code: def channel_shuffle(x, groups):
      batch_size, num_channels, height, width = x.shape[0:4]
      assert (
          num_channels % groups == 0
      ), "num_channels should be divisible by groups"
      channels_per_group = num_channels // groups
      x = paddle.reshape(
          x=x,
          shape=[batch_size, groups, channels_per_group, height, width],
      )
      x = paddle.transpose(x=x, perm=[0, 2, 1, 3, 4])
      x = paddle.reshape(
          x=x, shape=[batch_size, num_channels, height, width]
      )
      return x
  
imports: import paddle
  import paddle.nn.functional
  import paddle.nn
  from paddle import ParamAttr
  from paddle.regularizer import L2Decay
  from paddle import in_dynamic_mode
  from paddle.common_ops_import import Variable, LayerHelper, check_variable_and_dtype, check_type, check_dtype
label_desc: Use image node_id 16 for calling a global function with example usage: channel_shuffle(x, groups) and returns: x