code: def cholesky_inverse(input, upper=False, out=None, inplace=True):
      u = paddle.cholesky(input, upper)
      u = paddle.linalg.triangular_solve(
          u, paddle.eye(u.shape[-1]), upper=upper
      )
      if len(u.shape) == 2:
          uit = u.T
      elif len(u.shape) == 3:
          uit = paddle.transpose(u, perm=(0, 2, 1))
      elif len(u.shape) == 4:
          uit = paddle.transpose(u, perm=(0, 1, 3, 2))
      if inplace:
          input = u @ uit if upper else uit @ u
          return input
      else:
          out = u @ uit if upper else uit @ u
          return out
  
imports: import os
  import argparse
  import numpy
  import matplotlib
  import matplotlib.pyplot
  from sklearn.metrics import roc_curve, auc
  from tqdm import tqdm
  from skimage import measure, morphology
  from skimage.segmentation import mark_boundaries
  import paddle
label_desc: Use image node_id 3 for calling a global function with example usage: cholesky_inverse(input, upper, out, inplace) and returns: input, out