LoRA load Torch tuple and string version checking

Due to BitsandBytes trying to use tuple and comparison to check Torch version which is given as a string, using LoRA with a quantized model results in a TypeError. This commit adds support for both.

modules/lora/lora_load.py

@@ -16,6 +16,24 @@ forbidden_network_aliases = {}
 available_network_hash_lookup = {}
 dump_lora_keys = os.environ.get('SD_LORA_DUMP', None) is not None
 
+def patch_torch_version():
+    import torch
+    if not hasattr(torch, '__version_backup__'):
+        torch.__version_backup__ = torch.__version__
+        # Convert string version to tuple format to solve TypeError caused by BnB
+        version_parts = torch.__version__.split('+')[0].split('.')
+        torch.__version_tuple__ = tuple(int(x) for x in version_parts[:3])
+        # Support both string and tuple
+        class VersionString(str):
+            def __ge__(self, other):
+                if isinstance(other, tuple):
+                    self_tuple = tuple(int(x) for x in self.split('+')[0].split('.')[:len(other)])
+                    return self_tuple >= other
+                return super().__ge__(other)
+        torch.__version__ = VersionString(torch.__version__)
+
+# Call before loading LoRA
+patch_torch_version()
 
 def load_diffusers(name, network_on_disk, lora_scale=shared.opts.extra_networks_default_multiplier) -> Union[network.Network, None]:
     t0 = time.time()