code: def _prepare_bounds(bounds, x0):
      lb, ub = [np.asarray(b, dtype=float) for b in bounds]
      if lb.ndim == 0:
          lb = np.resize(lb, x0.shape)
  
      if ub.ndim == 0:
          ub = np.resize(ub, x0.shape)
  
      return lb, ub
  
file_path: catboost/contrib/python/scipy/py2/scipy/optimize/_numdiff.py
imports: from __future__ import division
  import numpy
  from numpy.linalg import norm
  from scipy.sparse.linalg import LinearOperator
  from ..sparse import issparse, csc_matrix, csr_matrix, coo_matrix, find
  from ._group_columns import group_dense, group_sparse
label_desc: Use image node_id 3 for calling a global function with example usage: _prepare_bounds(bounds, x0) and returns: lb,  ub