code: def test_float64_constants(self):
      def fn():
          # NOTE: tensors of all the same value are constant folded, so we
          # need a tensor with two distinct values
          a = torch.tensor(
              [1 / 10, 2 / 10], dtype=torch.float64, device="cuda"
          )
          return a * 2e50
  
      cfn = torch.compile(fn)
      expect = fn()
      actual = cfn()
      self.assertEqual(expect, actual, atol=0, rtol=0)
  
imports: import math
  import sys
  import unittest
  import torch
  import torch._dynamo.config
  import torch.backends.cuda
  import torch.nn.functional
  from torch import nn
  from torch._dynamo.debug_utils import same_two_models
  from torch._dynamo.testing import rand_strided
  from torch._dynamo.utils import same
  from torch._inductor import config
  from torch._inductor.compile_fx import compile_fx_inner
  from torch.fx.experimental.proxy_tensor import make_fx
  from torch.testing._internal.common_cuda import PLATFORM_SUPPORTS_FLASH_ATTENTION
  from torch.testing._internal.common_utils import DeterministicGuard, freeze_rng_state, IS_FBCODE, skipIfRocm, TEST_WITH_ASAN
label_desc: Use image node_id 37 for calling the CudaReproTests obj's underlying member method code with example usage: obj.test_float64_constants() and returns: unknown