import os

os.environ["TORCH_COMPILE_DEBUG"] = "1"

import torch


class Model(torch.nn.Module):
    def forward(self, x, ks0):
        return x.sum()


example_inputs = (
    torch.tensor([0, 3, 6], device="cuda", dtype=torch.int64),
    70,
)
_ = torch._export.aot_compile(
    Model(),
    example_inputs,
)
print("done")

/torch/_inductor/compile_fx.py:751, in fx_codegen_and_compile(gm, example_inputs, cudagraphs, static_input_idxs, is_backward, graph_id, cpp_wrapper, aot_mode, is_inference, user_visible_outputs, layout_opt, extern_node_serializer)
    740     return fd.getvalue()
    742 torch._logging.trace_structured(
    743     "artifact",
    744     metadata_fn=lambda: {
   (...)
    748     payload_fn=lambda: log_graph_runnable(),
    749 )
--> 751 V.debug.fx_graph(gm, example_inputs)
    752 # TODO: Should we actually dump this?  It should be redundant with the aot
    753 # structured logs...
    754 # trace_structured("inductor_input_graph", payload_fn=lambda: gm.print_readable(print_output=False))
    756 shape_env = shape_env_from_inputs(example_inputs)
/torch/_inductor/debug.py:474, in DebugFormatter.fx_graph(self, gm, inputs)
    468 def fx_graph(
    469     self,
    470     gm: torch.fx.GraphModule,
    471     inputs: List[torch.Tensor],
    472 ) -> None:
    473     with self.fopen("fx_graph_runnable.py") as fd:
--> 474         save_graph_repro(fd, gm, inputs, "inductor")
    476     with self.fopen("fx_graph_readable.py") as fd:
    477         fd.write(gm.print_readable(print_output=False))
/torch/_dynamo/repro/after_aot.py:279, in save_graph_repro(fd, gm, args, compiler_name, stable_output, save_dir, command, accuracy, tracing_mode, check_str)
    274     fd.write(
    275         "Repro is not generated due to existence of BackwardState in graph input"
    276     )
    277     return
    278 fd.write(
--> 279     generate_compiler_repro_string(
    280         gm,
    281         args,
    282         stable_output=stable_output,
    283         save_dir=save_dir,
    284     )
    285 )
    286 if accuracy is None:
    287     accuracy = "_accuracy" in compiler_name
/torch/_dynamo/repro/after_aot.py:249, in generate_compiler_repro_string(gm, args, stable_output, save_dir)
    247         writer.tensor(placeholder, arg)
    248     else:
--> 249         raise TypeError(f"arg is neither SymInt/int nor torch.Tensor, {arg}")
    251 model_str += "\n".join(writer.lines()) + "\n"
    253 model_str += "mod = Repro()\n"
TypeError: arg is neither SymInt/int nor torch.Tensor, None