code: def compute_inv_(self, mean, covariance, eps=0.01):
      c = mean.shape[0]
      # if self.inv_covariance == None:
      # covariance hwcc  #.transpose((2,3, 0, 1)))
      # self.inv_covariance = paddle.linalg.inv(covariance)
      self.set_dist_params(
          mean, cholesky_inverse(covariance + eps * paddle.eye(c))
      )
  
imports: import numpy
  from tqdm import tqdm
  import paddle
  import paddle.nn
  import paddle.nn.functional
  from paddle.vision.models.resnet import resnet18, resnet50, wide_resnet50_2
  from scipy.ndimage import gaussian_filter
  from qinspector.cvlib.workspace import register
  from qinspector.uad.utils.utils import cdist, cholesky_inverse, mahalanobis, mahalanobis_einsum, orthogonal, svd_orthogonal
  from qinspector.uad.utils.k_center_greedy import KCenterGreedy
label_desc: Use image node_id 17 for calling the PaDiMPlus obj's underlying member method code with example usage: obj.compute_inv_(mean, covariance, eps) without return types