code: def test_arg_dupe_via_dynamo_recompiles_many_args_param_non_tensor_arg(
      self,
  ):
      class F(torch.nn.Module):
          def __init__(self):
              super().__init__()
              self.mean = torch.nn.Parameter(torch.randn(3, 3))
  
          def forward(self, a, b, c, d, e, f):
              a.trunc_()
              b.trunc_()
              c.trunc_()
              d.trunc_()
              return (a + b + c + d + self.mean) * e * f
  
      a = torch.randn(3, 3, requires_grad=True)
      b = torch.randn(3, 3, requires_grad=True)
      a1, a2, a3, a4 = a.clone(), a.clone(), a.clone(), a.clone()
      b1, b2, b3, b4 = b.clone(), b.clone(), b.clone(), b.clone()
  
      failure_reason = None
  
      def guard_fail_fn(failure):
          nonlocal failure_reason
          failure_reason = failure[0]
  
      self.assertTrue(failure_reason is None)
  
      cc = torch._dynamo.testing.CompileCounterWithBackend("aot_eager")
  
      f = torch._dynamo.optimize(cc, guard_fail_fn=guard_fail_fn)(F())
      f(a1, a1, a1, a1, 2, 2)
      f(a2, b2, b2, b2, 2, 2)
      self.assertEqual(cc.frame_count, 2)
      self.assertIn(
          """L['a'] is L['b']""",
          failure_reason,
      )
  
      torch._dynamo.reset()
  
      cc = torch._dynamo.testing.CompileCounterWithBackend("aot_eager")
  
      c = torch.randn(3, 3, requires_grad=True)
      d = torch.randn(3, 3, requires_grad=True)
      c3, c4 = c.clone(), c.clone()
      d3, d4 = d.clone(), d.clone()
  
      f = torch._dynamo.optimize(cc, guard_fail_fn=guard_fail_fn)(F())
      f(a3, b3, c3, c3, 3, 3)
      f(a4, b4, c4, d4, 3, 3)
      self.assertEqual(cc.frame_count, 2)
      self.assertIn("""L['c'] is L['d']""", failure_reason)
  
imports: import re
  from textwrap import dedent
  from unittest.mock import patch
  import torch
  import torch._dynamo
  import torch._dynamo.test_case
  import torch.fx.traceback
  import torch.utils._pytree
  from torch._dynamo.testing import CompileCounter, expectedFailureDynamic, rand_strided
  from torch._functorch.aot_autograd import _aot_export_function, create_functional_call
  from torch.profiler import profile
  from torch.testing._internal.common_utils import compare_equal_outs_and_grads
label_desc: Use image node_id 12 for calling the AotAutogradFallbackTests obj's underlying member method code with example usage: obj.test_arg_dupe_via_dynamo_recompiles_many_args_param_non_tensor_arg() and returns: unknown