fix: disable inference_mode entirely for training via inference_mode(False)

torch.enable_grad() alone is insufficient: operations on inference tensors
(created inside ComfyUI's outer inference_mode context) produce inference
tensors even inside enable_grad, breaking autograd. inference_mode(False)
exits the inference context so the deepcopy, apply_lora, and training loop
run with a fully clean autograd context.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

nodes/selva_lora_trainer.py

@@ -365,10 +365,11 @@ class SelvaLoraTrainer:
             raise ValueError("[LoRA Trainer] No clips could be loaded.")
         print(f"[LoRA Trainer] {len(dataset)} clip(s) ready.", flush=True)
 
-        # Everything from here runs inside enable_grad: ComfyUI wraps nodes in
-        # inference_mode, and nn.Parameters created in that context are inference
-        # tensors that can't enter autograd even with requires_grad=True.
-        with torch.enable_grad():
+        # ComfyUI executes nodes inside torch.inference_mode(). Inference tensors
+        # can't participate in autograd even with enable_grad — disable inference
+        # mode entirely so deepcopy, apply_lora, and the training loop all run
+        # with a clean autograd context.
+        with torch.inference_mode(False), torch.enable_grad():
             return self._train_inner(
                 model, dataset, feature_utils_orig, seq_cfg,
                 device, dtype, variant, mode,