code: def compute_inv(self, mean, covariance, eps=0.01):
      c, H, W = mean.shape
      for i in tqdm(range(H), desc="compute inverse covariance"):
          covariance[i, :, :, :] = cholesky_inverse(
              covariance[i, :, :, :] + eps * paddle.eye(c)
          )
      self.set_dist_params(mean, covariance)
  
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 18 for calling the PaDiMPlus obj's underlying member method code with example usage: obj.compute_inv(mean, covariance, eps) without return types