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>

requirements.txt

@@ -9,3 +9,4 @@ descript-audio-codec
 vector-quantize-pytorch
 scipy
 tqdm
+torchaudio