mm: guard against double pin and unpin explicitly (#10672)

As commented, if you let cuda be the one to detect double pin/unpinning
it actually creates an asyc GPU error.

comfy/model_management.py

@@ -1103,6 +1103,12 @@ def pin_memory(tensor):
     if not is_device_cpu(tensor.device):
         return False
 
+    if tensor.is_pinned():
+        #NOTE: Cuda does detect when a tensor is already pinned and would
+        #error below, but there are proven cases where this also queues an error
+        #on the GPU async. So dont trust the CUDA API and guard here
+        return False
+
     size = tensor.numel() * tensor.element_size()
     if (TOTAL_PINNED_MEMORY + size) > MAX_PINNED_MEMORY:
         return False
@@ -1123,6 +1129,12 @@ def unpin_memory(tensor):
     if not is_device_cpu(tensor.device):
         return False
 
+    if not tensor.is_pinned():
+        #NOTE: Cuda does detect when a tensor is already pinned and would
+        #error below, but there are proven cases where this also queues an error
+        #on the GPU async. So dont trust the CUDA API and guard here
+        return False
+
     ptr = tensor.data_ptr()
     if torch.cuda.cudart().cudaHostUnregister(ptr) == 0:
         TOTAL_PINNED_MEMORY -= PINNED_MEMORY.pop(ptr)