code: def test_bin_edge_cases(self):
      # Ensure that floating-point computations correctly place edge cases.
      arr = np.array([337, 404, 739, 806, 1007, 1811, 2012])
      hist, edges = np.histogram(arr, bins=8296, range=(2, 2280))
      mask = hist > 0
      left_edges = edges[:-1][mask]
      right_edges = edges[1:][mask]
      for x, left, right in zip(arr, left_edges, right_edges):
          assert_(x >= left)
          assert_(x < right, msg=f"{x}, {right}")
  
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 16 for calling the TestHistogram obj's underlying member method code with example usage: obj.test_bin_edge_cases() without return types