code: def empirical(X):
      """Compute empirical covariance as baseline estimator."""
      print("Empirical")
      cov = np.dot(X.T, X) / n_samples
      return cov, np.linalg.inv(cov)
  
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 12 for calling a global function with example usage: empirical(X) and returns: cov,  np