code: def upsample_convtranspose(
      in_channels=64,
      out_channels=3,
      kernel_size=2,
      stride=2,
      padding=0,
      bias=True,
      mode="2R",
      negative_slope=0.2,
  ):
      assert len(mode) < 4 and mode[0] in [
          "2",
          "3",
          "4",
      ], "mode examples: 2, 2R, 2BR, 3, ..., 4BR."
      kernel_size = int(mode[0])
      stride = int(mode[0])
      mode = mode.replace(mode[0], "T")
      up1 = conv(
          in_channels,
          out_channels,
          kernel_size,
          stride,
          padding,
          bias,
          mode,
          negative_slope,
      )
      return up1
  
imports: from collections import OrderedDict
  import numpy
  import paddle.nn
label_desc: Use image node_id 5 for calling a global function with example usage: upsample_convtranspose(in_channels, out_channels, kernel_size, stride, padding, bias, mode, negative_slope) and returns: up1