code: def calc_eigenvalues(
      L: TensorLike, m: Sequence[int], tl: ModuleType = np
  ):
      """Calculate eigenvalues of the Laplacian."""
      S = np.meshgrid(*[np.arange(1, 1 + m[d]) for d in range(len(m))])
      S_arr = np.vstack([s.flatten() for s in S]).T
      return tl.square((np.pi * S_arr) / (2 * L))
  
imports: import numbers
  import warnings
  from types import ModuleType
  from typing import Optional, Sequence, Union
  import numpy
  import pytensor.tensor
  import pymc
  from pymc.gp.cov import Covariance, Periodic
  from pymc.gp.gp import Base
  from pymc.gp.mean import Mean, Zero
label_desc: Use image node_id 2 for calling a global function with example usage: calc_eigenvalues(L, m, tl) and returns: tl