code: def __init__(self, shape, groups: int = 2, **kwargs):
      super(ChannelShuffle, self).__init__(**kwargs)
      batch_size, height, width, num_channels = shape
      assert num_channels % 2 == 0
      channel_per_group = num_channels // groups
  
      # Tuple of integers, does not include the samples dimension (batch size).
      self.reshape1 = layers.Reshape(
          (height, width, groups, channel_per_group)
      )
      self.reshape2 = layers.Reshape((height, width, num_channels))
  
imports: import tensorflow
  from tensorflow.keras import layers, Model
label_desc: Use image node_id 1 to create a new ChannelShuffle object from inherited base classes: layers with example: obj = ChannelShuffle(shape, groups)