import torch
@torch.compile(fullgraph=True, dynamic=True, backend="inductor")
def func(a, b, c):
    torch._check(a.size()[0]==b.size()[0])
    return a * 10, c.item()


a = torch.rand(1,1)
b = torch.rand(2,2)
c = torch.tensor([2])

torch._dynamo.decorators.mark_unbacked(a, 0)
torch._dynamo.decorators.mark_unbacked(a, 1)
torch._dynamo.decorators.mark_unbacked(b, 0)
torch._dynamo.decorators.mark_unbacked(b, 1)
with fresh_inductor_cache():
    func(a, b, c)