code: def atleast_1d(*arys):
      """
      Convert inputs to arrays with at least one dimension.
  
      Scalar inputs are converted to 1-dimensional arrays, whilst
      higher-dimensional inputs are preserved.
  
      Parameters
      ----------
      arys1, arys2, ... : array_like
          One or more input arrays.
  
      Returns
      -------
      ret : ndarray
          An array, or list of arrays, each with ``a.ndim >= 1``.
          Copies are made only if necessary.
  
      See Also
      --------
      atleast_2d, atleast_3d
  
      Examples
      --------
      >>> np.atleast_1d(1.0)
      array([ 1.])
  
      >>> x = np.arange(9.0).reshape(3,3)
      >>> np.atleast_1d(x)
      array([[ 0.,  1.,  2.],
             [ 3.,  4.,  5.],
             [ 6.,  7.,  8.]])
      >>> np.atleast_1d(x) is x
      True
  
      >>> np.atleast_1d(1, [3, 4])
      [array([1]), array([3, 4])]
  
      """
      res = []
      for ary in arys:
          ary = asanyarray(ary)
          if ary.ndim == 0:
              result = ary.reshape(1)
          else:
              result = ary
          res.append(result)
      if len(res) == 1:
          return res[0]
      else:
          return res
  
imports: from __future__ import division, absolute_import, print_function
  import functools
  import operator
  import types
  import warnings
  from .None import numeric
  from .None import overrides
  from .numeric import array, asanyarray, newaxis
  from .multiarray import normalize_axis_index
label_desc: Use image node_id 2 for calling a global function with example usage: atleast_1d() and returns: res, res