code: def generate_normals(m, P):
      """Generate a Gaussian sample with mean m and precision P
  
      Parameters
      ----------
      m array of shape n: the mean vector
      P array of shape (n,n): the precision matrix
  
      Returns
      -------
      ng : array of shape(n): a draw from the gaussian density
      """
      icp = inv(cholesky(P))
      ng = nr.randn(m.shape[0])
      ng = np.dot(ng, icp)
      ng += m
      return ng
  
imports: import math
  import numpy
  import numpy.random
  from scipy.linalg import cholesky, eigvalsh, inv
  from scipy.special import gammaln
  from .gmm import GMM
  from .utils import kmeans
label_desc: Use image node_id 3 for calling a global function with example usage: generate_normals(m, P) and returns: ng