# Add a small amount times the identity matrix to prevent errors
identity = tf.Variable(tf.convert_to_tensor(np.eye(mu_shape[-1].value), dtype=tf.float32))
Sigma = tf.batch_matmul(L,tf.matrix_transpose(L)) + 1e-4*identity

# Check positive definite
def _debug_print_func(Sigma,L):
  try:
      C = np.linalg.cholesky(Sigma)
  except np.linalg.LinAlgError:
      print 'LinAlgError'

  return Sigma

[Sigma] = tf.py_func(_debug_print_func, [Sigma,L], [tf.float32])