Support 4bit torch.compile fullgraph with PyTorch nightly (#1616)

bitsandbytes/nn/modules.py

@@ -290,6 +290,13 @@ class Params4bit(torch.nn.Parameter):
 
         return self
 
+    @classmethod
+    def __torch_function__(cls, func, types, args=(), kwargs=None):
+        if kwargs is None:
+            kwargs = {}
+        with torch._C.DisableTorchFunctionSubclass():
+            return func(*args, **kwargs)
+
     def _quantize(self, device):
         w = self.data.contiguous().to(device)
         w_4bit, quant_state = bnb.functional.quantize_4bit(
@@ -486,7 +493,7 @@ class Linear4bit(nn.Linear):
 
         bias = None if self.bias is None else self.bias.to(self.compute_dtype)
 
-        return bnb.matmul_4bit(x, self.weight.t(), bias=bias, quant_state=self.weight.quant_state).to(inp_dtype)
+        return bnb.matmul_4bit(x, self.weight.data.t(), bias=bias, quant_state=self.weight.quant_state).to(inp_dtype)
 
 
 class LinearFP4(Linear4bit):