code: def test_broadcast_in_dim_sum(self, device, dtype):
      def _wrapper(a):
          a_sum = prims.sum(a, [0, 1])
          a_bc = prims.broadcast_in_dim(a_sum, [], [])
          return a_bc
  
      traced = make_traced(_wrapper)
      make_arg = partial(make_tensor, device=device, dtype=dtype)
  
      for executor in ("aten",):
          fn = partial(traced, executor=executor)
          shape = (5, 5)
          a = make_arg(shape)
          result = fn(a)
  
          self.assertEqual(result.shape, ())
          self.assertTrue(result.is_contiguous)
          self.assertEqual(_wrapper(a), result)
  
imports: from functools import partial
  from itertools import product
  import unittest
  import torch
  from torch.testing import make_tensor
  from torch.testing._internal.common_utils import parametrize, run_tests, TestCase, TEST_SCIPY, set_default_dtype
  from torch.testing._internal.common_device_type import instantiate_device_type_tests, onlyCUDA, dtypes, OpDTypes
  from torch.testing._internal.common_methods_invocations import op_db
  from torch.testing._internal.common_device_type import ops
  from torch.testing._internal.logging_tensor import LoggingTensor, capture_logs, log_input
  import torch._prims
  from torch._prims_common import CUDARngStateHelper
  from torch._prims.executor import make_traced
  import torch._refs
label_desc: Use image node_id 2 for calling the TestPrims obj's underlying member method code with example usage: obj.test_broadcast_in_dim_sum(device, dtype) and returns: a_bc