class_docstr: Procedure: [N,C,H,W] -> [N,g,C/g,H,W] -> [N,C/g,g,H,w] -> [N,C,H,W].
class_docstr_tok: ["Procedure",":","[","N",",","C",",","H",",","W","]","-",">","[","N",",","g",",","C\/g",",","H",",","W","]","-",">","[","N",",","C\/g",",","g",",","H",",","w","]","-",">","[","N",",","C",",","H",",","W","]","."]
code: def __init__(self, groups):
      super(ChannelShuffle, self).__init__()
      self.groups = groups
  
imports: from __future__ import absolute_import, division, print_function
  import torch
  import torch.nn
  import torch.nn.functional
label_desc: Use image node_id 1 to create a new ChannelShuffle object from inherited base classes: nn with example: obj = ChannelShuffle(groups)