code: def test_large_integers(self):
      big = (
          2**60
      )  # Too large to represent with a full precision float
  
      x = np.asarray([0], dtype=np.int64)
      x_edges = np.array([-1, +1], np.int64)
      y = big + x
      y_edges = big + x_edges
  
      hist, edges = histogramdd((x, y), bins=(x_edges, y_edges))
  
      assert_equal(hist[0, 0], 1)
  
imports: import functools
  from unittest import expectedFailure, skipIf
  from pytest import raises
  from torch.testing._internal.common_utils import instantiate_parametrized_tests, parametrize, run_tests, slowTest, TEST_WITH_TORCHDYNAMO, TestCase, xpassIfTorchDynamo
label_desc: Use image node_id 14 for calling the TestHistogramdd obj's underlying member method code with example usage: obj.test_large_integers() without return types