diff --git a/ldm/models/diffusion/ddpm.py b/ldm/models/diffusion/ddpm.py
index bbedd04cf..dfeb6545e 100644
--- a/ldm/models/diffusion/ddpm.py
+++ b/ldm/models/diffusion/ddpm.py
@@ -1027,7 +1027,7 @@ def p_losses(self, x_start, cond, t, noise=None):
         loss_simple = self.get_loss(model_output, target, mean=False).mean([1, 2, 3])
         loss_dict.update({f'{prefix}/loss_simple': loss_simple.mean()})
 
-        logvar_t = self.logvar[t].to(self.device)
+        logvar_t = self.logvar.to(self.device)[t]
         loss = loss_simple / torch.exp(logvar_t) + logvar_t
         # loss = loss_simple / torch.exp(self.logvar) + self.logvar
         if self.learn_logvar:
diff --git a/main.py b/main.py
index e8e18c18f..b64ed0079 100644
--- a/main.py
+++ b/main.py
@@ -400,7 +400,7 @@ def on_train_epoch_start(self, trainer, pl_module):
         torch.cuda.synchronize(trainer.root_gpu)
         self.start_time = time.time()
 
-    def on_train_epoch_end(self, trainer, pl_module, outputs):
+    def on_train_epoch_end(self, trainer, pl_module):
         torch.cuda.synchronize(trainer.root_gpu)
         max_memory = torch.cuda.max_memory_allocated(trainer.root_gpu) / 2 ** 20
         epoch_time = time.time() - self.start_time