Is it possible to define a custom back-end wrapped with aot_autograd which does not use fake tensors?

torch.compile
1

Is it possible to define a custom back-end wrapped with aot_autograd which does not use fake tensors? Solely considering forward compilation, a custom back-end can be registered as follows:

def my_forward_compiler_fn(gm, tensor_inputs):
  pass

register_backend(name="my_backend", compiler_fn=aot_autograd(fw_compiler=my_forward_compiler))

In my_forward_compiler, tensor_inputs are of type FakeTensor. A human-readable table of the GraphModule can be printed using gm.graph.print_tabular(), however, there appears to be no way to access the underlying data of the arg tensors.