parameters: (skipna, args, kwargs, name)
return_statement: return skipna
docstring: If this function is called via the 'numpy' library, the third
      parameter in its signature is 'dtype', which takes either a
      'numpy' dtype or 'None', so check if the 'skipna' parameter is
      a boolean or not
docstring_summary: If this function is called via the 'numpy' library, the third
      parameter in its signature is 'dtype', which takes either a
      'numpy' dtype or 'None', so check if the 'skipna' parameter is
      a boolean or not
docstring_tokens: If this function is called via the numpy library the third parameter in its signature is dtype which takes either a numpy dtype or None so check if the skipna parameter is a boolean or not
function: def validate_cum_func_with_skipna(skipna, args, kwargs, name):
      """
      If this function is called via the 'numpy' library, the third
      parameter in its signature is 'dtype', which takes either a
      'numpy' dtype or 'None', so check if the 'skipna' parameter is
      a boolean or not
      """
      if not is_bool(skipna):
          args = (skipna,) + args
          skipna = True
  
      validate_cum_func(args, kwargs, fname=name)
      return skipna
function_tokens: def validate_cum_func_with_skipna ( skipna , args , kwargs , name ) : if not is_bool ( skipna ) : args = ( skipna , ) + args skipna = True validate_cum_func ( args , kwargs , fname = name ) return skipna