@torch._dynamo.config.patch(capture_scalar_outputs=True)
    def test_while_loop_tensor_constant_idx(self):
        def while_loop_decomp(x, y0):
            out = torch.zeros_like(x)

            def cond_fn(idx, out, y0):
                return idx < out.size(0)

            def body_fn(idx, out, y0):
                i = idx.item()

                y0 = x[i] + y0
                out = out.clone()
                out[i] = y0
                return idx + 1, out, y0

            cnt = torch.tensor(0)
            _, out, _ = while_loop(cond_fn, body_fn, [cnt, out, y0])
            return out

        class TestModel(torch.nn.Module):
            def forward(self, x, y0):
                return while_loop_decomp(x, y0)

        x, y0 = torch.randn(16, 8), torch.randn(8)
        exp_out = TestModel()(x, y0)
        ep = export(TestModel(), (x, y0))
        out = ep.module()(x, y0)
        self.assertEqual(exp_out, out)

  self.push(fn.call_function(self, args, kwargs))  # type: ignore[arg-type]
  File "/home/lsakka/pytorch10/pytorch/torch/_dynamo/variables/lazy.py", line 212, in realize_and_forward
    return getattr(self.realize(), name)(*args, **kwargs)
  File "/home/lsakka/pytorch10/pytorch/torch/_dynamo/variables/higher_order_ops.py", line 1237, in call_function
    return self._call_function(tx, args, kwargs)
  File "/home/lsakka/pytorch10/pytorch/torch/_dynamo/variables/higher_order_ops.py", line 106, in graph_break_as_hard_error
    return fn(*args, **kwargs)
  File "/home/lsakka/pytorch10/pytorch/torch/_dynamo/variables/higher_order_ops.py", line 1521, in _call_function
    return _call_while_loop(self, tx, args, kwargs, stack_output=False)
  File "/home/lsakka/pytorch10/pytorch/torch/_dynamo/variables/higher_order_ops.py", line 475, in _call_while_loop
    ) = speculate_subgraph(
  File "/home/lsakka/pytorch10/pytorch/torch/_dynamo/variables/higher_order_ops.py", line 997, in speculate_subgraph
    output = f.call_function(tx, args, sub_kwargs)
  File "/home/lsakka/pytorch10/pytorch/torch/_dynamo/variables/functions.py", line 598, in call_function
    return super().call_function(tx, args, kwargs)
  File "/home/lsakka/pytorch10/pytorch/torch/_dynamo/variables/functions.py", line 342, in call_function
    return tx.inline_user_function_return(self, [*self.self_args(), *args], kwargs)
  File "/home/lsakka/pytorch10/pytorch/torch/_dynamo/symbolic_convert.py", line 1283, in inline_user_function_return
    return InliningInstructionTranslator.inline_call(self, fn, args, kwargs)
  File "/home/lsakka/pytorch10/pytorch/torch/_dynamo/symbolic_convert.py", line 4197, in inline_call
    return tracer.inline_call_()
  File "/home/lsakka/pytorch10/pytorch/torch/_dynamo/symbolic_convert.py", line 4410, in inline_call_
    self.run()
  File "/home/lsakka/pytorch10/pytorch/torch/_dynamo/symbolic_convert.py", line 1482, in run
    while self.step():
  File "/home/lsakka/pytorch10/pytorch/torch/_dynamo/symbolic_convert.py", line 1343, in step
    self.dispatch_table[inst.opcode](self, inst)
  File "/home/lsakka/pytorch10/pytorch/torch/_dynamo/symbolic_convert.py", line 899, in wrapper
    return inner_fn(self, inst)
  File "/home/lsakka/pytorch10/pytorch/torch/_dynamo/symbolic_convert.py", line 2377, in CALL_FUNCTION_EX
    self.call_function(fn, argsvars.items, kwargsvars)
