class_docstr: A Multigrid Method for Efficiently Training Video Models
  Chao-Yuan Wu, Ross Girshick, Kaiming He, Christoph Feichtenhofer, Philipp Krähenbühl
  CVPR 2020, https://arxiv.org/abs/1912.00998
class_docstr_tok: ["A","Multigrid","Method","for","Efficiently","Training","Video","Models","Chao-Yuan","Wu",",","Ross","Girshick",",","Kaiming","He",",","Christoph","Feichtenhofer",",","Philipp","Kr\u00e4henb\u00fchl","CVPR","2020",",","https",":","\/\/arxiv.org\/abs\/1912.00998"]
code: def get_scale_beta(self, beta):
      short_scale = self.scale(self.short_cycle[beta])
      return short_scale
  
file_path: gluon-cv/gluoncv/torch/data/video_cls/multigrid_helper.py
imports: from functools import reduce
  import numpy
  from torch.utils.data import Sampler
label_desc: Use image node_id 5 for calling the multiGridHelper obj's underlying member method code with example usage: obj.get_scale_beta(beta) and returns: short_scale