docstr: Test the handling of small vs. large tensor constants.
docstr_tok: ["Test","the","handling","of","small","vs.","large","tensor","constants","."]
code: def test_tensor_constants(self):
      """
      Test the handling of small vs. large tensor constants.
      """
      data = FxGraphCachePickler.dumps(torch.tensor(list(range(9))))
      self.assertIsInstance(pickle.loads(data), TensorMetadata)
  
      data = FxGraphCachePickler.dumps(torch.tensor(list(range(8))))
      self.assertIsInstance(pickle.loads(data), TensorMetadataAndValues)
  
imports: import functools
  import pickle
  import tempfile
  import unittest
  from unittest.mock import patch
  import torch
  from torch._dynamo.test_case import run_tests, TestCase
  from torch._dynamo.utils import counters
  from torch._inductor import config
  from torch._inductor.codecache import AsyncCompile, FxGraphCachePickler, FxGraphHashDetails, TensorMetadata, TensorMetadataAndValues
  from torch.testing._internal.common_cuda import SM80OrLater
  from torch.testing._internal.common_device_type import largeTensorTest
  from torch.testing._internal.common_utils import instantiate_parametrized_tests, parametrize
  from torch.testing._internal.inductor_utils import HAS_CUDA
  from torch.utils._triton import has_triton
label_desc: Use image node_id 1 for calling the TestFxGraphCacheHashing obj's underlying member method code with example usage: obj.test_tensor_constants() without return types