docstr: Test the special handling of the kwargs when hashing, i.e.,
  ordering of the kwargs dict and any set arguments.
docstr_tok: ["Test","the","special","handling","of","the","kwargs","when","hashing",",","i.e.",",","ordering","of","the","kwargs","dict","and","any","set","arguments","."]
code: def test_hash_kwargs(self):
      """
      Test the special handling of the kwargs when hashing, i.e.,
      ordering of the kwargs dict and any set arguments.
      """
      # Dict order of the kwargs should not affect hashes.
      details1 = FxGraphHashDetails(None, [], {"a": 0, "z": 1})
      details2 = FxGraphHashDetails(None, [], {"z": 1, "a": 0})
      self.assertEqual(
          FxGraphCachePickler.dumps(details1),
          FxGraphCachePickler.dumps(details2),
      )
  
      # Different kwarg values should affect hashes.
      details1 = FxGraphHashDetails(None, [], {"a": 0})
      details2 = FxGraphHashDetails(None, [], {"a": 1})
      self.assertNotEqual(
          FxGraphCachePickler.dumps(details1),
          FxGraphCachePickler.dumps(details2),
      )
  
      # Set order should not affect hashes. Sets are unordered, but
      # sorting and creating a new set seems to change the order.
      set1 = {"a", "b", "c", "d", "e", "f", "g"}
      set2 = set(sorted(set1))  # noqa: C414
      details1 = FxGraphHashDetails(None, [], {"a": set1})
      details2 = FxGraphHashDetails(None, [], {"a": set2})
      self.assertEqual(
          FxGraphCachePickler.dumps(details1),
          FxGraphCachePickler.dumps(details2),
      )
  
      # But different set contents should affect hashes.
      details1 = FxGraphHashDetails(None, [], {"a": {1, 2, 3}})
      details2 = FxGraphHashDetails(None, [], {"a": {1, 2}})
      self.assertNotEqual(
          FxGraphCachePickler.dumps(details1),
          FxGraphCachePickler.dumps(details2),
      )
  
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 3 for calling the TestFxGraphCacheHashing obj's underlying member method code with example usage: obj.test_hash_kwargs() without return types