code: def randn(*args):
      """
      Return a random matrix with data from the "standard normal" distribution.
  
      `randn` generates a matrix filled with random floats sampled from a
      univariate "normal" (Gaussian) distribution of mean 0 and variance 1.
  
      Parameters
      ----------
      \\*args : Arguments
          Shape of the output.
          If given as N integers, each integer specifies the size of one
          dimension. If given as a tuple, this tuple gives the complete shape.
  
      Returns
      -------
      Z : matrix of floats
          A matrix of floating-point samples drawn from the standard normal
          distribution.
  
      See Also
      --------
      rand, random.randn
  
      Notes
      -----
      For random samples from :math:`N(\\mu, \\sigma^2)`, use:
  
      ``sigma * np.matlib.randn(...) + mu``
  
      Examples
      --------
      >>> import numpy.matlib
      >>> np.matlib.randn(1)
      matrix([[-0.09542833]])                                 #random
      >>> np.matlib.randn(1, 2, 3)
      matrix([[ 0.16198284,  0.0194571 ,  0.18312985],
              [-0.7509172 ,  1.61055   ,  0.45298599]])       #random
  
      Two-by-four matrix of samples from :math:`N(3, 6.25)`:
  
      >>> 2.5 * np.matlib.randn((2, 4)) + 3
      matrix([[ 4.74085004,  8.89381862,  4.09042411,  4.83721922],
              [ 7.52373709,  5.07933944, -2.64043543,  0.45610557]])  #random
  
      """
      if isinstance(args[0], tuple):
          args = args[0]
      return asmatrix(np.random.randn(*args))
  
file_path: catboost/contrib/python/numpy/py2/numpy/matlib.py
imports: from __future__ import division, absolute_import, print_function
  import numpy
  from numpy.matrixlib.defmatrix import matrix, asmatrix
  from numpy import *
label_desc: Use image node_id 7 for calling a global function with example usage: randn() and returns: asmatrix