  File "/home/lsakka/pytorch10/pytorch/torch/_dynamo/symbolic_convert.py", line 1261, in call_function
    self.push(fn.call_function(self, args, kwargs))  # type: ignore[arg-type]
  File "/home/lsakka/pytorch10/pytorch/torch/_dynamo/variables/lazy.py", line 212, in realize_and_forward
    return getattr(self.realize(), name)(*args, **kwargs)
  File "/home/lsakka/pytorch10/pytorch/torch/_dynamo/variables/functions.py", line 598, in call_function
    return super().call_function(tx, args, kwargs)
  File "/home/lsakka/pytorch10/pytorch/torch/_dynamo/variables/functions.py", line 342, in call_function
    return tx.inline_user_function_return(self, [*self.self_args(), *args], kwargs)
  File "/home/lsakka/pytorch10/pytorch/torch/_dynamo/symbolic_convert.py", line 1283, in inline_user_function_return
    return InliningInstructionTranslator.inline_call(self, fn, args, kwargs)
  File "/home/lsakka/pytorch10/pytorch/torch/_dynamo/symbolic_convert.py", line 4197, in inline_call
    return tracer.inline_call_()
  File "/home/lsakka/pytorch10/pytorch/torch/_dynamo/symbolic_convert.py", line 4410, in inline_call_
    self.run()
  File "/home/lsakka/pytorch10/pytorch/torch/_dynamo/symbolic_convert.py", line 1482, in run
    while self.step():
  File "/home/lsakka/pytorch10/pytorch/torch/_dynamo/symbolic_convert.py", line 1343, in step
    self.dispatch_table[inst.opcode](self, inst)
  File "/home/lsakka/pytorch10/pytorch/torch/_dynamo/symbolic_convert.py", line 464, in impl
    self.push(fn_var.call_function(self, self.popn(nargs), {}))
  File "/home/lsakka/pytorch10/pytorch/torch/_dynamo/variables/builtin.py", line 1346, in call_function
    return handler(tx, args, kwargs)
  File "/home/lsakka/pytorch10/pytorch/torch/_dynamo/variables/builtin.py", line 1306, in _handle_insert_op_in_graph
    return wrap_fx_proxy(tx, proxy)
  File "/home/lsakka/pytorch10/pytorch/torch/_dynamo/variables/builder.py", line 2708, in wrap_fx_proxy
    return wrap_fx_proxy_cls(target_cls=TensorVariable, **kwargs)
  File "/home/lsakka/pytorch10/pytorch/torch/_dynamo/variables/builder.py", line 2774, in wrap_fx_proxy_cls
    return _wrap_fx_proxy(
  File "/home/lsakka/pytorch10/pytorch/torch/_dynamo/variables/builder.py", line 2874, in _wrap_fx_proxy
    return handle_traced_output(
  File "/home/lsakka/pytorch10/pytorch/torch/_dynamo/variables/builder.py", line 2886, in handle_traced_output
    var = construct_tensor_variable(
  File "/home/lsakka/pytorch10/pytorch/torch/_dynamo/variables/builder.py", line 3140, in construct_tensor_variable
    set_example_value(proxy.node, example_value)
  File "/home/lsakka/pytorch10/pytorch/torch/_dynamo/utils.py", line 2713, in set_example_value
    := torch.fx.experimental.symbolic_shapes.compute_unbacked_bindings(
  File "/home/lsakka/pytorch10/pytorch/torch/fx/experimental/symbolic_shapes.py", line 1310, in compute_unbacked_bindings
    raise PendingUnbackedSymbolNotFound(
torch._dynamo.exc.InternalTorchDynamoError: PendingUnbackedSymbolNotFound: Pending unbacked symbols {u2} not in returned outputs FakeTensor(..., size=(), dtype=torch.int64) ((), 0).
Did you accidentally call new_dynamic_size() or item() more times than you needed to in your fake implementation?
For more help, see https://docs.google.com/document/d/1RWrH-3wLEpzR9kCS6gGBNen_-Fs-8PVbWWFE5AcgeWE/edit