code: def test_logdiffexp():
      a = np.log([1, 2, 3, 4])
      with warnings.catch_warnings():
          warnings.filterwarnings(
              "ignore",
              "divide by zero encountered in log",
              RuntimeWarning,
          )
          b = np.log([0, 1, 2, 3])
  
      assert np.allclose(logdiffexp_numpy(a, b), 0)
      assert np.allclose(logdiffexp(a, b).eval(), 0)
  
imports: import warnings
  import numpy
  import numpy.testing
  import pytensor
  import pytensor.tensor
  import pytest
  from pymc.math import LogDet, cartesian, expand_packed_triangular, invprobit, kron_dot, kron_solve_lower, kronecker, log1mexp, log1mexp_numpy, logdet, logdiffexp, logdiffexp_numpy, probit
  from pymc.pytensorf import floatX
  from tests.helpers import verify_grad
label_desc: Use image node_id 11 for calling a global function with example usage: test_logdiffexp() without return types