last tweak

train.py

@@ -651,6 +651,9 @@ def main(args):
                 del timesteps, encoder_hidden_states, noisy_latents
                 #with autocast(enabled=args.amp):
                 loss = torch_functional.mse_loss(model_pred.float(), target.float(), reduction="mean")
+                
+                del target, model_pred
+
                 if batch["runt_size"] > 0:
                     grad_scale = batch["runt_size"] / args.batch_size
                     with torch.no_grad(): # not required? just in case for now, needs more testing
@@ -661,7 +664,6 @@ def main(args):
                             for param in text_encoder.parameters():
                                 if param.grad is not None:
                                     param.grad *= grad_scale
-                del target, model_pred
 
                 if args.clip_grad_norm is not None:
                     torch.nn.utils.clip_grad_norm_(parameters=unet.parameters(), max_norm=args.clip_grad_norm)