code: def linspace(start, stop, num):
      r"""
      Generate a one-dimensional vector/tensor of size `num` whose values are evenly spaced from `start` to `end`, inclusive.
  
      Args:
          start(float): Start value.
          stop(float): End value.
          num(int): Size of the constructed vector/tensor.
  
      Returns:
          ~nnabla.Variable: 1-D array with the generated values.
      """
      from .function_bases import linspace as linspace_base
  
      if not isinstance(num, int):
          raise TypeError(
              "'{}' object cannot be interpreted as an integer".format(
                  type(num).__name__
              )
          )
      if num < 0:
          raise ValueError(
              "Number of samples, {}, must be non-negative.".format(num)
          )
  
      return linspace_base(start, stop, num)
  
imports: from __future__ import absolute_import
  from .function_bases import *
  from .None import dtypes
  import nnabla
  import numpy
  from .normalization_functions import *
  from .numpy_compat_functions import *
label_desc: Use image node_id 32 for calling a global function with example usage: linspace(start, stop, num) and returns: linspace_base