code: def compute_inv_incremental(self, B, eps=0.01):
      c = self.mean.shape[0]
      # if self.inv_covariance == None:
      self.mean /= B  # hwc
      self.inv_covariance /= B
      # covariance hwcc  #.transpose((2,3, 0, 1)))
      self.inv_covariance -= paddle.einsum(
          "hwc, hwd -> hwcd", self.mean, self.mean
      )
      # covariance = (covariance - B*paddle.einsum('chw, dhw -> hwcd', mean, mean))/(B-1)
      self.compute_inv(
          self.mean.transpose((2, 0, 1)), self.inv_covariance, eps
      )
  
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 16 for calling the PaDiMPlus obj's underlying member method code with example usage: obj.compute_inv_incremental(B, eps) without return types