code: def sk_ledoit_wolf(X):
      """Estimate inverse covariance via scikit-learn ledoit_wolf function."""
      print("Ledoit-Wolf (sklearn)")
      lw_cov_, _ = ledoit_wolf(X)
      lw_prec_ = np.linalg.inv(lw_cov_)
      return lw_cov_, lw_prec_
  
imports: import sys
  import numpy
  import tabulate
  import time
  from sklearn.model_selection import GridSearchCV
  from sklearn.datasets import make_sparse_spd_matrix
  from sklearn.covariance import GraphicalLassoCV, ledoit_wolf
  import matplotlib.pyplot
  from inverse_covariance import QuicGraphicalLasso, QuicGraphicalLassoCV, QuicGraphicalLassoEBIC, AdaptiveGraphicalLasso, ModelAverage
label_desc: Use image node_id 14 for calling a global function with example usage: sk_ledoit_wolf(X) and returns: lw_cov_,  lw_prec_