code: def downsample_maxpool(
      in_channels=64,
      out_channels=64,
      kernel_size=3,
      stride=1,
      padding=0,
      bias=True,
      mode="2R",
      negative_slope=0.2,
  ):
      assert len(mode) < 4 and mode[0] in [
          "2",
          "3",
      ], "mode examples: 2, 2R, 2BR, 3, ..., 3BR."
      kernel_size_pool = int(mode[0])
      stride_pool = int(mode[0])
      mode = mode.replace(mode[0], "MC")
      pool = conv(
          kernel_size=kernel_size_pool,
          stride=stride_pool,
          mode=mode[0],
          negative_slope=negative_slope,
      )
      pool_tail = conv(
          in_channels,
          out_channels,
          kernel_size,
          stride,
          padding,
          bias,
          mode=mode[1:],
          negative_slope=negative_slope,
      )
      return sequential(pool, pool_tail)
  
imports: from collections import OrderedDict
  import numpy
  import paddle.nn
label_desc: Use image node_id 7 for calling a global function with example usage: downsample_maxpool(in_channels, out_channels, kernel_size, stride, padding, bias, mode, negative_slope) and returns: sequential