feat: LoRA trainer and loader nodes for PrismAudio DiT fine-tuning

Adds PrismAudioLoRATrainer and PrismAudioLoRALoader nodes enabling
low-rank adaptation of the DiT on paired (video features + audio) datasets.

- LoRALinear wraps nn.Linear with trainable lora_A/lora_B matrices
- Rectified flow training loop with fp16 GradScaler, AdamW, cfg dropout
- Checkpoint saving every N steps + _config.json metadata alongside weights
- _unapply_lora restores base model state after training completes
- Weight-merge loader: delta_W added in-place, no deep copy overhead
- Three target presets: attn_only, attn_ffn (default), full

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

nodes/__init__.py

@@ -7,6 +7,8 @@ _NODES = {
     "PrismAudioFeatureExtractor": (".feature_extractor", "PrismAudioFeatureExtractor", "PrismAudio Feature Extractor"),
     "PrismAudioSampler": (".sampler", "PrismAudioSampler", "PrismAudio Sampler"),
     "PrismAudioTextOnly": (".text_only", "PrismAudioTextOnly", "PrismAudio Text Only"),
+    "PrismAudioLoRATrainer": (".lora_trainer", "PrismAudioLoRATrainer", "PrismAudio LoRA Trainer"),
+    "PrismAudioLoRALoader":  (".lora_loader",  "PrismAudioLoRALoader",  "PrismAudio LoRA Loader"),
 }
 
 for key, (module_path, class_name, display_name) in _NODES.items():