Compatible with cpu machines

src/interfaces/vae_model_loader.py

@@ -29,7 +29,7 @@ class SeedVR2LoadVAEModel(io.ComfyNode):
     def define_schema(cls) -> io.Schema:        
         devices = get_device_list()
         vae_models = get_available_vae_models()
-        
+
         return io.Schema(
             node_id="SeedVR2LoadVAEModel",
             display_name="SeedVR2 (Down)Load VAE Model",

src/optimization/compatibility.py

@@ -683,16 +683,18 @@ def _check_conv3d_memory_bug():
 # Bfloat16 CUBLAS support
 def _probe_bfloat16_support() -> bool:
     if not torch.cuda.is_available():
-        return True
+        return False
+    try:
+        torch.cuda.device('cuda:0')
+    except (RuntimeError, AssertionError):
+        return False
     try:
         a = torch.randn(8, 8, dtype=torch.bfloat16, device='cuda:0')
         _ = torch.matmul(a, a)
         del a
         return True
     except RuntimeError as e:
-        if "CUBLAS_STATUS_NOT_SUPPORTED" in str(e):
-            return False
-        raise
+        return False
 
 BFLOAT16_SUPPORTED = _probe_bfloat16_support()
 COMPUTE_DTYPE = torch.bfloat16 if BFLOAT16_SUPPORTED else torch.float16

src/optimization/memory_manager.py

@@ -45,7 +45,7 @@ def get_gpu_backend() -> str:
     return 'cpu'
 
 
-def get_device_list(include_none: bool = False, include_cpu: bool = False) -> List[str]:
+def get_device_list(include_none: bool = False, include_cpu: bool = True) -> List[str]:
     """
     Get list of available compute devices for SeedVR2
 
@@ -119,7 +119,15 @@ def get_basic_vram_info(device: Optional[torch.device] = None) -> Dict[str, Any]
             free_memory = mem.total - mem.used
             total_memory = mem.total
         else:
-            return {"error": "No GPU backend available (CUDA/MPS)"}
+            from loguru import logger
+            logger.info("SeedVR2_VideoUpscaler: use fake memory info")
+            free_memory, total_memory = (24893718528*2, 25438126080*2)
+            free_gb = free_memory / (1024**3)
+            total_gb = total_memory / (1024**3)
+            return {
+                "free_gb": free_gb,
+                "total_gb": total_gb
+            }
 
         return {
             "free_gb": free_memory / (1024**3),