resume training
     last_epoch = -1
     for epoch_i in serialization_dir.glob("epoch-*"):
@@ -213,6 +210,9 @@ def main():
             state_dict = torch.load(f, map_location="cpu", weights_only=True)
         optim_d.load_state_dict(state_dict, strict=True)
 
+    scheduler_g = torch.optim.lr_scheduler.ExponentialLR(optim_g, gamma=config.lr_decay, last_epoch=last_epoch)
+    scheduler_d = torch.optim.lr_scheduler.ExponentialLR(optim_d, gamma=config.lr_decay, last_epoch=last_epoch)
+
     # training loop
 
     # state