class_docstr: A tool for image augmentation.
  
  For operations with inplace=True, the returned value is the ImageTool
  instance self, which is for chaining multiple operations; Otherwise, the
  preprocessed images would be returned.
  
  For operations that has countable pre-processing cases, argument num_case
  could be set to decide the number of pre-processing cases to apply.
  Typically, it is set to 1 for training phases and to the max for test
  phases.
class_docstr_tok: ["A","tool","for","image","augmentation",".","For","operations","with","inplace=True",",","the","returned","value","is","the","ImageTool","instance","self",",","which","is","for","chaining","multiple","operations",";","Otherwise",",","the","preprocessed","images","would","be","returned",".","For","operations","that","has","countable","pre-processing","cases",",","argument","num_case","could","be","set","to","decide","the","number","of","pre-processing","cases","to","apply",".","Typically",",","it","is","set","to","1","for","training","phases","and","to","the","max","for","test","phases","."]
docstr: Args:
      rng: a tuple (begin,end) in degree, include begin, exclude end
      inplace: inplace imgs or not ( return new_imgs)
code: def rotate_by_range(self, rng, inplace=True):
      """
      Args:
          rng: a tuple (begin,end) in degree, include begin, exclude end
          inplace: inplace imgs or not ( return new_imgs)
      """
      angle_list = list(range(rng[0], rng[1]))
      return self.rotate_by_list(angle_list, 1, inplace)
  
imports: from __future__ import division
  from builtins import range
  from builtins import object
  import random
  import numpy
  from PIL import Image, ImageEnhance
  import math
label_desc: Use image node_id 13 for calling the ImageTool obj's underlying member method code with example usage: obj.rotate_by_range(rng, inplace) and returns: self