code: def test_numpy_compare(self):
      rng = np.random.default_rng(utt.fetch_seed())
  
      M = matrix("A", dtype=config.floatX)
      V = vector("V", dtype=config.floatX)
  
      a = rng.random((4, 4)).astype(config.floatX)
      b = rng.random(4).astype(config.floatX)
  
      A = (
          [
              None,
              "fro",
              "inf",
              "-inf",
              1,
              -1,
              None,
              "inf",
              "-inf",
              0,
              1,
              -1,
              2,
              -2,
          ],
          [M, M, M, M, M, M, V, V, V, V, V, V, V, V],
          [a, a, a, a, a, a, b, b, b, b, b, b, b, b],
          [
              None,
              "fro",
              inf,
              -inf,
              1,
              -1,
              None,
              inf,
              -inf,
              0,
              1,
              -1,
              2,
              -2,
          ],
      )
  
      for i in range(0, 14):
          f = function([A[1][i]], norm(A[1][i], A[0][i]))
          t_n = f(A[2][i])
          n_n = np.linalg.norm(A[2][i], A[3][i])
          assert _allclose(n_n, t_n)
  
imports: import numpy
  import numpy.linalg
  import pytest
  from numpy import inf
  from numpy.testing import assert_array_almost_equal
  import pytensor
  from pytensor import function
  from pytensor.configdefaults import config
  from pytensor.tensor.math import _allclose
  from pytensor.tensor.nlinalg import SVD, Eig, MatrixInverse, TensorInv, det, eig, eigh, lstsq, matrix_dot, matrix_inverse, matrix_power, norm, pinv, qr, slogdet, svd, tensorinv, tensorsolve, trace
  from pytensor.tensor.type import lmatrix, lscalar, matrix, scalar, tensor3, tensor4, vector
  from tests import unittest_tools
label_desc: Use image node_id 5 for calling the TestNormTests obj's underlying member method code with example usage: obj.test_numpy_compare() without return types