code: def compute_stats_incremental(self, out):
      # calculate multivariate Gaussian distribution
      H, W, B, C = out.shape
      if isinstance(self.inv_covariance, type(None)):
          self.mean = paddle.zeros((H, W, C), dtype="float32")
          self.inv_covariance = paddle.zeros(
              (H, W, C, C), dtype="float32"
          )
  
      self.mean += out.sum(2)  # mean hwc
      # cov = paddle.einsum('bchw, bdhw -> hwcd', outs, outs)# covariance hwcc
      for i in range(H):
          self.inv_covariance[i, :, :, :] += paddle.einsum(
              "wbc, wbd -> wcd", out[i, :, :, :], out[i, :, :, :]
          )
  
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 15 for calling the PaDiMPlus obj's underlying member method code with example usage: obj.compute_stats_incremental(out) without return types