code: def validate(self, input_mat):
      x = pytensor.tensor.matrix()
      f = pytensor.function([x], self.op(x))
      out = f(input_mat)
      svd_diag = np.linalg.svd(input_mat, compute_uv=False)
      numpy_out = np.sum(np.log(np.abs(svd_diag)))
  
      # Compare the result computed to the expected value.
      np.allclose(numpy_out, out)
  
      # Test gradient:
      verify_grad(self.op, [input_mat])
  
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 2 for calling the TestLogDet obj's underlying member method code with example usage: obj.validate(input_mat) without return types