code: def __init__(self, channels, groups):
      super(ChannelShuffle, self).__init__()
      if channels % groups != 0:
          raise ValueError("channels must be divisible by groups")
      self.groups = groups
  
imports: import numpy
  from torch.autograd import Variable
  from pytorch2keras.converter import pytorch_to_keras
  import torch
  import torch.nn
  import torch.nn.functional
  import torch.nn.init
label_desc: Use image node_id 1 to create a new ChannelShuffle object from inherited base classes: nn with example: obj = ChannelShuffle(channels, groups)