code: def channel_shuffle(x, groups):
      """Channel Shuffle operation from ShuffleNet [arxiv: 1707.01083]
      Arguments:
          x (Tensor): tensor to shuffle.
          groups (int): groups to be split
      """
      batch, channels, height, width = x.size()
      channels_per_group = channels // groups
      x = x.view(batch, groups, channels_per_group, height, width)
      x = torch.transpose(x, 1, 2).contiguous()
      x = x.view(batch, channels, height, width)
      return x
  
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 3 for calling a global function with example usage: channel_shuffle(x, groups) and returns: x