Upload 163 files

hugging/td_fuse/td_benchmark.py

@@ -488,7 +488,6 @@ def check_instruction_answer(response: str, test: dict) -> bool:
 def load_model(model_path: str):
     """Load model and tokenizer. Validates checkpoint integrity first."""
     from transformers import AutoModelForImageTextToText, AutoTokenizer
-    from pathlib import Path
 
     # Validate checkpoint before loading — catch stale/corrupt checkpoints
     p = Path(model_path)
@@ -682,7 +681,6 @@ def run_benchmark(cfg: BenchmarkConfig = None) -> Dict:
 
     # Auto-detect model
     if not cfg.model_path:
-        from pathlib import Path
         base = Path("td_fuse_outputs/self_improve")
         if base.exists():
             for n in range(50, 0, -1):

hugging/td_fuse/td_loop.py

@@ -293,7 +293,7 @@ def _run_loop_inner(cfg: LoopConfig, shutdown_requested: list):
         import torch
         if torch.cuda.is_available():
             gpu_name = torch.cuda.get_device_name(0)
-            gpu_mem = torch.cuda.get_device_properties(0).total_mem / 1e9
+            gpu_mem = torch.cuda.get_device_properties(0).total_memory / 1e9
             print(f"\n  GPU: {gpu_name} ({gpu_mem:.1f} GB)")
             if gpu_mem < 20:
                 print(f"  WARNING: GPU has only {gpu_mem:.1f} GB — Qwen3-VL-8B needs ~24 GB for training!")