code: def avg_max_reduce_channel(x):
      # Reduce hw by avg and max
      # Return cat([avg_ch_0, max_ch_0, avg_ch_1, max_ch_1, ...])
      if not isinstance(x, (list, tuple)):
          return avg_max_reduce_channel_helper(x)
      elif len(x) == 1:
          return avg_max_reduce_channel_helper(x[0])
      else:
          res = []
          for xi in x:
              res.extend(avg_max_reduce_channel_helper(xi, False))
          return paddle.concat(res, axis=1)
  
imports: import paddle
  import paddle.nn
  import paddle.nn.functional
label_desc: Use image node_id 2 for calling a global function with example usage: avg_max_reduce_channel(x) and returns: avg_max_reduce_channel_helper, avg_max_reduce_channel_helper, paddle