switch to save for backward since are now a tensor input

torchao/dtypes/nf4tensor.py

@@ -863,13 +863,13 @@ class LinearNF4(torch.autograd.Function):
     @staticmethod
     def forward(ctx, input: torch.Tensor, weight: NF4Tensor):
         """Save the quantized nf4 weight for backward pass"""
-        ctx.nf4_weight = weight
+        ctx.save_for_backward(weight)
         return F.linear(input, weight.to(input.dtype))
 
     @staticmethod
     def backward(ctx, grad_output):
         """The nf4 weight will never require grad so we can just return the grad_output @ weight.to(grad_output.dtype)"""
-        weight: NF4Tensor = ctx.nf4_weight
+        weight: NF4Tensor = ctx.saved_tensors[0]
         return grad_output @ weight.to(grad_output.dtype), None