code: def unflatten_cholesky_unique(L_flat):
      """
      Converts a vector of elements into a triangular matrix
      (Cholesky factor). Exponentiates diagonal to make
      parameterization unique. Inverse of flatten_cholesky_unique.
      """
      L = tfp.math.fill_triangular(L_flat)
      # exp diag for unique parameterization
      L = tf.linalg.set_diag(L, tf.exp(tf.linalg.diag_part(L)))
      return L
  
file_path: brainiak/brainiak/matnormal/utils.py
imports: import tensorflow
  import tensorflow_probability
  from scipy.stats import norm
  from numpy.linalg import cholesky
  import numpy
label_desc: Use image node_id 6 for calling a global function with example usage: unflatten_cholesky_unique(L_flat) and returns: L